LETTERS
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4
Recent Trends in Female
Labour Force Participation
T
he transition of India’s labour market demographics has been a subject of discourse in recent decades. With
a drastic decline in female labour force
participation over the last 15 years,
India recorded the lowest female labour
force participation rate (LFPR) among
all the Group of Twenty countries reflecting a continuous decline since the
2000s. The nationally represented data
sets of the National Sample Surveys,
Employment–Unemployment Survey, and
the Periodic Labour Force Survey point
out that the female LFPR has been very
low in comparison to male counterparts
over the years.
Claudia Goldin, winner of the Sveriges
Riksbank Prize in Economic Sciences,
also known as the Nobel Prize in Economics, highlights in her research that
gender-based discrimination and lower
participation of women in the labour
market have existed historically over the
years and several factors have influenced and continue to influence the
demand and supply of female labour.
These include gendered occupational
segregation, inadequate growth of labour
demand within sectors predominantly
occupied by women, educational opportunities, cultural norms, family responsibilities, including marital status, presence of children, a larger household, and
the overall socio-economic environment
that facilitates or hinders women’s engagement in the labour market. However,
this declining trend showed signs of reversal where India’s female labour force
participation of 15 years and above age
group has shown a steady increase from
23% in 2017–18 to 37% in 2022–23. The
LFPR has demonstrated rapid growth in
the rural areas rising from 24% in 2017–18
to 41% in 2022–23 compared to a change
from 20% to 25% in urban areas.
A very similar scenario can be seen
in Jharkhand where the female labour
force participation in the rural areas
has been much higher than in the urban
areas attributing to the high incidence
of poverty and lack of opportunities in
rural areas. In light of the employment
condition index (ECI), constituted by the
Institute of Human Development and
the International Labour Organization,
Jharkhand has been one of the bottom
ECI states with a composite score of
0.49 for 2021–22. Based on different
indicators to capture the labour market
outcomes, though the overall employment quality in the state has shown an
improved score from 0.42 to 0.49 between 2005 and 2022, most female
workers in the state are self-employed,
indicating a paucity of jobs offering
regular wages and salary in the state.
The labour absorption of women (especially married women) is much higher
in the agrarian-dependent rural areas
of Jharkhand. The proportion of females working as unpaid helpers in
household enterprises is considerably
higher in comparison to other self-employment categories of work, highlighting the traditional roles, social stigma,
and other institutional barriers limiting
their influence in the state.
The LFPR and workforce participation rate (WPR) have both risen in the
state over time. However, WPR has increased faster than LFPR, which is said
to cause a decrease in female unemployment over the period. But the question that arises here is that though
there has been an increase in the participation rate of women in the labour
force and a decrease in female unemployment in recent times, has it enhanced the quality of jobs for women
engaged in the state?
The growing prevalence of self-employment in the state not only underscores the inferior quality of jobs and
income disparities but also signifies a
struggle for survival. Women predominantly engaging in micro-entrepreneurial endeavours is one of the survivalists’
strategies to evade poverty and enter
the market relations. Addressing this
concern, attention needs to be given to
boosting non-farm employment, including intensive manufacturing employment in the state, scaling up the smallscale household enterprises by suitable
support and awareness, and formulating
a gendered approach framework to reduce the labour market inequalities
may 4, 2024
vol lix no 18
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among women and marginalised social
groups in the state.
Annesha Biswas, Mahesh E
Bengaluru
State Repression over
Disabled Embodiment
Between me and the other world, there is
ever an unasked question: unasked by some
through feelings of delicacy, by others,
through the difficulty of rightly framing it.
Instead of saying it directly, how does it feel
to be a problem?
—W E B Du Bois, American sociologist
and civil rights activist
T
his profound question, “How does it
feel to be a problem?” asked by Du
Bois in the context of the civil rights
movement in the United States, fits neatly
into disabled lived experiences. The state
treats disabled people as those who need
either “empowerment” or “charity,” while
non-governmental organisations (NGOs)
treat us as those who need “reasonable
accommodation” and removal of attitudinal barriers for our true inclusion in
the “mainstream.” Such stories of inclusion present a benevolent face of the
state that uses the euphemism divyang
for the disabled. These narratives also
enable NGOs to merely seek politically
soft disability rights and primarily attempt to articulate disability empowerment in an apolitical vocabulary. However, the two outliers of G N Saibaba and
Hem Mishra are chilling reminders that
such stories of inclusion and empowerment favoured by the state and neo-liberal NGOs hide more than they reveal.
Saibaba’s story is the most chilling and
“spectacular” exhibition of torture over a
disabled body in recent memory. A wheelchair-bound 90% disabled individual, Saibaba was jailed for almost 10 years in a
most inhumane situation. While staying
his release from jail after a judgment from
the Nagpur bench of the Bombay High
Court in 2022, the Supreme Court commented on the request of Saibaba for
house arrest, as reported by Hindu, “as far
as terrorist activities are concerned, the
brain plays a very important role … A
brain for such activities is very dangerous.” This brutal and violent expression
was not merely semantic. This expression
and the entire ordeal of Saibaba expose
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the most illiberal face of our courts, which
are meant to protect our civil liberties.
Saibaba’s torture was so spectacular
that Mishra’s disability and the torture he
faced were not mentioned in our discourse
on state repression over disabled embodiment. In his interview on a YouTube channel, Gaon Ke Log, he narrated how authorities presented his childhood disability in
his left hand as an outcome of “bombmaking.” He was made a figure of terror among
inmates due to his disability.
Incarcerations of Saibaba and Mishra
are not merely examples of taking away
political liberty; they are examples of
denuding disabled people of human dignity in case they attempt to raise their
political voice beyond the state-prescribed limits. Philosopher Giorgio
Agamben gives a unique example of concentration camps where inmates were
referred to as Muselmänner by Nazis.
They were excluded from their social
and political contexts, and humiliation
and horror were used to take away their
human consciousness and personality.
Saibaba and Mishra faced a similar exclusion and loss of dignity at the hands
of the state instrumentalities because
they refused to adhere to what Ashis
Nandy calls a “well-monitored, subtly
controlled dissent.” This striping of the
human dignity of Saibaba and Mishra
was done by a so-called “liberal” state.
Sadly, most of the neo-liberal disabilityfocused NGOs, except for a few golden
examples, such as the National Platform
for the Rights of the Disabled, did not
raise their voice against these examples
of state brutality.
The cases of Saibaba and Mishra call
for greater accountability of the state
and NGOs who claim to speak for them.
Disability studies scholar Anita Ghai argues that an apolitical and middle-class
articulation of disability rights excludes
the voices of many disabled people who
do not have the “bare minimum.” In
Mishra and Saibaba’s case, they were
stripped of their human dignity and
faced the worst state repression over
and against disabled bodies. If, as a society, we have any sense of justice, then I
think the republic, civil society, and NGOs
who claim to speak for the disabled should
undertake an honest introspection.
Vijay Kishor Tiwari
Kolkata
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MAY 4, 2024
A Skewed Recovery Limits Global Growth Prospects
The savings and investment constraints shackle India’s medium-term prospects.
T
he World Economic Outlook, a flagship publication of the
International Monetary Fund (IMF), provides interesting
insights into the pace and structure of the global recovery.
The report notes that the much-awaited recovery has not only
been challenging but also skewed. A series of setbacks, including
the disruption of supply chains, the Ukraine war, a food crisis,
surging inflation and the synchronised tightening of the monetary policy across nations, had constrained a sustained recovery.
To add to the complexities, recovery has been largely skewed
and mainly spurred by the emerging and developing Asia (EDA).
Though global growth had bounced back sharply to 6.5% in
2021, after declining by 2.7% during the 2020 pandemic, growth
has subsequently slowed down to 3.5% and 3.2% in 2022 and
2023. However, what is more worrisome is that prospects of a
sustained recovery still remain elusive with the IMF forecasts
estimating that global growth will hover at a marginally lower
level by the end of the decade.
The report also highlights the substantial variations in the
pace of recovery in the advanced economies and the emerging
market and developing economies (EMDEs). The numbers indicate that while growth in the advanced economies slowed down by
more than a quarter to 1.5% in the post-2019 period (2020–23),
that of the EMDEs only went down about one-fifth to 3.4%. However, the IMF forecasts further indicate that growth in the advanced economies will move up marginally through the decade,
while that in the EMDEs will slow down a little over the years.
Clearly, the prospects of a sustained global recovery are very
much constrained by these skewed gains.
One reason for the slow pace of global recovery is the near
stagnancy in global savings and investments. Global savings to
GDP ratio has moved up only marginally by a few decimal points
to 27.6% in the post-2019 period. Moreover, it is forecast that the
savings levels will slow down by around 1 percentage point by
the end of the decade.
The disparity in the savings rates between the advanced
economies and the EMDEs has further expanded in the post2019 era. Realising the consequences of the limitations of government support during a major crisis, there has been a steady
improvement in the level of savings in the EMDEs. Consequently,
savings rates in the EMDEs have gone up by close to 2 percentage points to 33.8% of the GDP in recent years, while those in
the much-richer advanced economies have stagnated at 23%.
Economic & Political Weekly
EPW
MAY 4, 2024
This has now further pushed up the disparities in the savings
rates across the two groups to double-digit levels. These disparities in the savings rate are also mirrored in investment rates
which are also forecast to remain stagnant in both the advanced
economies and the EMDEs till the end of the decade. This would
also seriously limit the prospects of global recovery.
A quick glance at the numbers of the six major analytical
groups indicates that growth in the post-2019 period has surpassed that in the pre-pandemic period only in Latin America
and the Caribbean (LAC). However, the highest growth rate in
the post-2019 period was in EDA (4.3%), followed by sub-Saharan Africa (2.6%), emerging and developing Europe (EMDE)
(2.5%), the Middle East and Central Asia (MECA) (2.3%), LAC
(1.6%), and the major advanced economies (1.3%). This again
highlights the skewed nature of the global recovery.
To add to the complexities, growth in EDA, the most buoyant
region, was mainly powered by China and India. Though average growth in both countries has declined by around a quarter
to 4.7% each in the post-2019 phase, their growth rates were
still at a more respectable 5.2% and 7.8%, respectively, in 2023.
However, both countries are expected to register slower growth
over the decade. While the IMF forecasts that structural constraints will slow down growth in China to 3.3% by the end of
the decade, India’s growth will still be at a reasonably high 6.5%
in this period.
A major contrast between the two countries is the substantial
disparities in the savings and investment levels. Savings and investment rates in China had remained stagnant at very high levels
(44% and 43% of the GDP) in both pre- and post-2019 phases.
In the case of India, both savings and investments have moved
up marginally to 31% and 32% of the GDP in the post-2019 period.
However, while investment rates in China are forecast to largely
remain at the current levels till the end of the decade, that of
India is estimated to slow down marginally. The larger share of
the manufacturing sector and the huge infrastructure projects,
with their larger capital requirements, will partially explain the
large investment disparities between Cina and India.
An important factor that has helped fuel India’s recovery is
the pick-up in exports of goods and services. Global trends show
that the share of exports of goods and services from EMDEs has
gone up marginally to 38.3% in the post-2019 period. At the
national level, while almost all major advanced economies have
vol lix no 18
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7
COMMENT
lost the market share of exports in the post-2019 phase, EMDEs
like China, India, Russia, Brazil, and Mexico have registered
marginal gains. The IMF estimates also show that the growth in
8
the volume of goods and services from India will be marginally
higher than that of China till the end of the decade. Clearly, it is
certainly a case of mixed signals for India.
MAY 4, 2024
vol lix no 18
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Economic & Political Weekly
COMMENT
From 25 Years Ago
Vol XXXIV, No 18
MAY 1, 1999
A Nation Searching for
a Narrative in Times of
Globalisation
Neera Chandhoke
It is also conceivably time to explore the structural inadequacies in the way in which the nation has been in Benedict Anderson’s admittedly overused but nevertheless useful formulation ‘imagined’, at least by some sections of
the body politic. In fact, an engagement with
received narratives of nationalism may be profoundly constructive. For it is only through this
process, that we can shift from being consumers of received narratives, to being producer of
a shared narrative of the nation.
This narrative in order to prove viable and
relevant for our needs – that of a multi-cultural,
Economic & Political Weekly
EPW
MAY 4, 2024
multi-religious and multi-ethnic society –
should possess in the main one property. It
should of course possess the potential to address the problems of the here and now, as well
the capacity to take on undesirable formulations on the nation. But more importantly, it
should be able to fashion the nation in a democratic mode. For there happens to be no earthly
reason why societies that aspire towards democracy should speak languages of nationalism that are founded on intolerance, chauvinism, and fascism. Such languages, we need to
recognise, neutralise, and even betray democracy. In other words, if our society has to fulfil
its own promise of democracy, our narratives of
the nation have to be democratic. There is no
other choice, for no healthy society that also
happens to lay claim to being a great civilisation can live with schizophrenia.
Today, however, our society is fast approaching the verge of schizophrenia, because
we proclaim our commitment to democracy at
the very time discourses of fascism have made
their appearance on the political stage. But
there is no way that we can live with democracy
as a constituent political principle, and fascism
as the constituent national principle. The two
are fundamentally incompatible, and attempts
to commensurate such incompatible principles
are not only politically and morally flawed,
they are frankly dishonest. If we adopt democracy as the founding principle of the body politic, we will have to subscribe to a democratic
nation; if we adopt fascism, we abdicate all
pretensions to democracy. And whether we
want to give up democracy as the organising
principle of the body politic is something we
need to urgently reflect on. For this will inevitably happen if we continue to watch silently
the untamed communalisation of our society.
And silence I may remind the audience, signifies acquiescence. We really have no option except to intervene immediately in this matter.
The nation has to be re-narrated in a democratic mode in order to recover the nation for
the people of India. It has to be re-narrated in a
democratic mode to retrieve it from fascist,
right wing elements that parade intolerance,
violence against minorities, and frank criminality, as patriotism.
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COMMENT
From 50 Years Ago
Vol IX, No 18
MAY 4, 1974
Uruguay: Rule by Military
Proxy
Lajpat Rai
The September 1973 fascist military coup
d’etat in Chile seems to have overshadowed
two other coups which took place in the same
year in Uruguay and Bolivia. While the
National Stadium in Santiago where thousands of political prisoners are being held and
tortured has become known all over the
world, El Clindro Stadium in Montevideo
where Uruguayan patriots and leftists are being tortured has remained relatively unknown. El Clindro acquired this sinister reputation after the coup d’etat of June 27, 1973,
when Juan Maria Bordaberry established a
Economic & Political Weekly
EPW
MAY 4, 2024
dictatorial regime supported by the Uruguayan of oligarchy, US corporate interests and
the reactionary military. On this day President Bordaberry in order to save his faltering
regime riven by dissensions, plagued by a 60
percent per annum inflation, harassed by the
Tupamaros and threatened by a countrywide
general strike of industrial workers, dissolved
the Congress and called in the military to
take over the reins. The local point of the
struggle between the military and the Congress was the former’s demand that the Congress lift the immunity of the leftist Senator,
Enrique Erro, whom it accused of subversion
and alleged links with the Tupamaros — a Fidelista urban guerilla organisation operating
in the country since 1905. […]
Bordaberry came to power on a populist
programme after defeating the candidate of
the Frente Amplio. The reforms he promised to
the people included a programme of “Garibi
Hatao” or “Lucha Contra la Pobreza” (struggle
against poverty). He also promised to halt inflation, increase wages, strengthen the social
security system for the workers, and the inevitable land reform. But in less than two years he
had to call in the army to maintain his faltering regime in power — a regime which could
not solve or even make a beginning towards
solving a single problem of the people.
The manner in which the situation is shaping in this country (if odious comparisons can
be made), Indira Gandhi is more likely to act as
a Bordaberry of Uruguay than as an Allende of
Chile. But the traditional communists, clinging
to their outmoded heroes like a drowning man
to a twig, cannot learn even from the disastrous experiences with their figment of imagination — the “progressive” national bourgeoisie. Fidel Castro could not be more correct
when he declared some time ago in reference
to the traditional communists: “If anyone
should ask me who the most important allies of
imperialism are, I would not answer that they
are the professional armies, not even the Yankee marines. I would not say that they are of
oligarchies or the reactionary classes. I would
say they are the pseudo-revolutionaries”.
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9
COMMENT
Who Is Afraid of Redistribution?
There is a growing attack on the entire idea of redistribution, with social benefits being decried as freebies
even as the super-rich are praised as wealth creators.
Jean Drèze writes:
A
ny assistance the Indian government provides to poor
people is a form of redistribution. The reason is that the
cost is typically borne by more affluent sections of the
population in one way or another. There are, of course, exceptions to this rule. If the government vaccinates the poor against
communicable diseases, the rich may benefit too, even if they
have to pay for it. In practice, however, most forms of social
assistance have a redistributive element.
Redistribution is a well-accepted role of the state in market
economies, where income and wealth flow in arbitrary ways.
The rich often attribute their wealth to hard work, but this is a
sweet delusion. Their domestic helpers are likely to work much
harder, for a pittance. In some countries, redistribution makes a
substantial difference to disparities of income and wealth. In
France, for instance, taxes and social benefits reduce the ratio of
top-decile to bottom-decile average incomes from 24 to 6 according to one recent study.
As parliamentary elections unfold in India, political parties
are vying to promise social benefits to the underprivileged—
cash, housing, pensions, healthcare, and more. This is not a bad
thing, given that the poor count for so little at other times. The
election period is a short interlude when their interests and demands receive some attention. The electoral promises are largely symbolic, but sometimes they do lead to significant change
later on. Indeed, most of the big social-policy initiatives in India,
whether at the state or central level, had something to do with
electoral politics. The National Rural Employment Guarantee
Act and the National Food Security Act are two examples.
The Congress party makes some new promises of this sort in
its election manifesto. For instance, it promises an unconditional
cash transfer of `1 lakh per year to every poor family—a variant
of the Nyuntam Aay Yojana (NYAY) scheme it had proposed in
2019. Other important promises with a redistributive element
include an urban employment guarantee programme and free
healthcare in all public health centres. No doubt, all these proposals will be the subject of much scrutiny and debate in due
course. Meanwhile, as electoral promises go, there is nothing
outlandish about them.
None of these proposals caused an uproar when the Congress
manifesto was released in Delhi on 5 April. The next day, however, the party’s star campaigner created some confusion by
stating that the party, if voted to power, would “begin revolutionary work” to do justice to disadvantaged groups after the
promised caste census. The speech left the details of this revolutionary work to the listeners’ imagination. Intentionally or
8
otherwise, some media reports misquoted it as a clarion call for
“wealth redistribution.” Soon enough, critics cried wolf. One
even claimed that the Congress wanted to redistribute the
country’s wealth equally.
Congress spokespersons, unfortunately, overreacted to this
mischief by insisting that there was no talk of any redistribution
in the party’s manifesto. The point is technically correct, but it
denies the redistributive element implicit in the manifesto. This
was unnecessarily defensive and a little odd coming from a
party that takes pride in standing for the underprivileged.
Despite these disclaimers, attacks on the Congress and its alleged
redistribution mania continued, not only from the Bharatiya Janata
Party (BJP) but also from a broad section of the corporate-sponsored media. The BJP star campaigner himself raised the pitch
in a provocative speech on 21 April. Aside from insinuating that
the Congress was after the wealth of the poor, not the rich, he
gave the matter a reprehensible twist by claiming that people’s
wealth would be redistributed to Muslims. For good measure,
he referred to Muslims in the same breath as “people with many
children” and even “infiltrators.” The worst part is that this
communal speech set the tone for many others from then on.
Three days later, the chairperson of the Indian Overseas Congress unwittingly poured ghee on the fire in an interview with
ANI, where he made a casual reference to the fact that the United States had an inheritance tax. This led to shrill accusations
that the Congress was planning to reinstate India’s inheritance
tax, followed by another round of defensive denials by the party. The controversy is unlikely to die out soon.
Political fireworks aside, what is revealing is the organised
attack we are seeing today on the entire idea of redistribution.
On the one hand, social benefits are routinely decried as “freebies.” On the other, India’s super-rich are increasingly projected
as benign “wealth creators,” entitled to keep their wealth and to
be praised for it too. Any suggestion that they should be taxed is
denounced as a return to the socialist excesses of the Licence
Raj. Even during the Covid-19 crisis, when millions were
pushed to the wall, no demand was made on the super-rich.
Wealth inequality in India defies imagination. To convey the
point, I often ask friends the following question: If a hundred
workers were to work day after day at the minimum wage and
save their entire earnings, how long do you think it would take
for them to accumulate as much wealth as India’s richest business leader already has? Answers rarely cross a thousand years.
The correct answer, however, is close to a million years. If you
do not believe it, do the math.
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COMMENT
The argument for some form of wealth taxation is not just
that wealth inequality in India is so staggering, but also that
wealth has a tendency to snowball: the richer you are, the easier
it is to get even richer. As a recent report by the Organisation for
Economic Co-operation and Development (OECD) aptly puts it,
“wealth accumulation operates in a self-reinforcing way and is
likely to increase in the absence of taxation.” Wealth taxation
may not halt this snowball, but it can slow it down at least.
There are various ways of taxing wealth, such as property taxes,
inheritance taxes and, of course, a wealth tax. All OECD countries
have property taxes, most have inheritance taxes, and some have a
wealth tax as well. India has none of those, except for symbolic
property taxes. In addition, top income tax rates in India are relatively low (just 30%), and the Indian rich enjoy plenty of subsidies.
Economic & Political Weekly
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MAY 4, 2024
The case for an inheritance tax is particularly strong because
disparities of inherited wealth (the ultimate freebie) are the
anti-thesis of equality of opportunity. In India, these disparities are magnified by vast disparities of inherited “social capital,” for instance, in the form of privileged connections. Perhaps the sacrosanct nature of family privilege in India helps to
explain the shock waves that followed the passing comment on
inheritance taxes.
Political discourse in India normally takes place within certain boundaries set by the privileged and powerful. If you overstep these boundaries, expect some trouble.
Jean Drèze (jaandaraz@gmail.com) is a visiting faculty at the
Department of Economics, Ranchi University, Ranchi.
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ALTERNATIVE STANDPOINT
Some believe that the radicalRevisiting Intersectionality in India studies.
ism with which the concept arose has
A Dalit Feminist Perspective
Vaishali Khandekar
The intersectional framework has
been one of the most important
contributions to feminist studies.
It has since travelled outside
the United States in the last
three decades and has also gone
through much development in
India during this time. Along with
other categories like sexuality and
religion, it has rightly brought
attention to Dalit women who
were often overlooked in earlier
conceptions and movements
under feminist studies in India.
The author would like to thank the
anonymous reviewer for their helpful and
guiding comments.
Vaishali Khandekar (khandekar.vaishali1902@
gmail.com) is a PhD student at the Indian
Institute of Technology Hyderabad.
10
D
espite the emergence of intersectionality as a popular framework
to understand different axes of
oppression, difference, and power, there
has been little discussion about intersectionality as a methodology (McCall 2005).
The intersectional theory has also travelled outside the United States during the
last three decades. Around the same time
in India, an academic discourse emerged
about the positionality of Dalit women
within the feminist as well as the anticaste discourse. The term “intersectionality” began to be used in the late 1990s
and the early 2000s within the realm of
social sciences in India. And over the span
of more than a decade, it experienced a
proliferation and came to be overused as
a buzzword in universities, popular around
social media platforms and entering everyday conversations in mostly urban spaces.
In India, intersectionality was received
with enriching debates about its suitability
and methodology (Menon 2015; John
2015). It has foregrounded an understanding of a difference in positionality and
engaging in self-critical situated research
(Guru 1995; Rege 1998). There were
present life narratives and literary works
from Dalit women, but only more recently
has intersectionality triggered more work
from Dalit feminists, thus inviting new
perspectives and theoretical engagement.
Since its inception, Kimberlé Crenshaw has expressed some reservations
regarding certain contemporary studies
employing the intersectional approach.
Due to many studies with careless readings of intersectionality, she claims that
the original concept has become increasingly unrecognisable and that it may be
necessary to revisit the initial aims and
origins of the concept (Guidroz and
Berger 2009). Many other scholars have
resounded these concerns about the
usage of intersectionality in different
been diluted (Salem 2018), that Black
feminists have not been duly cited or
represented (Tomlinson 2013) and that
the concept has been depoliticised and
turned into a product of neo-liberal
academies serving White managerial
feminists rather than driven towards
social justice (Bilge 2013; Tomlinson
2018). Taking these important developments into account, it is important to
examine the complexities and methodological concerns it has brought with
itself. Over the last three decades, feminist scholarship in India has tried to utilise the intersectionality framework to
understand differences in the social
identities of different women. This article attempts to examine the chronology
of this development after the intersectional framework had travelled to India.
What has been its intellectual trajectory
in India? What is the politics of creating
Dalits as subjects of study? How has
caste become the central concern of
intersectional studies in India?
Intersectionality as a
Methodological Intervention
Strong and articulate Dalit women social
actors were creating knowledge in many
forms and spheres of life like literature,
politics, and various social movements
and activism. The active participation and
presence of many Dalit women as active
social and political actors and existence
of Dalit women writers producing rich
literature will confirm the fact that Dalit
feminism was present much before its
theorisation in academia. However, the
term “Dalit feminism” appeared in institutions, universities, and other academic
debates only after intersectional theory
had travelled to India. As a result, a new
wave of production of literature on a
new theme, generally termed as “Caste
and Gender” with Dalit women as its
primary subjects began and gained
much popularisation.
It must be acknowledged that the feminist movement in India also addressed
many singular cases about Dalit women,
a notable advocacy would be surrounding
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the case of Bhanwari Devi. This article
refrains from dismissing those accomplishments and instead focuses on the
period after the adaptation of intersectionality as a theoretical framework in
the works of feminist scholarship. It
seeks to show how this adoption has
contributed to the advancement of
existing work.
Although considerable scholarship has
emerged on the subject of Dalit women,
many such studies rely upon objectivising archives and knowledge produced
within the binary of colonial and nationalist projects (Paik 2021). This has
resulted in the inability in recognising
Dalit women as active subjects producing knowledge throughout history. However, since then, touchable women who
empathise with Dalit women’s problems
have made several attempts to contribute to their cause. The caste location of
these elite women came along with a
real fear of transgression of these caste
boundaries which can also become a
constraint to build a bridge between
lower- and upper-caste women.
However, Paik suggests that the problems Dalits or Dalit women face cannot
be dealt with in isolation, and allying
with different communities may yield
better results. There are different strategies to do so. Paik disagrees with Guru’s
(1995) articulation of the authenticity of
the experience of Dalits and Rege’s
(1998) call for touchable women to reinvent themselves as Dalit feminists.
Rather, Paik reinforces Anandi and
Kapadia’s (2017) position, as they urge
such scholars to stand in solidarity with
Dalit women. However, the nature and
the extent of these solidarities have not
been expanded upon in this discussion.
Utility generated for anti-caste politics:
McCall (2005) has devised some methodological strands of intersectionality
such as anti-categorical and intra-categorical complexities where the former
breaks down and analyses identity categories, while the latter takes them as the
starting analytical point. Additionally,
the inter-categorical approach stresses
on studying the existing categories to
understand unequal relationships between
social groups. This approach advocates
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may 4, 2024
for strategic use of categories in order to
disclose the ties between categories of
identities and inequalities among them.
Intersectionality on a fundamental level
says that a focus on the most privileged
group members marginalises those who
are differently burdened and obscures
claims that cannot be understood as
resulting from discrete sources of discrimination (Crenshaw 1989). This argument is based on the presumption that
before this intervention, the issues and
problems of the privileged group were
erroneously subsumed within the overarching ambit of universal issues pertaining to privileged groups. Therefore,
recognition of a “difference” would
ideally shed light on the unprivileged
groups in order to understand their
problems and issues.
The development of the intersectional
framework initially originated within the
discipline of critical legal studies propelled by Crenshaw towards addressing
a pivotal challenge concerning the legal
treatment of Black women as both racial
and gender subjects. However, in India,
the inception of this concept unfolded
only as an academic or theoretical pursuit.
This could be regarded as a small deviation as even in the Western context, it
swiftly transformed into an academic
quest. Although the problems related to
this transition in India have been discussed earlier (Menon 2015; Nash 2015),
it must be noted that to a certain extent,
the adoption of this framework in India
remained confined to scholarly circles
and was preoccupied with theorisation
instead of concerted efforts directed
towards its transformative application.
This theoretical absorption of Dalit
women was even more inconsistent with
the assertion that the development of
feminist theory in India has been in continuous connection with the development of women’s movements. Granted
that these movements dealt with the
concerns of high-caste women, nevertheless, it still began through public contention, negotiations with the state, and
ultimately a grounded social movement
about important issues affecting uppercaste women. However, till the time
intersectionality was introduced and
began getting popularised in India, there
was neither a rallying call for a movement
nor was it compulsory to reflect on this
category through a particular movement
with respect to anti-caste ideology. This
is in no way to suggest that Dalit women
did not participate in social movements
or led autonomous ones. Rather, it raises
the question of whether the arrival of
intersectional theory and its theorists
played any role in accelerating its discourse or in reaching its potential
impact. Although there was surely an
engagement with the then existing literature by Dalit women, the intersectional
approach still runs towards the danger of
fulfilling itself with the use of the subject
of Dalit women as well as reproducing the
literature and life narratives present by
Dalit women. Though, the anti-caste politics formed by Dalit ideologues intended
as a process of self-evolution of a conscious
practice of intersectional pedagogy can
be seen in Rege’s use of Phule’s philology
of Trutiya Ratna in university education
but could not come into practice in
teaching practices within universities.
If in the West the academic pursuit of
intersectionality has contributed to its
depoliticisation (Salem 2018), in India,
it never began with the aim of politics
at all but brought fruition to a new academic category to be capitalised upon.
In fact, today, intersectionality is also
celebrated in neo-liberal institutions
in India as well. There is a corner in
academic spaces in these neo-liberal,
mostly private universities, where intersectionality runs the risk of almost
turning into diversity management/
tokenism without any methodological
deliberation. I believe that the treatment of intersectionality in India and
its development as a solely inclusion
project has facilitated this process.
Sunaina Arya (2020) shows how our
legal system needs an intersectional
framework to understand the violence
faced by Dalit women. She explains that
the vertical structure of caste and the
horizontal strata of patriarchy leave
Dalit women vulnerable to “intersectional violence,” which is often overlooked by many Savarna feminists. Arya
is more clear than other scholars that
there is a purpose to intersectionality. For
Arya, intersectionality is a philosophical
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11
ALTERNATIVE STANDPOINT
and methodological endeavour, but she
retains a utility to her intersectional
framework and therefore qualifies intersectionality as “an excellent candidate”
for Dalit feminists.
For Arya, there is a direct link between
intersectionality and its methodological
potential. Her investment in explaining
the sexual violence faced by Dalit
women leads to legal recommendations
as well, focusing curiously on the different aspects where utility can be generated through intersectionality. Hence,
this framework also provides the possibility of a transformative potential
within Dalit feminism (Pan 2021).
The theoretical reliance on Dalit
women: Nash (2008), in her critique of
intersectionality, argues that intersectional theory burdens a theoretical reliance on Black women, which has created Black women as “prototypical intersectional subjects whose experiences of
marginality are imagined to provide a
theoretical value-added.” Conjuring the
figure of the Black woman becomes a
way to promise a “redemptive complexity” to the discipline to redeem itself
from earlier mishaps. It also becomes a
metaphor, a site of hope as well as failure
curating a moral atmosphere. The call to
adopt intersectionality in India and the
recognition of “difference” from a Dalit
standpoint embodied some of these
moral concerns as well. This theoretical
instinct inclined towards the codification of quantifiable oppression is an
impulse to measure the most “deplorable” oppression.
The theoretical reliance on “Dalit
women” could be seen as an inadequate
manoeuvre to contain the subjectivities
involving a deeper intersectional analysis, even involving two categories of
identities like caste and gender. In this
context, one might pose the question:
Why were Dalit women (and not caste)
such evident and inevitable subjects of
intersectionality in India? The evident
claim was that Dalit women face discrimination on both the basis of their
caste as well as of gender. This claim is
true and it has generated many important interventions in social sciences
about Dalit women. But it is equally
12
important to understand the trajectory
in which this inquiry has been predominantly undertaken by scholars, mostly
belonging to the Savarna community.
Nash (2008) views this theoretical
dependence as problematic because:
(i) it treats the category of Black women
as a unitary and monolithic entity, and
(ii) intersectionality “recycles black feminism without demonstrating what new
tools it brings to black feminism to help it
fashion a more complex theory of identity.” She further mentions how a symbolic version of a Black woman is animated through the term intersectionality
and, in a similar fashion, a South Asian
woman is animated through “transnationalism.” It would be interesting to
question how a symbolic image of a Dalit
woman was animated through words
like intersectionality in the early engagement with this concept in Indian academic spaces.
Moving forward, there is a stark difference that seems important in this
context between the academic explorations of intersectionality and other
theoretical developments about caste
and historical articulations within anticaste politics. The theorisation of caste
emerged from the anti-caste struggle
during the 19th and 20th centuries and
it was characterised by a relational perspective where the upper castes played
the predominant and oppressive role.
Without delving much deeper into the
intricacies and repercussions of the concepts developed in the works of thinkers
like Jotirao Phule, B R Ambedkar, and
Periyar, let us see how they employed
these terminologies and their choice of
words, what groups they chose to specify
and study, and what does their thought
mean for us today.
Phule, for instance, formulated a
visionary and striking concept of a caste
society with the category of Shetji–Bhatji.
This category exposes the nexus of social
consensus and mutual benefits between
merchants, moneylenders, and the Brahmins. And the rest, for Phule, were Bahujans. I am trying to bring attention to his
efforts in naming the oppressor group
while understanding the other members
of society as both deprived and powerful
in terms of their numbers. It is clear that
in early India, Phule reminded us as students that the power of maintenance of
caste resides with the powerful and the
category of Shetji–Bhatji uncovered the
mechanism of this sustenance by studying the oppressor groups. The focus,
therefore, remained on the mechanism
of caste and its workings through an
understanding of caste as an instrument
operating by the power duo of Shetjis
and Bhatjis.
The Politics of Naming
The primary context in which intersectionality was used in India was through
caste. Terms like Dalit feminism and subject positions like Dalit women emerged
following this theoretical position. This
was probably the first time where an academic debate was geared solely towards
Dalit women. Now, unlike the case of
the West where intersectionality entered
through organic theorists from Black
feminism, in India, this discussion began
with a notable absence or erasure of Dalit
women, despite the presence of several
Dalit feminists. Furthermore, universities
and departments of women’s studies and
their syllabi also became dominated
majorly by these Savarna theorists who
came and endowed their wisdom of
“inclusion” for Dalit women.
Nevertheless, if intersectionality was
at all the first recognition of Dalit women
as primary and active social actors
which needed a different kind of recognition and this ideological construction
was named “Dalit feminism,” and if this
started a recognition of caste within the
feminist discourse as a social reality,
would it not be the case that the feminism proceeding from this process
would be or could be aptly characterised
as “Savarna feminism”?
The invocation of the term “Savarna
feminism” may prima facie appear as a
polemical stretch, an overstatement or
an ostensible political rhetoric. But in
this case, it is intended as a forgotten
possibility. The discomfort with the
term also exhibits a discomfort with
standing in such a subject position. It
points towards a world unbeknownst to
seeing in terms of studying and examining the Savarna community. Other
words or variables like “elite” are used
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but the word “Savarna” is refrained
from. A part of the answer to this riddle
must lie in this discomfort of being
named and exposed as a subject. Other
parts may have different explanations
and reasonings. Since the colonial
period, the reality of caste has been a
source of embarrassment to a section of
the educated upper-caste elite. Caste’s
persistent presence “reinforced the
colonial stereotypes of Indian traditional cultures as grounded in irrational
religious belief and inhuman practices
of exclusion and hierarchy” (Jodhka
2017). At the same time, the product
of the same colonial effect produces
anthropological devices to study Dalits
and other oppressed groups. Although
in contemporary India, social scientists
cannot deny the modern manifestations
of caste, studying it as a phenomenon
among them(selves) in the most liberal
circles is still faced with some anxiety.
Apart from a conscious politics of naming, there are several other reasons provided to us by history for the inclusion of
Brahmin, Kshatriya and women from
other upper castes in the intersectional
framework. For example, during the 19th
century, the highest recorded rate of suicide was among Brahmin women
(Chakravarti 2001). This indicates how
caste affected their lives and being a Brahmin woman made them into emblems of
purity, which, in turn, imposed a need for
patriarchal control, leaving no means but
suicide for these women as an escape.
Here, caste and gender among Brahmin women was and continues to remain
an important factor for studying patriarchy. This may result in a political shift
from earlier understandings, but ultimately it enriches our knowledge about
different manifestations of caste. Debates
of intersectionality in the West have also
resulted in several interesting studies
focussing on white women as subjects
of intersectionality, for instance, through
the categories of whiteness and middleclassness (Levine-Rasky 2011).
What Is the Meaning of ‘Non-Dalit’?
I will conclude this article by raising
a question about another term used
widely today in academic circles.
The term “non-Dalits” can be heard in
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may 4, 2024
classrooms, conferences or even in academic texts. However, every time I stop
and try to grasp its meaning, I failingly
forfeit. Let us first ask: What is Dalit?
The word Dalit as we know was developed in Marathi literature, which
means broken or oppressed. It was then
adapted to signify the ex-untouchables
and was taken up in the social sciences
as well. In empirical studies about Dalits, the term ceases to be a reliable analytical category, mainly due to regional
specificities. Dalit in itself is not a caste,
it is a category of castes. In a fine contrast with terms such as Shetji–Bhatji,
the term “non-Dalit” takes the opposite
way of using terminologies used to
define the oppressed group being
reused to define the oppressor group.
The term “non-Dalits” has been used
to signify people who do not belong to the
Dalit community. Based on this discussion on the culture of naming, it seems
like the term is yet another device used
by Savarnas to name themselves without naming themselves. Not only that, it
is a Brahminical invention to name
themselves through the category of the
oppressed to serve a specific purpose of
neutralising themselves in the process.
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Social Identities, Vol 17, No 2, pp 239–53.
McCall, L (2005): “The Complexity of Intersectionality,” Signs, Vol 30, No 3, pp 1771–1800.
Menon, N (2015): “Is Feminism about ‘Women’?: A
Critical View on Intersectionality from India,” Economic & Political Weekly, Vol 50, No 17, pp 37–44.
Nash, J C (2008): “Re-thinking Intersectionality,”
Feminist Review, Vol 89, No 1, pp 1–15.
— (2015): “The Institutional Lives of Intersectionality,” Economic & Political Weekly, Vol 50,
No 38, pp 74–76.
Pan, A (2021): Mapping Dalit Feminism: Towards an
Intersectional Standpoint, New Delhi: SAGE.
Paik, S (2021): “Dalit Feminist Thought,” Economic
& Political Weekly, Vol 56, No 25, pp 127–36.
Phule, J G (2017): Gulamgiri, New Delhi: Vani
Prakashan.
Rege, S (1998): “Dalit Women Talk Differently: A
Critique of ‘Difference’ and towards a Dalit
Feminist Standpoint Position,” Economic &
Political Weekly, WS39–WS46.
Salem, S (2018): “Intersectionality and Its Discontents: Intersectionality as Traveling Theory,”
European Journal of Women’s Studies, Vol 25,
No 4, pp 403–18.
Tomlinson, B (2013): “Colonising Intersectionality:
Replicating Racial Hierarchy in Feminist Academic Arguments,” Social Identities, Vol 19,
No 2, pp 254–72.
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13
COMMENTARY
Citizenship (Amendment)
Rules, 2024
moral or immoral, are contained in their
guiding legislation.
Background: The Refugee
Question
An Immanent Scrutiny
Ayan Guha
The newly notified Citizenship
(Amendment) Rules, 2024 have
not so far been subjected to a
sufficient amount of immanent
evaluation, a kind of scrutiny
that will objectively assess CAR’s
potential to fulfil the Citizenship
(Amendment) Act’s declared
objective, which is to resolve the
citizenship woes of non-Muslim
migrants from neighbouring
Islamic countries. Such scrutiny
reveals several shortcomings of
the CAR.
The author acknowledges the funding received
from the British Academy, United Kingdom (UK).
Ayan Guha (ag928@sussex.ac.uk) is a British
Academy International Fellow, School of
Global Studies, University of Sussex, UK.
14
T
he Citizenship (Amendment) Rules
(CAR), 2024 have been notified to
implement the Citizenship (Amendment) Act (CAA), 2019 and the old debate
over the contentious issue of citizenship
has got a fresh fillip. Importantly, the
recently notified rules have thrown
up new questions, which need to be addressed by going beyond the old frame
of argumentation, while not abandoning it. The CAA fast-tracked the grant
of Indian citizenship to Hindu, Sikh,
Parsi, Jain, Buddhist, and Christian
migrants, who had entered India from
three neighbouring Islamic states of
Afghanistan, Bangladesh, and Pakistan
by 31 December 2014 due to religious
persecution.
The fast-tracking for these non-Muslim
migrants was done by reducing the requirement of residency from 11 years to
just five years excluding the mandatory
one-year residency immediately preceding the citizenship application.1 The CAA,
and by implication the CAR, has been
severely criticised as being unconstitutional for exclusion of the Muslims from
this fast-tracking process. However, the
newly notified rules have not so far been
subjected to a sufficient amount of immanent evaluation, a kind of scrutiny
that will objectively assess the CAR’s
potential to fulfil the CAA’s declared objective, which is to resolve the citizenship woes of the non-Muslim migrants
from the neighbouring Islamic countries. And, it is highly imperative to conduct such a scrutiny with regard to the
CAR. This is due to the fact that legislative rules like the CAR, unlike enacted
legislation like the CAA, do not define
legislative purpose but simply put in
place a practical mechanism to execute
whatever objectives, sound or unsound,
The rationale of the CAA is derived from
the persecution of religious minorities in
the neighbouring Islamic states of Afghanistan, Bangladesh, and Pakistan. However, in reality, CAA is largely aimed at
the Bengali Dalit refugees, mainly concentrated in West Bengal and also to a
lesser extent in Assam. They mainly belong to the lower caste Namasudra community and the anti-Brahminical Matua
sect. In colonial times, the Namasudras
constituted the largest Hindu caste
group in East Bengal, which became
East Pakistan after the partition of India
in 1947 and later Bangladesh in 1971–72.
The Namasudras have been one of the
worst victims of the partition of Bengal
in 1947. As a result of the partition, the
Namasudras lost their traditional habitat as the Namasudra-dominated districts went to East Pakistan. The vast
majority of the population influx in the
initial waves of partition-induced migration was made up of higher caste families that were relatively well-off and
were in a position to deal with the financial implications of displacement. They
mostly belonged to the educated middle
classes with jobs or professional skills
and the gentry class with a fair amount
of landed property and social connections. Few belonging to the Namasudra
and other lower caste groups could migrate at this stage because of livelihood
concerns. Due to their reliance on agriculture and lack of social networks on
the other side of the border, they were
not in a position to immediately abandon their traditional cultivable land.
In December 1949, communal violence
broke out in Khulna and it quickly spread
to other parts of East Pakistan. With the
rise in communal tension after the riots
in Khulna, the Namasudras began to migrate to India and their exodus kept happening on the heels of every major event
of communal disturbance throughout the
following decades in East Pakistan/Bangladesh (Basu-Raychaudhury 2004). As a
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consequence, the Hindu population of
Bangladesh has been continuously declining. Apart from the threat to life and
honour, one major reason for migration
is the land-grabbing of the Hindu peasantry with the help of enemy/vested
property legislation.2 This legislation allowing the government to confiscate the
land of the people identified as the enemies of the state was widely and selectively applied to the Hindu peasantry,
mainly belonging to the Namasudra
community (Yasmin 2015; Panday 2016).
Abul Barkat’s (2008) famous study shows
that a whopping 44% of Hindu households were affected by this law, resulting in the dispossession of 45% of all
land owned by the Hindus. The largest
exodus of refugees, however, happened
in 1970–71 during the Bangladesh liberation war. Thus, the Namasudra migration in Bengal happened in phases unlike in Punjab, where massive intercommunity violence at the time of partition
led to a de facto exchange of population
along religious lines. It is against this
backdrop that citizenship emerged as a
major issue for the Namasudras.
Citizenship Conundrum
The citizenship status of post-1971
migrants is particularly tricky. In this
context, it needs to be mentioned that
Article 6 of the Constitution draws a distinction between two categories of migrants from Pakistan (including the present-day Bangladesh or previously East
Pakistan): those crossing over to Indian
territory before 19 July 1948, and those
who arrived in India after 19 July 1948.3
While the former would automatically
become citizens of India, the latter will
need to apply for citizenship. But in view
of the massive influx of refugees in the
wake of the Bangladesh liberation war,
the Government of India (GoI) adopted a
policy of not granting citizenship to those
who crossed over to India from East Bengal on 25 March 1971. It issued a letter (No
26011/16/71-10 dated 29/11/1971) to all
chief secretaries of states and union territories, which stated:
Refugees who have crossed over to India
from East Bengal since the 25 March 1971 on
account of the situation in the area cannot
be treated as ordinarily resident of India.
Economic & Political Weekly
EPW
MAY 4, 2024
They are expected to return to their native
places when the condition permit. They
should not be considered for registration as
Indian citizenship under Section 5(1)(a) of
the Citizenship Act, 1955 read with citizenship rules, 1956. If such refugees make applications to the collectors who are prescribed
authorities for purpose of registration as
Indian citizenship under Section 5(1)(a) of
the Citizenship Act, 1955, such applications
should be rejected.
The Indian government felt that with
the establishment of Bangladesh as a secular state, refugees displaced by the Bangladesh liberation war could go back to Bangladesh and lead a safe and peaceful life
there. However, the GoI was ready to legally accommodate those who came before
25 March 1971 from East Pakistan. In its
letter (No 11/180/72/TX dated 30 September 1972), the union home ministry stated:
according to the understanding between the
governments of India and Bangladesh, the
refugees who came to India before 25 March
1971, whether Bengalis or non-Bengalis
would not be sent back to Bangladesh.
However, after the assassination of Mujibar Rahman, the founding father and
the first Prime Minister of Bangladesh in
1975, and the subsequent declaration of
military rule, the situation became different in Bangladesh and consequently no
large-scale repatriation could happen.4
But the GoI consistently maintained the
policy of not recognising the post-1971
migrants as citizens. For instance, in
1988–89, the union home ministry in its
written submission before the Estimates
Committee of the Parliament stated:
A large number of migrants have crossed
over to India from East Pakistan (now Bangladesh) after 25 March 1971. Although these
persons are eligible for grant of citizenship
claiming the benefit of Indian origin for registration under Section 5(1)(a) of the Citizenship Act, a policy decision was taken in 1971
not to consider the requests of such persons
for grant of citizenship by registration since
they are expected to return to their native
places as soon as the conditions permit ...
However, persons who migrated from East
Pakistan prior to March 1971 are eligible to
be considered for grant of Indian citizenship
by registration U/S 5(1)(a) of the Act provided they fulfil the statutory requirements.
(Estimates Committee 1988–89: 8)
Therefore, those who migrated from
East Pakistan before 19 July 1948 automatically became citizens. Those who
migrated from East Pakistan between 19
July 1948 and 24 March 1971 were eligible to obtain citizenship subject to the
fulfilment of residency requirements
and many of them received citizenship.
Often the officers in charge of the refugee camps provided such refugees with
citizenship certificates (Biswas 2020: 36).
However, those who migrated from
Bangladesh since 25 March 1971 remained
ineligible for citizenship. Amid such a
scenario, the CAA, 2003 complicated the
situation further by legally categorising
migrants without valid travel documents
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15
COMMENTARY
as illegal migrants or infiltrators. Since
most of the Namasudras and other Hindu
refugees arrived in India escaping persecution, they could not bring with them
valid travel documents like passports and
visas. Consequently, after the enactment
of the 2003 amendment to the Citizenship
Act, from refugees they became illegal
immigrants in legal terms. Further, the
2003 amendment provides that, those
born after 3 December 2004 will only be
deemed as citizens of India by birth if
one of their parents is an Indian and the
other is not an illegal immigrant.
Thus, the 2003 amendment to the Citizenship Act made it impossible for children born in refugee families after the
cut-off date of 3 December 2004 to become Indian citizens by birth, if either of
their parents is legally an “illegal migrant.” Previously, in accordance with
the CAA, 1986, it was sufficient if either
of the parents of a person was an Indian
citizen at the time of their birth for obtaining Indian citizenship. Since the enactment of the 2003 amendment, Namasudra refugees have been regularly
suspected of being “Bangladeshis” or illegal infiltrators during registration for the
electoral rolls and issuance of documents like passports and caste certificates (Guha 2022: 33).
of government documents like Aadhaar,
voter, and ration cards.
However, they are likely to face difficulties in producing the country-of-origin documents, which are documents issued by the Government of Afghanistan/Bangladesh/Pakistan.6 Is it wise to
assume that everyone who fled these
nations in order to safeguard their lives
and dignity was able to bring such documents with them? Even if some of them
could, is it prudent to presume that these
documents are still in the custody of their
second- or third-generation descendants? In this connection, a further question arises with regard to the verification
of these foreign government documents.
The CAR provides for verification through
the security agencies and this has been a
long-standing position of the concerned
government agencies, while the political
leaders have been promising the grant
of citizenship to non-Muslim refugees
without the production of any documents. In the Joint Parliamentary Committee (JPC) on the Citizenship (Amendment) Bill 2016, the Ministry of Home
Affairs had submitted:
New Rules, New Puzzles
But this verification process appears
to be quite opaque and with this kind of
verification mechanism, the EC’s decision in all likelihood will be based upon
a highly subjective assessment. Further,
will it be possible for the Indian security
agencies to gather information about the
past antecedents of a foreign national
without the cooperation of the concerned
government in the form of any formal
arrangement? And, why would these
foreign governments—some of which
have strained relations with the Indian
government—be prepared to provide Indian security services with evidence
which will prove that religious persecution had occurred on their territory?
Even though it could theoretically be argued that security agencies have alternative ways to obtain information, will
it not be extremely time-consuming, if
not fully impossible, to obtain reliable
information without the assistance of
The CAA promises to resolve these problems faced by non-Muslim refugees by
granting them citizenship with the help
of the CAR. It is in this context that a dispassionate analysis of the CAR becomes
imperative. The CAR sets up two committees: empowered committee (EC) and
district level committee (DLC). The DLC
will first examine the online application
for citizenship and after preliminary
checks will forward it to the EC, which will
take the final call after due verification
through security agencies. The applicants
will have to submit two proofs—one
document to prove their country of origin and the other to prove their entry
into India by the cut-off date of 31 December 2014. In simple terms, the entry
document could be any Indian government document issued before the cut-off
date.5 The targeted beneficiaries like the
Namasudras generally are in possession
16
Inputs from security agencies along with
other corroborative evidence in the print/
electronic media would help to establish religious persecution in a foreign land. (Joint
Parliamentary Committee 2019: 37)
the concerned country’s government? It
is interesting to note that, as regards authentic verification of the claims of the
applicants, the Intelligence Bureau (IB)
itself had accepted the difficulty of obtaining such information before the JPC:
The individuals claiming religious persecution and seeking Indian citizenship had
entered India decades ago, mostly in the
aftermath of partition of the country when
a large-scale migration between India and
Pakistan took place. It is not possible to
verify their claim now. However, for recent
cases, if any, due verification would be made
before their claim for Indian Citizenship is
entertained. (Joint Parliamentary Committee 2019: 38)
Last but not the least, the applicants
are required to submit an affidavit declaring their nationality, including religion. Hence, in the event that the application is rejected, the applicant will formally become a foreign national by virtue of their own admission. Moreover,
most of the refugees already possess a
voter card and exercise their voting
rights. But as a part of the application
process, they will need to declare their
nationality as Afghani, Bangladeshi, or
Pakistani. Will it not imply that they
committed fraud in enrolling themselves as voters without being citizens of
India (Chatterjee 2024)? All of these
anomalies are likely to discourage many
proposed beneficiaries from even initiating the application process.
Conclusions
Is there a way to get out of this maze?
Possibly not. But one option could be
recognising all the Indian origin residents as citizens with effect from a cutoff date. Under the CAR, this will mean
waiving off the requirement of proving
the country of origin. This will also lead
to the secularisation of the entire endeavour. In this connection, it also needs
to be mentioned that in all probability
this maze is a creation of electoral calculations. These calculations are constitutive of two components: One pertains to
the Namasudras and the other is linked
with the attempts to build a larger proHindu electoral narrative. In the short
run, the CAR is likely to provide electoral
dividends by consolidating the Namasudra support in favour of the ruling
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Bharatiya Janata Party (BJP). In the long
run, it could, however, be politically
counterproductive. The process of granting citizenship is ultimately a bureaucratic
process. Bureaucracy by its own logic
will look at each application impersonally without emotions and sentiments.
And, as we have seen, it is indeed tricky,
cumbersome, and time-consuming for
any governmental system to reasonably
establish the fact of religious persecution in a foreign land on the basis of documents issued by foreign governments.
So, there remains ample prospect of
delay and red tape and even unfavourable outcomes, which might very well
lead to disillusionment and resentment
among the expected beneficiaries in the
long run. But the notification of the
CAR also has ramifications beyond the
Namasudra-dominated regions, as this
sends out a clear and powerful pro-Hindu
message to the larger electorate across
the country.
2
3
4
5
Notes
1
Under the Citizenship Act, 1955 for the acquisition of citizenship through registration, the
residency requirement for a person of Indian
origin is seven years while for the acquisition
of citizenship through naturalisation, the
6
requirement is 11 years for anyone in addition
to one year of residency immediately preceding
citizenship application. A person of Indian origin is a person who or either of whose parents,
was born in undivided India.
Enemy Property Act which came into effect
first in 1965 was remodelled as Vested Property
Act in 1974. It was finally repealed in 2001 and
the Vested Properties Return Act (2001) was
enacted. However, the property restoration
process has not kicked off in any meaningful
way since the leaders of the major parties have
allegedly been the biggest beneficiaries of
land-grabbing.
Migrants here refer to only those who or whose
parents/grandparents were born in undivided
British India.
Secularism was replaced in Bangladesh’s Constitution with “absolute trust and faith in Almighty Allah” in 1977. In 1988, Islam was
declared as the state religion.
The admissible documents are visa and
immigration stamps, registration certificates
or residential permits, slips issued by the census enumerators, ration cards, Aadhaar cards,
PAN cards, driving licenses, birth certificates,
land or tenancy records, bank or post office accounts, marriage certificates, educational certificates, insurance policy, electricity or utility
bills, court records, municipality trade licences, certificates issued by an elected member of
any rural or urban body or officer thereof or a
revenue officer, any government letter and any
other government (including bank and public
sector undertakings) document. The notable
omission is the specific mention of voter card,
though it should ideally come within any other
government document.
The admissible documents are passport, registration certificate or residential permit, birth
certificate, school certificate, identity document of any kind, any licence or certificate,
land or tenancy record or any other document
issued by the Government of Afghanistan,
Bangladesh or Pakistan. A document that
shows either of the parents or grandparents or
great grandparents of the applicant is or had
been a citizen of one of these three countries,
will also be admissible.
References
Barkat, Abul et al (2008): Deprivation of Hindu
Minority in Bangladesh: Living with Vested
Property, Dhaka: Pathak Shamabesh.
Basu-Raychaudhury, Anasua (2004): “Life after
Partition: A Study on the Reconstruction of
Lives in West Bengal,” Panel 33: Ethnic Cleansing, Migration, and Resettlement: Partition &
Post-Partition Experiences, Proceedings of the
18th European Association for South-Asian
Studies, Sweden: Swedish South Asian Studies
Network, pp 1–15.
Biswas, Sukriti Ranjan (2020): Rajnoitik Dhokar
Shikar: Deshantarito Udbastu, Machlandopur,
West Bengal: Chiyanobboi Prakashani.
Chatterjee, Partha (2024): “Chholona, Na Ki Pratarona,” Anandabazar, 18 March.
Estimates Committee (1988–89): “Rehabilitation
of Migrants from East Bengal (8th Lok Sabha),”
New Delhi: Lok Sabha Secretariat.
Guha, Ayan (2022): The Curious Trajectory of Caste
in West Bengal Politics: Chronicling Continuity
and Change, Leiden/Boston: Brill.
Joint Parliamentary Committee (2019): “Report on
the Citizenship (Amendment) Bill, 2016 (16th
Lok Sabha),” New Delhi: Lok Sabha Secretariat.
Panday, Pranab Kumar (2016): “Politics of Land
Grabbing: The Vested Property Act and the
Exploitation of Hindu Communities in Bangladesh,” International Journal on Minority and
Group Right, Vol 23, No 3, pp 382–401.
Yasmin, Taslima (2015): “The Enemy Property
Laws in Bangladesh: Grabbing Lands under the
Guise of Legislation,” Oxford University Commonwealth Law Journal, Vol 15, No 1, pp 121–47.
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17
COMMENTARY
Bharatiya Nyaya Sanhita and
the False Promise to Marry
S M Aamir Ali, Anuska Vashist, Anuttama Ghose
Section 69 of the Bharatiya Nyaya
Sanhita, 2023 focuses on the
criminalisation of sexual
intercourse by a false promise to
marry, which may be through
deceitful means with no genuine
intention to be fulfilled. This
provision has been discussed to
have a contrary effect to its actual
purpose by reinforcing patriarchal
norms and curtailing women’s
autonomy, threatening and
restricting live-in relationships
based on inter-caste and
inter-religious lines, and lastly,
creating ambiguity in defining the
law and urging progressive
judicial interpretation.
T
his article is a continuation of the
series of Law & Society columns
published in EPW with respect to
the Bharatiya Nyaya Sanhita (BNS), 2023
and the changes brought by the union
government within the act in replacing
the Indian Penal Code (IPC). In this article,
the insertion of Section 69 of the BNS is
discussed, which criminalises the “false
promise to marry” through an argument
based on how the continuation of Section
69 of the BNS attracts more harm than
benefit to society, which has been entirely
ignored by the government even after
facing harsh criticism of the first draft.
This provision seeks to punish men who
lure women into sexual relationships by
concealing their identities or by a promise
to marry later and then leave them
stranded. The section aims to punish the
accused with an imprisonment of up to
10 years and a fine. Under the same
section, the act construes the false
promise of employment or promotion
under “deceitful means.”
False Promise to Marry under
the IPC
The authors thank the anonymous reviewer for
their valuable suggestions, which immensely
helped in improving this article.
S M Aamir Ali (smaamiraliofficial@gmail.com)
teaches at the Symbiosis Law School, Pune
Symbiosis International (Deemed University)
Pune, Maharashtra. Anuska Vashist (anuska.
vashist004@gmail.com) is a student at the
Symbiosis Law School, Pune. Anuttama Ghose
(anuttamaghose@gmail.com) teaches at the
School of Law, Dr Vishwanath Karad MIT
World Peace University, Pune.
18
Before the introduction of Section 69 in
the BNS, the courts in India interpreted
cases of sexual intercourse on false
promise to marry under Section 375,
read along with Section 90 of the
IPC. Section 375 defines consent as an
“unequivocal voluntary agreement when
the women by words, gestures or any
form of verbal or non-verbal communication, communicates willingness to participate in the specific sexual act,” and
Section 90 defines that consent obtained
under “fear of injury” or “misconception of
facts” is not a valid consent (Kalia 2023).
The courts have found it challenging
to identify intent and consent in the cases
of false promise to marry and have
distinguished between “false promise”
and “breach of promise” over a few decades. After many conflicting high court
judgments, the Supreme Court in Uday v
State Karnataka (2003) clarified its position by observing that whether a false
promise to marry amounts to rape must
be decided on a case-by-case basis. It depends on whether a man obtained consent under a false promise to marry and
had never intended to marry the woman, or the man believed that the woman
gave consent based on a false promise to
marry (Project 39A 2023).
Subsequently, in Dileep Singh v State of
Bihar (2005), the accused was acquitted by
the Supreme Court for a breach of promise
on no evidence of the intention of the man
not to marry the girl even when he was
accused of rape on the basis that a genuine
reason for not fulfilling the promise
cannot be equated as an act of rape. This
is when the apex court’s interpretations
also create ambiguity in identifying a
mala fide nature of the promise. After
Dileep Singh in Deepak Gulati v State of
Haryana (2013) and in Pramod Suryabhan
Pawar v State of Maharashtra (2019), the
court recognised that when a promise of
marriage is made with an intention to
break it, the consent obtained will be determined as a “misconception of fact”
and be considered as rape. In 2023, the
Supreme Court in Naim Ahamed v State
(NCT of Delhi) discussed a new dimension to such cases by observing whether
consent was gained under a false promise
to marry given from the very beginning or
if there was any reason for the change of
a genuine promise to marry to the false
promise to marry at a later stage of the
relationship. By applying this jurisprudence, the courts in India have enforced
social hierarchies such as caste and religion, as critics have argued (Garg 2019).
Section 69 of the BNS has merely codified the offence previously interpreted
under the IPC without clearly distinguishing between false promise and breach of
promise, thereby having no effect in clearing the ambiguity under the existing laws.
Intention to Marry
Section 69 requires to fulfil three criteria
for the act to be an offence: (i) gaining
consent by deceitful means; (ii) making
a false promise to marry without intention to fulfil it; and (iii) having consensual sexual intercourse with a woman.
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The jurisprudence, precedents, and the
provisions under criminal law have, to
date, not been able to define intention and
consent. Civil law has expressly defined
the term “free consent,” providing a definite course of interpretation of laws
and a quick disposal of judgments. On
the contrary, criminal law faces numerous complexities in determining valid
consent, making it impossible for the
parties, litigants, and judges to prove
and interpret cases. Section 69 is based
on the two most intimate acts, that is,
marriage and sexual intercourse, and the
former holds a more significant influence
on the latter because sexual intercourse
is first influenced through psychological
and biological factors and second is
conventionally opposed by Indian society
before marriage, thereby making a
promise of marriage more convincing. In
such circumstances, proving valid consent becomes extremely difficult, and
the new law seems ineffective in defining the same.
The second ingredient is intention,
which is a psychological and intrinsic
factor of a human being and cannot be
proved by a second person. The criminal
jurisprudence has, to date, not provided
a set definition of intention, and litigants
find it impossible to prove it in a court of
law, which has the same effect in the
cases of false promise to marry. While
“deceitful means” may be proved through
the acts of the accused, the mala fide
intention, which is the core ingredient,
may not be legally proved. The codification
of the offence of false promise to marry
has narrowed the interpretation of the
offence, making it disadvantageous to
the genuine victims of such an offence.
Ambiguous Application
and Overlap
Section 376C of the IPC (Section 68 of the
BNS) covers situations where there was
consent at the time of the sexual intercourse, which was not vitiated. But the
terminology “not amounting to rape”
under Section 69 of the BNS causes ambiguity as deceit conceptually vitiates
consent; and so does a breach of promise,
which involves the accused not having
any intention of going through with
the promise (Satish et al 2023). Further,
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MAY 4, 2024
Sections 68 and 69 of the BNS are
observed to overlap with each other. The
former criminalises the use of fiduciary
relationships or the power of authority to
coerce women into sexual intercourse,
and the latter criminalises sexual intercourse by deceitful means and false
promises to marry (Project 39A 2023).
While Section 68 provides a clear definition of the term “sexual intercourse,”
that is, sexual acts beyond penile-vaginal penetration, Section 69 continues to
be ambiguous about the term. Moreover,
Section 69 fails to provide a minimum
punishment and only prescribes a maximum punishment of 10 years. Through
this provision, the government retains
the colonial penal philosophy by over-relying on imprisonment and mandatory
minimum punishment to invoke fear in
the people’s minds.
Curtailing Women’s Bodily
Autonomy
Feminist scholars have argued that the
law permits the terrorisation and sexualisation of women’s bodies (Frug 1992).
The courts interpreted the offence of
false promise to marry under rape as
these cases were at their peak in 2016,
and the main target were women who
either belonged to educationally and
socially backward classes or were incapable of seeking legal remedies. The
courts aimed to punish the accused
with the same punishment as rape as
consent was not free and created a fear
of deterrence.
Feminist scholars have also raised a
concern regarding the interpretation of
false promises to marry by the judiciary
under the IPC, where free consent of a
woman is subjected to acute scrutiny.
Through a series of precedents, it can be
observed that consent given by a woman
is not considered to be violated based on
her age, past sexual experiences, marital
status, education, and societal background
(Garg 2019). It is assumed that the
woman is mature while giving consent if
they satisfy any of the said criteria. This
interpretation has been a significant
impairment to the autonomy of women
and reinforces patriarchal norms.
The courts have exempted the accused
from a breach of promise when the promise
of marriage is broken due to genuine reasons. However, this is merely circumstantial evidence and does not prove the
man’s mala fide intentions (Tiwari 2021).
In such cases, the man’s intentions become
the core issue of the case and shift the
burden of proof on the woman to prove
that her consent was violated. The codification of an offence creates more ambiguity
in proving a man’s intention. It takes away
the autonomy of a woman to give free consent or have a mind of her own to perform
consensual sexual intercourse (Karwa
2023). The law re-victimises women regardless of their educational or societal
background. Previously, such cases were
judged through courts’ interpretation,
giving them a broader scope and room for
improvement. However, the codification
of the offence needs to be clarified and
made consistent with its purpose of safeguarding women’s rights.
Endogamy and Interfaith
Relationships
India has historically followed the concept of endogamy even before we gained
independence, and it has been a massive
struggle since then to abolish it and find
a way forward that allows a person to
choose their partner freely. Section 69
of the BNS becomes a tool to curtail that
freedom. It acts as a threat to bring back
the struggles and oppressions from the
past, which have led to not only the
exploitation of women but also men
belonging to lower castes or marginalised communities. It could be argued
that Section 69 of the BNS will promote
endogamy within society under the
umbrella of allegedly safeguarding
women from sexual exploitation. This
can be foreseen in circumstances where
the guardians of the couple gain knowledge of the premarital sexual relationship of the couple, thereby initiating
criminal proceedings of rape, especially
by the guardians of the girl under Section 69 of the BNS (Vishwanath 2023).
The fear of criminal proceedings under
Section 69, not for a lack of consent but
because of consent, will act as a tool for
promoting endogamy.
On the contrary, it is argued that by
the introduction of Section 69, women will
be safeguarded from sexual exploitation
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through unlawful conversion to a different
faith by deceitful means. Some people
have suggested codifying such a law to
prevent cases specifically of “love jihad”
(Nath 2023). The law protects the rights
of women who are lured into acts of sexual intercourse on the promise of marriage and then converted into different
faiths. The same has proven to have no
remedy through judicial interpretation.
While the concerns of coerced conversion and sexual exploitation hold valid
ground, they also raise the possibility of
restricting interfaith marriages and getting couples targeted based on their religious or caste identity. It can be argued
that there is nothing like “love jihad,” as
the government failed to provide any
data on this phenomenon (Sonkar 2022).
Adult men and women are free to marry
as it is their fundamental right protected
under the Constitution, and also their
right to convert, which is guaranteed by
the fundamental right to religion. The
issues concerning relationships and
marriage are personal, and criminalising “a promise to marry” without proving the requisite intention would be
tantamount to infringement of people’s
right to privacy.
Instances such as the Government of
Maharashtra’s resolution to track interfaith/inter-caste marriages, which insidiously target “love jihad” or seeks to “reconcile” “estranged” women with their
family, highlights the government’s endogamous stand that one should not marry
outside one’s faith (Chander 2023). With
such a law in force, the government aims
to promote endogamy while denying
women sexual agency and any live-in
relationship outside their caste, religion,
or culture. These initiatives by the government prove to be contrary to their true
nature as they target only interfaith relationships, putting them under the spotlight and raising a reasonable suspicion
of a certain political and religious idea
sponsored by the government.
Another reason for rising endogamy
and hurdles faced by interfaith couples
is that under Section 6 of the Special
Marriage Act, 1954, it is mandatory to
publish the intention of the parties to
marry for a period of 30 days for raising any
objections against the notified marriage,
20
and during this period, interfaith couples face societal pressure, harassment,
or even violence (Bhandare and Karwa
2020). The cases of killing over interfaith
marriages by the family of the other party is an unfortunate yet frequent consequence of interfaith marriages. In fact, in
many circumstances, the courts have
failed to provide protection to these interfaith couples (Ahmed 2024). In light of
these challenges, the provision under
Section 69 of the BNS will become a
weapon in the hands of the executive to
curb many interfaith marriages.
Conclusions
The BNS has made no significant changes
after being given a more profound analysis
by the Standing Committee. Section 69
faced an intense backlash and criticism
from legal scholars and academicians as
it could result in casteist and religious
prejudice and discrimination. When
initially introduced by the committee, the
law was based on replacing the colonial
roots from Indian legal history. However,
promoting caste and religious endogamy
through such laws has counteracted the
entire objective of the act.
Furthermore, the introduction of this
law, along with specific other laws in the
BNS, was to protect the rights of women,
but it has proven to significantly position
them at a weaker status and question
their autonomy in the act of consensual
sexual intercourse, thereby promoting
the already existing patriarchal norms in
the society. The law has created a dichotomy between the Indian gender roles in
society. The essentials to prove the man’s
intention leave a very narrow approach
for a remedy for women, resulting in a
contradictory effect of the law.
The laws under the BNS have brought
no gender neutrality, a prevalent and
essential factor in contemporary Indian
society. The law becomes a bane to couples
in live-in or intimate relationships with
bitter endings. It becomes a tool for
vengeance, and targets marginalised men
whose innocence becomes challenging
to prove. It is hoped that such a law can
be well interpreted by the judiciary
with a more forward-looking approach
which overcomes the disadvantages of
this law.
References
Ahmed, A U (2024): “How Procedure Upended
Personal Liberty in Allahabad High Court’s Refusal to Protect Interfaith Couples,” Article 14,
https://article-14.com/post/how-procedureupended-personal-liberty-in-allahabad-highcourt-s-refusal-to-protect-interfaith-couples65cc3a68346e2.
Bhandare, Namita and Surbhi Karwa (2020): “How
the Special Marriage Act Is Killing Love,”
Article 14, https://www.article-14.com/post/
how-the-special-marriage-act-is-killing-love.
Chander, M (2023): “Why Maharashtra Govt’s
Move to Track Interfaith Marriages Is Unconstitutional and Further Endangers Women,”
Article 14, https://article-14.com/post/whymaharashtra-govt-move-to-track-interfaithmarriages-is-unconstitutional-further-endangers-women-63be1cdc5f5a1.
Frug, M J (1992): “A Postmodern Feminist Legal
Manifesto (An Unfinished Draft),” Harvard
Law Review, Vol 105, No 5, pp 1045–75.
Garg, Arushi (2019): “Consent, Conjugality and
Crime: Hegemonic Constructions of Rape Law
in India,” Social and Legal Studies, Vol 28, No 6,
pp 737–54.
Kalia, Saumya (2023): “How Are ‘False Promise to
Marry’ Cases Treated in the New Criminal
Law Bill?” Hindu, https://www.thehindu.com/
news/national/how-are-false-promise-to-marry-cases-treated-in-the-new-criminal-law-billexplained/article67213081.ece.
Karwa, Surbhi (2023): “Criminal Law Bills: The
Section on ‘False Promise to Marry’ Aids Victim
Blaming,” Quint, https://www.thequint.com/
opinion/new-criminal-law-bills-ipc-crpc-evidence-act-false-promise-of-marriage-sectionanalysis.
Nath, Mishra B (2023): “Will Proposed Criminal
Laws Curb Marriages through Deceit?” NDTV,
https://www.ndtv.com/opinion/will-proposedcriminal-laws-curb-marriages-through-deceit4600106.
Satish, M, P P Dash and A Pandey (2023): “Bharatiya
Nyaya Sanhita Bill: Implications of Proposed
Changes to the Indian Penal Code,” NLS Blog,
https://www.nls.ac.in/blog/bharatiya-nyayasanhita-bill-implications-of-proposed-changes-to-the-indian-penal-code/.
Sonkar, S (2022): “Policing Interfaith Marriages:
Constitutional Infidelity of the Love Jihad
Ordinance,” Journal of Law and Religion,
Vol 37, No 3, pp 432–45.
Tiwari, A (2021): “Make Women’s Voices Central to
False Promise to Marry Cases,” NewsClick,
https://www.newsclick.in/make-women-voices-central-alse-promise-marry-cases.
Vishwanath, N (2023): “Controlling Women’s Sexual
Autonomy,” Hindu, https://www.thehindu.com/
opinion/op-ed/controlling-womens-sexual-autonomy/article67251409.ece.
MAY 4, 2024
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Bridging the Gender Gap
The Promise and Peril of Using
Artificial Intelligence and Machine
Learning to Accelerate Gender Equality
Satender Rana, Anand Rao
The use of algorithms is fast
becoming the status quo in
tackling complex social issues.
Machine-learning tools are also
penetrating the social impact
space. While these tools offer
prospects for solving complex
social issues, there are concerns
pertaining to the development of
biased algorithms, which in turn
aggravate the already existing
inequalities. This article delves
into how these technologies
may affect the pursuit of gender
equality. It also attempts to
identify potential solutions
to address biases in historical
data, human cognitive biases,
and the under-representation of
marginalised groups in teams
developing the algorithms.
Satender Rana (satender.rana@isdm.org.in)
is with the Knowledge Institute in the Global
Knowledge Hub, Indian School of Development
Management, Noida. Anand Rao (anandr2@
andrew.cmu.edu) teaches at the Heinz College
of Information Systems and Public Policy at
Carnegie Mellon University, Pittsburgh.
30
A
rtificial intelligence (AI) and
machine learning (ML) are having
a dramatic impact on economies
and politics across the world. Tools such
as generative AI are bringing a paradigm
shift across sectors and disciplines.
Generative AI would boost productivity
by giving humans a new “superpower”
(Chui et al 2023). While data technologies
can certainly be leveraged for economic
growth, it remains to be seen what they
can offer to advance Sustainable Development Goals (SDGs) such as gender equality,
on which progress has slackened in
recent times (UN 2023).
The world is falling short of achieving
goals for gender equality by 2030, as the
progress on SDG 5 (gender equality) has
been slow, and it will take significant
time to address gaps in various areas
such as legal protection, leadership representation, and economic and political
participation (UN 2023). In addition, the
COVID-19 pandemic has sharpened gender inequalities in healthcare, education, and the economy.
Emerging data technologies such as
AI, ML algorithms, and generative AI can
help accelerate progress on gender
equality in various ways. For example,
developing innovative credit models for
women’s financial inclusion can help
overcome the traditional trust barrier
that deems women less creditworthy
because they do not own assets as collaterals, and therefore prevents their
financial inclusion.
Furthermore, generative AI has the
potential to catalyse the synthesis of a vast
amount of existing research evidence on
gender equality. By leveraging AI, policymakers and organisations can gain comprehensive insights much faster relative
to traditional systematic literature reviews
and meta-analyses to inform the design
and implementation of targeted interventions aimed at advancing gender equality.
Potential of AI
Financial inclusion: The application of
AI-based credit scoring systems is improving the delivery of financial services.
Emerging credit platforms are overcoming traditional barriers to accessing credit,
such as lack of collaterals or credit history,
by using alternative data sources and innovative credit scoring models. Some of
these platforms use mobile phone data
such as spending habits and bill payments to assess creditworthiness, which
can provide a more accurate picture of a
borrower’s financial situation than traditional credit scores. This approach is
beneficial for women who may not have
formal credit histories but have active
mobile phone accounts.
In this way, machine learning models
(MLMs) can play a significant role in improving financial inclusion for women.
Additionally, digital platforms can offer
greater convenience and privacy for
women who may encounter cultural or
social barriers while visiting physical
bank branches. With more women opening bank accounts, and with banking
sakhis (female friend) and mobile banking taking services to doorsteps, mobile
wallets for spending can further enhance
women’s economic mobility and build
their credit history. Digitising the transactions of self-help group banking can
generate additional data for credit scoring.
Addressing gender-based violence:
ML tools present opportunities to develop
prediction models that can help prevent
gender-based violence. These models
can be used to identify hotspots of gender-based violence, predict future violence
trends in different regions, and assess the
recidivism risk of perpetrators of genderbased violence (González-Prieto et al
2023). By leveraging these technologies,
proactive steps can be taken to address
violence before it occurs, making communities safer for women.
Synthesise evidence: Research and development is one of the four key areas
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where applied generative AI will create
significant value (Chui et al 2023). In the
context of development research, a treasure trove of evidence exists in unstructured data, such as research reports and
journal articles. Generative AI can help
synthesise specific, granular insights from
these large data repositories, which is a
time- and labour-intensive task. The use of
generative AI for evidence synthesis offers
excellent potential to catalyse social research and develop evidence-informed
social policies and interventions. For example, UNDP’s Artificial Intelligence for
Development Analytics (AIDA) portal
employs Generative AI to sift through a
volume of nearly 6,000 evaluation reports in its repository to synthesise evidence (UNDP 2023). These tools offer great
promise for synthesising evidence faster,
catalysing the generation of evidence
gap maps, and zeroing in on solutions.
Pitfalls of Data Technologies
While data technologies offer big development promises, there is also the danger of widening existing gender biases
and contributing to further exclusion if
the algorithms are perverted by historically gender-biased data and human
cognitive bias.
Algorithmic bias: Algorithmic biases
are like human cognitive biases and
prejudices. AI algorithms are only as good
as the data they are trained on, so the
algorithm will be biased if the data is
biased. This can have negative consequences. A recent study reported that
cognitive biases can threaten women’s
financial inclusion, mainly due to algorithmic bias (Kelly and Mirpourian 2021).
For instance, many emerging fintech
companies use mobile phone data to
approximate the creditworthiness of individuals. But if a credit score model is
based on historical data that exhibits
gender skew, AI would only further that
bias. An algorithmically biased credit
scoring model could lead to a situation
where a woman who is as creditworthy as
a man is more likely to be denied credit.
Generative AI hallucinations: Generative
AI hallucinations are results developed
by generative models that are irrational,
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MAY 4, 2024
fabricated, false, provide misleading information, or are inconsistent with logic
(Moran 2023). Hallucinations can happen when AI models misunderstand inputs, misconstrue queries, or are trained to
provide results without connection to
empirical data. When they fabricate information, generative AI hallucinations
can be dangerous.
Generative AI models are still in their
early stages of development and will
need time to evolve to the point where
the content they generate is reliable and
replicable. The team at ISDM conducted
a small experiment using ChatPDF, a
ChatGPT-based tool that allows users to
upload a PDF document and interact
with it by giving prompts related to the
PDF content. When we prompted the
system to generate results on a report on
the evaluation of the Beti Bachao, Beti
Padhao scheme (NCAER 2020), it produced 100% fabricated data. The algorithms kept hallucinating the same error.
Without SQL, ChatGPT primarily relies
on NLP approaches to understand and
generate responses based on tabular data,
which could lead to inaccurate responses
(Pragnakalp 2024). However, by directly
running SQL queries, ChatGPT may perform more sophisticated and flexible interactions with tabular data when paired
with SQL capabilities. This improves the
overall capabilities of ChatGPT in handling tabular data by enabling more
accurate and exact information retrieval
from databases.
Therefore, ChatGPT cannot aggregate
data, but can help create SQL tables and
then have the English query translated
to SQL queries to get accurate results. It is
essential to be aware of the limitations of
generative AI models and use them cautiously. Unchecked use of information
generated by these models without domain knowledge, common sense, and
triangulation is dangerous. Organisations
may utilise completely misleading information and make incorrect decisions,
which could adversely affect individuals
and outcomes.
Poor data quality: While good quality,
unbiased data can help the prospects of
achieving gender equality and inclusion,
poor-quality data, if fed to ML algorithms,
poses the risk of exacerbating prevailing
gender biases and worsening the prospects of achieving equality and inclusion. For example, suppose credit reliability and facilities are based on historical data that has deprived women of
availing of those facilities. In that case,
they can further the bias and exclude
women from availing of financial services.
Such data aggravates existing inequalities, furthers exclusion, and strengthens
real-life prejudices. Since it is hard to
imagine historical data without gender
biases, it is critical for the data and algorithms to be transparent to ensure optimal
results and prevent discriminatory outcomes. Regarding AI-based tools for credit
models, lenders should be able to explain
how their algorithms work, and how they
make decisions about who to lend to.
Lenders should also be held accountable
for any discriminatory practices.
Myopic point of view: Assuming that
well-made algorithms, beautiful prediction models, and deployment of AI is a
panacea can be a serious mistake. While
they can certainly improve service delivery, social fabrics are far more complex
than what data or data technologies alone
can capture. Therefore, it is critical to
pre-train, finetune and contextualise AI
models to leverage their best potential
for social impact.
Lack of context: When it comes to differentiating between desired and undesired biases, context matters. For example,
sex, a biological construct, is a desired differentiation when it comes to addressing,
say, a particular health issue, as it can help
identify and treat conditions that are more
common in one sex or the other. Gender,
on the other hand, is a social construct,
and an undesirable bias that can lead to
discrimination and inequality. Thus, when
and when not to leave gender out of a
model requires subject matter expertise.
More so, removing a gender column from
data may not help, as gender biases are reflected not only in a single column but
have affected the rest of the data.
Power imbalance: There is a significant
gender divide in access to technology,
both between and within countries. This
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puts women across age groups at a disadvantage, as they are less likely to be
able to afford and access the skills and
opportunities to participate in the digital
economy. The gender imbalance in the
technical teams developing frontier technologies contributes significantly to this
divide (NS 2019). These teams are overwhelmingly male, and this gender bias is
reflected in the technologies they develop.
As a result, these technologies may be less
inclusive of women and girls and may
even perpetuate gender stereotypes.
Solutions
Transparent and unbiased algorithms:
Algorithms must be comprehensible to
an ordinary person. Furthermore, AI
systems need to incorporate a robust bias
identification and mitigation system.
Algorithms should actively promote desirable biases (biological) while concurrently reducing undesirable (sociocultural) ones (Cirillo et al 2020). Particularly, in
biomedicine and healthcare, algorithms
should consider biological (sex-related)
factors to advance the designing of
tailored health interventions.
Ethical data technologies: Policymakers,
developers, and industry must place ethics
at the core of the development and implementation of AI and ML technologies
so that they promote and maximise the
well-being and empowerment of women
and girls. However, when reflecting on
the question of whether there are existing
AI normative instruments or principles
that effectively address gender equality,
perspectives shared during UNESCO’s
Dialogue suggest a consensus that such
instruments are either non-existent or
currently insufficient (UNESCO 2020).
beginning of the cycle when the use case
and features are being considered. Additionally, if the team creating the AI is not
representative, they may not consider
the perspectives of other genders, which
can lead to biased outcomes. A diverse
team that includes women can help prevent gender bias in AI development.
Awareness programmes: It is also imperative to raise awareness among the
public, policymakers, and technology developers regarding AI’s negative and positive implications for women. With AI
gaining ground and expected to penetrate
every aspect of our lives, there is an urgent
need to develop curricula and teaching
methods that better integrate cross-disciplinary social sciences, ethics, and AI literacy at the secondary and tertiary levels.
Ensuring AI fairness: When AI technologies do not account for sex and gender
differences, it can lead to suboptimal results, mistakes, and discriminatory outcomes (Cirillo et al 2020). For instance,
credit platforms can perpetuate bias if
they rely on biased data or algorithms.
One way to ensure fairness is to avoid
using gender as a factor in credit scoring.
This can be done by using alternative
data sources, such as mobile phone data,
to assess creditworthiness. The AI Fairness
360 Toolkit, an open-source library written
by IBM research, contains techniques to
detect and mitigate bias in MLMs. Bias
and fairness in generative AI are a complex issue. Recognising that getting entirely unbiased data might be difficult
and that using synthetic data is not always the best option is important. It is
critical to discuss the constraints and
potential biases built into the technology rather than pretending to have a solution to every issue with generative AI.
Addressing AI hallucinations: While
high-quality data sets play a crucial role
in training generative models, generative
AI hallucinations can further be addressed
by understanding the underlying mechanisms of such models. This can enhance
the robustness, interpretability, and control of AI-generated outputs, including
minimising the occurrence of hallucinations or unrealistic outputs. Also, models
can learn to recognise and reject unrealistic, nonsensical, and biased outputs if
adversarial examples are incorporated
during training. Furthermore, involving
human reviewers or validators who assess and provide feedback on the generated outputs helps identify and correct
any hallucinatory or misleading results.
We must develop tools and interfaces
that allow users to guide and influence
the generative process, enable them to
shape the output and reduce the likelihood
AI role diversity: Having a diverse
range of people in algorithm development teams would ensure that biased
and judgmental perspectives do not find
a place in algorithms and prediction
models. Therefore, it is necessary to promote more women in data and data science domains. Potential biases can become part of AI algorithms when women
are not part of the development team.
Biases can arise in AI development at the
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of hallucinations. It is equally important
to establish ethical guidelines and best
practices for the development and deployment of generative AI models.
have negative consequences, such as denial of loans or insurance, based on the
gender of the individual.
In Conclusion
Policy and regulation: It is necessary to
ensure fairness and inclusion in financial
services, particularly in markets where
authorities can create and enforce policy.
The National Strategy for Artificial Intelligence (NSAI) released by the NITI Aayog
in 2018, provided a detailed plan for advancing and using AI in India. To address
data privacy issues, the NSAI proposed
creating a framework for data protection
with legal support by considering the report by the Committee of Experts on a
Data Protection Framework for India
(2018). The committee suggested establishing a framework on the seven-core
data protection and privacy principles—
informed consent, technology agnosticism, data controller accountability, data
minimisation, holistic application, deterrent penalties and structured enforcement (NITI Aayog 2018).
In addition, several other measures
have been proposed, including establishing sectoral regulatory frameworks,
benchmarking national data protection
and privacy laws against international
standards, encouraging AI developers to
conform to international norms, developing tools for assessing the impact of
data privacy, and investing in collaborative
AI research aimed at preserving privacy.
Understanding context: To effectively
deploy AI technologies to improve global
health and tackle inequalities, it is important to consider sex and gender differences in the design of algorithms and
experimental design and incorporate
bias detection and mitigation strategies.
Da Silva (nd) stressed that developers
must be aware of the potential for algorithmic bias and take steps to mitigate
it. It is critical to ensure that the data
sets used for AI algorithms are diverse
and representative, which can help to
prevent biased outcomes. For example,
if an AI algorithm used in hiring processes is biased against women, it could
lead to fewer women being hired, and
end up perpetuating the gender pay gap.
Additionally, biased AI algorithms can
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Applications for AI and ML build on the
data they are fed. Therefore, providing
good quality data to researchers and developers is fundamental to leveraging
the AI and ML revolution for gender
equality. Unless data is made available
in time, applications and models will
remain in development for a long time
or cannot be created in the first place. A
lot of data is available today in various
sectors. However, this data often remains in silos, or is applied in isolation.
Data integration across sectors has the
potential to improve gender equality
outcomes dramatically (Committee-B on
Leveraging AI for Identifying National
Missions in Key Sector 2019).
Using data that is representative of the
population, which encompasses a diverse
range of people, including people from
different genders, will provide a more
precise, inclusive ground reality and context. It is also critical to use unbiased algorithms that are transparent, easy to
understand, and do not favour one group
of people over another. Lastly, prediction
models should be tested for bias before
implementation. It is important to identify patterns in data that favour one group
over another, such as male over female.
While AI and ML offer the opportunity
to hasten the movement towards gender
equality, their effective and safe usage
depends on various factors. This includes
the availability of high-quality and representative data, a diverse team of researchers and developers to remove biases
from algorithms, an understanding of
context, and the establishment of stringent compliance to ethical standards and
practices. It is essential to have sector-specific use cases before these models can
be effectively deployed, or the consumption of information hallucinated by algorithms could intensify existing inequalities and discrimination.
REFERENCES
Chui, M, E Hazan, R Roberts, A Singla, K Smaje,
A Sukharevsky, L Yee and R Zemmel (2023):
“The Economic Potential of Generative AI: The
Next Productivity Frontier,” McKinsey &
Company, https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier#introduction.
Cirillo, D, S Catuara-Solarz, C Morey, E Guney,
L Subirats, S Mellino, A Gigante, A Valencia,
M J Rementeria, A S Chadha and N Mavridis
(2020): “Sex and Gender Differences and Biases
in Artificial Intelligence for Biomedicine and
Healthcare,” NPJ Digital Medicine, Vol 3, No 1,
pp 1–11.
Committee of Experts on a Data Protection Framework for India (2018): “A Free and Fair Digital
Economy: Protecting Privacy, Empowering
Indians,” Ministry of Electronics and Information Technology, Government of India, New
Delhi.
Committee-B on Leveraging AI for Identifying
National Missions in Key Sector (2019): “Report
of Committee-B on Leveraging AI for Identifying
National Missions in Key Sector,” Ministry of
Electronics and Information Technology, Government of India, New Delhi.
Da Silva, Laura (nd): “The Danger of Gender Bias in
AI and ML,” Outside Insight, https://outsideinsight.com/insights/the-danger-of-gender-biasin-ai-and-ml/.
González-Prieto, Á, A Brú, J C Nuño and J L GonzálezÁlvarez (2023): “Hybrid Machine Learning
Methods for Risk Assessment in Gender-based
Crime,” Knowledge-Based Systems, Vol 260,
pp 1‒15.
Kelly, S and M Mirpourian (2021): “Algorithmic
Bias, Financial Inclusion, and Gender: A Primer
on Opening Up New Credit to Women in Emerging Economies,” Women’s World Banking,
https://www.womensworldbanking.org/wpcontent/uploads/2021/02/2021_Algorithmic_
Bias_Report.pdf.
Moran, Lyle (2023): “Federal Judge Seeks to Prevent
Generative AI Mistakes in Briefs,” LegalDive,
1 June, https://www.legaldive.com/news/generative-ai-hallucinations-federal-judge-orderon-ai-brantley-starr/651817/.
NCAER (2020): “An Evaluation of India’s Beti
Bachao Beti Padhao Scheme,” New Delhi, https://
www.ncaer.org/wp-content/uploads/2020/08/1611336563NCAER_BBBP_Scheme_Report_
August_2020.pdf.
NITI Aayog (2018): “National Strategy for Artificial
Intelligence,” Government of India, New Delhi,
https://niti.gov.in/sites/default/files/2019-01/
NationalStrategy-for-AI-Discussion-Paper.pdf.
N S, Aakanksha (2019): “Exploratory Data Analysis
(EDA)—Understanding the Gender Divide in
Data Science Roles,” Medium, 30 October, https://
medium.datadriveninvestor.com/exploratorydata-analysis-eda-understanding-the-genderdivide-in-data-science-roles-9faa5da44f5b.
Pragnakalp (2024): “Data Extraction from Tabular
Data with ChatGPT,” 13 February, https://
www.pragnakalp.com/data-extraction-fromtabular-data-with-chatgpt/.
UN (2023): “Progress towards the Sustainable Development Goals: Towards a Rescue Plan for People
and Planet,” https://hlpf.un.org/sites/default/
files/2023-04/SDG%20Progress%20Report%20
Special%20Edition.pdf.
UNDP (2023): “Artificial Intelligence for Development
Analytics (AIDA),” United Nations Development
Programme, https://aida.undp.org/about.
UNESCO (2020): “Artificial Intelligence and Gender
Equality: Key Findings of UNESCO’s Global
Dialogue,” Division of Gender Equality, United
Nations Educational, Scientific and Cultural
Organization, Paris, GEN/2020/AI/2 REV https://
unesdoc.unesco.org/ark:/48223/pf0000374174.
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COMMENTARY
Identifying Vulnerable
Sections through Fractile
Classification Technique
Shyamsundar Parui, Onkar Prosad Ghosh
Identification of the poorest
section of people has always been
important for any state or region
to implement any focused policy.
To identify the most vulnerable
section of common people
through the fractile classification
technique, the article follows
permanent income hypothesis,
where the expenditure is
corrected for transitory
consumption and reporting/
non-reporting effects by adopting
a use-based approach.
The views expressed are personal and not of
the organisation to which the authors belong.
Shyamsundar Parui (parui.iasri@gmail.com)
and Onkar Prosad Ghosh (onkar.ghosh@
gmail.com) are with the Directorate General
of Commercial Intelligence and Statistics,
Ministry of Commerce and Industry.
Economic & Political Weekly
EPW
MAY 4, 2024
T
he mainstreaming of the common
people, in the sense of economic
and social development, has always
been a challenge to any democratic government. A continent-sized country like
India, always intends accelerated improvement of the welfare of the common
people through economic and social policies. In the context of macroeconomy,
there is no doubt in the fact that a rapid
growth of the gross domestic product
(GDP) is highly desired to establish the
country in the world economy. This
accelerated growth or desired rapid
improvement may not be uniform for
all sections (social, religious, or other
groups) of the population or even for all
regions of the economy. However, this
desired uniformity of improvement can
be achieved with proper identification of
common people—who they are, what is
their level of consumption and their position in total population, etc (Sengupta et
al 2008). In addition, there are persons
who belong to the most vulnerable section and might feel more deprived if
their deprivation is shared by a minority
group than if the majority were similarly
deprived (Desai and Shah 1988: 512).
Identification of the poorest section or
most vulnerable section of common people would be extremely helpful to implement any focused (for any particular
sector, region of economy, religion community, states, etc) poverty alleviation
scheme, study the standard of living like
social status, literacy, sex ratio, landholdings, etc.
In the National Sample Survey (NSS),
Monthly Per Capita Consumption Expenditure (MPCE) is defined at the household
level (household monthly consumption
expenditure ÷ household size). This
measure serves as the indicator of the
household’s level of living and each
member of those households is consid-
ered to be in that level. In order to see
the distribution of level of living, in NSS,
a relative method is adopted. On the basis of per capita (overall expenditure),
the individuals are ranked and categorised in bottom 5%, next 5%, next 10%
… up to top 5% (See: Key Indicators of
Household Consumer Expenditure in India, GOI [2013]). In other words, 12-point
fractile classes are considered.
Identification of the poorest or most
vulnerable section of common people
can be achieved using the poverty line
approach as well as the fractile classification approach. Literature is enriched
with numerous contributions towards
poverty line construction and studying
poverty ratio, gap indices, etc, which
started nearly three decades ago. In this
article, we have tried to identify the poorest or most vulnerable section of common people using the fractile classification approach, which we define as bottom 10% of population or lower two
fractile classes (0%–5% and 5%–10%)
after correcting for consumption expenditures with respect to transitory consumption expenditure and reporting/
non-reporting effects. As per the latest
available official headcount ratio (HCR),
using the Tendulkar Committee (Government of India 2009) methodology at the
national level, and National Sample Survey (NSS) 68th round of Consumer Expenditure Survey (CES), it is 25.7% and
13.7% in 2011–12 for rural and urban sectors, respectively. In line with this, and
considering the variability in HCR among
different states, most vulnerable sections of common people are defined as
bottom 10% of the population or as bottom two fractile classes. We will start
with defining transitory consumption
expenditure in a later section.
Motivation
In the absence of data, either due to difficulty in measurement or its erratic fluctuation from time to time, income is often
replaced by expenditure which is also considered as a proxy for permanent income
following Milton Friedman’s permanent
income hypothesis (Kumar et al 2009).
First, we discuss Friedman’s permanent
income hypothesis for a better understanding of the problem.
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COMMENTARY
Permanent income hypothesis: Friedman (1957) rejected the traditional
Keynesian consumption hypothesis and
introduced the permanent income hypothesis. Hence, permanent income was
the relevant determinant of consumption and not the current income, and
that permanent consumption was proportional to permanent income (the proportionality hypothesis). The permanent
component of income may be attributed
to all factors like capital value or wealth,
their training, ability, personality, occupation, and so on, which generates income, or the same pattern of income
may prevail for a long period of time.
Similarly, the transitory component may
be attributed to all those factors that are
in fact treated as “accidental” or “chance”
factors like occurrences, though they may,
from another point of view, be the predictable effect of specifiable forces; for
example, cyclical fluctuations in economic
activity, illness, a bad guess about when
to buy or sell, and the like. And similar
are the chance errors of measurement.
In the same line, consumption expenditure may have been composed of
two parts—permanent consumption expenditures and transitory consumption
expenditures. Similar to transitory income, transitory consumption expenditures may be attributed to all those factors
that are in fact treated as “accidental” or
“chance” factors like illness, bountiful
harvest or some opportunity to buy, etc.
In general, the pattern of transitory consumption expenditure may not prevail for
long periods of time. The general assumption is that for any considerably
large group of consumer units, the resulting transitory components tend to
average out. But, some may be largely
common to the members of the group—
for example, unusually good or bad
weather if the group consists of farmers
in the same locality; or a sudden shift in
the demand for some product, if the
group consists of consumer units whose
earners are employed in producing this
product. If such factors are favourable
for any period, the mean transitory component is positive; if they are unfavourable, it is negative (Friedman 1957). In
small populations, the probability of mean
transitory consumption to get averaged
22
out is very less. So, to get better and reliable idea of permanent income or to
study household consumption patterns
in the context of poverty, transitory
component of consumption expenditure
of households should be considered. In
India, NSS uses uncorrected monthly
consumption expenditures for transitory
consumption of each household, which
may not depict the real picture of consumption patterns. For example, suppose
a household is a regular wage earner and
it gets one-time benefit in terms of, say,
bonus, which resulted in the purchase of
a durable good and an increase in the
monthly consumption pattern. This is
clearly not its permanent consumption
pattern and this pattern will not prevail
in the future for this household.
Reporting/non-reporting effects: Like
transitory consumption expenditure, NSS
does not take care of the extent of reporting of consumption expenditure for different broad item groups. As the relative level
of living of an individual is determined by
total consumption expenditure in different broad item groups, non-reporting of
any such item groups in the respective
household basket heavily affects the relative position of that household, and if such
non-reporting is considerably high, then
the entire study gets jeopardised.
The non-reporting of an item group may
happen due to following reasons:
(i) The households had not actually consumed any such item.
(1) it is likely to not be in the household
consumption basket, (2) it is likely to be
in the basket but the nature of the
items is such that the consumption continued beyond the reference period.
(ii) They have consumed but not reported.
Another household maybe allotted a
better standard of living despite its similar nature, due to expenditure on such
item(s) that they have not reported,
within the reference period. In largescale surveys, it is believed that the
transitory component of consumption
expenditure and reporting/non-reporting effects are averaged out in the overall scenario.
Although the magnitude and directions of both transitory consumption expenditures and reporting/non-reporting
effects are unknown, we assume that for
a large-scale survey (national level), effects of both tend to average out. In this
article, we propose a methodology to
identify the most vulnerable section of
common people (bottom two fractile
classes) after reducing the effects of both
transitory consumption expenditures
and reporting/non-reporting effects by
maintaining a trade-off between the reporting percentage and budget share. It
is assumed that the total household expenditure is the same as the total budget of that household and these two
terms shall be used interchangeably
throughout this article. We will start
with data description.
Data Description
The study is based on Household Consumer Expenditure Survey (HCES) conducted by the National Sample Survey
Office (NSSO). In the NSS 68th round,
alternative schedule types for measuring
household consumption based on different
sets of reference periods were canvassed
on matching sample sizes. Using unit-level
data relating to Schedule 1.0 (Type II),
the different reference periods of 34
broad item groups are enlisted in Table 1.
It may happen that the reporting percentage of rice would be high in West
Bengal, while in Rajasthan, it will be
wheat. The primary reason may be the
nature of household consumption baskets. Here, both households from West
Table 1: Differences (in reference period) in Schedule Type 2 (as per NSSO Classification)
Category
Item Groups
Reference Period
I
Cereals, cereal substitute, pulses and products, milk and products, salt and
sugar, fuel and light, medical (non-institutional), entertainment, minor
durable-type goods, toilet articles, other household consumables, consumer
services excl. conveyance, conveyance, rent, consumer taxes and cesses.
Edible oil, egg, fish and meat, vegetables, fruits (fresh), fruits (dry), spices,
beverages, served processed food, packaged processed food, pan, tobacco,
intoxicants
Clothing, bedding, etc, footwear, education, medical (institutional), durable
goods
Last 30 days
II
III
Last 7 days
Last 365 days
Source: NSS 68th round.
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COMMENTARY
Bengal and Rajasthan are consuming
similar types of nutrients (present in
cereals) from different products. Hence,
to correct the consumption expenditure
for reporting/non-reporting effects, studying broad item groups is more valid rather
than individual items of broad item
groups which are, in fact, similar in
nature. In line with this, we investigated
all 32 broad item groups except “salt and
sugar” as the consumption of “salt” does
not have any effect on the consumption
of “sugar” and vice versa.
Methodology
We have ranked all 34 major item groups
on the basis of their reporting percentage along with their budget shares in
the total consumption expenditures to see
the reporting/non-reporting effects. For
example, all ranked 34 major item groups
for Kerala are presented in Appendix
Tables (A1 and A2 [p 30] for rural and urban sectors, respectively).
Problems can be summarised as follows:
(i) For transitory consumption,
(1) How to identify transitory consumption expenditure? (2) Which broad item
groups are consumed from transitory income part? (iii) What percentage of total budget has been spent on transitory
consumption?
(ii) For reporting/non-reporting effects,
(1) Up to what percentage of reported
items should we take and what would
provide a valid platform of comparability?
To address the problem of reporting/
non-reporting, one may argue to take
highly reported (say, >80% reporting or
>90% reporting or >99% reporting)
item groups to calculate MPCE and form
fractile classes to obtain the distribution
of the level of living. The problem here is,
high reporting percentage will include
fewer broad items to calculate MPCE
(hereinafter partial MPCE1). If a household
reports an item, its MPCE will be higher
and a higher fractile class is assigned to
it. In case the household does not report
that item due to non-consumption in the
reference period, its MPCE becomes less
and a comparatively lower fractile class
is assigned. Therefore, it is recommended to use those items which are reported
by most of the population to assign fractile
classes. For example, a household has
Economic & Political Weekly
EPW
MAY 4, 2024
reported a consumption of 28 out of 34
broad item groups as per the survey
questionnaire. Thus, the entire household
budget becomes the total expenditure
incurred on 28 broad item groups. Consideration of only highly reported items
may exclude a few, say five, out of these
28 broad item groups. Therefore, partial
MPCE will be calculated based on only 23
broad item groups, and accordingly, the
household budget will be less than earlier.
It is obvious that, as reporting percentage
increases, the number of items to calculate the partial MPCE decreases and it
will significantly affect the budget share.2
Five randomly selected high-reporting
percentage cut-off3 item groups (80%
reporting [21 item groups selected], 85%
reporting [17 item groups selected], 90%
reporting [15 item groups selected], 95%
reporting [8 item groups selected], and
99% reporting [2 item groups selected]) are chosen to study the transition of
population across different fractile classes and the effect on the budget share of
households. The illustration for Kerala is
given in the appendix (Figure A4, p 28).
Figure A1 (p 28) in the appendix illustrates the extent of transition of individuals, that is, the percentage of the population that moves to the higher fractile
classes from the bottom two classes). As
the reporting percentage cut-off increases, the number of broad item groups satisfying the reporting percentage cut-off
decreases, for calculating the partial
MPCE. Moreover, when the reporting
percentage cut-off increases, the percentage of the population that comes
down to the two lowest fractile classes
from the upper fractile classes increases.
This highlights the extent of mismatch
in assigned classes by partial MPCE and
total MPCE.
Figure A2 (p 28) indicates the extent
of mis-classification in fractile classes
due to choosing different partial MPCE in
the rural sector based on different reporting cut-offs in Kerala. In Figure A2, the absolute ranking difference (new rank of
partial MPCE and old rank based on total
MPCE) is plotted on the x-axis on a cumulative basis, except rank 0, that is, the
first point.
(i) From Figures A1 and A2, it is almost
obvious that the extent of mismatch
increases with increase in the reporting
percentage cut-off. The higher mismatch
may be due to the following: with highreporting percentage cut-off, less broad
item groups are included to calculate
partial MPCE, resulting in high budget
differences among households with the
total MPCE calculated from all broad
item groups.
(ii) Calculation of partial MPCE based on
very few broad item groups (for highreporting percentage cut-off) may not
include primary consumable items for a
household and may be a small share of
the total household budget.
The budget share pattern of Kerala is
studied for different reporting percentage
cut-offs and presented in Figure A3 (p 28)
(overall budget share) and Figure A4
(distribution of percentage of population having different budget shares). It
has been found that as the reporting
percentage cut-off increases, less number of commodities gets included in calculating partial MPCE. This results in
drastic reduction in the overall budget
share (Figure A3) and reduction in the
percentage of populations with highbudget shares (Figure A4).
Clearly, it would not be valid or would
not provide any comparable platform to
study the relative level of living of populations through fractile classifications if
MPCE is calculated with few items that
contribute very less to the overall budget
share, or very few populations with high
budget shares. For sure, one cannot
compare households only with their 6%
household budget for more than 99% reporting percentage cut-off (Figure A3).
One cannot compare households for
>99% reporting percentage cut-off as
very less population have at least 70%
budget share of their respective total
household budget (Figure A4). A trade-off
should always be maintained between
the reporting percentage cut-off and the
budget share percentage.
To obtain a suitable cut-off of the reporting percentage (should be high) and
budget share (high overall share and large
percentage of populations having high
budget share), an exhaustive study has
been performed for Kerala. True positive
and true negative rates have been computed. Since the main objective of this
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COMMENTARY
study is to correctly identify the bottom
10% of the population, the true positive
rate is defined as the probability of correctly classifying a population in higher
fractile classes (other than bottom two
classes) between total and partial MPCE by
fractile classification technique. Similarly,
the true negative is defined as the probability of correctly classifying a population
in the bottom two fractile classes between
total and partial MPCE by fractile classification technique. The minimum value of
probability of true positive rate is 0.9 as, at
most, 10% of the total population can be
misclassified in upper fractile classes from
the bottom two fractile classes.
From more than 60% to 99% reporting cut-off considered for Kerala to study
the pattern of the budget share, true positive rate, true negative rate, and matching percentage4 with total MPCE are
used to find out the suitable strict cut-off
percentage points to maintain the tradeoff. The results are presented in Figures
A5 and A6 (p 31) for rural and urban sectors of Kerala, respectively.
As discussed, the probability of the
true positive rate cannot be less than 0.9
as, at most, 10% of the total population
can move up to upper fractile classes
from the lower ones. But there are several spike-down and spike-up points for
the budget share, true negative rate, and
matching percentage for the proportion
of populations to come down to lower
fractile classes from the upper ones
when there is a different choice of reporting percentage cut-off. For the budget share and matching percentage, it is
quite easy to interpret such types of spike
ups and downs. As the reporting percentage cut-off increases, less items are
included to calculate partial MPCE,
which eventually decreases the matching
percentage and budget share percentage.
Four significant cut-off points are identified, considering the trade-off between
reporting percentage cut-off and budget
shares for rural and urban sectors of
Kerala, respectively (Tables A3 and A4
[p 31]). This study range has been chosen considering the trade-off between
reporting percentage cut-off and budget
share percentage.
From Figures A5 and A6 (p 31) and
Tables A3 and A4, it is evident that all
24
parameters are behaving systematically.
Each drop point is noticed when one or
more items get excluded from the calculation of partial MPCE. No sudden spikedrops or spike-ups have been observed for
a certain combination of these parameters. It has been clear that, graphically, it
is very difficult to identify strict cut-off
points for reporting percentage and budget share while maintaining trade-off.
To deal with this issue, a new approach has been adopted. We call it usebased approach.
Use-based Approach
Instead of obtaining a strict cut-off point
for reporting percentage, most commonly used/reported items are identified
statewise. This approach automatically
considers all broad items with high reporting percentage. Then, partial MPCE
is calculated using all broad items that
are used by most of the population. The
procedure is discussed here step by step.
(i) Identify all item groups which are
used by most of the population (commonly used items) and rank them.
(ii) Consider all those items whose reporting percentage is more than 80%.
This 80% cut-off is chosen randomly
considering the fact that most of the
population is using these items.
(iii) Fractile classes are formed using these
selected items (step [ii]). Selected items
are used to calculate the partial MPCE.
Based on these partial MPCEs, the fractile
classes are formed. Here, more that 80%
reporting percentage items are considered to calculate partial MPCE and fractile classes.
(iv) For the rest of the items (less than
80% reporting percentage), check whether these items are well represented
among the lower four fractile classes or
not; poverty-weighted items are emphasised here. The lower four classes are
chosen as they cover the headcount ratio of the poor in rural and urban sectors as per the Tendulkar Committee
report (2009):
(iv[i]) If it is well represented among the
bottom four fractile classes, then check the
pattern of consumption, whether it is a
decreasing (poverty-weighted approach
[Deaton 2008]) or a stable trend across
the classes with no wide variation in
consumption between the lower two
and upper two classes.
(1) If they exhibit any of the patterns discussed in (iv[i]), include it in the calculation of partial MPCE along with items of
step (ii) and obtain the fractile classes. After fractile classification, observe if any
sharp increasing pattern of consumption
across classes exists. If not, then finally include those items along with the items
identified in step [ii].
(2) Otherwise, exclude those items.
(iv[ii]) If not represented in the bottom
four fractile classes, exclude those items.
(v) Finally, classify the population in 12
fractile classes based on partial MPCE
computed from selected items from step
(ii) and those from step (iv) (selected, if
any). Finally, the budget share of both
overall and individual (percentage of
population having a certain budget
share percentage) can be computed to
observe the adequate percentage of the
budget share to obtain the relative
standard of living and elimination of
transitory consumption expenditures.
It is clear from the above steps that an
item has to pass several criteria {step (ii)
and step (iii) [a and b]} to get selected in
the calculation of partial MPCE. To ease
this selection, each broad item group
can be scored based on the performance
in the different criteria as mentioned in
step (ii), that is, reporting percentage,
and step (iii [a {1 and 2}]) that is, trends
across fractile classes.
Score: The formula to calculate the
score is,
ଵଶ
ܵൌ
݊
‫݌‬௜
෍ ‫ݎ‬௜
ܰ ݉ܽ‫ݔ‬ሺ ܴଵ ǡ ܴଶ ሻ
௜ୀଵ
where n will be the number of classes reporting at least 50% for a broad item
group, R1 and R2 are the range between
the 1st and 12th classes, and 2nd and 11th
classes, respectively. pi is the reporting
percentage in the ith class while ri is the
rank of the ith class. Here, N is 4 as discussed in step (iv).
The score (S), as defined above, is an
unbounded function. The lower limit of
S is 0 as n can be 0, when none of the
lower four classes have reporting percentages of at least 50% for a particular
broad item group. The upper limit of
score (S) is ∞ as max (R1, R2) can be 0 for
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certain broad item groups. The cut-off
value of score (S) for the selection of
each broad item group has been obtained following the methodology discussed here.
Cut-off: Score is composed of three
parts,
݊
(i) ܵଵ ൌ ; quantifies “at least one of the
ܰ
four N that 50% of the population is consuming.” Here, we assume that a minimum two out of four classes should have
at least 50% of their consumption inʹ
cluded, that is, Ͷ
ଵ
(ii) ܵଶ ൌ ୫ୟ୶ሺோభǡோమሻ ; quantifies “the range
of consumption between lower two and
upper two fractile classes in consumption proportion.” Here, we assume the
lower limit of max (R1, R2) can be 20%.
௣೔
(iii) ܵଷ ൌ σଵଶ
௜ୀଵ ௥ ;; quantifies “decreasing
೔
pattern of consumption across classes”
and “stable trend across the classes.”
ଵ
ଵ
ଵ
ଵ
Here, we assume ܵଷ ൌ ሺଵ ൅ ଶ ൅ ଷ ൅ ସ).
(iv) S = (S1 × S2 × S3) = 5.2. Here, we
take the cut-off as 5.00 considering the
flexibility of all the criteria.
The inclusion of broad item groups is to
be done in the following steps:
(i) Score (S) will be computed for all
broad item groups having less than 80%
reporting and if the score is found to be
more than 5, then those broad item
groups are selected for inclusion to calculate partial MPCE.
(ii) Partial MPCE and the respective fractile classes will be formed by including
broad item group selected using step (i)
and score (S) will be computed again. If
the score (S) is found to be more than 5,
then the broad item group is finally included in the commodity basket to calculate partial MPCE.
(iii) The above two steps are repeated
for all broad item groups having less
than 80% reporting.
The above discussed methodology is
described using an example from Kerala
for both rural and urban areas and are
described below.
Example: As discussed above, all broad
item groups are ranked based on their
reporting percentage, that is, identifying the most-used broad item groups.
Then, few items are directly included in
the calculation of partial MPCE based on
their reporting percentage (if more than
80% people are reporting their usage).
Rest of the items are scored and selected
based on their performance in score.
All 34 broad item groups along with
their budget share, reporting percentage, and selection criteria are given in
Tables A5 and A6 for rural and urban
sectors of Kerala.
To summarise, total 22 item groups
are directly selected to compute partial
MPCE using the criterion as mentioned
in step (ii) of use-based approach for
both rural and urban sectors of Kerala
(Tables A5 and A6). For rest of the item
groups, only “served processed food
(14)” and “cereal substitute (02)” are
Table 2: Statewise Analysis for Newly Selected Broad Items for Six States
State
Items
Selected
Overall
Matching
(%)
Rural Urban
Kerala
Rural
22
41.9
42.4
76
73
1.61
2.11
Uttar Pradesh
21
52.3
60.3
90
80
1.44
1.52
West Bengal
21
59.3
66.3
90
85
2.06
1.17
Maharashtra
22
47.8
49.2
85
81
2.06
1.78
Gujarat
19
49.9
48.1
86
79
1.63
1.49
Bihar
21
47.7
56.5
Budget share
(%)
88
Percentage of Bottom
10% Population Moves to
Higher Fractile Classes (%)
Urban
Rural
Urban
85
1.75
Source: Authors’ estimation based on NSS 68th round.
Economic & Political Weekly
EPW
MAY 4, 2024
1.62
Budget Share
Cut off (%)
>70
>80
50–98
>70
>80
50-98
>70
>80
50–98
>70
>80
50–98
>70
>80
50–98
>70
>80
50–98
Population Having
That Budget Share
(%)
Rural
Urban
86
73
92
97
91
82
99
93
89
95
81
98
96
85
96
98
88
92
84
67
91
95
84
93
94
83
98
88
69
98
88
60
99
93
80
94
included after studying the “before inclusion” and “after inclusion” effect for
the rural sector of Kerala. S is calculated
for all remaining items groups. Only
“served processed food (14)” and “cereal
substitute (02)” item groups have scored
more than 5.00 in the rural sector of
Kerala (Table A5). Similarly, for urban
sector (Table A6), S is calculated for all
remaining items groups and only “medical (non-institutional) (22)” and “served
processed food (14)” are included following the criteria mentioned above.
The problems (as discussed in Motivation and Methodology) are still prevailing here,
(i) Are these selected item groups and
associated partial MPCE able to eliminate the reporting/non-reporting effect?
(ii) Are these selected item groups and
associated partial MPCE able to take care
of transitory consumptions?
(iii) Is the trade-off between budget
share and the cut-off percentage maintained here?
To address these questions, a study on
the overall budget share, budget share
cut-off (chosen three cut-offs), and percentage of the population having that
budget share cut-off are studied for the
major six states (randomly chosen) and
presented in Table 2. Here, we have chosen three budget share cut-offs—more
than 70%, more than 80%, and between
50% and 98%. More than 70% and more
than 80% are chosen considering the
fact that the average transitory consumption expenditure for a household
can be on average 30% or 20% of the total household budget and have visualised what percentage of populations are
having that household budget. A similar
approach has been followed in the third
cut-off, that is, the budget share between 50% and 98%. Here, we assume
that transitory consumption expenditure can be at most 50% of a household
budget and minimum 2% of the total
household budget.
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COMMENTARY
Summarising the results of Table 2:
(i) six states are selected randomly from
the major states having population more
than 20 million (See: Key Indicators of
Household Consumer Expenditure in
India, 2011–12) and the proposed methodology has been applied to select the
broad item groups to calculate partial
MPCE and 12 fractile classes; (ii) it is interesting to see that the selected items for
different states are contributing more
than 75% of the overall budget share for
all states. This implies that the proposed
methodology, with selected broad items
groups which form a large portion of overall budget, may provide a suitable base for
household comparison with respect to
their standard of living; (iii) the transition
of population to the bottom two fractile
classes from the higher ones (assigned on
the basis of total MPCE) is quantified. It can
be seen that the percentage of the bottom 10% population that moves to higher fractile classes is significant; (iv) it is
interesting to see that for all states, more
than 95% of the populations are having
more than a 70% budget share included
in the selected items, except urban and
rural sector of Maharashtra and Gujarat.
For all states, more than 90% of the population with a budget share between
50% and 98% have been included. Except the urban sector of Maharashtra
and Gujarat, more than 80% of the population with more than 80% budget share
are included in the selected item groups.
It is clear that a significantly high percentage of population’s budget is composed of selected items.
Conclusions
We have seen that the effect of transitory consumption expenditure and reporting/non-reporting concerns are significant. A significant mismatch of population across fractile classes is observed
based on their reporting percentage
when using a different set of broad item
groups to calculate the partial MPCE.
Likewise, in the bottom two classes, a
significant population transited from
upper fractile classes when a different
choice of broad item groups was used to
calculate partial MPCE. The proposed
methodology is able to capture both
transitory consumption expenditures
and reporting/non-reporting effects. It
is understood that an amount of transitory expenditure is present in each
household budget. Therefore, it would
not be wise to calculate MPCE considering the total consumption expenditure
of a household. But the magnitude of
transitory consumption is unknown and
may vary for each household. However,
quantifying the transitory consumption
for each household, it would be very difficult as the consumption pattern is not
uniform. An exhaustive study for different budget shares (both overall and individual with a certain budget share
cut-off) has been made (Table 2) with
INSTITUTE OF ECONOMIC GROWTH
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Job Code: IEG/HDFC/Prof./25/2024/Date: April 26, 2024
THE APPOINTMENT OF CHAIR PROFESSOR
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The Institute of Economic Growth (IEG), an autonomous research and training Institution established in 1952, conducts research in several areas of
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in the newly established HDFC Bank Chair of Banking and Finance at the Institute for a period of 4 years. Funding for the Chair is likely to be extended.
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The candidate should have an outstanding academic record with a Ph.D and, should process the following qualifications:
Essential Qualifications
Eligibility (A or B)
A.
(i) An eminent scholar having a Ph.D. degree in Economics or Finance and published work of high quality, actively engaged in research and
policy with evidence of published work, with a minimum of 10 very good research publications in the peer-reviewed or UGC-listed journals
and a total research score of 120 as per the criteria given in Appendix-II, Table 2 (enclosed).
(ii) A minimum of ten years of teaching experience in university/college as Assistant Professor/Associate Professor and/or research experience
at an equivalent level at University/National Level Institutions with evidence of having guided doctoral candidates.
Or
B.
An outstanding professional, having a Ph.D. degree in Economics or Finance from any academic institution (not included in A above)/industry,
who has significant publications and has made contributions to the field of Economics/Finance supported by documentary evidence provided
he/she has ten years’ experience.
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c. Candidates’ work should be in the areas of: banking and finance, macroeconomics, financial economics, monetary economics, financial
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educational qualification certificates and testimonials (hard copy). Also required to send the names of three references and copies of the ten best
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On the top of the envelope, write “Application for the Post of Chair Professor, HDFC Bank Chair of Banking and Finance addressed to the Director, Institute of Economic Growth, University of Delhi Enclave, North Campus, Delhi–110007. The hard copy of the application should arrive by June 11, 2024.
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26
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COMMENTARY
different choice of budget share cut-offs.
It has been found that a high percentage
of the population with a high budget
share (not 100% of budget) with selected
items is covered through use-based approach. Similarly, for reporting/non-reporting effects, broad item groups are
selected with high reporting percentage,
that is, most commonly used broad item
groups are selected. This eliminates the
reporting/non-reporting effects and provides a comparable platform to study the
relative level of living based on MPCE.
So, the proposed approach will be able to
maintain the trade-off between high reporting percentage and budget share,
resulting in the selection of broad items
with a high reporting percentage with a
high budget share to compute MPCE.
notes
1
2
3
4
MPCE computed using a subset of 34 broad
item groups.
The budget share is defined as the share in total household budget by the expenditure of
highly reported broad item groups considered
for partial MPCE.
Each broad item group of survey questionnaire shall have a reporting percentage. For
example, broad item group “clothing” with
80% reporting percentage indicates 80% of
the population has reported their expenditure
on “clothing.”
Matching percentage is defi ned as the percentage of total population that are assigned
same fractile classes in both partial MPCE
and total MPCE.
References
Deaton, A (2008): “Price Trends in India and Their
Implications for Measuring Poverty,” Economic
& Political Weekly, Vol 43, No 6, pp 43–49.
Desai, M and A Shah (1988): “An Econometric
Approach to the Measurement of Poverty,”
Oxford Economic Papers, Vol 40, No 3, pp 505–22.
Friedman, M (1957): A Theory of the Consumption
Function, Princeton.
Government of India (2009): “Report of the Expert
Group to Review the Methodology for Estimation of Poverty,” chaired by S D Tendulkar.
Kumar, T K, S Mallickand J Holla (2009): “Estimating
Consumption Deprivation in India Using Survey Data: A State-level Rural–Urban Analysis
Before and During Reform Period,” Journal of
Development Studies, Vol 45, No 4, pp 441–70.
Sengupta, A, K P Kannan and G Raveendran
(2008): “India’s Common People: Who Are
They, How Many Are They and How Do They
Live?” Economic & Political Weekly, Vol 43,
No 11, pp 49–63.
Appendix
Table A1: Percentage of Households (arranged in descending order)
Reporting Consumption of Broad Item-groups and Their Respective
Percentage of Budget Shares for Rural Kerala
Table A2: Percentage of Households (arranged in descending order)
Reporting Consumption of Broad Item-groups and Their Respective
Percentage of Budget Shares for Urban Kerala
Item
Code
Item
Code
Description
Share
Percentage
Reporting
100
Description
Percentage Percentage
Budget Share Reporting
32
Clothing
4.85
100
32
Clothing
4.89
21
Fuel and light
4.55
99.9
25
Toilet articles
1.45
99.2
25
Toilet articles
1.59
99.6
21
Fuel and light
4.65
98.9
13
Beverages
2.18
99.5
27
Consumer services excl conveyance
5.64
98.9
26
Other household consumables
1.53
99.3
26
Other household consumables
1.34
98.8
27
Consumer services excl conveyance
4.72
99.2
34
Footwear
0.79
98.7
34
Footwear
0.8
98.8
28
Conveyance
7.11
98
28
Conveyance
6.09
98.2
13
Beverages
1.98
97.6
10
Fruits (fresh)
4.1
97.9
10
Fruits (fresh)
3.93
94.4
01
Cereals
5.38
97.7
1
Cereals
4.57
93.2
44
Sugar
0.93
97.7
44
Sugar
0.76
92
09
Vegetables
3.49
97.5
9
Vegetables
3.01
91.9
07
Edible oil
1.84
97.4
12
Spices
2.23
91.8
12
Spices
2.82
97.4
7
Edible oil
1.62
91.7
45
Salt
0.08
95.5
3
Pulses and products
1.4
90.7
03
Pulses and products
1.55
95.2
45
Salt
0.07
89.5
08
Egg, fish and meat
8.07
90.3
4
Milk and products
3.31
87
04
Milk and products
3.44
88
8
Egg, fish and meat
6.9
84.7
15
Packaged processed food
2.2
84.9
30
Consumer taxes and cesses
0.55
84.6
30
Consumer taxes and cesses
0.31
84
35
Education
4.94
83.6
35
Education
3.65
82.2
15
Packaged processed food
1.96
83
22
Medical (non-institutional)
5.68
80.6
23
Entertainment
1.35
81.6
23
Entertainment
1.37
77.5
22
Medical (non-institutional)
5.03
74.9
37
Durable goods
14.4
68.2
37
Durable goods
16.64
70.4
14
Served processed food
6.26
63.5
14
Served processed food
4.68
63.5
02
Cereal substitute
0.32
53.2
33
Bedding, etc
0.29
44.9
33
Bedding, etc
0.19
41.1
2
Cereal substitute
0.15
42.3
36
Medical (institutional)
3.48
28.9
36
Medical (institutional)
3.03
26
17
Tobacco
0.9
27.4
11
Fruits (dry)
0.40
23.9
11
Fruits (dry)
0.34
21.6
29
Rent
3.21
23
24
Minor durable-type goods
0.22
16.8
17
Tobacco
0.66
22
18
Intoxicants
1.57
15.6
18
Intoxicants
1.15
13.2
16
Pan
0.21
9.7
24
Minor durable-type goods
0.24
12.5
29
Rent
0.9
8.3
16
Pan
0.06
4.9
‘Sugar’ and ‘Salt’ have been assigned code ‘44’ and ‘45’.
Source: Authors’ estimation based on NSS 68th round.
Economic & Political Weekly
EPW
MAY 4, 2024
‘Sugar’ and ‘Salt’ have been assigned code as ‘44’ and ’45.
Source: Authors’ estimation based on NSS 68th round.
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COMMENTARY
Proportion of 10% of population
Appendix
Figure A1: Percentage of Bottom 10% of Population that Moves to Higher
Fractile Classes, Kerala
7
5.94 5.76
6
120
100
80
60
40
20
0
5
3.65
4
3
3.05 2.91
2.94 3.24
2.83
Figure A5: Distribution of Populations (in Percentage) with Budget Share,
Matching Percentage, Percentage of Bottom 10% Population Moves to
Higher Fractile Classes,True Positive Rate and True Negative Rate for
Reporting Percentage Cut-off Range (>60->99%)
3.14
2.37
2
60616263646566676869707172737475767778798081828384858687888990919293949596979899
Reporting Qercentage Dutt-off Sange (>60 to >99%)
Budget share (%)
Matching with Uotal MPCE (% population)
Percentage of bottom 10% population moves to higher classes
Trure Qositive Sate (%)
True
True Oagetive
negativeSate
rate(%)
(%)
1
0
>80% Reporting >85%Reporting >90%Reporting >95%Reporting >99%Reporting
(MPCE: 21 Jtem (MPCE: 17 Jtem (MPCE: 15 Jtem (MPCE: 8 JItem (MPCE: 2 Jtem
Hroups)
Hroups)
Hroups)
Hroups)
Hroups)
6rban
Rural
Figure A6: Distribution of Populations (in Percentage) with Budget Share,
Matching Percentage, Percentage of Bottom 10% Population Moves to
Higher Fractile Classes,True Positive Rate and True Negative Rate for
Reporting Percentage Cut-off Range (>60–>99%)
Figure A2: Extent of Mismatching in Partial MPCE Based on Different
Reporting Cut-off Chosen, Rural Kerala
Cumulative aggregate in
percentage of population
90
80
70
60
50
40
30
20
10
0
0
>80% Reporting (21 Jtem
Hroups)
>85%Reporting (17 Jtem
Hroups)
>90%Reporting (15 Jtem
Hroups)
>95%Reporting (8 Jtem
Hroups)
>99%Reporting (2 Jtem
Hroups)
10
11
32.4 67.58 21.95 5.29 2.5 1.43 0.74 0.5 0.25 0.22 0.02
1
2
3
4
5
6
7
8
0
33.1 66.92 25.11 8.51 2.82 1.18 0.67 0.45 0.31 0.07
0
0
31.5 68.46 25.74 8.65 3.04 1.19 0.58 0.46 0.2 0.07
0
0
29.1 70.89 32.92 12.43 4.59 1.64 0.71 0.19 0.06
9
0
0
17.3 82.67 55.88 34.11 18.62 9.85 4.45 1.79 0.4 0.16 0.02
0
0
Rank difference 0 indicates that assigned classes in both total MPCE and partial MPCE are
same or matching in classes. Rank difference 1 indicate that there is at least difference in
rank of one. Similarly, Rank difference 2: at least difference of rank of 2.
Reporting
percentageDutt-off
cut-offSange
range(>60
(>60toto>99%)
> 99%)
Reporting Qercentage
Matching with Uotal MPCE (% population)
Budget share (%)
True positive rate (%)
negetive rate
True negative
rate(%)
(%)
Percentage of bottom 10% population moves to higher classes
Table A3: Drop Points for Rural Sector of Kerala
Drop in Drop in Population Percentage Percentage
Budget Matching Come Down Drop in
Drop in
Share
(%)
to Lower
True
True
(%)
Two Fractile Negative
Positive
Classes from
Upper
(% Increase)
64 63
60
Budget share (%)
60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99
Sl Reporting Excluded
No Percentage Broad
(Cut-off) Item Group
Figure A3: Overall Buget Share with Different Choice of Reporting
Percentage-wise Consumption Expenditure
70
120
100
80
60
40
20
0
50 49
50
46 45
40
26 28
30
20
6
10
6
0
>80% 3eporting >85% 3eporting >90%
>95% 3eporting>99% 3eporting
(21 item groups) (17 item groups) 3eeporting (15 (8 item groups) (2 item groups)
item groups)
Rural Cudget Thare
Urban Cudget Thare
1
2
3
4
63–64
68–69
74–75
82–83
Served processed food 6
Durable goods
14.14
Medical (institutional) 5
Education
3
Percentage of population
60
50
55
43
40
30
20
10
29
Sl Reporting Excluded
No Percentage Broad
(Cut-off) Item Group
0.09
0.17
0.76
-0.71
Drop in Drop in Population Percentage Percentage
Budget Matching Come Down Drop in
Drop in
Share
(%)
to Lower
True
True
(%)
Two Fractile Negative
Positive
Classes from
Upper
(% Increase)
63–64
68–69
74–75
77–78
Served processed food
Durable goods
Medical (institutional)
Entertainment
5
17
5
1
10.1
11.2
0.9
-0.3
1
0.1
0.08
-0.07
9.9
0.11
1.43
-0.97
1.11
-0.02
0.08
-0.08
Source: Authors’ estimation based on NSS 68th round.
24
16
6
11
10
41
00
41000
000000
000000
available at
0
>80% Reporting >85%Reporting >90%Reporting>9%Reporting >99%Reporting
(2Jtem Hroups)
(17 Jtem
(15 Jtem
( Jtem
JUFN
HSPVQT
HSPVQT
HSPVQT
HSPVQT >70% Budget Thare
>90% Budget Thare
28
0.99
2.84
6.28
-1.52
Table A4: Drop Points for Urban Sector of Kerala
1
2
3
4
65
0.09
0.15
0.95
0.27
Source: Authors’ estimation based on NSS 68th round.
Figure A4: Percentage of Populations with Budget Share Based on
Different Reporting Cut-off Chosen, Urban Kerala
70
11.9
12.6
2.2
0.6
>75% Budget Thare
>95% Budget Thare
>80% Budget Thare
>99% Budget Thare
>8% Budget Thare
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COMMENTARY
Table A5: Broad Item Groups Selection along with Their Scores For Rural
Sector of Kerala
Table A6: Broad Item Groups Selection along with Their Scores for Urban
Sector of Kerala
Item Description
Code
Share Percentage Score (S) Post
Reporting
Score (S)
Selection
Item Description
Code
32
21
25
13
26
27
34
28
10
01
44
09
07
12
45
03
08
04
15
30
35
22
23
37
14
02
33
36
17
11
24
18
16
29
4.85
4.55
1.59
2.18
1.53
4.72
0.8
6.09
4.1
5.38
0.93
3.49
1.84
2.82
0.08
1.55
8.07
3.44
2.2
0.31
3.65
5.68
1.37
14.4
6.26
0.32
0.19
3.48
0.9
0.34
0.22
1.57
0.21
0.9
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
No
Yes
Yes
No
No
No
No
No
No
No
No
32
25
21
27
26
34
28
13
10
1
44
9
12
7
3
45
4
8
30
35
15
23
22
37
14
33
2
36
11
29
17
18
24
16
Clothing
Fuel and light
Toilet articles
Beverages
Other household consumables
Consumer services excl. Conveyance
Footwear
Conveyance
Fruits (fresh)
Cereals
Sugar
Vegetables
Edible oil
Spices
Salt
Pulses and products
Egg, fish and meat
Milk and products
Packaged processed food
Consumer taxes and cesses
Education
Medical (non-institutional)
Entertainment
Durable goods
Served processed food
Cereal substitute
Bedding, etc
Medical (institutional)
Tobacco
Fruits (dry)
Minor durable-type goods
Intoxicants
Pan
Rent
100
99.9
99.6
99.5
99.3
99.2
98.8
98.2
97.9
97.7
97.7
97.5
97.4
97.4
95.5
95.2
90.3
88
84.9
84
82.2
80.6
77.5
68.2
63.5
53.2
41.1
28.9
27.4
21.6
16.8
15.6
9.7
8.3
3.25 2.89
3.89 2.81
8.6 26.49
14.02 10.42
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Post score= score calculated after inclusion of particular broad item group in partial MPCE
calculation.
Source: Authors’ estimation based on NSS 68th round.
Share Percentage Score (S) Post
Reporting
Score (S)
Clothing
4.89
Toilet articles
1.45
Fuel and light
4.65
Consumer services excl conveyance 5.64
Other household consumables
1.34
Footwear
0.79
Conveyance
7.11
Beverages
1.98
Fruits (fresh)
3.93
Cereals
4.57
Sugar
0.76
Vegetables
3.01
Spices
2.23
Edible oil
1.62
Pulses and products
1.4
Salt
0.07
Milk and products
3.31
Egg, fish and meat
6.9
Consumer taxes and cesses
0.55
Education
4.94
Packaged processed food
1.96
Entertainment
1.35
Medical (non-institutional)
5.03
Durable goods
16.64
Served processed food
4.68
Bedding, etc
0.29
Cereal substitute
0.15
Medical (institutional)
3.03
Fruits (dry)
0.4
Rent
3.21
Tobacco
0.66
Intoxicants
1.15
Minor durable-type goods
0.24
Pan
0.06
100
99.2
98.9
98.9
98.8
98.7
98
97.6
94.4
93.2
92
91.9
91.8
91.7
90.7
89.5
87
84.7
84.6
83.6
83
81.6
74.9
70.4
63.5
44.9
42.3
26
23.9
23
22
13.2
12.5
4.9
30.05 47.99
1.82 1.54
28.74
8
0
0
3.05 3.05
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Selection
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
No
No
No
No
No
No
No
No
No
Post score= score calculated after the inclusion of particular broad item group in partial
MPCE calculation.
Source: Authors’ estimation based on NSS 68th round.
EPWRF India Time Series
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both on revenue and capital account, outstanding liabilities and their surplus/deficit position.
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Loans, External Debt, etc.)
●
Combined Expenditure: Total Expenditure (Developmental, Non-developmental, Loans and Advances, etc.)
This data is sourced from the publications of Department of Economic Affairs, Ministry of Finance, Government of India. These
data-sets are available from 1985-86 onwards.
Combined Government Finances module is one of the 37 modules of EPWRF ITS, which covers a wide range of macroeconomic,
financial and social sector indicators for India.
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INSIGHT
tend to be sticky and less reactive to
Rating Accuracy and Default Risk change with the market conditions.
Is Model Risk a Concern for
Indian Banks?
Arindam Bandyopadhyay
Model risk is evaluated from
the credit rating agency
perspective and its implications
on risk management practices
to be adopted by Indian banks
are elaborated upon. A sharp
deterioration in the accuracy of
agency ratings is observed from
2009 onwards in comparison
to high accuracy values during
2004–08. Time series tests
further reveal that a fall in the
predictive power of agency
rating leads to an increase in the
incidents of corporate defaults in
India. Banks need to follow due
diligence in lending and reduce
mechanistic reliance on external
credit rating for evaluating
corporate credit risk.
Arindam Bandyopadhyay (arindb@rediffmail.
com) is with the National Institute of Bank
Management, Pune.
40
C
redit risk is the largest element of
risk in the books of most banks
and financial institutions. Effective
management of credit risk is a critical
component of a comprehensive approach
to risk management and essential to the
long-term success of any banking organisation. Credit risk is generally measured through credit ratings and estimation of default probability. Credit rating
models are used to assess the probability
of default for the effective management
of bank capital. The probability of default of a company depends on factors
such as market outlook, company size,
competitive factors, quality of management, and financial position. The Basel
Committee believes that it is quite reasonable to view risk parameters as a
forecast for future realisations within a
one-year time horizon (Blockwitz and
Hohl 2007).
Rating is considered a useful tool for
credit risk measurement. It uses a process to detect the creditworthiness of
an entity. Credit rating agencies (CRA s)
provide information about the creditworthiness of corporate borrowers thereby helping to reduce the information
asymmetry between lenders and investors. The CRA s’ role in the financial markets has been further enhanced due to
the adoption of Basel II/III regulations
that suggest external ratings be used for
the computation of credit risk weights
(CRWs) to derive a bank’s capital adequacy
ratio (BCBS 2011, 2017; RBI 2015).
It is important to note that the Basel III
standard describes the prudential framework for risk-based capital requirements.
A company rating process conducts an
assessment of financial risk, business
risk, and management risk. However,
there is a criticism that credit ratings
Even though established CRA s have a
successful past and are also recognised
by the Basel Committee on Banking Supervision (BCBS) for estimation of CRWs,
today, CRA s face criticisms about their
slow reaction to market changes. The
United States (US) financial crisis in
2008, the European Debt Crisis, and the
recent non-banking finance company
(NBFC) crisis in India have prominently
highlighted these issues.
It is expected that there will be a significant correlation between ratings and
default frequencies. Model risk occurs
when the credit-rating model fails to
perform adequately. This happens because of a defective model, its opacity or
misuse, which can lead to unanticipated
losses, regulatory penalties and adverse
reputational impact for a bank. Model
risk measurement and mitigation is thus
becoming a central focus in banks and
financial institutions. How rating models are developed, tested, reviewed, and
used in the business is becoming critical
for sustaining business operations. The
Federal Reserve Board (2011) has released
US SR11-07 guidance on model risk management that provides useful information for banks to adopt an effective model validation policy.
There is an increased concern about
model risk since agency ratings are unable to update scores timely and provide
early warning signals causing a loss of
predictive power. This may be due to the
through-the-cycle (TTC) nature of the
rating process followed by the agencies
and, hence, failure to reflect current economic conditions. A TTC rating does not
fluctuate much with changes in business
cycle conditions (De Servigny and Renault
2004). Broadly, agency ratings are assumed to be more TTC, whereas bank
internal rating systems are considered to
be more point-in-time (PIT). This issue
has been further elaborated by Kiff et al
(2013). Their findings suggest that even
though the TTC-based rating is more stable, they are prone to rating cliff effects
(that is, sudden change in ratings) and
suffer from inferior performance in
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INSIGHT
predicting future default risk. This happens due to typically long-term view and
delay rating changes.
Moreover, Ellis (2008) has pointed out
a deficiency in Fair Isaac Corporation
(FICO) as a bureau credit score since it
had failed to indicate any relationship
between the borrowers’ credit scores and
default incidents during the US subprime
crisis. In India, the rising level of nonperforming assets (NPAs) and quantum of
restructured loans in banks and financial
institutions since 2014 has further raised
concerns about heightened model risk.
Bandyopadhyay (2019) compared the
historical rating migration pattern of
Indian corporates and found greater
variability in domestic ratings and, hence,
lesser early warning signal power in comparison with the global benchmarks.
As a credible tool to measure credit risk,
ratings are expected to differentiate good
credits from bad ones. Kiritz et al (2019),
in exploring industry practices and principles in model risk, have stressed on the
importance of creating proper metrics
that provide a transparent and consistent way to determine model risk. The
power to discriminate between good
and bad borrowers is often highlighted
as the main criterion for assessing the
predictive accuracy of a rating system.
The quality of a rating system is measured in terms of its discriminatory power
(Blochwitz et al 2005). To measure the
discriminatory power of a rating model,
the Gini coefficient or the area under a
cumulative accuracy profile (CAP) has
found widespread use both in academic
studies as well as in practice. It is a
measure of the risk-wise rank ordering
of credit ratings over a given time horizon.
In other words, an effective rating system should not only assign low ratings to
issuers that ultimately default but also
assign high ratings to those that are far
away from the default point. Gini values
range from zero to one and a higher Gini
indicates better rating accuracy that better discriminates between good (solvent) borrowers from its bad (defaulted)
counterparts.
Many studies have addressed this
estimation method and suggested different statistical measures to perform
quantitative validation. However, few
Economic & Political Weekly
EPW
may 4, 2024
studies quantify the model risk in
terms of capital or provisions. Few attempts have also been made to systematically analyse the validity of agency
ratings, especially in the Indian context. Gandhi (2014), former deputy governor of the Reserve Bank of India, in
his speech, had raised concerns about
the efficacy of ratings accountability
and transparency of CRA s due to the
rise in npa s in Indian banks. Singh and
Chavan (2020) studied the pattern of
the selected list of defaulted corporate
borrowers and found that external
credit ratings do not always reflect the
asset quality of borrowers on time. This
raises concerns about the rating quality
of Indian CRA s. Further, there are concerns about delays in reporting by
banks. Sharma et al (2023) utilised
firm-level financial and rating data
from India to find that competition
leads to inflated ratings and shopping
practices in the credit rating industry.
Their paper suggests that regulators
need to actively monitor and control
the competition among CRA s to warrant
the accuracy of credit ratings.
Financial institutions need to regularly
check the performance of their internal
rating models against external ratings to
understand model risk (BCBs 2005).
This article assesses the trend in model
performance of agency rating and relates it with the business cycle and corporate default rates. Using time series
data, it attempts to establish a linkage
between model performance and risk of
default at an aggregate level. The purpose is to understand the model risk inherent in the corporate lending business
and elaborate its implications in terms of
loss provisions, capital, and profitability
of banks in India.
Data and Methodology
We have studied the one-year estimate
of the Gini coefficient and its yearly
trends as reported by a leading CRA. The
accuracy index appears to be broadly
cyclical and negatively correlated with
default rates (Figure 1, p 42). That is, when
default rates are high, model performance is also poor. This enables us to
establish a linkage between model performance and default rates.
The correlation between domestic credit
rating agency (DCRA) model accuracy
and corporate default rates is statistically significant and is negative with a
coefficient value of –0.736.
We have also examined how the distribution of corporate ratings has changed
over time. This is presented in Table 1.
It is quite evident that over time, there
is a shift in the distribution of borrowers
across agency grades. During periods of
stress, the overall portfolio quality deteriorates, the median rating declines, and
the default rate also increases. This is
quite evident from the rating pattern of
a leading agency rating.
Figure 2 (p 42) shows that the global
rating accuracy has been quite stable
even during the crisis period when default rates peaked. The correlation between the global credit rating agency
(GCRA) model accuracy and the corporate default rate is estimated as
–0.16013. The correlation coefficient is
significantly lower in the case of the
global agency (GCRA) than its domestic
counterpart.
Utilising the annual time series data
of Indian corporate default probability
and the Gini index collated from several
default study reports of a leading CRA in
India, we have applied several statistical
tests to check the time series property of
both the series and their relationships.
Table 2 (p 42) provides a summary of
statistics of two key variables studied in
this article.
The mean corporate default rate (as
represented by the variable DEFR) is
around 3% with a standard deviation of
2%. The mean value and median values
are quite similar. The model accuracy as
reported by the CRA is represented by
the Gini coefficient. The mean Gini for
the sample period is 0.635, which is very
close to its median value. Both the series
Table 1: CRAs Rating Distribution
Grades
Share of Borrowers (%)
2003–04 2008–09 2013–14 2018–19 2022–23
AAA
AA
A
BBB
BB
B
CCC/D
10.87
29.88
33.70
14.73
7.97
0.80
2.04
6.57
13.69
16.94
33.20
17.29
6.50
5.81
0.98
2.04
4.07
16.30
32.60
34.64
9.37
1.36
4.91
8.24
21.82
37.10
21.28
5.29
3.25
9.15
16.25
31.30
26.50
9.40
4.15
Source: Author’s compilation from a leading rating
agency’s published default studies.
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41
INSIGHT
Figure 1: Corporate Rating Performance in India
0.9
0.8
0.76 0.75 0.76 0.78
0.79 0.80 0.81 0.81
Figure 2: Global Corporate Rating Performance
0.82 0.80
6%
0.71
5%
0.63
0.7
0.57
0.6
0.53
0.49 0.48 0.47
0.46 0.46 0.47 0.47 0.48
0.50
0.5
4%
2%
0.3
0.2
1%
0.1
0
4.00%
0.8
3.50%
0.7
3.00%
2.50%
0.5
2.00%
0.4
1.50%
0.3
0.2
1.00%
0.1
0.50%
0.0
0.00%
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
0%
Rating Bccuracy Satio
4.50%
0.9
0.6
3%
0.4
1.0
Default Sate
Accuracy Satio
Source: Author’s computations based on several published default study reports of a
leading credit rating agency in India.
are normally distributed as reflected in
their skewness and excess kurtosis values.
The normality of the series is also confirmed by Jarque–Bera test statistics (a
low Jarque–Bera value and higher p-value
confirm that it is normally distributed).
To check the non-stationarity of both
series, we have performed an augmented
Dickey–Fuller (ADF) unit root test with a
structural break. As evident from Figure 1,
there is a clear presence of a structural
break for Gini from 2009. This was the
year when the Basel-II regulation was
implemented in India and Indian commercial banks started using CRA ratings
to estimate their credit risk-weighted assets. The CRA s had started providing
loan ratings on a larger scale. The breakpoint date is selected based on the Dickey–
Fuller minimum t-statistic, and the lag
length is selected using the F-statistic
max lag, which is set at 4 by default.
These tests are conducted in a statistical
package named EViews 10.
The ADF test (Dickey and Fuller 1979;
Dickey 1981) tends to be inclined towards the non-rejection of a unit root
when structural breaks are present,
which can lead to incorrect conclusions.
Therefore, we have performed unit root
tests with structural breaks. The results
for the unit root test have been presented in Table 3. We have performed a unit
root test with a structural break in the
EViews statistical package. The breakpoint date is selected based on the Dickey–
Fuller minimum t-statistic, and the lag
length is selected using the F-statistic
max lag, which is set at 4 by default. We
observed a clear break in the intercept
for the Gini variable in 2009 and for
DEFR in 2021. Therefore, we selected the
trend and intercepted it in the unit root
test. The null hypothesis of the unit root
is rejected with a p-value less than 0.01,
indicating that both the variables are
stationary with a breakpoint in 2009
and 2021. The suggested lag lengths by
Perron (1989) are zero and 3 lags, based
on the F-statistic. The selection criteria
for the breakpoint date is the minimum
t-statistic. The ADF unit root test results
confirm that based on trend and intercept, both Gini and default rates are stationary series.
We have investigated if there exists
any temporal causal relationship between
two time series variables. Granger (1988)
causality detects the direction of causation between two variables. The reported
Table 2: Summary Statistics
Table 3: Results of the Unit Root Tests for Rating
Accuracy (Gini) and Default Rate (DEFR) with
Structural Break
Key Statistics
DEFR
Gini
Mean
Median
Minimum
Maximum
Standard deviation
Jarque–Bera
Prob>JB
Number of
observations
0.030
0.034
0.095
0.000
0.022
3.123
0.210
28
0.635
0.630
0.820
0.460
0.149
3.153
0.207
23
Source: External ratings accuracy and default rates from
various default studies.
42
Series
Gini
DEFR
Lag
No of
Length Observations
0
3
Default Sate
Source: Author’s own computations based on several published default study reports of a
leading global credit rating agency.
22
24
Break
Date
2009
2021
Level Series
With intercept
and Trend
–7.96***
–5.41***
Values are augmented Dickey–Fuller test statistics with
break adjustment; *** denotes significance at 1% or
better. Significance is derived based on Vogelsang’s (1993)
asymptotic one-sided p-values. Lag lengths are decided
based on the Schwarz information criterion.
F-statistics are Wald statistics for the joint
hypotheses of each equation. The null
hypothesis is that the x variable does not
Granger-cause y in the first regression and
y does not Granger-cause in the second regression. The test results are reported in
Table 4. It is quite evident that we cannot reject the hypothesis that default does
not Granger-cause model accuracy but
we do reject that model accuracy does
not Granger-cause corporate defaults.
Therefore, it appears that Granger causality runs one way from model accuracy to default and not the other way.
We have utilised a reduced form vector autoregression (VAR) framework to
find the multivariate relationship between
model accuracy and corporate default
rates. The regression results are presented
in Table 5 (p 43).
Table 5 shows the result obtained by
using reduced-form VAR with our test
variables. Each column represents a subequation. In the reduced-form VAR model,
each variable is considered as a linear
function of its past values, the past values of all other variables being considered, and a serially uncorrelated error
term (Stock and Watson 2001). Thus, in
our framework, the VAR involves two
equations, the current default rate is a
function of its past values and model
accuracy (Gini). Similarly, the current
Table 4: Results of Granger Causality
Null Hypothesis (H0)
F-statistic
Probability
Decision
Gini does not
Granger cause DEFR
DEFR does not
Granger cause Gini
6.387
0.00
2.154
0.148
Reject
the H0
Cannot
reject
the H0
Number of common observations = 23, lag length is
chosen as 2 periods.
Source: Author’s estimates.
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INSIGHT
Figure 3: Impulse Response
Response of DEFR to GINI
0.0050
0.0030
0.0010
-0.0010
-0.0030
-0.0050
-0.0070
-0.0090
-0.0110
-0.0130
1
2
3
4
5
6
7
8
9
10
Response to Cholesky on standard deviation (degrees of
freedom adjusted); Innovations ±±2 standard error.
Source: Based on the VAR estimates reported in Table 5.
Gini is a function of its past values and
default rate. The number of lagged values
to include in each equation is determined
by Akaike information criterion (AIC)
and Bayesian information criterion (BIC).
The VAR result confirms that model accuracy (Gini) has a significant impact on
default risk.
Estimated VAR for DEFR and Gini have
been further passed through the diagnostic tests. We have found there is no
serial correlation and no heteroscedasticity in the residual. The error terms in
a VAR system of equations are denoted
as impulses. The shocks or innovations
to an endogenous variable are introduced
through the error terms. The effects of
these shocks are presented in impulse
response functions (IRFs) (Figure 3).
Figure 3 shows the impulse responses
generalised to one standard deviation
innovation based on the VAR model reported in Table 3 with two endogenous
variables (Gini and DEFR). The dotted
Table 5: Vector Autoregression Results, 2002–22
DEFR (–1)
DEFR (–2)
Gini (–1)
Gini (–2)
Intercept
R-squared
Adjusted
R-squared
Log-likelihood
Akaike
information
criterion
Schwarz
criterion
DEFR
Gini
0.238954
(0.23486)
–0.287421
(0.23092)
–0.3312724***
(0.09610)
0.248238***
(0.08240)
0.077924
(0.02626)
0.772384
0.715480
–0.695065
(0.45499)
0.782454
(0.44737)
1.721249***
(0.18617)
–0.754105***
(0.15963)
0.015981
(0.05088)
0.987986
0.984983
70.66447
–6.253759
56.77721
–4.931163
–6.005063
–4.682468
Standard errors are in parentheses. *** indicates
significance at the 1% level or better.
Economic & Political Weekly
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may 4, 2024
line refers to a standard deviation confidence band. The continuous line inside
the bands indicates the median of impulses due to one standard deviation shock
given to model accuracy (that is, Gini). It
is quite evident that Gini has a strong
short-term impact on corporate default
rates. A one-standard-deviation shock
given to Gini will result in a fall in the default rate till the third period. Thereafter, it gradually peaks up in the long run.
Rating agencies are of the view that
in periods of high defaults, there tends
to be greater variation in the distribution of ratings before default, which reduces the Gini. However, our empirical
findings confirm that reverse-way causation is also taking place for Indian
corporates. This is also captured in our
Granger causality test, VAR results, as
well as impulse responses. This means
a fall in the power of agency rating
leads to an increase in the incidents of
corporate defaults.
When we benchmark this with global
corporates, we observe that despite
posting the 10th highest annual default
rate in 2020, the global Gini coefficient
of the GCRA remained quite stable. The
one-year Gini ratio in 2020 was 0.86
alongside a speculative-grade default
rate of 5.5%. This compares with a Gini
of 0.883 and a default rate of 2.5% in
2019. In 2012 as well, the one-year Gini
was 0.895. Even if cyclicality in rating
accuracy is present, the level of variations is significantly lower than in the
Indian situations. It indicates the presence of greater model risk inherent in
domestic agency ratings.
Model Risk Impact on Bank Capital
Noticeably, we observe that there is a
sharp deterioration in the Gini coefficient from 2014 onwards in comparison
to high accuracy values during 2004–08.
This captures the severe impact of model
risk on the overall banking business.
The average Gini value from 2004 to
2008 was 0.81. This has been drastically
reduced to 0.47 from 2014 to 2022. The
difference in the average default rate
between these two time periods is also
quite significant (0.21% versus 3.96%).
This gives us crucial statistics for capturing the impact of model risk in terms of
loss provisions. If the overall Indian
corporate loss given default (LGD) rate is
65%, then the additional expected loss
provisioning requirements for model risk
would be (3.96%–0.21%) ×65% = 2.44%.
If the average cost of borrowing of Indian
banks is 6%, then the additional cost of
credit for model risk would be around
146 basis points. This has an adverse
impact on the profitability and return
on equity of banks.
Conclusions and Suggestions
We have assessed the temporal trend in
the model performance of agency ratings and established its linkage with
corporate defaults. It is quite evident in
our empirical time series results that
there is a sharp deterioration in the
agency model predictive accuracy. This
has also increased corporate default
rates. Hence, an increase in corporate
default risk can be caused by a sharp
deterioration in the accuracy power of
rating agencies. Moreover, the domestic
CRA’s discriminatory power is more cyclical and volatile than its global counterparts. Thus, a mechanistic reliance
on CRA s for credit rating to estimate
credit risk capital may invite model risk
for Indian commercial banks. This may
result in a heightened increase in NPA s of
banks as these ratings may not reflect
the actual credit risk position of corporate borrowers. Indian banks need to
regularly validate and calibrate their
internal ratings to ensure proper due
diligence in lending.
It is of utmost necessity for banks to
understand the importance of model
risk since their credit risk weights and
capital adequacy ratio computations are
mainly based on agency ratings. It is
suggested that financial institutions
should have a regular cycle of internal
rating model validation that includes
monitoring of model performance and
stability, review of model relationships,
and testing of model outputs against
actual outcomes. Model validation, governance, and transparency have become
key regulatory oversight areas and model
risk needs to be explicitly addressed under
Pillar 2 of the Basel-III framework. Top
management of commercial banks in
India therefore needs to prioritise model
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43
INSIGHT
risk management as an important component of risk management activities and
establish an effective model governance
framework that inspires management
and regulatory confidence.
References
Bandyopadhyay, A (2019): “The Accuracy of Agency
Ratings,” Economic & Political Weekly, Vol 54,
No 36, pp 15–17.
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— (2017): “Basel III: Finalising Post-crisis
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Blochwitz, S and S Hohl (2007): “Validation of
Banks’ Internal Rating Systems: A Supervisory
Perspective,” The Basel Handbook, M Ong (ed),
pp 453–79.
Blochwitz, S, A Hamerle, S Hohl, R Rauhmeier
and D Rosch (2005): “Myth and Reality of
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Wilmott, January.
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and Managing Credit Risk, McGraw-Hill.
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Autoregressive Time Series with a Unit Root,”
Econometrica, Vol 49, No 4, pp 1057–72.
Dickey, D A and W A Fuller (1979): “Distribution of
the Estimators for Autoregressive Time Series
with a Unit Root,” Journal of American Statistical Association, Vol 74, No 366, pp 427–31.
Ellis, L (2008): “The Housing Meltdown: Why Did
it Happen in the United States?” BIS Working
Paper No 259.
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Supervisory Guidance on Model Risk Management, 4 April, US.
Gandhi, R (2014): “Growing NPAs in Banks-Efficacy
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of Credit Rating Agencies,” speech by deputy
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conference conducted by ASSOCHAM, New
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Model Marathi, Modern Marathi
The History of a ‘Vernacular’ in South Asia
Anubha Anushree
L
anguage historians have paid generative attention to the processes
that strengthened the socialisation
of various languages as global, national,
or regional. A critical and enduring insight
into these histories of languages is the
role played by the nation states in homogenising languages and making them
representatives of national communities. At the same time, these accounts
have barely touched upon the material
and technological practices that influenced the transformation of languages
from a mode of recording and storage to
a mode of communication. The modernisation of languages as a medium of
communication also heralded its democratisation that overlapped with the
emergence of modern states where literacy became a crucial benchmark of authority, privilege, and inclusion. Histories of scripts and literacy, more than a
quibble for more comprehensive histories of languages from the subcontinent,
are powerful chronicles of how modern
states condition accessibility to itself,
routinely structure welfare inclusion,
and manufacture consent.
Marathi as a Deshbhasha
Predicated on the assumption that scripts
are natural and organic to languages,
scripts and the history of their evolution
have often been marginalised or regarded
as a subset of the process of linguistic
standardisation. The relationship between
scripts and languages, as several scholars have shown, is neither “natural” nor
are they static. Exposing the artifice of
scriptural consistency requires writing
histories of languages that demonstrate
how ideologies of scriptural uniformity
were constructed as salient to a language.
A comprehensive understanding of the
histories of languages in the subcontinent
also demands a closer examination of
34
book reviewS
Scripts of Power: Writing, Language Practices,
and Cultural History in Western India by Prachi
Deshpande, Ranikhet: Permanent Black and Ashoka
University, 2023; pp 309 + xv, `695.
the interplay of power and privilege
with the material organisation of writing and literacy. These practices have
historically transformed languages into
potent symbols of social and geographic
belonging/identity.
Prachi Deshpande’s book, Scripts of
Power: Writing, Language Practices, and
Cultural History in Western India, is
a significant contribution to a growing
scholarship that interprets languages as
constituted by ideologies as well as
materiality, technology, and circulation.
As a cultural history of the Marathi
language, this book is interested in
the deeply material work involved in the
making of Marathi as a modern “vernacular”
or deshbhasha, and the successful claim to
a separate linguistic state based on Marathi
that culminated in the state of Maharashtra
in 1960. (p 28)
Thus, the book aims to not only examine
how Marathi was ideologically constructed as a “vernacular,” but also the
material and technological transformations that constituted its vernacular
status. In Deshpande’s work, these
transformations in Marathi are explored
by the changes in the use and circulation
of the Modi script.
Organised into eight chapters (including the introduction and the conclusion) that follow a rough chronology
from the early modern multilingual
and poly-scriptural world of scribes in
the Maratha and the Deccan region to
the modern early 20th-century world
of print and mass literacy, the book is
divided into two thematic parts that
address the complex cultural history
of Marathi. The first part deals with
the various multilingual scribal communities associated with the Modi script
and the “moral horizons of writerly
activity” (p 59).
The second part of the book, the
focus of this review, begins with the 19thcentury Orientalist attempts to codify
and standardise Marathi. It examines the
material practices, institutional regulations, and policies that clarified Marathi
as a modern and intelligible language.
This process of clarification of Marathi—as distinct from Sanskrit and
Prakrit on the one hand and Persian on
the other—was crucial to its construction as a deshbhasha. Deshpande affirms
that this process of clarification was
crystallised through regulation and
disciplining of scripts, so prominently
epitomised by the debate around Naastaliq and Nagari in North India. She
argues that Modi’s construction as the
domain of the “profane,” its disciplining,
and eventual containment established
Marathi’s ascendance as a coherent language with a representative script. Just
as with Kaithi in Bihar or Magadhi
Prakrit in Manipur, Modi’s identification
as a trans-regional script was also the
reason behind its reduction to a specific
register and function.
The production of Marathi as a deshbhasha hinged on the process of the
scriptural acculturation and cohesion of
Balabodh, the script currently in use for
Marathi. Deshpande demonstrates how
this process was heralded by a coalition
of literary, colonial, and cultural forces
that signalled the end of Marathi’s historic scriptural diversity and cemented
its status as an epistemologically coherent “modern,” “regional,” and “vernacular” language. While colonial anxieties of
native corruption, scribal inscrutability,
and the suspicion of Brahmin-dominated
anticolonial nationalism discredited Modi
as illegible and inefficient, Balabodh’s
manufactured proximity to Sanskrit also
engineered its ascension as a “democratic
and transparent” script (p 223). In tracing this binary genealogy of scripts,
Deshpande aligns with several South
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Asian historians, who highlight the 19th
century as the pivotal time when languages and the relationships between
them were debated and reorganised
(p 145).
Construction of Linguistic Practices
However, there are two ways in which
Deshpande’s work departs significantly
from the scholarship in the field. The
first is her attention to the construction
of Marathi as a regional exemplar, a
deshbhasha that seconded and expanded the remit of provincial nationalism.
The second, more interesting dimension
of the book, is the treatment of Marathi
as an intricate combination of tactile,
sensory, sonic, visual, and moral elements and how they were policed to
align with the demands of the provincial
nationalism of the 20th century.
The paramount strength of Deshpande’s
thesis is not the originality of the argument, but rather in the comprehensive
and subtle approach she adapts to the
survey of Marathi. For example, in
her discussion of the “invention” of
the history of the Marathi language,
Deshpande’s analysis extends beyond
the conventional focus on colonial orientalists, offices, missionaries, and educational institutions. She provides a nuanced exploration of a diverse array of
Indian figures, including those educated
in Western traditions, who played a
pivotal role in redefining Marathi into a
language that not only embraced its
Sanskritic heritage but also asserted
itself as the “natural,” “official” language
of an emerging regional state (p 147).
This dual subscription of Marathi to
its hoary Sanskritic past, as well as its
modernising present, meant that Marathi
also crystallised canonical forms of privilege even as it fashioned new literary
subjectivities. Deshpande demonstrates
this phenomenon through her study
of the 19th-century endeavours to craft
origin narratives for Marathi. For example,
examining the moral anxieties of the
19th-century Marathi grammarians, she
traces how a series of grammatical texts
“established the Marathi language as a
coherent object of analysis, rooted in a
particular geographical area and spoken
by specific groups of people” (p 154).
Economic & Political Weekly
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May 4, 2024
Deshpande interprets this grammatical
turn not merely as an academic pursuit
but as a mechanism that consolidated
social hierarchies based on caste, gender, and class. Marathi grammar, she
observes, “was also explicitly conceived
in caste and gendered terms as the ideal
instrument for correcting language”
(p 157). This very 19th-century necessity
for grammatical depth that included
orthographic sanitisation as well as etymological density, however, was far from
straightforward. Neither did Balabodh
neatly fit within a Sanskritic teleology,
nor was Modi without its Brahminical
endorsement.
Modi’s Transformation
and Marginalisation
Nevertheless, Deshpande navigates
through the complex attempts to “purify” Marathi, highlighting the contribution of notable colonial and Marathi personalities and institutions. This process
of linguistic refinement, Deshpande contends, was premised on the passive, infantilised figure of the samanya manus
(ordinary man) in need of Marathi edification (p 206). The emergence of this
figure catalysed the democratisation of
writing, fostering a diversity of scripts
and literary forms that surpassed nationalist mandates. In the case of Kaithi,
for instance, despite its obliteration at an
official level by the early 20th century,
the domestic circulation of the script
continued until well into the 1990s.
Although the exact trajectory of the Modi
script remains less clear, Deshpande
illustrates that the marginalisation of the
Modi script and the consolidation of
Marathi into Balabodh were accompanied by a remarkable expansion of writing publics and genres. In this regard,
Deshpande’s foray into the history of
shorthand in South Asia stands out as
particularly noteworthy. This segment,
though brief, opens new avenues for research by examining shorthand as an
interface where state imperatives intersect with the burgeoning public sphere
(pp 218–22).
Through the lens of the Modi script’s
transformation, Deshpande sheds light on
the broader narrative of state formation
and the crucial role of language and
script in mediating the relationship
between governance, knowledge, and
identity. Deshpande compellingly argues
that Marathi’s identification with a specific geography and its inhabitants, its
linguistic representation with Balabodh
and the dismissal of Modi goes beyond
the dictates of progressive nationalism.
For Deshpande, the journey of Modi
script from its cursive inclusivity in the
early modern period to its gradual assemblage into bureaucratic and archival
apparatuses of the various kingdoms of
southern India in the 18th century, and
finally its depiction as illegible and inefficient in the 19th century exemplifies
the intricate process through which the
modern state was crafted and consolidated. With the focus on transparency
and archiving, modern states transformed
languages from devices of storing and
recording to mediums of establishing
identity and authenticity.
In the process, she meticulously explores how colonial bureaucratic infrastructure, revenue collection, and practices of archiving contributed to the
transformation of documents into “public property” where “public records” were
increasingly rendered as impartial and
unmediated repositories of information.
Within such a frame, scripts such as
Modi were progressively stigmatised
as signs of “native” inscrutability and
corruption, Brahminical despotism and,
more provocatively, anticolonial nationalism (p 239). This evolving narrative
led to what Deshpande describes as the
“privatization” of Modi, where its systemic marginalisation was not merely a
linguistic endeavour but also a broader
sociopolitical project. This project, she
argues, was instrumental in producing
“the unmarked clerk,” a figure salient to
the modern state’s claims of a transparent bureaucratic apparatus (p 256).
Conclusions
Cornelia Vismann’s Files (2000) suggests
that to understand the modern state is
to apprehend its forms of recording.
Dwelling on the dual nature of the term
“record”—the record is both a noun and
a verb—Vismann points out that it signifies both storage and transmission. But
there is a third dimension of meaning in
vol lix no 18
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35
BOOK REVIEW
the word “record.” The record also
refers to the measurement, to the creation of new paradigms. Through her
detailed analysis of the simultaneous
processes of the “making of the public
revenue, public record, and Anglo-vernacular public servant,” Deshpande
extends this discussion by suggesting
how record-keeping involves not only
archiving and sharing of information
but also the creation of new epistemological frameworks (p 256), paradigms
of categorisation of both writing and
36
people. She demonstrates how new
epistemological categories of bureaucratic integrity, forgery, and corruption
were conceived of and reinforced
through assignations of legibility and
illegibility of scripts.
This extensive 400-year cultural history of Marathi deserves to be read not
only as an academic exploration of a
prominent language from South Asia
and its community. By unravelling the
complex story of Modi and Marathi,
Deshpande provides us with a rare
glimpse into a realm where linguistic
practices constantly intersected with
state mechanisms. Her work compellingly argues that any understanding of
state history is incomplete without a
thorough examination of the languages
it employs. Linguistic as well as political historians would benefit much from
this work.
Anubha Anushree (anubha1@stanford.edu) is a
PhD from the Department of History, Stanford
University, California, and currently teaches at
the University of Delhi.
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Lighting Up Creation through
the Creation of Light
Kashshaf Ghani
M
uhammad na hotey to kucch bhi
na hota (nothing would have
been created if Muhammad did
not exist) goes the popular na’at (poetry
praising Prophet Muhammad) celebrating the creation through Muhammad;
also indicative of his primordial form as
light (nur-i-Muhammadi) and the creation
of everything else from that light. Although
Adam is recognised as the first human
being, orthodox Sunni traditions often
do not recognise him as the first prophet,
supported by references to Hadith through
al-Tirmidhi (d 892), where Prophet
Muhammad is believed to have remarked
that he entered prophethood when Adam
was between the spirit and the body. Such
beliefs came to be adopted and circulated through multiple textual traditions
across the Islamicate world, whose precise
origins through an individual author and
date are debated.
The book under review, Meaningful
Rituals: Persian, Arabic, and Bengali in the
Nūrnāma Tradition of Eastern Bengal, by
Thibaut d’Hubert, explores the Nūrnāma
tradition through “a corpus of narrative
texts that relate the creation of the world
by God through his Prophet Muhammad
in his pre-eternal form as a luminous
entity” (p 1). These works provided
knowledge on Islamic beliefs, ethics,
36
Meaningful Rituals: Persian, Arabic, and
Bengali in the Nūrnāma Tradition of Eastern
Bengal by Thibaut d’Hubert, Delhi: Primus Books, 2022;
pp x + 183, `1,495.
and cosmology, while as a text and artefact, their reading and physical preservation brought protection and prosperity
to the household. Nūrnāma texts were
written and translated between the 17th
and 19th centuries, a period which also
marked the high point of Islamisation
of eastern Bengal through a combination
of political and cultural processes. Sufism
remains a major vehicle which introduced
Islam in the region of Bengal (Haq 1975),
while the expansion of the agrarian frontier into the heavily forested eastern Bengal allowed Sufis and pirs to preside over
agrarian communities and urban centres
(Eaton 1993). The book is an important
addition to that field of research, opening
up new avenues that allow us to grasp
Islamisation in Bengal through practices
of literacy and textual traditions.
By selecting multiple versions of the
Nūrnāma—written in Persian, carrying
“motifs also found in Indic creation
stories” (p 1), and translated into middle
Bengali, written in Arabic script in middle
Bengali—the author aims to show “the
high degree of multilingual literacy that
characterised the cultural landscape of
pre-modern and early colonial Bengal,”
and subsequently “contribute to the
study of this narrative and the role it
played in recording the views of Bengali
Muslims on cosmology and the written
word” (p 1). That rural Muslim authors of
middle Bengali were embedded in the
Perso–Arabic literary culture is made
evident through the first Bengali Nūrnāma,
also the most elaborate of the six Bengali
versions, which was translated from an
anonymous Persian text. The other
Nūrnāma selected for the current book is
by Muhammad Saphi, written in the
Arabic script. This preference of the script
brings into focus the debate in 17thcentury Bengal on the “legitimacy of the
vernacular language and the regional
Indic script to discuss Islamic topics” (p 4).
Nūrnāma as Sufi Literature
The author categorises the Nūrnāma tradition as Sufi literature, primarily because
these texts were composed by Sufi
authors who were mostly trained in the
non-tariqa tradition. However, what kind
of Sufi elements the Nūrnāma texts reflect
is something the reader will be curious
about. Sufism played a dominant role in
the Islamisation of Bengal throughout
the medieval and early modern period.
Could Sufi authors write esoteric texts
and works on Islamic cosmology and
ethics in the same breath? The textual
identification of the Nūrnāma, then, can
be done accordingly.
Chapter 1 elaborates on the Nūrnāma
tradition as part of the Sufi textual
corpus in middle Bengali, as well as in
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the larger context of Musalmani literacy
through registers of language, script, and
ritual use of Islamic texts in rural Bengal. The author mentions that textual
analysis of middle Bengali literature
allows for a better opportunity to understand Bengali Islam in the early modern
period. He identifies three approaches
as pertinent among the many that have
been undertaken. As far as the translation
of texts is concerned, Tony Stewart’s
(2001) approach has been emphasised,
which moves beyond the dated idea of
syncretism, in favour of understanding
Indic terminology in Bengali Muslim literature “as semantic phenomenon” (p 8).
Shaman Hatley’s (2007) closer analysis
of the contents of such texts allows us to
understand how Bengali Muslim literature on yoga could incorporate Nath elements from Sanskrit.
The author, however, argues that the
practice of intertextuality in Bengali
Sufi texts can be determined more conveniently in non-esoteric works than the
esoteric, whose textual roots remain unclear. The third scholar referred to is
Carl Ernst (2016), who studies yoga in the
history of Sufism and the adoption of
yoga practices by Sufi saints to achieve
their spiritual goals. The author, however, argues that local traditions, like yoga
and esoteric tantric practices, were not
the only knowledge systems influencing
middle Bengali Islamic texts. Rather, as
he shows, the Nūrnāma case is a clear example of how Persian and Arabic works
circulating across the Muslim world also
influenced Muslim authors in Bengal
who were drawn by “the genres and
modes of didacticism of the texts” (p 10).
The idea of the light of Muhammad
(Nur Muhammad) constituted a critical
component of middle Bengali Sufi works
on yoga written between the 16th and
18th centuries. It was preceded by praises
for God and Muhammad, and followed
by the stages of spiritual realisation and
teachings about various aspects of biocosmological knowledge (deha-tattva).
But as the author argues, while we are
unclear regarding the textual transmission of classical Sufi and Nath doctrines,
it is the opposite in the Nūrnāma tradition
which can be clearly traced to the Persian
source text. The Persian text of the
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May 4, 2024
Nūrnāma “fits remarkably well with Indic
creation stories” (p 12), an observation
which leads the author to argue, drawing
from the works of earlier scholars, that
the knowledge of Indic bio-cosmology was
already a part of Persian texts in South
Asia during the pre-Mughal period.
The current work is a textual analysis
of two Nūrnāma copies. The first one,
housed in Paris, is written in Persian.
The second one uses the Arabic script to
write the Nūrnāma in middle Bengali.
The Persian copy, translated by Abdul
Hakim, begins with the creation story,
followed by the importance of reciting
the Nūrnāma, the merits gained from
reading and listening to it, or just by
keeping it in one’s house. Then comes
the story of Imam Ghazali (d 1111) who
supposedly sent a copy of the text to Sultan Mahmud so that the latter can read
and relieve himself of sins. The author
argues that from the 17th century onwards,
“Nurnama was a ritual Persian text that
was part of the daily environment of
Bengali Muslims” (p 15).
Language becomes a key element in
the transmission of the Nūrnāma to its
Bengali readership, particularly in the
context of the debate as to whether Islamic texts and concepts should be (re)
produced in regional vernacular. Thus,
while the ritual reading and understanding the meaning of the text is emphasised, the latter exercise perhaps
also made it imperative to translate the
text into Bengali and use the Perso–Arabic script while retaining the middle
Bengali language to avoid strong censure. Hakim inserts a long apologia for
reproducing this religious work in Bengali. He also defends himself in favour of
the use of the vernacular for “those
friends who are not trained to read
[such] books” (p 15). It was to honour
and satisfy everybody’s wish “by rendering the poem about the creation of light
into the language of Banga” (p 15).
The other reason is more interesting,
as it is connected to the emotion of reading. Hakim is clear that “treatises in Arabic convey no emotion, but one is deeply
moved when he understands the work in
the regional idiom” (p 15). Hakim continues “the lord doesn’t ignore any language; whatever the kingdom he knows
its language” (p 16). However, as the author points out, the masses of eastern
Bengal were exposed in many degrees
and forms to Perso–Arabic literacy as
part of their education and religious
training. The Nūrnāma copies bring forth
an interesting aspect where premodern
texts can be defined through their language, the use of the alphabet (Persian/
Arabic/Bengali) or the format of the
manuscript, which is understood by the
author “as a codicological definition of
the book’s religious identity” (p 16). While
the Bengali alphabet is also identified as
hinduyani (Indic), Hakim draws a strong
parallel between the alif (first letter in
Arabic) and the anji, since the latter is
believed to have carried a “crucial function in the sanctification of Islamic texts
written in Bengali” (p 16).
Islamicisation of
Vernacular Literacy
The acceptance of anji, the author argues, recognised by Muslim authors of
middle Bengali as non-contradictory to
Islamic ethics, was weakened with the
introduction of the Arabic naksh script
to write middle Bengali texts, together
with the spread of modern standardised
Bengali alphabet. The strong reformist
current also played a part in relegating
Sufi texts on yoga like the Yoga-Kalandar
from a premier social position in courts
and literate milieus to the fringes of the
heterodox communities like fakirs and
bauls. The practice of yoga to meet Sufi
goals was central to Sufi traditions in
premodern Bengal.
An undated manuscript of Saphi’s
Nūrnāma is the second work analysed in
the current volume. The author assumes
EPW Index
An author-title index for EPW has been
prepared for the years from 1968 to 2012.
The PDFs of the Index have been uploaded,
year-wise, on the EPW website. Visitors can
download the Index for all the years from
the site. (The Index for a few years is yet to be
prepared and will be uploaded when ready.)
EPW would like to acknowledge the help of
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Institute for Development Research, Mumbai,
in preparing the index under a project
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the work to be from the late 18th and
early 19th centuries. The work is a translation from an Arabic original and is
written in the Arabic script, allowing the
author to argue—first, how Perso–Arabic
literacy became important in the “transmission of local forms of religious discourse” (p 17), and second, adopting the
Arabic script to write a Bengali text
“was primarily motivated by a will to
sacralize scribal practices” (p 17), using
the status of Arabic. The author further
discusses the trend of applying the Arabic
script to write Bengali manuscripts,
particularly from the regions of Chittagong and Arakan during the late 18th
and mid-19th centuries.
Though this practice seems to have
started in the 17th century, there is a
lack of a definitive reason as to why this
began in the first place. The author
argues that the Islamicisation of vernacular literacy could be a strong reason for
this trend, though it may be erroneous
to limit such a development to a single
religious-centric cause. The author elaborates on the categorisation, along communal lines, between the idea of the
Hinduyani and the Musalmani, where
the former indicated the use of the esoteric sign ajni and Indic alphabets. Hinduyani, according to the author, did not
indicate any religious or theological position, and was thus “not antithetical
with one’s identity as a Muslim” (p 18).
Being divorced from religion and theology, these terms were widely used in
Bengali and Persian texts from medieval
Bengal and contributed towards varied
approaches to learning and intertextuality. The author mentions that the use of
the Arabic script among the vernacular
languages of South Asia began at the
earliest during the 14th century with
Awadhi, followed by Panjabi, Sindhi,
Urdu, and Tamil, among others. In comparison, Sanskrit texts written using
Arabic scripts are very rare.
The author concludes the chapter by
emphasising the uniqueness of the practice of adopting the Arabic script for
writing Bengali, creating a shift as to how
texts came to be read and understood.
Nonetheless, Muslim scholars were familiar with Hinduyani literacy and their defence of the Indic script to write Bengali
38
clearly demonstrates their multilinguality. An important point is the separation
between religious identity and literary
identity where the use of Arabic did not
mean an Islamicisation of the content in
the Bengali language, which nonetheless
retained its highly Sanskritised nature
along with elements of Indian poetics
and religion.
Chapter 2 focuses squarely on the
Islamic concept of light through exegetical literature, theological facts, and devotional texts. Moving away from the
model of high and low traditions, the
author employs the binary of scholastic
and non-scholastic in examining texts
that treat light as a cosmological agent.
The author emphasises that scholastic
literature—like the Mishkat al-Anwar
by al-Ghazali—is grounded on strong
exegetical and speculative protocols. In
texts that constitute the scholastic literature, “Muhammad’s light … draws its
significance more as a cognitive process
than a mythical creation story” (p 5).
The author then goes on to argue that
the distinction between scholastic and
non-scholastic discourses on light lies in
the “personification and embodied representation of Muhammad’s light in preeternity” (p 5).
Light in the Islamic Tradition
The author categorises the discussion on
light in the Islamic tradition into three
overlapping groups—the exegetical corpus of the Quran and Hadith scholarship,
works based on canonical scriptures on
the theme of light, like the Mishkat, and
finally devotional texts which provide a
mythological treatment of the role of
light in creation. Given the categorisation of the Nūrnāma text as Sufi literature, the discussion on the Sufi interpretations of the Quranic light verse would
have been pertinent to the ideas expressed
in the Nūrnāma.
At a time when Bengali Sufis were
adopting texts like the Nūrnāma for a
multilingual readership in Bengal, scholars
like Abd al Haqq Muhaddith Dihlawi
from Mughal Delhi acted as a major mediator between Arabic scholarship and
Persianate readership through his works
on the life of the Prophet, like the Madarij
al-nubuwwa. The author, by including
Dihlawi in the discussion, argues that
the scholar “is an important link to connect these non-scholastic texts to the
classical exegetical tradition” (p 31). And
the Madarij helps us get a closer perspective on the issue of Muhammad’s
light which we find in non-scholastic literature. Hence, the necessity to trace the
larger context of the Nūrnāma tradition
to 17th-century South Asian works.
The author also surveys an Arabic text
of the Daqaiq al-Akhbar, the first few
sections of which describe the various
elements of creation starting with the
light of Muhammad. In this text, it is the
sweat from Muhammad’s light that led
to the various elements of creation. In
the South Asian edition, the author
states that the Daqaiq “provides an account of the creation of Muhammad’s
light” (p 35). This account, according to
the author, is much closer to the description one finds in the Persian Nūrnāma
which was in circulation in Bengal and
was the source of Bengali translations.
Chapters 3 and 4 carry edited and
translated versions of the Nūrnāma texts
collected from various sources. The first
one is an annotated edition and translation of the long recension of the Persian
Nūrnāma, together with the middle Bengali version of the text. The author has
chosen Hakim’s Bengali version to get a
sense of how “such ritual works were
read and commented by the vernacular
literati” (p 5), and also to argue that
Hakim’s strong defence of the use of
Bengali vernacular allows us to look into
“the linguistic economy of rural Bengal”
beyond the binary opposition of Arabic–
Persian and Bengali. What the author
does in Chapter 3 is select a Persian
version of the Nūrnāma, widely in circulation through multiple manuscripts across
the world and currently preserved in the
Bibliothèque Nationale de France in Paris,
whose contents are close to Hakim’s
middle Bengali version which allows to
“understand how the Bengali author approached this tradition” (p 38).
The author mentions that texts belonging to the Nūrnāma genre carry a
common set of features—opening with
a reference to the Hadith “First God Almighty created my light,” followed by a
dialogue between God and the light of
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the Prophet, followed by how various
parts were created from the drops of water coming out from the light of the
Prophet, followed by the decision of God
to finally create the four elements which
will be the domain of Muhammad’s
prophethood. The creation story is followed by the detailing of the rewards
one would obtain from copying, reading, hearing, and owning the text of the
Nūrnāma. The authority of the text and
its powers is attested through Ghazali’s
association with the work and his gifting
of the Nūrnāma to Sultan Mahmud who
thereafter rose to the heights of power
and glory. This is followed by a reiteration of the powers of the Nūrnāma to
protect the owner from various diseases.
The next section “describes the heavenly
origins of what constitutes each limb of
the Prophet” (p 39). It is followed by an
enumeration of the benefits gained by
reading the Nūrnāma. The work ends
with the final reminder that no soul can
escape death and, thus, one needs to
prepare for the afterlife by shedding
worldly pleasures.
Reception of the Nūrnāma
The author argues that the genre of the
Nūrnāma becomes critical in introducing the large masses of Muslim rural
population in South Asia to the fundamental teachings of the Islamic scriptures; serves as a talismanic text; and
helps believers obtain the merits from
acts of devotion like the Hajj pilgrimage
which are difficult to undertake for the
rural masses (p 39).
What then are the characteristic features of Hakim’s text? The author mentions that Hakim’s text is didactic in
approach and thus does not require the
presence of a Sufi master to elaborate on
the esoteric principle as in the case of
Saphi’s Nūrnāma. The text is both a
translation as well a commentary on the
original Perso–Arabic work. That Hakim
resides in multiple linguistic and religious spaces is evident from his Sanskritised middle Bengali and the vocabulary of Indic terms used in the text—
niranjana (attributeless God), prema
(selfless love), and Hindu deities like
Brahma, etc. His use of the Perso–Arabic
terms also, according to the author, gives
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May 4, 2024
a clear sense of his familiarity with
Islamic canons and religious practices.
Also, given the specific religious context of the Perso–Arabic terms, they are
not translated directly into middle Bengali, but retained in their original manner. Hakim also foregrounds the basic
principles of Muslim ethics (akhlaq),
projects the understanding of virtues
as being tied up to the essential traits
of creation, and argues that the ethical
teaching makes the Nūrnāma a very important work, almost a quasi-revealed
text whose reading brings rewards equivalent to those of the Taurat, the Psalms,
the Gospel, and the Quran. Hakim is
also consciously in favour of a Bengali
Islam, beyond the hegemonic discourses
of Persian and Arabic that can be expressed
and written in the regional vernacular to
be made accessible to the residents of a
distinct cultural space.
The second Nūrnāma, also known as
Nurkandil, which the author translates
and analyses, is by Mohammad Saphi.
The latter incorporated Indic elements
through yogic teachings, making the
text esoteric and obscure in its middle
Bengali version. The current version of
the text is an edition by Ahmed Sharif
based on two manuscripts, of which one
can be dated to the early 18th century. The
text reflects many things—Islamic exoteric and esoteric knowledge, the middle
Bengali vernacular, local scribal practices
through the use of the sign anji, as well
as the sacredness of Arabic as the language of revelation and religion (p 86).
The author also cites another work by
Saphi with the title Nurkandil, and the
copyist of the manuscript was a low-caste
Hindu called Madhuram Das, indicating a
possible reception of the Nūrnāma even by
the lower-caste Hindus, and a wide strata
of people in and around Chittagong.
Saphi’s Nūrnāma also witnesses a juxtaposition of Indic and Islamic elements—
triveni and kausar, naginis and buraq
among others. The author in the course of
his analysis argues that a proper understanding of the Indic context becomes necessary on many occasions while reading
and interpreting Saphi’s work. Saphi is
clear in his intention when he states that
he prefers not to repeat what has already
been shared earlier, but the knowledge
which is unknown till now and can be
accessed only through one’s master (pir).
The author concludes by arguing that
while Hakim’s work was not meant to be
an esoteric text, but something close to
the revealed texts; Saphi’s Nūrnāma is an
exclusive teaching of a master to his disciple through oral discourses.
In Conclusion
Meaningful Rituals brings forth many
issues that concern the study of Islamicate
experiences across the globe—regional
history, language, the significance of the
vernacular, the practices of intertextuality
through Arabic–Persian–middle Bengali,
Islamic cosmology, didacticism, esoteric
learning, trends of conversion in frontier
geographies, Sufi interactions with local
practices of culture and forms of knowledge, etc. It is a valuable addition to the
area of Bengal studies and opens up the
scope of further research by undertaking
the critical practice of translating and
engaging with lesser accessible texts.
Kashshaf Ghani (alkashshaf@gmail.com)
teaches at the School of Historical Studies,
Nalanda University, Bihar, and specialises in
premodern South Asia (1000–1800) with a
focus on Sufism.
References
Eaton, Richard (1993): The Rise of Islam and the
Bengal Frontier, 1204‒1760, Delhi: Oxford
University Press.
Ernst, Carl (2016): Refractions of Islam in India:
Situating Sufi sm and Yoga, New Delhi: Sage.
Haq, Muhammad Enamul (1975): A History of
Sufi sm in Bengal, Dhaka: Asiatic Society of
Bangladesh.
Hatley, Shaman (2007): “Mapping the Esoteric
Body in the Islamic Yoga of Bengal,” History of
Religions, Vol 46, No 4, 351–68.
Stewart, Tony (2001): “In Search of Equivalence:
Conceiving Muslim–Hindu Encounter through
Translation Theory,” History of Religions,
Vol 40, No 3, pp 260–87.
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From Aspiration to Oversaturation
A History of Legal Profession in Colonial Madras (1855–1930)
Gautam Chandra, Pranjali
The institutionalisation of India’s legal profession began
in the late 18th and early 19th centuries during the East
India Company era, evolving from loosely defined roles
to a structured profession through the establishment of
courts and legal education. This evolution transformed
law into a much sought-after career, subsequently
resulting in a demand–supply mismatch leading to
significant unemployment. The historiography of the
formalisation of the legal profession typically neglects
this aspect, which this paper seeks to remedy by
examining the legal profession’s growth and by
addressing unemployment among law graduates in the
Madras Presidency.
The authors are grateful to Venkata Raghotham and Dhrub Kumar Singh
for their comments and suggestions on an earlier draft of this paper. They
would also like to thank the editors, the copy editor, and the anonymous
reviewer of EPW for their valuable comments and thoughtful insights.
Gautam Chandra (gautam.pondy@gmail.com) teaches history at the
Department of History, B R Ambedkar Bihar University, Muzaffarpur,
Bihar. Pranjali (prnjl.anu@gmail.com) teaches history at the
Department of History, MDDM College, B R Ambedkar Bihar University,
Muzaffarpur, Bihar.
62
T
he institutionalisation of the legal profession in India
began during the British rule. The profession of law,
considered as “charming, honourable, dignified, and an
independent practice,” provided a career to the educated
class through which they hoped to make their way to private
fortune or public position (Report of the Indian Statutory Commission 1930: 22). Between 1640 and 1726, individuals who
practised law in the East India Company (EIC) courts, styled
themselves as solicitors or attorneys. The eligibility criteria
were to read and write the type of English language used in
legal circles. The eic was granted a Royal Charter in 1726 to
establish Mayor’s Courts in the presidency towns of Bombay,
Madras, and Calcutta. The Privy Council of the Sovereign of
the United Kingdom acted as an appellate body since the formation of the Mayor’s Court. In 1727, the Mayor’s Court in
Madras was established. Thereafter, attorneys of the Company courts were permitted to practise in the new court without any formal restrictions. These practitioners styled themselves as advocates, attorneys, and proctors but they did not
have any clear definition, formal restriction, and regulation
(Fawcett 1934: 171).
With the gradual expansion of British rule in various parts
of the Madras Presidency in the late 18th and early 19th centuries, the Company assumed increasing political and judicial responsibilities. As a result, the formalisation of the legal
profession started. The establishment of tier-based Company
courts, a Supreme Court, and law class at the Madras Presidency College—in 1855—led to the proper training of lawyers and the institutionalisation of the legal profession in the
presidency. By the late 19th century, the legal profession became one of the most sought-after professions. As the number of students increased, stringent qualification criteria
were imposed for admission into the course. By the 1930s,
unemployment was evident among the law students. In 1926,
the Madras Unemployment Committee was set up to investigate the issue. However, the historiography on the development of the legal profession is silent in this regard. The writings on the legal profession have primarily dealt with the
institutionalisation of knowledge and the history of the
courts (Schmitthenner 1969; Paul 1991; Chandrachud 2015).
Nonetheless, the problem of unemployment faced by law
graduates has not been discussed. Dharma Kumar (1998)
rightly pointed out that the services have been a forgotten
sector. Viewed in this context, the paper tries to study the
development of legal profession and contextualises the
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problem of unemployment among the law graduates in the
Madras Presidency.1
Institutionalisation of Legal Profession
The establishment of Company courts and the Supreme Court
at Madras—in the late 18th and early 19th centuries—introduced an elaborate apparatus of courts, judges, and legal practitioners for ensuring the peaceful collection of revenue and
settling disputes among the Indian subjects. The Supreme
Court which followed the English law was established by a
Royal Charter for the British-born subjects of the presidency.
The advocates and barristers practised law at the Supreme
Court and were supported by the attorneys. They appeared
and pleaded on behalf of the litigants while attorneys prepared briefs and advised the counsels. The posts of barristers
and attorneys at the Supreme Court were held by the British
(Fawcett 1934).
Under the Company court, civil courts or diwani adalats
were set up for the civil cases. Registrar courts, headed by the
Europeans and a number of subordinate courts, headed by
Indian judges known as munsifs and amin, were set up below
the district courts. Appeal from the district court was made to
the provincial courts of civil appeal and then to the chief court
of appeal or sadr diwani adalat. The civil courts applied the
customary law that prevailed in a particular area or among a
section of people since time immemorial.2 These courts were
practised by native Indian pleaders or vakils who had some
knowledge of Hindu and Islamic laws. Viewed in this context,
the term “vakil” which meant an “agent,” an “ambassador,” a
“representative,” or a “counsellor” of a nobleman acquired a
new meaning with the establishment of courts (Paul 1991: 17).
The terms pleader and vakil were used side by side. They acted, appeared, and pleaded on behalf of the client and served
as intermediaries between the court and the suitor.
In 1802, sadr diwani adalat was empowered to appoint and
license as many pleaders as might be required for the functioning of a multi-tier court system. In 1816, judges of the provincial courts were given the authority to issue licence for appointing pleaders. Meanwhile, an attempt to train pleaders
started at the College of Fort St George, Madras which was
founded by F W Ellis in 1812 for the purpose of training eic officials in native languages. The college opened its doors for
training native law officers who used to assist judges in deciding Hindu or Muslim law. With request from the College Board
of Fort St George, the government made a law that a certificate
from the college was essential to practise law. Candidates who
wished to become pleaders obtained the pleadership certificate after studying at the College of Fort St George and by
clearing the examination of the College Board or any similar
examination conducted by the district law officers. Pleaders
were examined in grammar, logic, and law, and the College
Board used to issue licences to successful candidates (Paul
1991: 31–35). However, the law classes were terminated in
1836 on the grounds that the colonial government was not
ready to pay stipends to the trained law officers in case of
their unemployment.
Economic & Political Weekly
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MAY 4, 2024
Meanwhile, Eurasians and Indian Christians—well versed
in Islamic and Hindu laws—were also authorised to become
pleaders in 1832, which was earlier only opened for Hindus
and Muslims (Clarke 1848). The regulations passed from time
to time did not provide any definite qualifications for a vakil.
They hardly possessed a fair knowledge of their cases which
led to altercations in the open court (Misra 1961: 164). Meanwhile, the Charter Act of 1833 mandated to appoint a law
member in the governor-general’s council and a law commission to ascertain and codify the laws of India. Lord Macaulay
was appointed as the first law member of the governor-general’s council and also headed the Law Commission. Subsequently, the judicial department deliberated to induce a better
class of educated individuals in the process of justice. In 1837,
it was discussed that a well-considered system should be
adopted by the government for securing duly qualified local
judicial officers on a regular basis (Home Department 1837).
Meanwhile, barristers and attorneys were allowed to practise in the Company courts—sadr diwani adalat and district
court, in 1846 and 1853 respectively. As a result of it, an era of
encounter, opposition, interaction, and competition among vakils, attorneys, and barristers began. Except for those who had
been practising at sadr adalat in the presidency towns, the mufassal pleaders or vakils were not adequately prepared to accept the challenge of a barrister and often lost their cases (Paul
1991: 22–25). The efficiency of pleaders was questioned and a
need for formal training was felt. In this context, a law class at
the Presidency College started in 1855; John Bruce Norton was
appointed as the professor of law (Richey 1922: 363). The
course of instruction was confined to the law of evidence, Hindu and Mohammedan laws, mercantile law, the procedure of
courts and regulation law, general jurisprudence, and political
philosophy. The lectures were delivered twice a week.
Unification of Judicial Structure
The assumption of political control by the Crown in 1858 paved
the way for a unification of the judicial structure. On 6 August
1861, the British Parliament passed the Indian High Court Act,
which empowered the Crown to issue letters of patent to erect
and establish the high courts of judicature at the presidency
towns of Calcutta, Bombay, and Madras. The Law Commission
headed by Lord Macaulay codified the Indian Penal Code
(ipc), the Civil Procedure Code (cpc), and the Criminal Procedure Code (crpc), which were introduced by the Government
of India in 1862 (Misra 1961: 172). In 1862, the new high court
replaced the former sadr adalat and Supreme Court. A fresh
hierarchy of civil and criminal courts was formed from village
to district to presidency towns.
The high courts were empowered to make regulations of admission under the new rules. In its rules of 1862 and 1863, the
high court prescribed the qualification of vakil, attorneys, and
advocates. As per the prescribed qualification, a bachelor of
law (bl) degree along with an apprenticeship for a year under
an advocate, a barrister, a vakil, or an attorney was needed to
become a vakil. To obtain a bl degree, the candidates were
required to pass the bachelor of arts (ba) exam and subsequent
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to passing it, the aspirants had to attend law classes for two
consecutive years at the law institution (The Madras University
Calendar 1876: 54–55). They were examined in the following
papers—the law of evidence, the law of contracts, the law of
torts, equity jurisprudence, Hindu law, Mohammedan law,
criminal law, the cpc, the crpc, and general jurisprudence.
After attending a single-year course at the law institution, the
candidates were eligible for pleadership examination, conducted by the high court. Students who kept six terms at one of
the Inns of Court in London, regularly attended the lectures,
and passed the examination were also eligible to become high
court vakils provided they completed an apprenticeship for
nine months under an authorised local practitioner. These
qualified vakils were permitted to practise on the original as
well as appellate sides of the courts. The rules of the Madras
High Court provided vakils the right to act, appear, and plead
before the high court (Paul 1991: 48–54). The pleaders of abolished sadr adalat were also admitted as vakils in the newly
formed high court, but they were permitted to appear and
plead only on behalf of litigants in any appellate matters. They
were excluded from practising on the original side because
they had no qualification to be a vakil.
Rules passed by the high court in 1863 prescribed mandatory academic qualifications for all those who had not been
called to the Bar in England, Ireland, or Scotland, but wished
to enrol as an advocate. Such candidates had to produce a degree of bl with a certificate attesting that the applicant had
completed 18 months of apprenticeship under an enrolled advocate (Paul 1991: 60). The degree of barristers had grown up
around the four Inns of Court in London—Gray’s Inn, Lincoln’s
Inn, Inner Temple, and Middle Temple (Carr-Saunders and
Wilson 1964). Prior to admission to these Inns, the student had
to pass the secondary school matriculation examination or an
entrance test. For three years or 12 terms, candidates were required to attend the lectures and have six diners3 in each term.
They had to also attend the chamber of a barrister with considerable practice for about a year. Before being called to the bar,
they had to pass an examination in real and personal property,
common law and enquiry, and roman civil law (Paul 1991: 67).
Barristers received government patronage and were appointed to the office of the advocate general, the first judge of the
court of small causes, Madras, and the registrar of the high
court. Since barristers were only permitted to appear and
plead in court, the attorney did all the spade work connected
with a suit, before and after it was heard. Unlike the barristers
who were always Europeans, attorneys tended to be a mixture
of Europeans, Eurasians, and Indians (Home Department 1895).
The attorney, also known as a solicitor, was an intermediary
between the client and the counsel. The attorneys received instruction from clients, prepared briefs, and advised the barristers
or advocates on the original side. Attorneys were also permitted
to plead on the appellate side. To become an attorney, candidates
from foreign countries should have proof of enrolment in one
of His/Her Majesty’s Courts at Westminster or Dublin, while the
aspirants from the presidency had to be a high school matriculate with an experience of four years as articled clerk under
64
high court attorneys (Paul 1991: 73–75). With these developments, the legal profession got institutionalised in Fort St George.
During the academic session 1866–67, 10 students took the
Madras University exam for the bl degree which increased to
37 in 1869–70 (Report on Public Instruction in the Madras Presidency 1878: 6). Amid the growing number of students, a second post of professor of law was added in 1884 at the Presidency College. In 1888, H B Grigg, the director of public instruction of the Madras Presidency, submitted proposals for
establishing a law college in Madras in place of the law classes
at the Presidency College. The government agreed with the
opinion of the director (GO No 634 1888). A separate law college was established in 1891. The college was thrown open to
candidates for the first and second grade pleadership examinations of the high court and the uncovenanted civil service law
examinations, besides the bl degree examination (Satthianadhan 1894: 252–53). In 1895, it was decided to continue
with the maintenance of the Madras Law College as a government institute (Home Department 1895).
Until the end of World War I, the legal profession remained
a male-dominated career. The Legal Practitioners Act, 1879
considered a male as the only “person” to be enrolled as vakil.
In fact, women were kept out of the Inns of Court in London
until the passing of the Sex Disqualification (Removal) Act in
1919. A breakthrough finally came in 1921 when the Allahabad
High Court admitted Cornelia Sorabji, a bachelor in civil law
from Oxford, as a vakil. Thereafter, with the effort of H S Gour,
a barrister and social reformer, the Legal Practitioners (Women)
Act, 1923 was passed in the Indian Legislative Assembly which
prohibited discrimination on the basis of sex in the matter of
enrolment (Paul 1991: 158–63). In colonial Madras, the foundation of entry into the legal profession was laid by B Ananda
Bai. The first woman law graduate of the Madras University,
Ananda Bai became an apprentice to V V Srinivasa Iyengar and
enrolled herself in the Madras High Court on 22 April 1929 (Paul
1991: 158–63; Menon 2014). Amid this development, women’s
participation in the legal profession began in the 1930s.
By 1925, a total number of 6,219 students (4,803 Brahmins,
1,115 non-Brahmins, 253 Christians, and 47 Muslims) passed
the bl degree from the University of Madras, whereas the number of graduates passed in medicine and engineering remained
limited to only 890 and 277, respectively (Table 1). This data
implied that law was the most sought-after profession. The
Malayalam Kerala Patrika, published from Calicut, in its report
dated 20 January 1894 observed that the number of vakils was
increasing every year in all the courts, although the number of
cases was decreasing (Report on Native Papers 1894: 18–19).
Amid the overcrowding of the profession, healthy competition
Table 1: Different Communities Passed in the Examinations of
the University of Madras up to 1925
Class of Graduates
Brahmins
Non-Brahmin Hindus
Christians
Licentiate in teaching
1,960
291
387
Mohammedans
19
Bachelor of laws
4,803
1,115
253
47
Medical
422
291
164
13
Engineering
216
31
29
1
Source: Report of the Unemployment Committee (1927b: 739).
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among lawyers began for taking up the cases which finally led
to their unemployment.
Competition for Cases and Unemployment
The law as a career for graduates remained one of the preferred
choices because of the growing impossibility of finding positions
in government services. Since the establishment of the high
court, a tussle between vakils and attorneys arose. The high court
gave permission to vakils to perform all three crucial functions
of acting, appearing, and pleading on the original side which
hampered the prospects of attorneys. Attorneys were only allowed to act and appear on the original side and not to plead.
They helped barristers and advocates in briefing their cases. In
such circumstances, barristers supported attorneys and a coalition between barristers and attorneys was formed. Barristers
were requested by attorneys not to take briefs from vakils in
cases of original suits of the high court. Attorneys filed a formal
petition in 1875 for revoking the right of vakils to practise on
the original side. Attorneys complained that admission of vakils
on the original side had inflected a great hardship on them.
However, the high court rejected the plea after hearing the petition on 14 January 1876 and made it clear that the legality of
permitting vakils on the original side was unquestionable.
Subsequently, attorneys discussed forming a society of attorneys
in their meeting held on 29 July 1882 (Paul 1991: 78–81). In
these ways, rivalries emerged in the judicial circle for appearing
in maximum cases and having more employment opportunities.
The internal fight for building law practice has also been
studied by David Washbrook in his writings on Madras politics. He analysed the regional politics in terms of internal confl ict between the “Mylapore” clique and its less successful
“Egmore” rivals. Kasturi Ranga Iyengar (from Tanjore, Egmore
group), who was qualified as a vakil in 1884, was unable to
build a legal practice in the city of Madras and spent nearly a
decade in the mofussil. He returned to the city in 1894, but
again “found himself starved of valuable cases, which fell into
the pockets of the Mylaporeans, and was forced to give up the
law for journalism” (Washbrook 2008: 240). Another Egmore
leader, T Rangachari from Tanjore could secure relatively few
of the plums of civil litigation and concentrated his attention
on the less lucrative criminal bar in spite of his brilliance in
this profession (Washbrook 2008: 240). At the same time, the
higher posts in the judiciary were dominated by Europeans. In
1883, Ilbert Bill was opposed by the Europeans, because it
brought Indian judges on equal footing with the Europeans. In
1886, only 12 Indians were working as advocates at the Madras
High Court (Seal 1968: 126). The Madras Mahajan Sabha was
formed by Subramania Iyer, a graduate of Madras University
and headmaster of a native school at Triplicane. The founder
of Hindu newspaper, P Ananda Charlu—a vakil of the high
court—S Iyer, and many others directed their attack against
the exclusion of native Indians from important positions, including judicial posts (McCully 1940: 363–64; The Madras Mahajan Sabha 1886; GO No 2357 1884). Around the same time,
associations like the Students’ Literary Association (sla) were
formed to discuss the students’ problems.
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MAY 4, 2024
By the early decades of the 20th century, limited opportunities
for higher posts and an increasing number of law graduates
led to competition for jobs. In 1917, the total number of students who passed in law degree in the Madras Presidency was
259 which rose to 606 in 1925 (Department of Industries and
Labour 1927). Whereas the number of suits instituted at the
Munsif Court, Madras declined during 1912–21 (Table 2). It
meant that the amount of litigation which was the pabulum for
the legal profession did not increase in the proportion of law
graduates. The number of graduates in law had more than
doubled, though the work in civil courts diminished. At the
same time, vakils and advocates from Calcutta and other places started to practise in the Madras High Court. It was reported that Calcutta was overcrowded with lawyers and attorneys,
and Madras also seemed to be in the same predicament.4 The
collector of Kurnool district noted that the candidates returning as barristers-at-law from England often found themselves
in no better position (Report of the Unemployment Committee
1927a: 128). In view of the overcrowding of the legal profession, it was highlighted that 60% of the lawyers had practically no work (Report of the Madras Retrenchment Committee
1923). The number of the population whose life was dependent
on earnings from the legal profession declined by 6% between
1911 and 1921 (Boag 1922: 173). Subsequently, the number of
lawyers’ clerks had come down by 15.5% during the same period. A Madras Unemployment Committee was set up by the
government to enquire into the question of unemployment
among the educated class in 1926. The committee submitted
its exhaustive reports in three parts, including evidence taken
from more than 200 individuals.
Amid the growing competition, unemployment, and plight
of lawyers, bls resorted to practice in the munsif courts and
applied for the posts of sub-registrars and clerks. As many as
500 vakils from the mufassil and the city applied for the post
of bench clerk in the high court (Report of the Unemployment
Committee 1927: 8–9). The colonial government itself accepted
that the “legal profession is so crowded that the struggle for
existence is very keen” (Report of the Unemployment Committee 1927: 13). Law graduates were facing the menace of unemployment. Subsequently, students started to think about some
other avenues of employment. It was suggested by A G Menon
in his evidence to the unemployment committee that to reduce
unemployment among law graduates they may be employed in
the magisterial, income tax, police, registration, and other departments (Report of the Unemployment Committee 1927a: 317–
23). The committee asked a question to T S Gangadhara Ayyar,
a graduate in law, pleader, and publicist from the Kumbakonam region of the presidency, “Are you of opinion that a lawyer
instead of looking to the law court can train himself in any
Table 2: Description of Suits at District Munsif Court, Madras, 1912–21
Year
Number of Courts
Suits Instituted
Suits Disposed of
Total Number of
Suits Pending
1912
1915
1918
1921
136
156
157
167
1,14,547
1,06,441
1,07,293
1,13,416
1,09,835
1,10,622
1,08,403
1,21,402
52,002
52,011
54,822
60,076
Source: Report of the Madras Retrenchment Committee (1923: 84).
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other walk of life and take up jobs in any office such as the income-tax office or something like that?” (Report of the Unemployment Committee 1927a: 225). Summing up the situation,
the written evidence of M Parthasaradhy—a graduate from
Godugupet area of Masulipatam district of the presidency—to
the Madras Unemployment Committee, dated 15 August 1926,
noted that
The Law College is manufacturing year after year hordes of Law graduates who, having nothing else to do, no higher studies to pursue, settle down calmly to life. Then their disillusion comes. They wait, wait
and then wait till almost the doomsday. The roaring practice never
comes; the smiles of fortune never come to them. However industriously they may work, however up to date they may be in legal knowledge and case law, the seniors alone will have all the practice while
the juniors at the bar are starving for want of a pittance. Nevertheless
and notwithstanding all this, they have to put up a show. They have to
maintain an establishment of a clerk, a carriage and a servant. They
have to purchase the law journals and reviews. They have to hire a
decent building and provide all comforts to their clients. They have
to accommodate and give commissions to the law touts and agents
who suck away the last drop of life-blood from the junior. However
low may be the income, the expenditure cannot be reduced by even a
single pie. Again after all the success at the bar is only a circumstance
of chance. The competition and rivalry at the bar is very keen and
deadly … clients want only a senior, not a junior, for their work.
(Report of the Unemployment Committee 1927b: 373–74)
Increasingly Stringent Regulations
was required to study hard for at least two years in order to
become a lawyer, 40% of the graduates of the Madras University joined the law college for bl course every year. “Why they
did so was a question,” on which Arthur Davies, the Principal
of the Madras Law College, collected the opinion of his students. It appeared that 24% of those who took the ba degree
joined the law college because they had nothing else to do,
30% preferred government service and 40% joined the college
in order to fulfil a desire to qualify themselves for practising at
the bar (Department of Industries and Labour 1927). In the
case of pleaders also, Davies found similar results. Sixty percent of the students had seriously aimed to become pleaders as
soon as possible and 30% drifted to college because they could
not get any kind of employment outside. The remaining 10%
were already in employment and joined the college with a
view of improving their chances of promotion, providing an
occupation and means of income if they were dismissed, or for
their retirement days (Report of the Unemployment Committee
1927b: 480). Filling the questionnaire circulated by the principal,
Arthur Davies, a few of the students reported thus:
I am not very much interested in law ... I am very much interested
in pedagogism. But as I could not get any teacher’s post so that ... I
joined the Law College so that waste of another year ... can be avoided.
(Report of the Unemployment Committee 1927b: 483–84)
Other students wrote:
Since the supply of lawyers was beginning to outstrip the demand, it became relatively easy to raise the standards. The
Calcutta High Court ruled that whereas previously a man passing the entrance examination had qualified for admission as a
pleader, now he must pass the first examination in arts (fa)
(Seal 1968: 128). Year after year both the high courts and government were suggesting to impose more stringent educational standards. The Bar Association, Kumbakonam suggested
that as in the case of the engineering and medical colleges—
where only Group I or Group II passed students were admitted—similar restrictions ought to be imposed in admitting
students to the law college. Further, the association pointed
out that as there was an abundant number of law graduates
available for jobs, they should be preferred for employment in
the public sector. Undergraduates and students with tinsel
qualifications should not be appointed for the posts of submagistrates, sub-registrars, and clerks in railways, local
boards, and municipalities (Report of the Unemployment Committee 1927b: 18–19). K Krishnan, a bl and the Chairman of
Municipal Council, Tellicherry, suggested abolishing the firstgrade pleadership examination. Menon expressed his view
that in the interest of the profession, the number of seats in the
law college and the number of vakils in a particular bar may be
limited. He also suggested that the standard of bl course may
be made stiffer (Report of the Unemployment Committee 1927b:
296, 317–23). However, after all the hardship, every year
scores of young men enrolled in the law colleges.
The Depression Days
Madras Law College as the ‘graduates unemployment bureau’: In spite of darkening clouds over the career opportunities
and the fact that a young student after taking the ba degree
In the wake of the Great Depression in the 1930s, unemployment continued to affect the prospect of educated men as the
colonial government followed the policy of retrenchment. A
Madras Retrenchment Committee was set up to recommend
66
Being stunned with the unemployment problem … I have resolved to
practise as a pleader … or preferable still to get an employment in the
Judicial department. If neither is available, I will try my chance in the
educational line. My last resource failing all the above three, will be to
take refuge in my village.
A period of probation … unable to face the actualities of life and the
dread of unemployment, I have sought refuge in the Law College.
(Report of the Unemployment Committee 1927b: 483–90)
Subsequently, V Appa Rao, a lecturer in physics at Government Arts College, Rajahmundry, observed that many graduates of his college, who were badly in need of an appointment
felt that they were too poor to wait for a job, but being unable
to get one, ran into debts and joined the law college to spend
two or three more years in ease and comfort (Report of the Unemployment Committee 1927a: 9). Principal Davies reported on
21 September 1926 that out of 858 university students, at least
300, possibly as many as 400 or even more, were unemployed
and the law college was called the “Graduates Unemployment
Bureau” (Report of the Unemployment Committee 1927b: 479–
80). The admission of disinterested and disoriented students
into law colleges swelled the ranks of unemployment. Explaining the scenario, the written evidence of the collector of the
South Arcot, dated 28 October 1926, highlighted that many
graduates drifted into law colleges without any special aptitude for the profession (Report of the Unemployment Committee 1927a: 142).
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ways to reduce government expenditure. Based on the recommendations of the committee, the District Court of Anantapur
and East Tanjore, the sub-court at Chingleput, and one of the
two temporary sub-courts at Nellore were abolished in spite of
the fact that the judicial department was struggling to cope
with the increasing number of appeals (Report of the Madras
Retrenchment Committee 1923: 65, 91). Stationary sub-magistrates who were recruited from the ranks of clerks were recommended to be replaced with the district munsifs (GO No 112
1924; Baliga 1960: 32). Amid the retrenchment measures,
earning of lawyers became “ridiculously low and sometimes…
not even enough to run the establishment” (Report of the Unemployment Committee 1927a: 9). The phrase “briefless barrister” described the grim reality experienced by young lawyers
(Schmitthenner 1969: 373). A good deal of stagnation and unemployment was found to a remarkable degree in the profession of law.
P C Ethirajulu Nayudu, a Member of the Legislative Council
and the Medical and Public Health Retrenchment Committee
sent his dissent note to the Retrenchment Committee’s proposals, but to no avail. In fact, government officials were also not
convinced by the irrational retrenchment. F Sayers, superintendent, Government Railway Police, Trichinopoly wrote to
the chief secretary to the Government of Madras that retrenchment must be reasonable (Report of the Medical and Public
Health Retrenchment Committee 1923: 36–37).
The colonial government did not maintain any concrete statistics to analyse the seriousness of the problem. In response to
requests from several quarters, for the very first time, an attempt was made in the 1931 Census to collect the statistics of
the educated unemployed. As the general schedule of the census was already inconveniently crowded, the calculation of
educated unemployed was intended to touch only those who
were fully literate and for this purpose, a separate schedule
was prepared to be filled in by the enumerated himself and not
by the enumerator (Hutton 1933: 336–37). The instructions on
the form for the calculation of educated unemployed stated
that the information was required in the interest of the public,
of the state, and of the unemployed themselves. As per the
census calculation, the number of educated unemployed, including law graduates in the presidency was 2,463 (Yeatts
1932: 261–62). However, the collected data was not reliable.
J H Hutton, the Census Commissioner for India in 1931, reported that an attempt to collect a return of the educated unemployed in separate schedules was a fiasco, as although large
numbers of the schedule were issued, very few were received
back (Hutton 1933: xiv). M W M Yeatts, the superintendent of
the Madras Census Operations in 1931, wrote that an attempt
was made by means of an enquiry carried out on a separate
schedule to collect facts about educated unemployment, but
the enquiry lacked the legal backing of the ordinary schedule
and the results were disappointing (Yeatts 1932: 4). Although
the collected number of unemployed was not reliable, it provided an insight into the problem of unemployment among the
educated class. Out of 2,463 unemployed, 1,171 were Brahmins,
1,095 non-Brahmins, 76 Muslims, 13 Anglo-Indians, 9 Depressed
Economic & Political Weekly
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MAY 4, 2024
Classes, and 99 from other classes. As far as the regional distribution was concerned, the unemployed were thoroughly
spread out in the presidency, but their main concentration was
in the Guntur (163), Madras (250), Tanjore (324), and Malabar
districts (395) (Yeatts 1932: 261–62). M Ramachandra Rao, a
retired judge, in his address delivered at the B K Mariappa’s
Charities Hostel Union, Bangalore on 16 March 1935, noted
that the educated unemployed constituted a million and a half
in the country (Rao 1935: 12).
Opinion of National Leaders
The national leaders and public figures associated with legal
and other professions also highlighted the issue of prevailing
unemployment in their speeches, writings, and debates (Chandra 2022). In a debate in the Bombay Legislative Assembly on
budget in 1938, B R Ambedkar supported schemes like unemployment benefits, greater industrialisation, and curtailment
of retrenchment measures to relieve unemployment (Dr Babasaheb Writings and Speeches 2020: Vol 2: 14; also see Vol 10).
Ambedkar also discussed involuntary unemployment in detail
and analysed that the main reason behind the unemployment
was the increasing number of educated class as compared to
the existing vacancies. At the Faizpur session of the Indian
National Congress, Jawaharlal Nehru highlighted that the urgent
problem of the country was the “appalling poverty, unemployment and indebtedness of the peasantry” (Zaidi 1987: 342).
Subsequently, another public figure and lawyer, Tej Bahadur
Sapru observed that the legal profession
is far too crowded ... there is a great deal of unemployment in it. It is,
and ought to be, a very honourable profession; but it has lost a great
deal of prestige and position ... and, unless some measures are taken
to re-organize profession … the conditions of the profession will be
even worse. (Report of the Unemployment Committee 1936: 242–44)
Further, Sapru suggested that a Council of Legal Education
should be created and a liaison should be established between the Faculty of Law and the Bar Council to solve the
menace of unemployment in the profession (Report of the Unemployment Committee 1936: 83–84). Based on this evidence,
it is clear that by the end of the 1930s, overcrowding, lack of
opportunity, and unemployment in the legal profession had
become one of the important issues among the leaders and
the educated fraternity.
In Conclusion
The profession of law in India began during the rule of the eic
and later became one of the most sought-after professions. By
the third quarter of the 19th century, law graduates started to
face difficulties in getting employment or cases as their numbers increased. After World War I, the cases of unemployment
were more visible which was evident by the overcrowding,
keen competition for fighting cases, and the decreasing number of families dependent on the legal profession. The Madras
Unemployment Committee, 1926 and the Madras Census of
1931 reported the prevalence of unemployment in the legal
profession and collected evidence regarding the same. Following the recommendation of the Retrenchment Committee
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amid the Great Depression, various posts and institutes were
abolished which increased the rate of unemployment.
Many of the lawyers reported that the legal profession lost
the dignity it once commanded. A large number of legal practitioners, both in Madras and in the mufassil districts, were
hardly able to earn a decent living and were often found willing to take up other work, even if moderately remunerative.
Ramchandra Chettiyar, a high court vakil and a resident of
Notes
1
2
3
4
The Madras Presidency, officially styled as the
Presidency of Fort St George, was an administrative subdivision of British India. The seat
of government was at the presidency town,
Madras city.
To deal with criminal cases, courts of circuit,
presided by the civil servants, were established. Below these courts, a large number of
Indian magistrates tried petty cases. Appeals
from the courts of circuit lay with the Sadr
Nizamat Adalat. The criminal courts applied
Muslim criminal law in a modified and less
harsh form so that tearing apart of limbs and
similar punishments were prohibited.
Candidates studying at the Inns were required
to have a certain number of dine in each term
in the dining hall of the institute with experienced barristers, staffs, and others in order to
enable entrants’ learning through contact and
networking.
As brilliant a lawyer as C R Das, who joined the
bar at Calcutta in 1893, spent the first 15 years
of his career experiencing hopelessness and
waiting at the Bar Library. Das fell into a debt
of `40,000 and was declared bankrupt by the
court. He did not make a success of legal practice until he won sudden fame for his defence
of “Aurobindo in the Alipore Bomb Case in
1908” (Schmitthenner 1969: 373).
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Union Budget 2023–24: The Long View
Massive Capital Expenditure, Modest Fiscal Consolidation,
and Cut in Pillars of Social Safety Net
Balancing Growth with Fiscal Consolidation
The Union Budget 2023–24 and the Financial Sector:
The Devil May Lie in the Details
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A Need for Comprehensive Approach for Transformation
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Unveiling the Shifting Dimensions of Deprivations
Exploring Multidimensional Poverty and Sustainable
Development Goals in India
Swati Dutta
Poverty, an enduring societal challenge, necessitates a
comprehensive understanding that surpasses traditional
measures. This paper explores the intricacies of
multidimensional poverty in India by assessing alignment
with Sustainable Development Goals. Using the National
Family and Health Survey data (NFHS-4 and NFHS-5), the
study scrutinises changes in multidimensional poverty,
severely multidimensional poor, and vulnerability to
multidimensional poverty. A noteworthy national
reduction in MPI signals progress in poverty reduction
and SDG attainment. Nonetheless, disparities persist
among states and social groups, with elevated poverty
in marginalised communities and rural areas. Alarmingly,
Assam, Bihar, Chhattisgarh, Gujarat, Jharkhand,
Karnataka, Madhya Pradesh, Odisha, Rajasthan, Tripura,
Uttar Pradesh, and West Bengal see a rise in the
population vulnerable to multidimensional poverty.
Swati Dutta (swati.dutta@ihdindia.org) is with the Institute of Human
Development, New Delhi.
Economic & Political Weekly
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may 4, 2024
P
overty remains one of the most pressing challenges faced
by society today. While significant progress has been made
in reducing global poverty over the past few decades, its
multidimensional nature necessitates a more nuanced understanding. Critiques of traditional poverty measurement have led
to the development of alternative approaches like the “capability
approach.” This highlights the need for a multidimensional
perspective that considers interconnected dimensions such as
health, education, water and sanitation, housing, nutrition, and
social inclusion to accurately assess living conditions and measure
poverty (Sen and Anand 1997; Sen 1997; Klasen 2000; Alkire and
Santos 2013, 2014; Alkire et al 2015; Rippin 2016; Bourguignon
and Chakravarty 2003; Coromaldi and Zoli 2012). These
dimensions are interconnected and contribute to a cycle of
chronic deprivation that affects individuals and communities.
Addressing these multidimensional aspects of poverty is crucial for effective policies and interventions that uplift marginalised groups, promote well-being, and support sustainable
development. India, with its vast population, cultural diversity,
and socio-economic disparities, provides a unique context to
study multidimensional poverty. As home to a large proportion of the global poor, India’s efforts to combat poverty are
vital for its own development and global poverty reduction.
The 2030 Agenda and its Sustainable Development Goals
(SDGs) provide a holistic framework to tackle poverty in all its
forms, considering its multidimensional nature (UN 2015). Poverty
reduction is foundational to SDG 1, aiming to eradicate poverty,
and is vital for achieving other SDGs such as zero hunger (SDG 2),
good health and well-being (SDG 3), quality education (SDG 4),
decent work (SDG 8), access to clean water and sanitation (SDG 6),
and reducing inequality (SDG 10). This paper explores multidimensional poverty in India, analysing progress, challenges, and
solutions aligned with the SDGs. It aims to understand and
address specific deprivations within diverse sociocultural
contexts. Examining the incidence, deprivation profile of multidimensional poor and challenges of multidimensional deprivation, the study highlights the importance of a holistic approach to
poverty measurement beyond income-based thresholds.
The multidimensional poverty index (MPI) has emerged as a
widely used measure in India, incorporating indicators such as
health, education, living standards, and more (Alkire and
Foster 2011; Alkire and Seth 2015; Alkire et al 2015; Alkire and
Santos 2013, 2014; Alkire et al 2019). It provides a holistic view
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of poverty, enabling policymakers to identify deprivations
across multiple dimensions. Studies have shown variations in
poverty levels and dimensions across different states and
regions (Aguilar and Sumner 2020; Vasishtha and Mohanty
2021; Mohanty and Vasistha 2021; Shah and Debnath 2021;
2022; Dehury and Mohanty 2015). The interplay of social
determinants, such as caste, gender, and ethnicity, also contribute to multidimensional poverty in India. Marginalised
groups, including Scheduled Castes (SCs), Scheduled Tribes
(STs), and women, face higher levels of deprivation across
various dimensions (Pradhan et al 2022; Baiju and Savaraman
2018). Discrimination and social exclusion exacerbate poverty,
limiting opportunities for social mobility and access to essential
services. The literature emphasises the importance of reliable
data and robust methodologies in measuring multidimensional
poverty accurately. Data limitations, including the availability, quality, and comparability of data across different regions
and time periods, pose challenges in capturing the true extent
of poverty (Chakravary and Ambrosio 2006). The existing literature review primarily focuses on the demonstration of regional disparities in multidimensional poverty at a specific
moment in time. In addition, NITI Aayog has developed indicators for measuring and understanding the progress of reduction in multidimensional poverty among Indian states
using the National Family and Health Survey, that is, NFHS-4
and NFHS-5 unit-level data (NITI Aayog 2021, 2023).
While previous literature has stressed the importance of using multidimensional measures, such as the MPI, to capture
various poverty dimensions beyond income or consumption,
there remains a dearth of studies examining the reduction in
poverty, vulnerability to poverty, and severity of poverty
contributing to multidimensional poverty (Alkire and Seth
2015; Seth and Alkire 2021; Alkire et al 2021). The existing
literature has primarily focused on demonstrating regional
disparities in multidimensional poverty at specific moments
in time, with limited attention to indicators contributing to
overall multidimensional poverty for various social groups.
Additionally, NITI Aayog has developed indicators for measuring and understanding the progress of reduction in multidimensional poverty among Indian states using NFHS-4 and
NFHS-5 unit-level data, but the social group-wise poverty
estimation of overall multidimensional poverty has not been
adequately addressed.
This paper seeks to address these gaps by examining
changes in the degree of poverty over time, utilising data
from two rounds of the NFHS-4 and NFHS-5. Through a comprehensive analysis, the study aims to provide insights into
the progress towards reducing vulnerability to multidimensional poverty, severity of poverty, and their contribution of
overall multidimensional poverty, aligning with the broader
SDG objectives.
Materials and Methods
The data for the analysis of multidimensional poverty in
this study is sourced from two rounds, NFHS-4 and NFHS-5.
The NFHS is a part of the Demographic and Health Survey.
46
The multistage sampling framework is used to create a representative sample for India.1 The NFHS-4 covered a nationally
representative sample of 28,69,043 from 6,29,892 households. Further, NFHS-5 covered sample of 28,43,917 from
6,36,699 households. The surveys provide information on
households’ access to basic facilities, mortality, nutrition,
education, all of which are relevant for constructing MPI. The
surveys also collect information on demographic characteristics (age, sex, marital status), household composition, caste/
tribe, religion. These data sources, comprising NFHS-4 and
NFHS-5, offer a rich set of indicators for analysing multidimensional poverty in India and provide insights into the
multiple deprivations faced by households and individuals in
different regions and demographic groups. Table 1 provides
the indicators of each dimension of MPI as adopted from OPHI
(2018). The study considered individuals who have information for all 10 indicators. Therefore, the analysis is restricted
to 28,01,958 individuals in the NFHS-4 round and 27,95,894
individuals in the NFHS-5 round.
Measuring MPI
The MPI is calculated using the following methodology. The
multidimensional deprivation headcount (H) measures the
number of individuals deprived based on a specified cut-off
point for deprivation.
For each individual i, the deprivation status (yk) of dimension k
is determined using the following criteria:
yk =1 if Di  K
yk=0 if Di< K
Table 1: Dimensions and Indicators of Multidimensional Poverty Index
Dimensions of Indicator
Poverty
Deprived if Living in the Household Where…
Health
Nutrition
A child or any adult in the household is
undernourished
Child/adolescent
mortality
Any child under the age of 18 years has died
in the five years preceding the survey
Years of schooling
No household member aged 10 years or
older who has completed six years of
schooling
School attendance
Any school-aged child is not attending
school up to the age at which they would
complete Class 8
Cooking fuel
The household cooks with dung, wood,
charcoal or coal
Sanitation
The household’s sanitation facility is not
improved or it is improved but shared with
other households
Drinking water
The household that does not have access to
improved drinking water or safe drinking
water is at least a 30-minute walk from
home, round trip
Electricity
The household has no electricity
Housing
Housing materials for at least one of roof,
walls and floor are inadequate: the floor is
of natural materials and/or the roof and/or
walls are of natural or rudimentary materials
Assets
The household does not own more than
one of these assets: radio, TV, telephone,
computer, animal cart, bicycle, motorbike
or refrigerator
Education
Standard
of living
Source: Indicators are as mentioned in OPHI (2018).
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The multidimensional deprivation headcount ratio was
calculated as follows:
݊
௤
H= ೖ , with qk = ෍ yk
௡
Figure 1: Nutrition and Health-related Indicators by Place of Residence and
Social Groups
(%)
50
40
݅=1
where,
qk = number of households/individuals affected by at least
K deprivations;
n = total number of households/individuals included in the
analysis;
yK = deprivation status of a household/individual I depending
on the cut-off point K;
Di = number of deprivations each household/individual i
experiences;
K = cut-off point.
The intensity of poverty (A) or the breadth of deprivation
captures the average weighted count of deprivations experienced by the multidimensional poor.
೜
σ ೖ
The Intensity of Poverty (A)= భ ௖ೖ with c
=
௤ೖ ௑ௗ
k = Di * yk
where,
d = total number of dimensions considered per household/
individual;
ck = number of deprivations each multidimensionally deprived
household/individual i experiences.
30
20
10
0
Rural Urban
ST
OBC Others Total Rural Urban
2015o16
Changes in Poverty between 2015−16 and 2019−21 and
Tracking the States
The study has also calculated the annualised present rate of
reduction and the required rate of reduction in poverty between
2015−16 and 2019−21 to understand progress in reducing
multidimensional poverty.
The present rate of reduction, that is, reduction between
2015−16 and 2019−21, that is five years.
భ
୍
AARR=ͳ െ ሺ మబభవషమభሻ౤ *100 n=5
୍మబభఱషభల
Required rate of reduction (RRR), that is, reduction to reach
the SDG target by 2030.
ୗୈୋ౪౗౨ౝ౛౪౟ ଵȀଽ
୍మబభవషమభ
ሻ
*100
If a state has successfully halved its poverty rate from
2015−16 to 2019−21, it is classified as “achieved.” States are
considered on track if their current rate of poverty reduction
exceeds the required rate. However, states are flagged for
attention if their present rate of decline falls below the required rate, regardless of the low existing poverty levels.
Inequality among the Poor
To further comprehend inequality among the impoverished,
we employ the variance of individual deprivation scores
among the poor. This measure is derived by subtracting each
multidimensionally poor person’s deprivation score from the
Economic & Political Weekly
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may 4, 2024
ST
OBC Others Total
2019o21
Figure 2: Education-related Indicators by Place of Residence and
Social Groups
(%)
25
20
15
10
5
0
Rural Urban SC
ST
OBC Others Total Rural Urban SC
Child School Attendance
Child school attendance
ST
OBC Others Total
Years of Schooling
Years of schooling
2015o16
As per the global cut-off as well as NITI Aayog (2021, 2023),
population with a deprivation score of at least 33.3% is considered as multidimensionally poor.
SC
Child/ Adolescent Mortality
Child/adolescent mortality
Source: Author’s calculation based on NFHS-4 and NFHS-5.
MPI = H * A
RRR =ͳ െ ሺ
SC
Child/ Adult Nutrition
Child/adult nutrition
2019o21
Source: Author’s calculation based on NFHS-4 and NFHS-5.
intensity, squaring the differences, and then dividing the sum
of the weighted squares by the total number of multidimensionally poor individuals. Given that the deprivation score is
bounded within the range of 0 to 1, utilising alternative forms
of inequality measures becomes challenging to substantiate
the results (Seth and Alkire 2014).
Results
Dimension specific deprivation—Nutrition and health: The
analysis reveals significant progress in health and nutritionrelated indicators, which are the crucial components of SDG 2
and SDG 3. National nutrition deprivation has decreased from
37% in 2015−16 to 35% in 2019−21, indicating a 2 percentage
point progress in addressing nutritional challenges and improving overall health. Child/adolescent mortality deprivation
has also decreased from 2.7% to 2.1% over the same period.
However, disparities persist among social groups and geographical areas. Rural areas have higher levels of nutrition
deprivation compared to urban areas. ST households consistently experience the highest levels of nutrition deprivation as
compared to other social groups (Figure 1).
Dimension specific deprivation—Education: The analysis
has significant implications for the SDG 4 dimension of quality
education in India. School attendance deprivation has decreased
from 6.4% in 2015−16 to 5.3% in 2019−21, indicating progress
in improving access to education. However, disparities persist
among social groups and geographical areas (Figure 2).
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Deprivation in school attendance varies among social groups,
ranging from 8.3% in ST households to 3.3% in other households. Rural areas have higher deprivation in school attendance,
with 1.8 times more deprivation compared to urban areas.
In terms of years of schooling, the reduction in deprivation
has been modest, declining by only 2.5 percentage points from
13.8% in 2015−16 to 11.3% in 2019−21. While progress has
been made, it indicates the need for continued efforts to ensure
access to quality education for all children, reduce dropout
rates, and promote the completion of years of schooling. The
findings also highlight variations in the reduction of years of
schooling deprivation among different social groups. ST households witnessed the highest reduction of 5 percentage points,
followed by SC households (2.8 percentage points), and Other
Backward Class (OBC) households (2.7 percentage points). Similarly, rural areas experienced a reduction of 3.2 percentage
points in schooling deprivation.
Dimension specific deprivation—Levels of living: The implications of the findings extend across various dimensions of the
SDGs in India, notably in clean energy (SDG 7) and clean water
and sanitation (SDG 6). The analysis reveals positive strides in
enhancing access to safe cooking fuel, improved housing, electricity, and drinking water. However, persistent challenges
and disparities are evident (Table 2).
In the realm of safe cooking fuel, there has been noteworthy progress, with the percentage of individuals lacking
access decreasing from 58% in 2015−16 to 43% in 2019−21
(refer to Table 3). In rural areas, this reduction is more pronounced, dropping from 77% to 59% during the same period.
The most substantial improvement is observed among SC
households, with an 18 percentage point reduction, followed
by OBC and ST households experiencing a 15 percentage
point reduction.
Similarly, the percentage of people without access to
improved housing has decreased from 45% to 41%. However,
in rural areas, over half the population remains deprived of
improved housing in 2019−21, with only a 6.8 percentage
point reduction over the past five years. Conversely, in urban
areas, there is no improvement, and 16% of the population
lacks access to improved housing in both periods.
Regarding sanitation facilities, there has been a noteworthy
reduction in households without improved sanitation, with a
decrease of 22 percentage points. The reduction in households
without improved toilet facilities in rural areas is more substantial, at 28 percentage points, compared to 10 percentage
points in urban areas. The highest reduction is observed
among ST households (30 percentage points), followed by SC
households (26 percentage points).
There is also a 2 percentage point reduction in households
without improved drinking water facilities, declining from
14.8% in 2015−16 to 12.5% in 2019−21. Rural areas experienced a 3.6 percentage point reduction, while there was no
improvement in urban areas regarding access to improved
drinking water. Among social groups, ST households experienced a 7 percentage point reduction, compared to 3 percentage points for SC households and 2 percentage points for
OBC households.
Access to electricity has significantly improved, with deprivation decreasing by 9 percentage points from 12% in 2015−16
to 3% in 2019−21. Rural areas have also experienced a 13 percentage point reduction, with ST and SC households witnessing a 12 and 10 percentage point reduction, respectively.
Multidimensional Poverty by Place of Residence
The analysis of the MPI and its components provides valuable
insights into the progress made towards achieving the SDGs
in India. Table 3 presents the levels of the multidimensional
headcount ratio, intensity, and MPI between 2015−16 and
2019−21.
At the all-India level, there has been a substantial reduction in the MPI, with an annual average decrease of 9.5%.
This reduction signifies significant progress in addressing
multidimensional poverty, as the MPI decreased from 0.12
in 2015−16 to 0.07 in 2019−21. Alongside this reduction,
there has been a 9.5% annual average decrease in the multiTable 2: Levels of Living-related Indicators by Place of Residence and Social Groups
(%) dimensional headcount ratio, indicating
a decline in the proportion of people
2015−16 2019−21 2015−16 2019−21 2015−16 2019−21 2015−16 2019−21 2015−16 2019−21 2015−16 2019−21
Electricity
Drinking Water
Sanitation
Cooking Fuel
Assets
Housing
living in multidimensional poverty
Rural
16.8
4.3
16.5
12.9
62.8
35.2
77.2
58.6
17.9
12.6
59.4
52.6
from 28% in 2015−16 to 17% in 2019−21.
Urban
2.4
1.0
11.4
10.9
28.9
18.8
18.2
10.5
5.9
4.6
16.1
15.6
Additionally, there has been a 0.9% anSC
14.7
4.3
14.3
11.7
62.2
36.6
66.6
48.6
16.2
11.9
52.8
47.8
nual average reduction in the intensity
ST
17.7
5.6
28.7
21.9
74.1
43.7
83.0
68.2
30.0
21.2
70.6
64.5
of poverty, reflecting improvements in
OBC
12.8
3.0
13.8
12.1
51.7
28.5
57.2
42.0
12.0
8.6
43.8
38.8
the deprivation levels among the multiOthers
6.4
1.4
11.5
10.2
34.3
20.1
40.9
28.1
8.9
6.1
30.6
26.6
dimensionally poor, with the poverty
Total
12.2
3.2
14.8
12.5
52.0
30.1
57.8
43.1
14.0
10.1
45.2
40.9
intensity decreasing from 44% in
Source: Author’s calculation based on NFHS-4 and NFHS-5.
2015−16 to 42% in 2019−21. To achieve
Table 3: Incidence of Multidimensional Poverty by Place of Residence
the SDG target of a 50% reduction in poverty by 2030, it is im2015−16
2019−21
2030
Present Required
perative to sustain ongoing efforts, ensuring the momentum
Target
Rate of
Rate of
Decline
Decline
in poverty reduction is upheld. This is especially vital given
H (%)
MPI
A (%) H (%)
MPI
A (%)
H (%)
the positive current rate of decline at 9.5%, surpassing the
Rural
37 0.164
45
22 0.094
43
18.5
9.9
1.9
required rate of 2.1%.
Urban
9 0.039
43
6 0.023
39
4.5
7.8
3.1
Analysing the rural−urban divide, it is observed that the
Total
28
0.12
44
17
0.07
42
14
9.5
2.1
Source: Author’s calculation based on NFHS-4 and NFHS-5.
reduction in the MPI has been more pronounced in rural
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areas, with an annual average decrease of 10.5%, compared
to a decrease of 10% in urban areas. This suggests that efforts
to alleviate multidimensional poverty have had a greater impact in rural regions. Moreover, rural areas have experienced
an annual average reduction of 9.8% in the multidimensional
headcount ratio as compared to 7.8% in urban areas, indicating a faster decline in the proportion of rural residents living
in multidimensional poverty. Similarly, there has been an annual average reduction of 0.9% in poverty intensity in rural
areas as against 1.9% in urban areas, highlighting a slightly
slower pace of improvement in rural areas compared to urban
areas in terms of severity of poverty.
India’s SDG status on multidimensional poverty reveals
progress, with rural areas witnessing a decline from 37%
(2015−16) to 22% (2019−21), and urban areas from 9% to 6%,
albeit falling short of the required rates, emphasising the need
for accelerated efforts to halve poverty by 2030.
Figure 3: Deprivation Profile of Multidimensional Poor by Their Severity (%)
Multidimensional Poverty by Social Groups
Table 5 presents the severity of multidimensional poverty
based on deprivation scores and highlights changes between
2015−16 and 2019−21. The proportion of households identified
as severely multidimensional poor decreased from 8.6% in
2015−16 to 4.8% in 2019−21. Additionally, there was a 7 percentage point reduction in the proportion of households
categorised as multidimensionally poor. These improvements
indicate progress in addressing poverty and improving living
conditions. Despite the reduction in severe and multidimensional poverty, approximately one-fifth of households are still
at risk of becoming multidimensionally poor in the future,
that is, they are vulnerable to multidimensional poverty. This
highlights the importance of implementing policies and
interventions that not only alleviate existing poverty but also
address the underlying factors that contribute to vulnerability.
While severe and multidimensional poverty decreased in
rural areas, there was a 1.5 percentage point increase in
vulnerability to multidimensional poverty. ST households
experienced a significant reduction of 8.6 percentage points
in severe multidimensional poverty, indicating positive progress. However, there was an increase in the vulnerability to
Data disaggregated by social groups reveal that, in 2019−21,
ST households exhibited the highest multidimensional poverty
headcount ratio, intensity of poverty and MPI, indicating a
higher prevalence and severity of poverty within this group
(Table 4).
Table 4: Incidence of Multidimensional Poverty by Social Group
2015−16
2019−21
SDG 2030
Target
Present
Rate of
Decline
Required
Rate of
Decline
H (%)
MPI
A(%)
H (%)
MPI
A (%)
SC
33
0.14
42
21
0.09
43
16.5
H
8.6
2.6
ST
50
0.23
46
32
0.14
44
25
8.5
2.7
OBC
27
0.13
48
16
0.07
43
13.5
9.9
1.9
Others
15
0.06
39
9
0.04
42
7.5
9.7
2.0
Total
28
0.12
44
17
0.07
42
14
9.5
2.1
Source: Author’s calculation based on NFHS-4 and NFHS-5.
.PSUBMJUZ
8BUFS
&MFDUSJDJUZ
"TTFU
4DIPPMBUBJONFOU
:FBSPGTDIPPMJOH
4BOJUBUJPO
/VUSJUJPO
)PVTJOH
$PPLJOHGVFM
/POQPPS
7VMOFSBCJMJUZUPQPPS
1PPS
4FWFSFMZQPPS
Source: Author’s calculation based on NFHS-5.
importance of considering multiple dimensions of poverty
and designing targeted interventions to address the specific
deprivations faced by different social groups.
Vulnerability to Multidimensional Poor and Severely
Multidimensional Poor
Regardless of social groups, the present rate of reduction in
the case of multidimensional poverty ranges from 8.5% in ST
to 9.9% in OBC, with required rates of decline varying from
2.7% in ST to 1.9% in OBC. This indicates that, across social
groups, progress is on track towards achieving the SDG targets
in the realm of poverty reduction.
Table 5: Severity of Multidimensional Poverty by Changing Cut-off
(%)
Also, OBC households exhibited the greatest re2015−16
2019−21
duction in poverty intensity per year, with an averSeverely
MultiVulnerability NonSeverely
MultiVulnerability
Nonage annual decrease of 2.2%. Similarly, other houseMultidi- dimensional
to Multipoor
Multidimensional
to Multipoor
mensional
Poor
dimensional
dimensional
Poor
dimensional
holds experienced a significant average annual reducPoor
Poor
Poor
Poor
tion of 1.5% in poverty intensity. In comparison, ST
Place of residence
households had a comparatively lower reduction of
24.8
21.8
41.7
6.5
15.3
23.3
55
0.9%, while SC households had the smallest reduc- Rural 11.6
Urban 2.3
5.9
14.7
77
1.2
3.7
12.8
82.3
tion of 0.5% in poverty intensity per year.
8.6
18.7
19.6
53.1
4.8
11.7
20.1
63.3
Furthermore, the analysis of MPI reveals differ- Total
ential progress in poverty reduction across social Social groups
10.5
22.3
21.2
46
6.5
14
22.2
57.3
groups. OBC households experienced the highest SC
18.7
31.4
19.9
30 10.1
21.5
23.5
45
reduction in MPI, with an average annual decrease ST
8
18.5
20.3
53.1
4.2
11.1
20.5
64.1
of 11.6%. This is followed by ST households with a OBC
4
11
16.9
68.1
2
6
15.7
76.3
reduction of 9.5%, SC households with a reduction Others
Multidimensional Poor (>0.50), Multidimensional Poor (0.33−0.49),Vulnerability to Multidimensional
of 8.5%, and other households with a reduction Severely
Poor (0.20 to 0.32), Non-poor(<0.20).
of 7.8% per year. These findings emphasise the Source: Author’s calculation based on NFHS-4 and NFHS-5.
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Figure 4: Deprivations Profile of Severely Multidimensional Poor
Households in India
Electricity
30
25
20
15
10 1.7
5 2.63.8
0
29.4
Nutrition
8
5
4
3
3
3
Years of Tchooling
2
2
2
2
2
2
2
1
1
1
1
1
1
1
Source: Author’s calculation based on NFHS-5.
multidimensional poverty among STs, rising from 20% in
2015−16 to 24% in 2019−21.
Deprivation Profile by Severity of Multidimensional Poor
Figure 3 (p 49) provides an analysis of deprivation levels
across various dimensions based on the severity of poverty.
Cooking fuel and housing exhibit the highest levels of deprivation among the severely poor, with over 90% lacking access to
proper cooking fuel and adequate housing. Nutrition shows a
concerning pattern, with deprivation remaining high across
all poverty categories. Even among those vulnerable to poverty,
a substantial percentage (73.4%) face deprivation in nutrition.
Education-related dimensions, such as years of schooling and
school attainment, demonstrate high levels of deprivation among
the severely poor and multidimensional poor. However, there
is a noticeable decrease in deprivation among the vulnerable
population and non-poor individuals. The dimensions of asset
ownership, electricity, water, and mortality display varying
levels of deprivation across poverty categories. While the
severely poor experience the highest levels of deprivation, the
multidimensional poor and vulnerable populations also face
significant challenges in these areas.
The study utilised the deprivation profile of severely multidimensional poor households, based on NFHS-5 data (Figure 4),
to gain insights into the most prevalent combinations of deprivations experienced by these households in India. As depicted
in Figure 4, a staggering 60% of severely poor households face
one of the 20 specific deprivation profiles.
At the all-India level, our findings indicate that 13% of
severely multidimensional poor households concurrently
experience poverty in the domains of nutrition, education,
sanitation, housing, and cooking fuels. Additionally, an additional 8% of households face simultaneous deprivations in
nutrition, education, sanitation, housing, cooking fuel, and
assets. Furthermore, another 5% of households are characterised
by deprivations in nutrition, school attainment, sanitation,
housing, and cooking fuel.
50
Figure 5: Contributions of Indicators to Multidimensional Poverty Index,
2019−21
(%)
13
d_nutr, d_educ, d_sani, d_hsg, d_ckfl
d_nutr, d_educ, d_sani, d_hsg, d_ckfl, d_asst
d_nutr, d_satt, d_sani, d_hsg, d_ckfl
d_nutr, d_educ, d_hsg, d_ckfl, d_asst
d_nutr, d_satt, d_educ, d_sani, d_hsg, d_ckfl
d_nutr, d_satt, d_educ, d_sani, d_hsg, d_ckfl, d_asst
d_satt, d_educ, d_sani, d_hsg, d_ckfl
d_cm, d_nutr, d_sani, d_hsg, d_ckfl
d_nutr, d_educ, d_wtr, d_sani, d_hsg, d_ckfl
d_nutr, d_satt, d_educ, d_hsg, d_ckfl
d_satt, d_educ, d_sani, d_hsg, d_ckfl, d_asst
d_nutr, d_educ, d_wtr, d_sani, d_hsg, d_ckfl, d_asst
d_nutr, d_satt, d_sani, d_hsg, d_ckfl, d_asst
d_nutr, d_educ, d_elct, d_sani, d_hsg, d_ckfl, d_asst
d_nutr, d_educ, d_wtr, d_hsg, d_ckfl
d_nutr, d_educ, d_elct, d_sani, d_hsg, d_ckfl
d_nutr, d_satt, d_educ, d_hsg, d_ckfl, d_asst
d_nutr, d_satt, d_wtr, d_sani, d_hsg, d_ckfl
d_nutr, d_educ, d_wtr, d_hsg, d_ckfl, d_asst
d_satt, d_educ, d_hsg, d_ckfl, d_asst
d_nutr, d_educ, d_sani, d_hsg, d_asst
16
14
12
10
8
6
4
2
0
(%)
Cooking Guel
15.7
Drinking Xater
Child Nortality
11.8
Assets
11.6 9.6 9.6
ChildTchool
Bttendance
Housing
Sanitation
Source: Author’s calculation based on NFHS-5.
Contributions of Indicators to
Overall Multidimensional Poverty
The analysis of the contribution of different indicators to the
MPI provides valuable insights into the progress towards
achieving the SDGs. Understanding the significance of each
indicator is crucial for designing effective policies and interventions to address multidimensional poverty (Figure 5).
Among the 10 indicators considered, nutrition deprivation
contributes the highest (29%) to the MPI, highlighting the critical
importance of addressing malnutrition in poverty reduction
efforts in 2019−21. Following nutrition, the indicators in
descending order of their contribution to the MPI are years of
schooling, cooking fuel, housing, sanitation, child school attainment, assets, child mortality, drinking water, and electricity.
Regional Variation in MPI
The analysis of the statewise multidimensional headcount ratio findings reveals important insights into poverty reduction
efforts in different regions of India (Table 6). The data shows
a wide variation in the headcount ratios among states, with
some states experiencing significantly higher levels of multidimensional poverty compared to others. This highlights the
need for tailored interventions and policies to address the
specific challenges faced by each state. The multidimensional
headcount was highest in Bihar, Jharkhand, Uttar Pradesh
(UP), Madhya Pradesh (MP), and Odisha and was lowest in
Kerala and Tamil Nadu.
Significant reductions in the headcount ratio have been
observed in states like Andhra Pradesh, Arunachal Pradesh,
Assam, Chhattisgarh, and Manipur, indicating successful
poverty reduction efforts in these regions. On the other hand,
states like Bihar, Gujarat, Jharkhand, MP, Odisha, and UP continue to face significant challenges in reducing multidimensional poverty as given by the present rate of reduction compared to other states.
The majority of states have witnessed a reduction in poverty
intensity, indicating progress in addressing the deprivation
experienced by individuals living in poverty. The magnitude
of intensity reduction varies across states. Some states, such as
Chhattisgarh, Andhra Pradesh, and Goa, Rajasthan, Telangana,
MP, Punjab, and Haryana, have experienced relatively higher
reductions in intensity, implying significant improvements
in deprivations among the poor. On the other hand, some
states like Assam, Gujarat, Bihar, Jharkhand, Manipur, UP,
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Figure 6: Disparity among the Poor (Variance)
0.018
0.016
0.014
0.012
0.01
0.008
0.006
0.004
0.002
0
Meghalaya
Bihar
Jharkhand
Assam
Mizoram
Odisha
Uttar Pradesh
Arunachal Pradesh
Chhattisgarh
Gujarat
Madhya Pradesh
Rajasthan
Tripura
Haryana
Maharashtra
Manipur
Nagaland
Punjab
West Bengal
Andhra Pradesh
Delhi
Jammu & Kashmir
Karnataka
Telangana
Uttarakhand
Goa
Himachal Pradesh
Sikkim
Tamil Nadu
Kerala
Total
Uttarakhand, West Bengal, and Assam have shown relatively
smaller reductions in deprivations among the poor, suggesting the need for more focused efforts to alleviate poverty.
Further, Himachal Pradesh, Meghalaya, and Sikkim have also
witnessed an increase in intensity among the poor in 2019−21
as compared to 2015−16. In terms of the MPI, Goa, Kerala,
Delhi, Sikkim, and Tamil Nadu emerge as the states with the
lowest MPI, underscoring their progress. Conversely, Bihar,
Meghalaya, Jharkhand, UP, MP, and Odisha exhibit the highest
MPI, signifying persistent challenges. Among the 30 states, onethird have successfully achieved the SDG goal of a 50% reduction in poverty, while another 17 states are on track to meet
this goal by 2030. However, attention is warranted for three
states—Delhi, Meghalaya, and Tripura—despite their relatively lower poverty rates, as their present rate of decline falls
below the required pace, necessitating intensified efforts to
align with SDG targets by 2030.
Appendix Table 1 (p 53) provides an overview of the
current status and advancements in reducing the severely
vulnerable population and vulnerability to multidimensional
poverty across Indian states. Remarkably, every state has successfully decreased the prevalence of severely multidimensional
poverty, with the exception of Sikkim, which has experienced
2019o21
2015o16
Source: Author’s calculation based on NFHS-4 and NFHS-5.
a slight increase in its proportion of severely multidimensional poor. Additionally, Assam, Bihar, Chhattisgarh, Gujarat,
Jharkhand, Karnataka, MP, Odisha, Rajasthan, Tripura, UP,
and West Bengal have encountered an increase in the share
of the population vulnerable to multidimensional poverty.
Notably, in 2019−21, the disparity among the poor was also
highest in Meghalaya, followed by Bihar, Jharkhand, Assam,
Mizoram, Odisha, and UP. It is worth mentioning that while
disparity among the poor has decreased in most states,
exceptions include Meghalaya and Goa. This underscores the
Table 6: Annualised Reduction in Multidimensional Poverty Headcount, Multidimensional Poverty Index and Average Intensity
2019−21
(%)
2015−16
(%)
Target
2030 (%)
Andhra Pradesh
8
15.6
7.8
12.5
Arunachal Pradesh
11.5
24.4
12.2
Assam
18
36.2
Bihar
35
52.5
Chhattisgarh
17.5
36.8
18.4
Delhi
3.7
4.3
2.15
3.0
5.9
Goa
0.8
5.3
2.65
31.5
-14.2
Gujarat
14.1
21.7
10.85
8.3
2.9
Haryana
Present Rate Required
of Decline
Rate of
(%)
Decline (%)
H
SDG Status
2019−21
(%)
0.3
Achieved
40
14.0
-0.7
Achieved
18.1
13.0
-0.1
26.25
7.8
3.1
13.8
-0.6
2015−16
(%)
Relative
Change (%)
2019−21
2015−16
47
-3.2
0.03
0.07
-15.3
42
44
-1
0.05
0.11
-14.8
Achieved
43
45
-0.8
0.08
0.16
-13.8
On track
45
47
-1
0.16
0.25
-8.6
Achieved
42
51
-3.7
0.07
0.19
-17.1
Need attention
40
42
-1
0.01
0.02
-3.9
Achieved
34
38
-2.1
0
0.02
-33
On track
42
42
-0.2
0.06
0.09
-8.3
A
Relative
Change (%)
MPI
7
10.9
5.45
8.5
2.7
On track
40
43
-1.2
0.03
0.05
-9.8
Himachal Pradesh
4.9
8.1
4.05
9.6
2.1
On track
38
37
0.6
0.02
0.03
-9.1
Jammu and Kashmir
6.3
15.2
7.6
16.2
-2.1
Achieved
40
42
-1
0.03
0.06
-17
Jharkhand
30.6
46.6
23.3
8.1
3.0
On track
43
45
-0.7
0.13
0.21
-8.9
Karnataka
8.6
17.3
8.65
13.0
-0.1
Achieved
40
40
0
0.03
0.07
-13
Kerala
0.7
1.1
0.55
8.6
2.6
On track
36
37
-0.7
0
0
-9.1
Madhya Pradesh
23
41.1
20.55
11.0
1.2
On track
42
44
-1.1
0.1
0.18
-11.8
Maharashtra
8.5
17.3
8.65
13.2
-0.2
Achieved
40
41
-0.6
0.03
0.07
-13.7
-10.9
Manipur
12.1
21
10.5
10.4
1.6
On track
39
40
-0.7
0.05
0.08
Meghalaya
27.6
32.8
16.4
3.4
5.6
Need attention
46
45
0.7
0.13
0.15
-3
Mizoram
5.9
9.8
4.9
9.7
2.0
On track
44
45
-0.4
0.03
0.04
-10.1
Nagaland
14.3
23.7
11.85
9.6
2.1
On track
39
42
-1.4
0.06
0.1
-10.9
Odisha
20.6
35.9
17.95
10.5
1.5
On track
42
43
-0.7
0.09
0.15
-10.9
Punjab
4.7
6.1
3.05
5.1
4.7
On track
39
41
-1.1
0.02
0.03
-6
Rajasthan
16.1
32
16
12.8
0.1
Achieved
42
45
-1.5
0.07
0.14
-14
Sikkim
3.6
4.9
2.45
6.0
4.2
On track
39
38
0.5
0.01
0.02
-5.5
Tamil Nadu
2.3
7.3
3.65
20.6
-5.3
Achieved
38
38
0.3
0.01
0.03
-20.6
-16.4
Telangana
7.7
17.5
8.75
15.1
-1.4
Achieved
39
42
-1.4
0.03
0.07
Tripura
16.3
20.3
10.15
4.3
5.1
Need attention
42
43
-0.4
0.07
0.09
-4.7
23
40.8
20.4
10.8
1.3
On track
43
45
-0.8
0.1
0.18
-11.6
Uttar Pradesh
Uttarakhand
9.2
17.3
8.65
11.9
0.7
On track
40
42
-0.8
0.04
0.07
-12.7
West Bengal
16.1
26.3
13.15
9.3
2.2
On track
40
42
-0.9
0.06
0.11
-10.2
Source: Author’s calculation based on NFHS-4 and NFHS-5.
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51
SPECIAL ARTICLE
ongoing challenges and the importance of targeted strategies
to address disparities within and among states (Figure 6, p 51).
Conclusions
This study unveils the multidimensional landscape of poverty
in India, drawing insights from NFHS-4 and NFHS-5 data. A
noteworthy reduction in national-level multidimensional poverty,
intensity, and MPI reflects substantial strides towards SDG 1.2.
According to Subramanian et al (2023), India has made significant progress in reducing multidimensional poverty, evident
in our findings showing a substantial annual reduction of 9.5%
between 2015–16 and 2019–21.
Highlighting state-level variations, Bihar, Jharkhand, UP,
MP, and Odisha exhibit the highest multidimensional headcount ratio, while Kerala and Tamil Nadu demonstrate the
lowest. Some states, including Bihar, Gujarat, Jharkhand, MP,
Odisha, and UP, lag in the rate of reduction compared to others.
One-third of the states have achieved the SDG of a 50% reduction
in poverty, with 17 more on track. However, Delhi, Meghalaya,
and Tripura require intensified efforts due to their present rate
of decline falling below the required pace for SDG alignment by
2030. Concerningly, states such as Assam, Bihar, Chhattisgarh,
Gujarat, Jharkhand, Karnataka, MP, Odisha, Rajasthan, Tripura,
UP, and West Bengal have experienced an increase in the share
of the population vulnerable to multidimensional poverty.
These findings underscore the critical need for targeted interventions to address escalating vulnerability and multidimensional poverty in specific regions. Further, in 2019–21, Meghalaya topped in the disparity among the poor, with Bihar,
Jharkhand, Assam, Mizoram, Odisha, and UP following suit.
While disparities reduced in most states, exceptions like
Meghalaya and Goa emphasise the ongoing challenges.
note
1
Details of the sampling design, sampling frame
and questionnaire were reported by NFHS and
are publicly available at https://dhsprogram.
com/data/available-datasets.cfm.
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Appendix
Table 1: Severity of Multidimensional Poverty with Different Cut-offs
Severely Multidimensional
Poor
Multidimensional
Poor
Andhra Pradesh
1.4
Arunachal Pradesh
2.7
(%)
Vulnerability to
Multidimensional Poor
Nonpoor
Severely Multidimensional
Poor
Multidimensional
Poor
5.8
17.9
74.8
3.1
12.0
21.5
63.4
8.9
18.1
70.4
7.3
16.3
20.6
55.8
NFHS-5
Vulnerability to
Multidimensional Poor
Nonpoor
NFHS-4
Assam
5.7
15.8
22.3
56.1
12.0
23.9
20.4
43.8
Bihar
13.9
20.5
21.0
44.5
22.1
29.8
19.5
28.6
Chhattisgarh
4.0
12.9
24.2
58.9
8.9
27.3
20.1
43.7
Delhi
0.5
2.3
10.2
87.0
0.9
2.5
15.5
81.1
Goa
0.0
0.9
6.5
92.6
0.4
4.6
9.8
85.3
Gujarat
3.1
10.0
20.4
66.5
5.4
15.3
19.7
59.6
Haryana
1.5
5.1
19.4
74.0
2.6
7.6
20.1
69.8
Himachal Pradesh
0.5
4.2
17.6
77.7
0.6
7.4
21.0
71.1
Jammu and Kashmir
0.9
4.7
11.6
82.7
3.3
11.4
17.6
67.7
Jharkhand
9.6
20.7
23.4
46.4
15.2
30.8
20.7
33.3
Karnataka
1.3
6.7
19.9
72.1
3.2
13.3
19.1
64.4
Kerala
0.0
0.6
9.2
90.1
0.1
0.8
9.8
89.3
Madhya Pradesh
5.4
16.8
22.9
54.9
12.8
27.6
20.9
38.7
Maharashtra
1.4
6.5
18.2
73.9
3.4
13.2
20.6
62.8
Manipur
1.7
10.2
19.1
69.1
3.4
17.4
23.7
55.5
44.3
Meghalaya
10.4
16.4
20.3
53.0
10.9
21.1
23.7
Mizoram
2.0
3.6
8.6
85.9
3.3
6.1
12.8
77.8
Nagaland
2.7
11.6
15.6
70.1
6.1
17.3
17.6
59.0
Odisha
5.5
14.8
19.6
60.1
10.5
25.1
19.2
45.2
Punjab
0.7
3.2
13.4
82.8
1.3
4.2
13.6
80.9
Rajasthan
3.9
11.8
23.6
60.8
11.1
20.1
22.5
46.3
Sikkim
0.5
3.1
9.3
87.1
0.5
4.1
12.3
83.2
Tamil Nadu
0.2
1.8
12.3
85.6
0.5
6.5
17.2
75.9
Telangana
1.1
5.4
19.7
73.9
3.5
13.6
21.5
61.5
Tripura
3.2
12.9
20.7
63.2
5.3
14.7
20.2
59.9
Uttar Pradesh
6.7
15.2
23.0
55.1
13.8
26.2
20.2
39.7
Uttarakhand
1.5
6.7
16.5
75.2
3.8
12.7
19.9
63.7
West Bengal
3.2
12.6
21.6
62.7
7.1
19.0
20.0
53.9
Severely Multidimensional Poor (>0.50), Multidimensional Poor (0.33-0.49), Vulnerability to Multidimensional Poor (0.20 to 0.32), Non-poor (<0.20).
Source: Author’s calculation based on NFHS-4 and NFHS-5.
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Development vs Welfare Populism at the State Level
Politics of Welfare Benefits in Andhra Pradesh
K C Suri
Regardless of the regime types at the state level, the
range of welfare schemes implemented, the number of
beneficiaries covered, and the magnitude of financial
support extended have significantly increased in recent
decades. The paper seeks to locate the broader issue of
the tension between welfare and development policy
framework by taking the case of Andhra Pradesh in the
last 10 years, especially the YSRCP government that came
to power in 2019. The paper examines whether the
spiralling political corruption and excessive centralisation
of political power in one person are related to the full
speed with which welfare benefits are expanded. It
argues that a new type of patron–client relationship is
developing between the politician and the voters as
welfare schemes are designed and implemented to
transform citizens into clients expected to vote for the
ruling party in gratitude for the welfare benefits received.
K C Suri (surikc@gmail.com) formerly taught political science at
University of Hyderabad and is presently an emeritus professor at
GITAM University, Visakhapatnam, Andhra Pradesh.
54
T
he expansion of government-sponsored welfare schemes
in Indian states has been spectacular in recent decades.
Regardless of the regime types, the range of welfare
schemes implemented, the number of beneficiaries covered
and the magnitude of financial support extended have significantly increased. For instance, the Government of Andhra
Pradesh (GoAP) claims to have spent an amount of `50,000 crore
or about a third of its revenue receipts on welfare schemes in
2022–23. Extensive and extended distribution of welfare benefits or a promise to do so is considered a sure strategy to secure an electoral victory. The victories of the Congress party
in the 2023 legislative assembly elections in Karnataka and
Telangana are mainly attributed to the welfare guarantees
made by the party. Therefore, it is time we shift our gaze onto
the nature of welfare policies of the principal contenders for
power in the party system, the politics of welfare schemes, and
their consequences to the polity.
In general, India is an appropriate case to understand how
democratic politics in a developing nation compels political
parties to opt for welfare schemes on a large scale. It is natural that in a democratic polity, many people are not in a position to meet their basic needs from their meagre incomes
look for government support. As society gets increasingly democratised, political leaders have to respond to the rising
aspirations of common people to secure education, health,
housing, and improved livelihood, and lead a life of dignity
and better opportunities. Leaders who promise and deliver
such benefits enjoy an edge over others in electoral contests.
This condition is the source of “welfare populism” in a
democracy such as India.
The vigorous adoption of neo-liberal policies in the 1990s
called for a free rein to market forces. Initially, many speculated that this new paradigm of development warrants
cutting down state expenditure on welfare schemes. Some
posited a tension between these two policy orientations—
between the logic of democracy expansion and the logic of
market economy (Nayyar 1998). But India’s political leaders
have been able to find ways out of this situation. Social sector
expenditure by the central and state governments did not go
down in the wake of liberalisation reforms (Dev and Mooij
2002). In recent decades, ruling parties have been able to
resolve this tension by limiting public investments and using
government revenues for welfare schemes. Political leaders
maintain that they are able to keep the two objectives of
welfare and development on an even keel by encouraging
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and attracting private capital on the one hand and allocating
more money for welfare on the other.
Corresponding these two themes of welfare and development, we see new styles of political leadership and party functioning emerging in Indian polity, namely centralisation and
personalisation of power in the party and government, decline
of parties as organisations, erosion of ideological orientation
of parties, and high-level political corruption. Is there a positive relationship between welfare populism and the emerging
aspects of personalisation of power, decline of party organisations and political corruption at higher levels? We see that party
organisations have become feeble and ideological differences
between parties have faded over the decades, especially in
state parties. Party loyalties among activists have become
weak and volatile. For most party workers, party work is
merely transactional. Just like politicians, voters too have become very mobile. The erstwhile social solidarities based on
caste are losing their steam. The old type of patron–client relationship based on feudal dependency has withered away yielding to a new type of patron–client relationship. Voters are still
dependent on leaders for their welfare, but these leaders are
no more the old-type notables. Voters seek welfare benefits
from the government. As free agents, they enter a relationship
based on transactions with the leaders and parties to exchange
votes for a welfare benefit.
When there is very little difference between contending
leaders in terms of integrity or policy framework and when
leaders aggressively seek to maximise their personal interest
using governmental power, voters also go by individual considerations, that is, the prospect of securing maximum personal material benefit. Such a situation will have a negative
impact on the whole system. We have observed that in recent
decades, maintenance of party machinery and conducting
election campaigns have become hugely expensive at every
level—be it the state, constituency, village or ward. Political
leaders need to stock huge amounts of money to meet election
campaign expenditure. Between elections too, they have to
spend considerable amounts of money on sustaining the party
machinery and the “cadre.” Hiring political consultants and
the extensive use of various media are the order of the day,
and they come at a huge cost. Most of the money spent on
elections at the constituency levels has to be met by candidates and that self-fi nancing of election expenditure makes
candidates look for ways to amass illegal wealth. Once a leader
starts stocking money for election purposes through illegal
ways, the boundaries between the legitimate need for campaign money and amassing personal wealth get erased. Now, a
politician requires political power to safeguard the ill-gotten
wealth and make it grow. The politician gets entangled in this
vicious circle.
This is where we find a nexus between the phenomena of
clientelism, high-level political corruption, policies that favour
crony business persons, and augmented expenditure on welfare schemes. We see the interplay of these dimensions of
our polity in a stark manner in most states. Among the states
in India, the Andhra Pradesh (AP) government spends a
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significant portion of its revenue receipts on welfare schemes.
Parallel to the increase in welfare expenditure and high visual
and decibel publicity about welfare schemes, we also see
spiralling political corruption, a massive increase in election
expenditure that allows only the super-rich to fight elections,
and excessive centralisation of political power in one supreme leader surrounded by close family members and a
small coterie of second-level leaders. A related question we shall
ask is whether benefits under the welfare schemes lead to empowering people as citizens who can stand on their own legs
holding governments accountable for good governance, or to
clientelism reducing citizens to the status of beneficiary voters, who vote for the ruling party in exchange for the benefits
they have received from the leader.
Although AP witnessed so much acrimony about welfare
schemes during the Telugu Desam Party (TDP) and the Yuvajana
Sramika Rythu Congress Party (YSRCP) regimes, there is hardly
any systematic examination of these schemes and their implementation. Carolyn Elliott (2016) made an attempt to analyse and assess the welfare-development-democracy interlinks
during the YSR rule. She pointed out that even as the welfare
benefits moved beyond the earlier types of clientelism, they
led to a democratic deficit in the form of increasing political
corruption and centralisation of power. Gopinath Reddy and
Aruna Kumar (2021), in their assessment of the welfare
schemes during the YSRCP government, were of the view that
these welfare schemes lead to development, participation and
empowerment of people of AP.
The paper seeks to locate the broader issue of the nexus
between welfare schemes, empowerment and development in
Indian states by taking the case of AP since its formation in
2014. The first part of the paper provides the background to
the wide range of welfare schemes by explaining the four-decade-long political contestation and rhetoric around the issues
of welfare and development, since the time the TDP government inaugurated massive welfare schemes in 1983. This will
enable to understand the shifts in the welfare-development
discourse and the departures we see in recent times. The second part of the paper takes stock of the various welfare schemes
implemented by Jagan Mohan Reddy-led YSRCP government in
AP. The third part discusses the politics of the welfare schemes
and how the ruling party uses them to garner voter support.
The last and concluding part identifies some consequences
of welfare populism to India’s polity.
Two Discourses of Welfare and Development:
The Swinging Policy Pendulum
Politics in AP since the 1980s oscillates between a development
discourse and a welfare discourse. The policy pendulum
moves back and forth. If one party moves it too much to one
side, it gets pulled back to the other side by the opposition,
with politicians on both sides often claiming that they are
engaged in finding an equilibrium position between welfare
and development. In reality, no politician can afford to hold on
to only one position and abandon the other. What is rather
interesting is to note the variation in terms of emphasis that
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different politicians lay upon welfare and development. Some
make welfare as key to their political strategy and policy
framework, while others consider development as central
to their political strategy. In AP, for instance, Chandrababu
Naidu, the TDP president and former chief minister, stresses on
development more than welfare, while Jagan Mohan Reddy,
president of the YSRCP and the chief minister, stresses on
welfare more than development.
The first discourse on development versus welfare in AP began in 1982 with N T Rama Rao (NTR), the founder of the TDP.
In the run-up to the elections held in 1983, he promised subsidised rice, free clothes, and free housing for the poor. He proclaimed that for him, society is like a temple, people are the
god, and that it is the responsibility of the government to
feed, clothe and shelter the poor. He declared that his party
stands for the transfer of power to the socially backward
classes of people, for the empowerment of women, and for a
dignified living for the poor. The TDP won the election with a
massive majority pushing aside the Congress that was in power for more than 30 years. The TDP government did deliver
on the promises it made: subsidy rice and clothes universally
to all the poor and free houses for targeted individuals. The
TDP government also supplied free electricity to farmers for
agricultural purposes.
Congress leaders termed these welfare schemes populist.
Many social scientists too at that time held the view that such
provision of goods at subsidised rates or free of cost is unproductive and inimical to the economic growth and overall
health of the economy. Criticism of such a “donative discourse”
became sharp after the liberalisation policies on a large scale
in 1991. In the 1994 assembly election, the Congress party led
by P V Narasimha Rao presented itself as development-oriented and the TDP led by NTR presented itself as welfare-centred.
The TDP won a landslide victory, winning more than a twothirds majority in the assembly.
With Naidu, NTR’s son-in-law, taking over the leadership of
the TDP in 1995, the party and government swung to the other
side. The new chief minister discarded NTR’s welfare rhetoric,
adopted a development discourse, stressing the need to roll back
the state and allowing a free rein for market forces. It was
now the turn of the Congress led by Y S Rajasekhara Reddy,
better known as YSR, to articulate the welfare discourse at the
turn of the century. He presented himself as the saviour of the
poor and the disadvantaged promising free electricity for agriculture, free medical facility for people in the low-income
brackets, and tuition fee reimbursement for poor students. He
sensed the aspiration of the people for decent education for
their children and the need for reasonable healthcare. The
welfare promises of full tuition fee reimbursement, free
healthcare, and free electricity for agriculture enabled the
Congress to win the 2004 election with a near two-thirds’ majority in the assembly. The Congress and the media that supported YSR termed this as a welfare-centric government in
contrast to the growth-oriented TDP government led by Naidu.
It was the same narrative that saw the Congress retain power
in 2009 election.
56
Thus, the defeat in 1994 and 1999 made the Congress party,
which claimed to have initiated market economic reforms in
India, to move to the other side of the policy pendulum, and
present itself as the saviour of the poor and the socially disadvantaged. On the other hand, the defeat of the TDP in the 2004
and 2009 elections made the its supremo, who earlier claimed
to be the champion of market economic policies in the state,
and compelled him to present himself as someone who is capable of a two-track strategy of simultaneous pursuit of development and welfare, of blending the two in equal measure. In
the 2014 assembly election, he spoke the same language that
NTR spoke in 1982: samajame devalayam, prajale devullu (society is our temple, people are the god). He promised several welfare schemes such as loan waivers for farmers and women’s
self-help groups, free electricity for agriculture, free housing,
pensions for the old, widows and the physically disabled persons, free education from kindergarten to post-graduation,
free health facilities for all diseases in all government, private
and corporate hospitals, free tap-water supply for each house,
and special schemes for the economic, social and political
empowerment of the backward classes of people. The party
scraped through the election with a small margin.
In 2019 election, Jagan Mohan Reddy promised more welfare schemes if elected to power. He promised to bring
back the “Golden Era” of Rajanna’s regime, a metaphor for
the supposedly welfare-centric government run by his father
Y S Rajasekhara Reddy, who was the chief minister of the
composite state of AP during 2004–09. The distinguishing
feature of the YSRCP’s election campaign was that the chief
minister candidate projected welfare schemes as his main
agenda, and their effective implementation his principal activity. He portrayed himself as the saviour of the poor and
the needy. Among various other factors, the prospect of getting more welfare benefits under the YSRCP government than
under the incumbent TDP government showed a positive effect on voting decisions. The YSRCP won the election with a
thumping majority, winning 151 out of 175 seats with 49.95%
popular vote. The TDP lost power by winning only 23 seats
with 39.10% vote. The two national parties, the Congress
and the Bharatiya Janata Party (BJP), lost deposits in all the
seats they put up candidates.
The Barrage of Welfare Schemes by the YSRCP Government
The 2019 election manifesto of the YSRCP promised a new
model of governance based on welfare schemes under nine
rubrics called Navaratnalu (Nine Gems). It promised pensions
for the old age people, single and widowed women, disabled
and the chronically sick (Pension Kanuka), free healthcare
scheme for the poor, including financial assistance after treatment till a person returns to work (Arogya Sri), free education
from nursery to post-graduation (Vidya Deevena), financial
assistance for mothers of schoolgoing children to be credited
directly in the mother’s bank account (Amma Vodi), concessions for women self-help groups (Sunna Vaddi), free housing
for the poor, financial assistance for farmers to meet cultivation
expenses (Rythu Bharosa), etc.
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Soon after the YSRCP assumed power in May 2019, the government declared:
The new government is committed to adopt a twin strategy of welfare and development. With an intent to provide service delivery at
the doorsteps of citizens, the government is going for a paradigm
shift in governance under the broad welfare framework of Nava Ratnalu wherein the village secretariat, newly put in place and assisted
by the village/ward volunteers will drive the service delivery, handholding the services personally to about 50 households in the village.
(GoAP 2019)
Speaking on the welfare schemes in the legislative assembly,
the chief minister stressed their importance in his scheme of
politics. He said:
My journey is with the common man, with the economically weaker
sections. My goal is to eradicate poverty, which is why my economics is
different. Only if economically weaker sections strengthen, will the
society strengthen, and then the state. I have believed it, followed it,
and implemented it. This is my economics, politics, and this is what I
have learnt from my father as history. (Print 2023)
To this, the finance minister added a development dimension. He said: “Our destination is holistic development of our
state through the inclusive role of the people. Our desire is to
demonstrate to the world that empowered people of our state
drive sustainable development” (Hareesh 2023). According
to him, a radically new governance model and innovations in
policy are the distinctive attributes of the YSRCP government.
The welfare schemes are of various types. The most important of them are the direct benefit transfer (DBT) schemes in
which money is directly credited or transferred into the bank
accounts of the beneficiaries. Unlike in the past, when welfare
benefit disbursal was usually in kind or in the form of state
subsidies, most of the welfare schemes now take the form of
DBTs. The government maintains that DBT schemes help prevent bureaucratic corruption and capture by political intermediaries, and ensure that the welfare benefits reach the intended beneficiaries in time and in full. Over the past four
years, ever since Jagan Mohan Reddy took over as the chief
minister in 2019, the AP government reported to have spent
about `1.97 lakh crore on DBT schemes, at an average of
`49,000 crore per year. For financial year 2023–24, the AP government allocated `54,228 crore or about a third of the revenue receipts for DBT schemes. A total of 22 schemes are covered under the DBT category (GoAP 2023a: 5).
Beneficiaries under most of the welfare schemes must meet
multiple criteria to become eligible for financial assistance.
One of the most important condition is that the beneficiary
shall belong to the identified below poverty line (BPL) category household having a white ration card. In order to be considered a BPL family, the total family income of a beneficiary
should be less than `10,000 per month in rural areas or
`1,20,000 per annum and `12,000 per month or `1,44,000 per
annum in urban areas. Such a family should also hold a white
ration (rice) card issued to BPL families. Further, no family
member of the beneficiary should be a government employee,
a government pensioner, an income tax payee, own a fourwheeler or own more than 1,000 sq ft of land or house (builtup area) in urban areas. Total landholding of the family should
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be less than 3 acres of wetland or 10 acres of dry land or 10
acres of land put together. The average consumption of electricity by a family in the last six months should not exceed 300
units per month.
The details of the annual expenditure on major welfare
schemes and the number of beneficiaries reported by the government for 2022–23 are given in Table 1. The table shows that
the number of beneficiaries is huge. It is possible that some
individuals benefit from more than one scheme. Also, one
household can have more than one beneficiary, each benefiting from different schemes. The government says that welfare
benefits reach to about 90% of the total households in the
state. Out of 1.27 lakh households in the state (2011 Census), there
are about 64 lakh pensioners, 51 lakh Rythu Bharosa beneficiaries, 21 lakh students getting full fee payment, etc. As per
NITI Aayog’s report, the poverty rate in AP was about 6%. It is
possible that the actual poverty rate is much higher. However,
what is interesting is the fact that 90% of the population is
availing of the welfare benefits that are primarily meant for
the poor. This mismatch between the official poverty rate and
the rate of welfare scheme beneficiaries needs further study.
Politics of Welfare Schemes
Surely, welfare schemes did not begin with the YSRCP in AP.
Most of the schemes implemented by the YSRCP were there
under the previous TDP government, such as free power for
agriculture, loan waivers, old age pensions, house sites and
houses for the poor, tuition fee reimbursements and scholarships for students to meet accommodation and food expenses, and so on. In fact, the introduction and expansion of
welfare schemes in the state have a long history, going back
to the time of the TDP under NTR who introduced several welfare schemes such as supply of rice at `2 a kg, free clothing,
free houses for the poor and free electricity for farming. He
Table 1: Year-wise Expenditure (in ` crore) on Welfare Schemes during the
YSRCP Government and the Number of Beneficiaries during 2022–23
Name of the Scheme
Amount
(` crore)
Number of
Beneficiaries
Jagananna Amma Vodi
Jagananna Vasati Deevena
Jagananna Vidya Deevena
YSR Rythu Bharosa
YSR Matsyakara Bharosa
YSR Pension Kanuka
YSR Netanna Nestam
YSR Law Nestam
YSR Vahana Mitra
YSR Arogya Asara
YSR Arogya Sri
YSR Sunna Vaddi Panta Runalu (farmers)
YSR free crop insurance
YSR Sunna Vaddi (SHGs)
YSR Cheyutha
YSR Kapu Nestam
Jagananna Chedodu
YSR Kalyaamasthu/Shaadi Tohfa
YSR Free Housing (cumulative payments made
directly to the beneficiaries over four years)
YSR Rice Card
6,651
1,061
2,096
6,900
113
17,866
206
10
271
399
2,900
552
3,165
1,261
4,949
534
330
38
43,96,402
11,10,214
21,87,025
50,92,579
1,13,212
64,06,240
83,123
2,011
2,70,521
6,74,686
10,07,037
8,22,411
15,89,010
1,02,16,410
26,39,703
3,56,143
3,30,145
4,536
8,632
21,31,564
3,680
1,46,00,000
Source: Compiled from AP Socio Economic Survey (GoAP 2023b) for the concerned year
and the information supplied to the Public Accounts Committee, Government of Andhra
Pradesh, in a communication dated 15 March 2023.
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was called a populist, but he remained very popular because
of his welfare schemes.
We should also note that all state governments in India today,
especially the neighbouring states such as Bharat Rashtra
Samithi and the Congress governments in Telangana, DMK
and ADMK in Tamil Nadu, and the Congress government in
Karnataka, implement various welfare schemes. The Finance
Accounts Reports for various years for major states of India
give full details of the welfare schemes and the amount spent
in each state. Taking all the welfare schemes, Gujarat, Maharashtra and Tamil Nadu have a greater number of welfare
schemes than AP. So, what makes the YSRCP different from the
previous TDP government in regard to the nature of welfare
schemes? Is the difference between the two regimes that vast
as claimed by the YSRCP government?
The YSRCP government emphasises the DBT mode of delivering the benefit. The government’s claims about this are
exaggerated. Over the past two decades, DBTs have become
the global norm in designing and delivering welfare benefits
in all developing societies. This was done in Latin American
nations in the 1990s and later extended to countries in Africa
and Asia. Within India, the United Progressive Alliance (UPA)
government began this a decade ago under the leadership of
the then finance minister P Chidambaram. This is now happening in all the states, the latest being the Aam Aadmi Party
governments. The present government in AP has repackaged
some already-existing schemes such as welfare scholarships
providing tuition fee and hostel expenditures into DBT
schemes. However, the chief minister seeks to sell DBTs
(transferring money by pressing a button) as a distinctive
feature of his government in his effort to get all the glory and,
with that, electoral support.
The government also claims to have expanded schemes to
include more people—everyone who is eligible to benefit from
a scheme. But this also appears to be exaggerated. The saturation model was initiated during YSR’s regime itself. He expanded the welfare cover, especially in regard to education, health,
housing and pensions. Unlike before, all eligible persons,
without any restriction on the number of beneficiaries, received
benefits. For example, all eligible persons would get old age
pension or widow pension, tuition fees for all eligible students
is paid by the government, or every poor person would get free
treatment whether in a private or government hospital. The
Jagan Mohan Reddy government followed and further consolidated this approach.
Administrative mechanisms for delivery: What was new
with the YSRCP government was that it put in place an administrative mechanism to deliver welfare benefits to eligible persons at their doorstep and ensured prompt and effective delivery of the scheme. The government had set up 15,004 secretariats in rural and urban areas, called village secretariat and
ward secretariat, respectively, spread over 13,000 villages and
120 towns and cities. One secretariat covers about 1,000 families. Each secretariat is headed by an administrative secretary.
It has eight to 10 secretaries, each responsible for the delivery
58
of a set of welfare benefits and welfare-linked services in their
locality. The village/ward secretaries are regular government
employees whose numbers come to about 1.35 lakh. To assist
the secretaries, who operate from their offices, there are parttime employees who actually go door to door and deliver welfare
benefits. They are called volunteers, whose numbers are estimated
at 2.55 lakh (GoAP 2024). Each volunteer takes care of 50 families in towns and cities and 100 families in villages that reside
within the area covered by the concerned secretariat. A normal-sized secretariat in a town would employ about 20 volunteers. They are paid an honorarium of `5,000 each per month.
Many young men and women found employment as secretaries or volunteers in the secretariats created soon after
YSRCP came to power. Thus, the ruling party created a vast
army of active supporters in the local administration through
these secretariats and volunteer network. Jagan Mohan Reddy
calls them “bridges between people and the government.”
These secretariats function parallelly to the village revenue office and the municipal offices. Once the secretariats were put
in place, people began to rely on the village and ward secretariats more than the revenue offices.
Political marketing and branding: YSRCP government went
far beyond YSR in refining the political strategy of putting the
welfare schemes to gain popularity and electoral success. The
government gives wide publicity to the welfare schemes. Full
front-page multicolour advertisements in major newspapers
are regularly carried out about one or the other welfare
scheme, almost on a daily basis. These advertisements prominently show the chief minister announcing that money is directly transferred into the bank accounts of the beneficiaries
by the chief minister pressing a button. These advertisements
are well-designed and well-planned sending signals to the
people by presenting the chief minister as the benefactor of
the disadvantaged. These advertisements show money spent
in each quarter, in each year, and cumulatively for all the years
and months since the YSRCP came to power.
The YSRCP government follows all the strategies and techniques of political marketing in implementing the welfare
schemes. All welfare schemes carry either the name of the
chief minister or his father, Rajasekhara Reddy, under the
acronym YSR. This practice began during the previous TDP
government. More than 20 welfare schemes were named after
Naidu, and a few were named after NTR, such as NTR Rythu
Bharosa or NTR Vaidya Seva scheme. It was the first time in
AP’s political history that welfare schemes were named after a
serving chief minister (Lasania 2017). Critics said that this was
done with a view to project the chief minister as the messiah of
the state, a benefactor of the poor, and establish a sentimental
bond with the beneficiaries (Times of India 2016).
Jagan Mohan Reddy followed his predecessor with greater
gusto, effect and success. He labelled many government
welfare schemes after his own name, with the brand name
Jagananna. Anna in Andhra culture has deep emotive overtones. Literally, the word means elder brother. It also connotes
a sentiment that anna is someone to rely upon and a saviour
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expected to care of the well-being of his sisters and brothers. It
is also an informal but respectful way of greeting someone
elder and superior. In Andhra politics, NTR was the first chief
minister to be called anna by the party cadres and supporters.
Later, it was cultivated by YSR. And after that Jagan too wanted
to go on the same path of becoming another anna.
This is in contrast to most other schemes either at the national or state level under different governments. Most of them
do not carry any individual name. They are usually named
after the position of power—such as Prime Minister if it is a
central scheme or chief minister in case the scheme is implemented by the state government. Sometimes, these schemes
are named after well-known leaders of the olden times such as
M K Gandhi or Rajiv Gandhi or Deendayal Upadhyaya. We do
not see welfare schemes being named after the chief minister
in the fraternal state of Telangana. Most state schemes in
neighbouring Karnataka are named after the state such as
Karnataka Bhoo Siri or some specific chief minister scheme. In
Tamil Nadu, most welfare schemes are not named after any
person and some after the names of well-known social reformers. In West Bengal, none of the schemes are named after any
big leader or the chief minister. But in AP, the scheme of naming the welfare schemes is different.
We should also note that many of the schemes that go under
the name of YSR and Jagananna were actually centrally sponsored schemes or jointly sponsored by the central and state
governments, such as Jagananna Gorumudda (mid-day meal
scheme), YSR rice card (national public distribution system), YSR
Arogyasri (Ayushman Bharat), YSR Rythu Bharosa (Pradhan
Mantri Kisan Samman Nidhi [PM-KISAN]) or YSR houses for
the poor (Pradhan Mantri-Awas Yojana), etc. In a scathing attack on Jagan Mohan Reddy, union home minister Amit Shah
said that money given to the state government by the union
under the PM-Kisan insurance scheme was being labelled by
Jagan Mohan Reddy as “Ryhtu Bharosa” and disbursed to the
people of the state. He further said: “The Chief Minister is
pasting his photograph on the rice bags as if he is giving them,
while the fact is that rice is being supplied by the Union government for the poor” (Bhattacharjee 2023).
Advertisement and promotion: Like business promotion of a
brand in the economic market, the government ensures that
the names of the schemes having the tag of YSR or Jagananna
are repeated many times with high frequency through different media. The objective is to build personal loyalty, a sense of
gratitude to the leader, and to make the beneficiary voter recall the name of the chief minister when they go to the polling
station during election time. On every occasion of disbursal of
welfare benefits, the chief minister drives the point that the
benefits are delivered directly into individual bank accounts
without any scope for corruption and siphoning of funds, or
involvement by middleperson asking for commission, or the
hassle of going around offices and government personnel. The
full-page government advertisements repeat this several
times in every advertisement: “Government deposit crores of
rupees directly into the bank accounts of beneficiaries with
Economic & Political Weekly
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may 4, 2024
the click of button.” There are many welfare schemes, and
benefits are disbursed in several instalments.
Let us take, as a representative case, the advertisement on
welfare schemes about transfer of money to students and
mothers of students under the Jagananna Vidya Deevena,
which was carried out in major newspapers on 24 May 2023.
This advertisement says that “Sri Y S Jagan Mohan Reddy,
Hon’ble Chief Minister to deposit `703 crore directly into the
bank accounts of mothers of 9.95 lakh students for January–
March 2023 quarter, with the click of a button.” It further says
that the “Jagananna government has so far paid `14,912 crore
(spread over four years) towards Jagananna Vidya Deevena
and Jagananna Vasathi Deevena alone.” The word “Jagananna”
occurs 22 times in the advertisement, out of which the term
“Jagananna government” appears 12 times. The benefits provided to the beneficiaries are contrasted with the previous TDP
government. The TDP government was characterised as having
a dubious commitment to the welfare of the downtrodden and
the weaker sections.
In almost all functions of pressing the button to disburse
financial assistance directly into the bank accounts of the beneficiaries under various welfare schemes, the chief minister
appeals to the people to support and vote for YSRCP and enable
it to secure all seats in the assembly in the next election (Outlook 2023a). At every public meeting, he would reel off data on
the amount of cash transferred under different welfare
schemes directly into individual bank accounts of the beneficiaries and the cumulative tally of the number of beneficiaries.
In the meetings of party leaders and cadres, he exhorts
them to work hard to win votes by explaining the welfare
schemes launched by the ruling party. Releasing financial assistance directly into the bank accounts of farmers under YSR
Rythu Bharosa scheme, the chief minister appealed to the
farmers to choose the “right party wisely” in the next elections. He likened the assembly elections to kurukshetra, a war
between DPT (dochuko, panchuko, tinuko, which roughly
translates in English to loot, share, and enjoy) and DBT (direct
benefit transfer) (Ramesh 2023). He often contrasts his performance in delivering welfare benefits with that of the TDP government by asking people to compare his rule with that of
CBN’s between 2014 and 2019. In one of the public meetings,
he said: “I am asking all of you to recollect how much money
Chandrababu deposited in your bank accounts when he was the
chief minister …. Did Chandrababu deposit even a single rupee?”
He further asked them to recall whether CBN had ever pressed
a button to disburse money through a DBT scheme and compared how their “son” Jagan Mohan Reddy is managing to do
it now (Outlook 2023b). He warns that a vote against his party
would be a vote against DBTs. If his government falls, the welfare schemes would be stopped, he warned (Print 2023).
Jagan Mohan Reddy accused the entire opposition of ganging up to scuttle his welfare schemes (Samdani 2022). He
went further and likened the political scenario in AP to that
of a class war between the poor backed by the government
and the privileged few backed by the opposition (ANI News
2023). It is interesting that he talks of a class war although he
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SPECIAL ARTICLE
is the richest chief minister in India. His movable and immovable assets, as per his 2019 election affidavit, are more
than the assets of all the other chief ministers in the country
combined (Sammad 2023). The opposition was quick enough
to term his welfare schemes as a cash war, not a class war.
The chief minister exhorted the party activists to go from
house to house, explain the welfare schemes launched by the
government, and ensure a clean sweep by winning all the 175
assembly seats in the next election. He says that he had done
his duty of disbursing direct benefits. It was now the time for
the party leaders and cadres to work hard and ensure the
party’s victory in all constituencies. According to him, he has
fulfilled 98% of his poll promises on welfare, and 87% of the
families were receiving benefits under various welfare
schemes launched by the government. He was confident that
a major chunk of them would vote for the YSR Congress party
in the elections (Varma 2022).
Consequences of Welfare Populism
The nexus between high political corruption and welfare
populism requires careful consideration in this context. AP,
like many other states, has been going through a phase of
political economy in which corruption in the delivery of welfare benefits is significantly reduced, but high political corruption became the norm. High-level political graft and
scandals are routinely reported in the media. It is common
for rival political leaders to accuse each other of amassing illicit wealth to the tune of thousands of crores of rupees when
they are in power. The union home minister and the former
president of the BJP, Amit Shah, said that the government
led by chief minister Jagan Mohan Reddy “is ridden with corruption …. Apart from corruption, the YSRCP government
has done nothing for the State” (Bhattacharjee 2023). “Jagan
is the most corrupt Chief Minister,” says former Congress
leader Ravinder Reddy (Umashankar 2022). YSRCP leaders
are immersed in crime and corruption, alleges Yanamala
Ramakrishnudu, TDP Polit Bureau Member and former finance
minister (Umashankar 2023). “Law and order is crumbling
…. The State is steeped in corruption. It is now synonymous
with the mafia of land, sand and liquor,” says the BJP president, Nadda (Naidu 2022).
In his study of YSR’s leadership, Maiorano observed that YSR
ensured benefits reached to all beneficiaries without corruption, much delay and discrimination based on party affiliation.
He wanted the government officials to implement these
schemes with full commitment and energy. Delivery of benefits to all eligible persons and delivering them without corruption and bribery at the local level made him very popular
among the electorate. Talking about the radical shift that YSR
brought about in the implementation of welfare schemes,
Maiorano observes that YSR put in place a simple yet very
smart political strategy. He made sure that the welfare
schemes remained corruption-free and the benefits reached
the intended beneficiaries. His actions were crucial to changing the perception of the state’s welfare schemes from rentseeking means for powerful elites to a means to retain power
60
and win elections next time. At the same time, he was able to
amass huge wealth for himself, his party and his supporters in
the government and the party—a clearly win-win situation
(Maiorano 2014: 102). His strategy was the same as the one
followed by YSR: taking great care that the welfare benefits
reach the intended beneficiaries without leakages, ensuring
that beneficiaries do not need to run around government
offices, or plead with the local ruling party leader to get their
name included in the list of beneficiaries, etc. Jagan Mohan
Reddy followed the footsteps of his father, YSR’s, strategy for
personal political popularity and electoral success.
Massive increases in welfare benefits also lead to the centralisation and concentration of power in the hands of the
supremo of the party. Since the welfare benefits flow out of
the election promise of the party supremo and he is seen as
the fountain of such benefits in their actual implementation,
politics at the state level revolves around the persona of the
top leader of the party. The electoral fight between two parties gets reduced to that of a wrestling match between two
great patrons who vie among each other in their commitment to the welfare of the poor and the needy and promises
of welfare benefits. Their control on the party finances and
machinery, whatever remains of that, is complete, comprehensive, and virtually untrammelled. A small number of persons form a circle around the supreme leader, often called a
coterie, who run the day-to-day show of the government.
These are not populists of old type, if we understand populism in the sense of a leader promising welfare benefits that
they cannot fulfil because the state has no capacity to provide those benefits promised. So much power is concentrated
in the party supremo and so much popularity is enjoyed by
him on his own that some of his party leaders and ministers
in the governments declare that Jagan Mohan Reddy should
be the permanent chief minister of the state. The YSRCP, in its
plenary meeting held in Guntur in July 2022, unanimously
elected Jagan Mohan Reddy as the permanent party president doing away with the usual rigmarole of electing president every two years as per party constitution (Hindu 2022).
Curiously, the expansion of state welfare schemes and the
massive expenditure on them go hand in hand with liberalisation reforms, although they appear to be rooted in divergent
policy frameworks. The expansion of welfare schemes became
possible precisely because of liberalisation reforms. When the
liberalisation reforms were introduced in the late 1980s and
the early 1990s, especially after the big-bang reforms under
the P V Narasimha Rao–Manmohan Singh duo, it was widely
believed that the Indian state had to be downsized and rolled
back to allow a greater free play of market forces in the economy. The motto was less state and more governance. But very
soon, politicians realised that they cannot win elections articulating the liberalising policy framework and there was renewed thinking on the need for the state to increase spending
on welfare. The release of the state from investing in setting
up industries or developing infrastructure in the public sector,
and passing on these tasks to the private sector on the one
hand, and the tremendous increase in state finances enabled
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the leaders to focus more on welfare benefits than ever before. The predicted diminution of the social sector did not
happen. The diminution of the state sector in the economy and
the enhanced presence of private capital in industry and infrastructure had the effect of turning the government at the state
level into a welfare-centric government.
A great debate is going on about the nature of welfare benefits in India and their social, economic and political consequences. Some tend to view the welfare benefits as freebies,
which they think undermine, the state’s ability to invest in
infrastructure, industry and ensure economic growth. However, the distinction between a freebie and a welfare benefit
is not clear. Are all welfare benefits freebies? The RBI considers expenditure which brings economic benefits such as the
public distribution system, employment guarantee schemes,
state support for education and health as public or merit
goods. According to it, provision of free electricity, water and
public transportation, waiver of pending utility bills and
farm loans are non-merit subsidies or freebies. There is a
widespread perception among the urban middle classes that
the freebies undermine the credit culture, distort prices
through cross-subsidisation, erode incentives for private investment, disincentivise work at the current wage rates,
thereby precipitating a drop in labour force participation.
The Prime Minister has denounced the revdi (a sesame-coated sweet rock candy distributed free during festivals) or freebie culture (Punj and Mahajan 2022). However, chief ministers of the non-BJP states maintained that the welfare
schemes implemented by them should not be confused with
freebies. They think that the welfare benefits empower poor
people, lower poverty, lead to increase demand for goods in
the market, and result in economic development.
Welfare schemes provide opportunities for the disadvantaged and economically backward social groups to reduce
their suffering due to lack of income, employment and the
References
ANI News (2023): “Welfare Schemes Bring Us
Back to Power: CM Jagan Mohan Reddy,”
28 February.
Bhattacharjee, Sumit (2023): “Andhra Pradesh:
YSRCP Government Steeped in Corruption,
Alleges Union Home Minister Amit Shah,” Hindu,
11 June.
Dev, Mahendra S and Jos Mooij (2002): “Social
Sector Expenditures in the 1990s: Analysis of
Central and State Budgets,” Economic & Political Weekly, Vol 37, No 9, pp 853–66.
Elliott, Carolyn (2016): “Clientelism and the Democratic Deficit,” Studies in Indian Politics, Vol 4,
No 1, pp 22–36.
GoAP (2019): Outcome Budget, 2019–20, Volume
VII-1, Department of Finance, Government of
Andhra Pradesh, https://apfinance.gov.in/uploads/budget-2019-20-books/Volume-VII-1.pdf.
— (2023a): Speech of Finance Minister, 16 March
2023, Government of Andhra Pradesh, https://
apfinance.gov.in/uploads/budget-2023-24books/SpeechEnglish.pdf.
— (2023b): Socio Economic Survey, Planning
Department, Government of Andhra Pradesh.
— (2024): Grama-Ward Secretariats, Government
of Andhra Pradesh, https://gramawardsachivalayam.ap.gov.in/GSWS/Home/Main.
Economic & Political Weekly
EPW
may 4, 2024
wherewithal to carry on their economic activities, provide
education to their children, access healthcare, etc. The DBTs
have reduced the role of political intermediaries and corruption at the lower level of the bureaucratic apparatus, while
the saturation mode took the benefits to all the eligible members of different social categories of people. In that sense,
they are welcome. But we do not have any estimate of the
effect of the welfare benefits on the individual life conditions
of the beneficiaries. There are no systematic studies on the
outcome of the welfare schemes commensurate with the
claims made by the politicians.
The welfare schemes are introduced by politicians under
the pressure of democratic politics not on their volition, out of
a commitment to welfare, or to treat welfare as a right of the
people, but as a charity. Welfare benefits are used to promote a
perception of loyalty and obligation towards the supreme leader
in the party and the government. That is where the scheme
behind welfare schemes becomes suspect. The leaders see citizens not as equal fellow citizen but as consumers in the political market who possess the vote. The personal stakes of leaders to “capture political power” or retain political power to
serve their own interests of amassing wealth and exercising
power over others are very high. Leaders do not merely want
to return to power, but want to permanently keep power with
themselves, till their death, and then pass it on to their children or their family when they see that their time is coming to
an end. They are brazenly declaring their ambition to keep
power for themselves for ever. The welfare benefits are called
kanuka or tohfa (gift), deevena (blessing), nestam (companion), etc, to indicate that they are a result of the leader’s benevolence. The citizen who is a recipient of the benefit directly
bestowed by the leader is expected to vote for renewing the
term of the leader. As a result, the citizen gets transformed
into a client who is recipient of welfare benefits with an obligation to vote for the patron.
Hareesh, P (2023): “Andhra Pradesh Budget: Lion’s
Share for Welfare Schemes,” New Indian Express,
17 March.
Hindu (2022): “EC Orders YSRCP to Publicly Deny
Reports of Jagan Being Elected ‘President for
Life,’” 21 September.
Lasania, Yunus Y (2017): “Andhra Pradesh: Chandrababu Naidu Unveils Schemes Named After
Himself,” Mint, 18 December.
Maiorano, Diego (2014): “The Politics of the Mahatma Gandhi National Rural Employment
Guarantee Act in Andhra Pradesh,” World
Development, Vol 58, pp 95–105.
Naidu, Appala T (2022): “Andhra Pradesh Steeped in
Corruption, Alleges Nadda,” Hindu, 7 June.
Nayyar, Deepak (1998): “Economic Development
and Political Democracy: Interaction of Economics and Politics in Independent India,”
Economic & Political Weekly, 5–11 December,
Vol 33, No 49, pp 3121–31.
Outlook (2023a): “Slew of Welfare Schemes Implemented by Govt Will Help YSRCP Sweep 2024
Polls: Andhra CM,” 28 February.
— (2023b): “How Many DBT Schemes Existed
during Chandra Babu Naidu’s Regime, Andhra
CM Questions,” Outlook, 12 April.
Print (2023): “Welfare Schemes Will Go If My
Govt Falls, Warns AP CM Jagan,” 9 July.
Ramesh, Susarla (2023): “Andhra Pradesh: Chief
Minister Jagan Mohan Reddy Asks Farmers
to Choose the Right Party Wisely in the Next
Elections,” Hindu, 1 June.
Reddy, Gopinath M and M Aruna Kumar (2021):
“AP Govt’s Thrust on Welfare Agenda under
Y S Jagan Reddy’s Regime: A Quick Assessment,”
Indian Journal of Political Science, Vol 82, No 4,
pp 539–48.
Samdani, M N (2022): “Opposition Ganged Up
To Stop Welfare Schemes in Andhra Pradesh:
Y S Jagan Mohan Reddy,” Times of India, 22 April.
Sammad, Shaik Abdul (2023): “Jagan the Richest
CM,” ADR India, 20 April, https://adrindia.
org/content/jagan-richest-cm-ap-under-hugedebt-burden
Shweta, Punj and S Mahajan Anilesh (2022): “Freebies vs Welfare,” India Today, 5 September.
Times of India (2016): “Most Andhra Schemes Sport
‘Chandranna’ Monicker,” 13 May.
Umashankar, K (2022): “Jagan Is the Most Corrupt
Chief Minister,” Hindu, 22 December.
— (2023): “Jagan Wants to Win Elections by Hook
or By Crook, Alleges TDP Leader Yanamala
Ramakrishnudu,” Hindu, 25 February.
Varma, Sujatha P (2022): “Majority of Beneficiaries
of Welfare Schemes Will Support YSRCP in
Elections, Says Andhra Pradesh Chief Minister,”
Hindu, 19 October.
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CURRENT STATISTICS
EPW Research Foundation
Wholesale Price Index
Foreign Trade
The year-on-year (y-o-y) growth rate of WPI decreased to 0.5% in March 2024
from 1.4% registered a year ago. The index for primary articles grew by 4.5%
compared to 2.5% a year ago. The rate of inflation for food articles increased
to 6.9% from 5.4% a year ago. The index for fuel and power and manufactured
products declined by (-)0.8% against 8.7% a year ago and that for manufactured
products fell by (-)0.8% compared to (-)0.7%. The annual inflation rate in the
financial year (FY) 2023–24 declined to -0.7% from 9.4% in FY 2022–23.
The trade deficit narrowed to $15.6 bn in March 2024 from $19.0 bn
registered a year ago. Exports decreased by (-)0.7% to $41.7 bn and imports
by (-)6.0% to $57.3 bn compared to $42.0 bn and $60.9 bn, respectively. Oil
imports stood lower at $17.2 bn compared to $18.0 bn a year ago and non-oil
imports at $40.0 bn against $42.9 bn. Exports declined by (-)3.1% to $437.1 bn
in FY 2023-24 from $451.1 bn in FY 2022–23 and imports by (-)5.4% to $677.2 bn
from $716.0 bn.
Consumer Price Index
Index of Eight Core Industries
The CPI-inflation rate decreased to 4.9% in March 2024 from 5.7% reported
a year ago and 5.1% a month ago. The consumer food price index grew by
8.5% compared to 4.8% a year ago. The CPI-urban inflation rate was down to
4.1% and the rural inflation rate to 5.45% from 5.9% and 5.51%, respectively.
According to Labour Bureau data, the CPI for agricultural labourers (CPI–AL)
stood at 7.4% in February 2024 compared to 6.9% and that for industrial
workers (CPI–IW) at 4.6% in January 2024 against 6.2% a year ago.
The ICI increased by 5.2% in March 2024 compared to 4.2% registered a year
ago. Growth in the cement segment rose to 10.6%, electricity generation to
8.0%, natural gas to 6.3% and crude oil to 2.0% from their respective growth
rates of -0.2%, -1.6%, 2.7% and -2.8%, a year ago. Production of coal grew by
8.7% and steel by 5.5% compared to 11.7% and 12.1%, respectively. Growth
in refi nery products segment declined to -0.3% from 1.5% a year ago and
fertilisers segment to -1.3% from 9.7%.
Movement of WPI-Inflation Rate January 2023–March 2024
Merchandise Trade March 2024
Year-on-Year in %
20
Fuel and Power
Over Month
(%)
Over Year
(%)
April–March
(2023–24 over 2022–23) (%)
41.7
57.3
-15.6
0.7
-4.7
-16.6
-0.7
-6.0
-17.7
-3.1
-5.4
-9.3
Exports
Imports
Trade balance
Primary Articles
10
March 2024
($ bn)
4.5%
0
Data is provisional. Source: Ministry of Commerce and Industry.
Trade Balance January 2023–March 2024
-10
$ billion
-0.8% -0.8%
Manufactured
Products
7
0
Non-oil
-20
Jan
2023
F
M
A
M
J
J
A
S
O
N
D
Jan
2024
F
Mar*
-$3.8 bn
Oil
-7
* Data is provisional; Base: 2011–12 = 100.
-$11.8 bn
-14
Trends in WPI and Its Components March 2024* (%)
Over Month
Over Year
Financial Year (Averages)
2021–22 2022–23 2023–24
-21
Weights
100
22.6
15.3
13.2
64.2
0.4
0.9
1.0
0.1
0.2
0.5
4.5
6.9
-0.8
-0.8
13.0
10.2
4.1
32.5
11.1
-28
All commodities
Primary articles
Food articles
Fuel and power
Manufactured products
9.4
10.0
7.3
28.1
5.6
-0.7
3.5
6.6
-4.5
-1.7
-15.6 bn
Total Trade Balance
-35
Jan
2023
F
M
A
M
J
J
A
S
O
N
D
Jan
2024
Feb
Mar
Oil refers to crude petroleum and petroleum products, while non-oil refers to all other commodities.
*Data is provisional; Base: 2011–12=100. Source: Ministry of Commerce and Industry.
Movement of Index Values of Components of IIP January 2023–February 2024
Movement of CPI Inflation January 2023–March 2024
Index Value
210
Year-on-Year in %
Electricity
187.1
144.5
168
15
Consumer Food
126
12
8.5%
9
139.6
Mining
Manufacturing
84
CPI
42
4.9%
6
0
Miscellaneous
3
3.5%
Jan
2023
F
M
A
M
J
J
A
S
O
N
D
Jan
2024
Feb*
* February 2024 are quick estimates; Base: 2011–12=100.
0
-3
Index for Eight Core Industries March 2024* (%)
Jan
2023
F
M
A
M
J
J
A
S
O
N
D
Jan
2024
F
* Data is provisional. Source: National Statistical Office (NSO), Ministry of Statistics and Programme Implementation,
Base: 2012=100.
Infrastructure industries
Coal
CPI: Rural and Urban March 2024* (%)
CPI Combined
Rural (2012 = 100)
Urban (2012 = 100)
Latest
Month Index
Over
Month
Over
Year
185.8
187.7
183.6
0.0
0.2
-0.2
4.9
5.4
4.1
138.9
1258
0.1
0.1
4.6
7.5
CPI: Occupation-wise
Industrial workers (2016 = 100)#
Agricultural labourers (1986–87 = 100)@
Weights
Mar*
Financial Year (Avgs)
2022–23 2023–24
Over
Month
Over
Year
Financial Year (Avgs) in %
2022–23 2023–24
40.27@
9.9
5.2
7.8
7.5
10.3
20.7
8.7
14.8
11.7
0.6
Crude oil
9.0
7.4
2.0
-1.7
Natural gas
6.9
6.4
6.3
1.6
6.1
Petroleum refinery products
28.0
9.0
-0.3
4.8
3.4
6.7
6.8
6.4
5.4
5.6
5.1
Fertilisers
2.6
2.9
-1.3
11.3
3.7
Steel
17.9
6.6
5.5
9.3
12.3
2021–22
2022–23
Cement
5.4
11.7
10.6
8.7
9.1
5.1
4.0
6.1
6.8
Electricity
19.9
8.5
8.0
8.9
7.0
* Provisional; @ February 2024; # January 2024; Source: NSO (rural and urban); Labour Bureau (IW and AL).
(Base: 2011–12=100); *Data is provisional; @ The revised eight core industries have a combined weight of 40.27% in the IIP.
Source: Ministry of Commerce and Industry.
Comprehensive current economic statistics with regular weekly updates are available at: http://www.epwrf.in/currentstat.aspx.
Economic & Political Weekly
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69
CURRENT STATISTICS
EPW Research Foundation
India’s Quarterly Estimates of Final Expenditures on GDP
2021–22
` Crore | At 2011–12 Prices
Q1
Private final consumption expenditure
Government final consumption expenditure
Gross fixed capital formation
Change in stocks
Valuables
Net Trade (Export–Import)
Exports
Less imports
Discrepancies
Gross domestic product (GDP)
2022–23
Q2
Q3
Q4
Q1
Q2
Q3
Q4
1828296 (18.0) 2109196 (13.6) 2429098 (11.0) 2365983 (6.1)
2166248 (18.5) 2282920 (8.2) 2473262 (1.8)
379485 (-8.0) 325630 (5.0) 329449 (-0.6) 445830 (5.1)
416509 (9.8) 336707 (3.4) 352789 (7.1)
1144395 (71.0) 1227684 (14.1) 1220749 (4.8) 1421436 (5.6) 1303951 (13.9) 1285349 (4.7) 1282287 (5.0)
37314 (1287.8) 40524 (875.4) 38513 (826.0) 43852 (821.6) 44647 (19.6) 44039 (8.7)
42943 (11.5)
22378 (490.3) 136471 (160.6) 74741 (46.8)
49510 (-50.9) 35436 (58.4) 109678 (-19.6) 46214 (-38.2)
25120
-37031
-82715
-56012
-23414
-80422
-28286
785791 (50.0) 848922 (28.5) 847632 (31.1) 910763 (25.5) 935660 (19.1) 948378 (11.7) 939984 (10.9)
760671 (46.9) 885953 (28.5) 930346 (21.4) 966775 (8.2)
959074 (26.1) 1028800 (16.1) 968270 (4.1)
-86257 (-207.1) -130034 (-272.3) -139727 (-443.8) -142030 (-849.0) -163422 (89.5) -105414 (-18.9) -134318 (-3.9)
3350730 (23.0) 3672438 (9.7) 3870108 (5.7) 4128570 (4.4)
3779954 (12.8) 3872858 (5.5) 4034890 (4.3)
2023–24
Q2
Q1
Q3
2401395 (1.5) 2281433 (5.3) 2338416 (2.4) 2560203 (3.5)
507720 (13.9) 415961 (-0.1) 383289 (13.8) 341625 (-3.2)
1474836 (3.8) 1414766 (8.5) 1434931 (11.6) 1418043 (10.6)
51836 (18.2)
45367 (1.6)
48734 (10.7) 46352 (7.9)
37839 (-23.6) 27921 (-21.2) 108460 (-1.1)
74773 (61.8)
60844
-230608
-152046
-75920
1023721 (12.4) 874885 (-6.5) 999043 (5.3) 972383 (3.4)
962877 (-0.4) 1105493 (15.3) 1151090 (11.9) 1048303 (8.3)
-150742 (6.1)
135705 (-183.0) 23853 (-122.6) 6935 (-105.2)
4383726 (6.2) 4090545 (8.2) 4185636 (8.1) 4372011 (8.4)
India’s Overall Balance of Payments (Net): Quarterly
2022–23 ($ mn)
Q2
Q3
Q1
Current account
Merchandise
Invisibles
Services
of which: Software services
Transfers
of which: Private
Income
Capital account
of which: Foreign investment
Overall balance
-17964
-63054
45090
31069
30692
22874
23065
-8853
22055
-1238
4595
Q4
-30902 -16832 -1356
-78313 -71337 -52587
47411 54505 51231
34426 38713 39075
32681 33541 34370
24773 28467 24762
24991 28641 25080
-11788 -12675 -12606
1461 28887 6540
12741 6641 4691
-30379 11069
5579
Q1
2023–24 ($ mn)
Q2
Q3
-9120
-56703
47583
35121
33928
22838
23073
-10377
34318
20666
24432
-11420
-64526
53106
39941
35237
24926
25170
-11761
13042
4318
2519
-10519
-71603
61084
45020
36267
29302
29438
-13238
17358
16189
5998
Q1
Q2
2022–23 (` bn)
Q3
Q4
-1387 [-2.1] -2466 [-3.8] -1384 [-2.0] -111.6 [-0.2]
-4867
-6249
-5864
-4326.1
3480
3783
4481
4214.5
2398
2747
3182
3214.5
2369
2608
2757
2827.4
1766
1977
2340
2037.1
1780
1994
2354
2063.2
-683
-941
-1042
-1037.1
1702 [2.6]
117 [0.2] 2375 [3.4] 538.0 [0.7]
-96
1017
546
385.9
355 [0.5] -2424 [-3.7] 910 [1.3] 459.0 [0.6]
2023–24 (` bn)
Q2
Q1
-750 [-1.1] -944 [-1.3]
-4661
-5334
3911
4390
2887
3302
2789
2913
1877
2060
1897
2081
-853
-972
2821 [4.0] 1078 [1.5]
1699
357
2008 [2.8]
208 [0.3]
Q3
-876 [-1.2]
-5962
5087
3749
3020
2440
2451
-1102
1445 [1.9]
1348
499 [0.7]
Figures in square brackets are percentage to GDP.
Foreign Exchange Reserves
Excluding gold but including revaluation effects
` crore
$ mn
Variation
19 April
2024
21 April
2023
31 March
2024
Month
Ago
Year
Ago
4832058
578894
4375573
532920
4913067
589082
-59281
-7589
456485
45974
Financial Year So Far
2023–24
2024-25
2019–20
2020–21
Financial Year
2021–22
2022–23
2023–24
35276
4837
668976
56831
590416
94535
302585
21435
102680
-31532
572770
60999
Monetary Aggregates
` Crore
Money supply (M3) as on 5 April
Components
Currency with public
Demand deposits
Time deposits
Other deposits with RBI
Sources
Net bank credit to government
Bank credit to commercial sector
Net foreign exchange assets
Banking sector’s net non-monetary liabilities
Reserve money as on 19 April
Components
Currency in circulation
Bankers’ deposits with RBI
Other deposits with RBI
Sources
Net RBI credit to government
of which: Centre
RBI credit to banks and commercial sector
Net foreign exchange assets of RBI
Govt’s currency liabilities to the public
Net non-monetary liabilities of RBI
Financial Year
2021–22
2022–23
1649151 (8.8)
1850032 (9.0)
2594773 (11.6)
11606 (0.3)
160633 (6.2)
371548 (2.0)
1598 (1.9)
283860 (10.3)
217871 (10.9)
1136327 (8.1)
11093 (23.4)
240746 (7.9)
107607 (4.9)
1482361 (9.8)
19317 (33.1)
142228 (4.3)
266291 (11.5)
2179194 (13.1)
7061 (9.1)
204341 (2.9)
170702 (1.2)
34973 (0.7)
-23491 (-0.6)
34533 (0.8)
298807 (4.0)
162537 (0.9)
43869 (0.8)
-40172 (-0.8)
-22254 (-0.5)
627255 (10.7)
948054 (8.1)
275216 (6.0)
202475 (6.2)
468905 (13.0)
687903 (10.6)
1813117 (14.4)
57704 (1.2)
710964 (20.4)
317872 (7.8)
239220 (3.3)
2770660 (19.2)
572750 (11.7)
990769 (23.6)
295589 (6.7)
111165 (3.2)
109594 (12.2)
18043 (26.4)
76883 (2.3)
-32897 (-3.5)
-9453 (-12.2)
50803 (1.4)
-66672 (-6.2)
-6385 (-6.9)
279954 (9.8)
177859 (25.4)
11094 (23.4)
244803 (7.8)
53751 (6.1)
19317 (33.1)
137245 (4.1)
143369 (15.4)
14975 (19.3)
-198470 (-14.0)
-212820 (-15.0)
7376 (-16.9)
565020 (12.2)
3146 (9.6)
138270 (8.6)
-31026 (-2.1)
-33381 (-2.3)
50749 (-53.7)
41707 (0.9)
0 (0.0)
26897 (1.7)
87027 (7.7)
71831 (6.3)
-100657 (-156.4)
-39682 (-0.8)
0 (0.0)
-31058 (-1.7)
350911 (31.9)
352626 (32.2)
-174345 (47.2)
243079 (5.8)
1101 (4.1)
-48160 (-3.5)
528 (0.0)
1405 (0.1)
449259 (-82.6)
144877 (3.3)
2272 (8.1)
279065 (21.3)
-316523 (-21.8)
-318032 (-21.9)
158782 (-168.1)
646409 (14.1)
3146 (10.4)
196225 (12.4)
Over Month
Over Year
25483919
636422 (2.6)
2706651 (11.9)
433507 (1.9)
545385 (2.2)
3430269
2747522
19219708
86420
47677 (1.4)
228373 (9.1)
357503 (1.9)
2868 (3.4)
129872 (3.9)
385966 (16.3)
2175806 (12.8)
15008 (21.0)
23962 (0.7)
40958 (1.8)
374936 (2.2)
-6349 (-8.2)
7703559
17362834
5528385
5144057
4660094
162242 (2.2)
289142 (1.7)
136532 (2.5)
-48506 (-0.9)
61376 (1.3)
333686 (4.5)
2762495 (18.9)
581646 (11.8)
974088 (23.4)
238802 (5.4)
3566568
1007174
86352
46494 (1.3)
13352 (1.3)
1530 (1.8)
1221629
1204176
-36318
5194083
33432
1752732
227235 (22.9)
222990 (22.7)
-175755 (-126.0)
-12279 (-0.2)
234 (0.7)
-21942 (-1.2)
2022–23
Over Month
(As on 5 April)
Outstanding
2024
Aggregate deposits
Demand
Time
Cash in hand
Balance with RBI
Investments
of which: Government securities
Bank credit
of which: Non-food credit
20998289
2601856
18396433
89274
932312
6124286
6123155
16601870
16580661
578206 (2.8)
227307 (9.6)
350899 (1.9)
-8932 (-9.1)
30455 (3.4)
20035 (0.3)
19705 (0.3)
288135 (1.8)
298629 (1.8)
26 April
2024
S&P BSE SENSEX (Base: 1978–79 = 100)
S&P BSE-100 (Base: 1983–84 = 100)
S&P BSE-200 (1989–90 = 100)
CNX Nifty-50 (Base: 3 November 1995 = 1000)
CNX Nifty-500
Variation
Financial Year So Far
2023–24
Outstanding
2024
Scheduled Commercial Banks’ Indicators ( ` Crore)
Capital Markets
-81009
-10188
73730.16 (22.3)
23553.74 (30.3)
10275.81 (35.3)
22419.95 (25.9)
20839.35 (39.0)
Over Year
2022–23
Month
Ago
72470.30
22962.80
9968.10
22004.70
20005.25
2550345 (13.8)
382116 (17.2)
2168229 (13.4)
-14972 (-14.4)
127819 (15.9)
600490 (10.9)
600133 (10.9)
2751313 (19.9)
2751068 (19.9)
Year
Ago
60300.58 (5.1)
18074.63 (2.1)
7596.40 (0.8)
17813.60 (3.6)
14994.40 (0.6)
2020–21
Variation
Financial Year So Far
2023–24
404030 (2.2)
39309 (1.8)
364721 (2.3)
13983 (15.5)
-5414 (-0.7)
108648 (2.0)
108700 (2.0)
175321 (1.3)
174263 (1.3)
Financial Year So Far
Trough
Peak
72488.99
23072.88
10049.61
21995.85
20324.7
75038.15
23827.44
10366.12
22753.80
20915.20
2020–21
523062 (2.6)
158002 (6.5)
365060 (2.0)
-159 (-0.2)
829 (0.1)
17728 (0.3)
17546 (0.3)
169706 (1.0)
171578 (1.0)
1351801 (8.9)
211554 (11.4)
1140246 (8.6)
-4823 (-5.3)
140745 (25.9)
266422 (6.0)
266547 (6.0)
1044026 (9.6)
1050269 (9.7)
2023–24
Trough
Financial Year
2021–22
2022–23
1578601 (9.6)
107684 (5.2)
1470917 (10.2)
4338 (5.0)
126469 (18.5)
686200 (14.5)
686143 (14.5)
1783922 (15.0)
1819027 (15.4)
2431313 (13.5)
263423 (12.1)
2167890 (13.7)
-830 (-0.9)
121576 (15.0)
691410 (12.8)
691287 (12.8)
2756928 (20.2)
2753753 (20.2)
End of Financial Year
Peak
59106.44 74119.39
17644.91 23408.17
7406.09 10158.44
17398.05 22493.55
14601.95 20434.80
2021–22
2022–23
2023–24
57362 (18.4)
17423 (20.1)
7412 (20.9)
17153 (19.7)
14652 (22.2)
58992 (0.7)
17602 (-0.7)
7389 (-2.0)
17360 (-0.6)
14558 (-2.3)
73651 (27.8)
23294 (35.6)
10100 (40.0)
22327 (31.7)
20255 (42.5)
Figures in brackets are percentage variations over the specified or over the comparable period of the previous year. | (-) = not relevant | - = not available | NS = new series | PE = provisional estimates
Comprehensive current economic statistics with regular weekly updates are available at: http://www.epwrf.in/currentstat.aspx.
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POSTSCRIPT
ART, MUSIC, CINEMA
Alienation, Punjab, and Gender in Imtiaz Ali’s
Amar Singh Chamkila
Imtiaz Ali’s film about Punjabi firebrand singer, Amar Singh Chamkila, is undone by its “Hindi gaze.”
Jasmine Kaur
I
to believe that Amarjot, who was an artist in her own
t feels almost wrong to critique the film Amar Singh
right and had a strong stage presence, would be as meek
Chamkila (2024; dir Imtiaz Ali) because I believe Chamkila
as she is shown in the film and that her romance with
should be better known, and that we need more—not
Chamkila would be so shy and muted. She points out that
less—narratives about people who have been marginalised,
the Chamkila of live performances does not seem nearly as
especially along the lines of caste. Ultimately, it is better for a
hesitant as the Chamkila of the film. In the live recordings,
film like this to exist than not, but the more time I have
he establishes his boundaries more clearly and is a lot more
spent with Amarjot Kaur and Chamkila, the more this film
comfortable in being critical of his audience. I find myself
alienates me; and the following is an articulation of that
agreeing with Zakariya when she says that the Amarjot and
alienation from a personal lens.
Chamkila of the film pale in comparison to the ones that
The first time I saw the film, I felt as if I was watching
remain in their songs and video records.
the mechanics of the film rather than the film itself. I could
Another thing that 22 Chamkila Forever gets right is that it
tell what sorts of emotions I was supposed to feel in most
does not waste time in pre-emptively responding to future
scenes, but somehow the scenes themselves felt too
criticisms. Amar Singh Chamkila, in comparison, seems too
mechanical to really arouse those emotions in me. I know
this film was just not made for me; it was made The Chamkila of live self-conscious. This is exemplified in the scene
for people unfamiliar with Chamkila and Punperformances does between Chamkila and a reporter functioning as
a stand-in for a straw-man understanding of
jab. This is clear in the very “Hindi gaze” of the
not seem nearly as
feminism. I am not saying that non-intersectionfilm—a phrase used by Akhil Arora in his review
hesitant as
al and clueless feminists do not exist, but it gets
of the film, titled “A Disorderly Protest”—that I
the Chamkila of
tiring when those are the majority of feminists
think aptly captures some of my experience of
the film
that films seem to be interested in portraying.
watching the film as well.
The same film that encourages our understanding of ChamAmarjot and Chamkila were killed for their words—their
kila to be generous, engages ungenerously with another noPunjabi words. So, I cannot help but feel strange that this
toriously misunderstood phenomenon of feminism. As if
major project on their lives is in the realm of a different
feminists would not also be interested in interviewing Amlanguage. Maybe this is because my relationship with
arjot alongside Chamkila. As if the feminist critique is simPunjab is a very fractured one, though I am not sure if there
ply that his songs are “vulgar.” As if concepts of vulgarity
is a way to have an unfractured relationship with a frachave not been used to control women as well. Chamkila
tured state. I thought that maybe watching Jodi, a 2023
responds to the reporter by saying that he does not have the
Punjabi film also loosely based on Chamkila, might be less
privilege to think about what is morally right or wrong,
alienating, but I could not find a copy of it. I did, however,
which automatically made me wonder what kind of morality
come across another Punjabi film called 22 Chamkila Forevwas being referred to here. Because as far as I can tell, privier (2022), which seemed to be a small-budget and much
lege and power make it easier for people to be unethical,
lesser well-known film. The language landscape definitely
because power cushions you from facing repercussions for
had an effect on my experience. Its similarity to other Punyour actions.
jabi films and storytelling traditions that I have grown up in
So, what is this privilege? I can only assume that the
and the absence of a Bollywood sheen made it feel more fafilm’s point is that Chamkila does not have the privilege
miliar and less alienating.
to follow the prescribed morality of the dominant social
Sabahat Zakariya, on her YouTube channel “Feminustani,”
ideology—an ideology that vulgarises anything to do with
talks about how the beauty of Amar Singh Chamkila takes
sexuality. Instead of examining why anything “sexual”
away from the grittiness of Punjab and the subject matter. If
automatically gets categorised as “vulgar,” the film, via its
the idea is to portray an authentic and realistic story, then
constant labelling of Chamkila’s songs as vulgar, suggests
this overly polished format acts as a glossy barrier for
its acceptance of dominant notions of vulgarity. Then,
the audience. She argues that this polish is not just in the
by illustrating the widespread nature of Amarjot and
filming technique but also in the overly respectful and
Chamkila’s songs, the film seems to suggest that vulgarity
sophisticated demeanour of multiple characters. It is hard
Economic & Political Weekly
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71
POSTSCRIPT
ART, MUSIC, CINEMA
should perhaps be accepted given most people’s engagement with it. I do not think this argument works. An
act does not become okay simply because everyone does it.
If everyone were to constantly hit each other all the time,
it would not become morally okay to hit each other by
virtue of the fact that everyone does it. A better argument
would be to question why the sexual is vulgar. What is the
issue with vulgarity? What do we get from controlling
sexuality? Why do we feel so entitled to force our world
views on others?
It is too simplistic to argue that Amarjot and Chamkila’s
songs simply mirror the reality that Chamkila and his listeners
grew up in. That we, from our privileged position, cannot
judge Chamkila on the morality of his songs. The world is
not divided into clear categories of people who are oppressors and those who are oppressed. Chamkila was oppressed
along the lines of caste but also enjoyed privileges along the
lines of gender. He could get away with domestic abuse, but
there were clearly limits to how much space he was allowed
to take up as a musician. His songs are sexually liberating,
but also often objectify women. Because as liberating it
might have been for a lot of men and women to hear these
desires talked about, it does not change the fact that
women are punished a lot more for expressing their sexuality
than men are. This liberation does not apply equally across
genders and sexualities. We can accept an artist’s flaws
even as we celebrate them.
As a woman, I often consume misogynistic art because
(i) there is a dearth of art that is not misogynistic and
(ii) such art often has other redeeming qualities. My relationship with art is also more complex than that of simple
consumption. I often find myself to be the harshest critic of
the musicians I listen to the most, especially when they are
being sexist. I do not need a justification for why or why not
Amarjot and Chamkila sang the songs they did. They are
fun songs! It is possible to enjoy fun songs without adopting
their lyrics as personal world views.
Jasmine Kaur (jasmine5396@gmail.com) is a writer/artist from Punjab. She likes to
surround herself with stories and poetics in any medium, including audio, video, still
images, and performance.
available at
Delhi Magazine Distributors
Pvt Ltd
110, Bangla Sahib Marg
New Delhi 110 001
Ph: 41561062/63
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Economic & Political Weekly
POSTSCRIPT
HEALTH, OTT, ILLNESS
Representation of Cancer
in the Digital Space
The Korean drama, Thirty-Nine, prioritises the
vulnerability of the patient in its portrayal of the
experience of cancer.
Renuka Shyamsundar Belamkar, Sankar Varma
S
cott Armstrong, a blood cancer expert at the Dana-Farber
Cancer Institute in the United States (US), headed a
team of researchers in developing the pill “Revumenib”
for leukaemia. The drug showed promise by curing the
aggressive disease in a third of patients. While such advances
challenge the threat of cancer and promise a potential cure,
they address only the medical challenges. It is important for
us, as a society, to also pay attention to the nuances of the
experience of this illness. Terminal illnesses such as cancer
affect not only the physical body but have deeper emotional
and psychological impacts too.
Each of these
Although there are awareness protasks is commonly
grammes that encourage and atperformed for the
tempt to start conversations about
dead, whereas in
cancer, the stigma related to it conthis case, Young
tinues to add to the trauma of the
does it for herself
experience, for patients and carers
alike. Alongside the many awareness programmes, knowledge about the illness takes various other forms too. Popular
culture today plays an integral role in the dissemination and
creation of a perception about the illness experience. Digital
mediums contribute to this perceived reality through their
large reach. The growth of pop culture through accessibility
across digital mediums such as Netflix, Prime and other
over-the-top (OTT) platforms has blurred the boundaries of
language and culture creating a wide fan base for Korean
pop culture across the world.
Thirty-Nine (2022) is a 12-episode series about three
women—Cha Mi Jo, Jeong Chan-Young, and Jang Joo-Hee—
in their late 30s. The Korean drama revolves around the
lives of these childhood best friends. The second episode reveals Jeong Chan-Young’s diagnosis of cancer through her
friend Cha Mi Jo, who becomes the bearer of the news to
Young. The conversation between the two friends portrays
Cha Mi Jo’s anxiety while she hints at the CT scan without
even uttering the word “cancer,” reflecting the taboo and
fear around the very word. Young’s refusal to receive treatment shows her acceptance of the illness and the impending
reality of death. She also fears the effects of chemotherapy
on herself. Young decides to use her limited time ticking off a
to-do list she prepares for herself. The list includes not only
her dream to become an actress but also her aspirations for
friends and family. The narrative shows the patient as a
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HEALTH, OTT, ILLNESS
selfless individual focused on making the world around her
a better place.
The plot traces the changing relationships and attitudes of
its characters towards Young. Characters become more empathetic as her identity as a patient gains dominance with
the passage of time. While she refuses to embrace that identity embedded by others onto her, she nonetheless accepts
this condition of her “self.” It is reflected when she decides
to do a series of tasks that further make her death a closer
reality. She goes to take a picture of herself for her funeral,
reserves a spot at the memorial hall, and makes a list of
people to be invited for her funeral. Each of these tasks is
commonly performed for the dead, whereas in this case,
Young does it for herself. Therefore, while she battles the
emotional trauma of her illness, she continues to think and
feel for her loved ones, taking care to make their lives easy.
The narrative does not explore the physical trauma of cancer,
instead portraying a romanticised version of the journey.
The initial plot mirrors the common response of fear, panic,
and silence towards the news about cancer. The stigma looming large over the narrative of cancer prevented Cha Mi Jo
from informing Young, the patient, of her diagnosis. This can
also be viewed as a classic response similar to many other cases
of cancer where the continued stigma and immediate association with death prevents the informer from conveying the
message immediately to the patient or to those closely associated with the patient. Such instances not only expose the
silence engulfing an illness like cancer but also the fear that
prevents the possibility of a reprieve from the disease. In other
words, such silence adds to the existing fear of the disease that
is deeply stigmatised and, at the same time, well-entrenched
in society. It also shrouds the experiences isolating the patients
in their ordeal of trauma and prevents dialogues that can
facilitate assistance and create a safe environment for the
patients. Therefore, the presence of cancer narratives in pop
culture can help in addressing the taboo surrounding the illness.
The same is proven through the Korean drama narrativised
here as it brings the illness a step closer to reality through the
portrayal of the vulnerability of the patient as the prime
concern. These representations of illness, especially cancer,
within the creative spaces also run the risk of romanticising
the experience of illness, although the presence of such stories
in popular culture also initiates the conversation surrounding
illness and its experience. Therefore, the confrontation with
such realities can be viewed as the first step towards healing
from the trauma of the experience of cancer.
Korean dramas and K-pop music occupy a significant place
in the sphere of popular culture, and their influence and impact can be seen in the growing consumption and demand
for the same. These dramas often interweave social issues
within the narratives and address the stigma surrounding
various forms of illness. The drama, It’s Okay to Not Be Okay
(2020), deals with the mental health issues of its female lead
who is rumoured to have an antisocial personality. Another
Economic & Political Weekly
EPW
may 4, 2024
show, Extraordinary Attorney Woo (2022), traces the journey
of a young attorney who is autistic. Such shows address topics
on a humane level, where the mental, physical and emotional
experience of illness are explored beyond just a medical understanding. They present the multiple layers of such experience
and draw attention to the many ways in which illness affects
the lives of the patients and those around them. They help
destigmatise and create a space for conversations about illness
through a creative medium.
Renuka Shyamsundar Belamkar (renuka.belamkar@res.christuniversity.in) and Sankar
Varma (sankarvarma93@yahoo.com) are research scholars at the Department of English
and Cultural Studies, and the Department of Economics, respectively, at Christ (Deemed
to be) University, Bengaluru.
vol lIX no 18
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POSTSCRIPT
CINEMA
Mofussil Modernity and
the Post-romantic
Vision of Love
Pokhar Ke Dunu Paar addresses the underexplored
theme of post-rebellion romance and how it
might be sustained.
Supriy Ranjan
D
waipayan Bhattacharya, a commentator on Indian
politics, captures the difficulties of thinking about
social change in India by characterising Indian politics
and society to be “a messy terrain of myriad contradictions.”
It is messy because the social totality that encompasses Indian
politics is mired with multiple contradictions. Social transformation in the wake of economic liberalisation has further
exacerbated schisms along the lines of geographies, gender,
economic might, caste, migration, and political ideologies.
Capturing this changing complex totality makes understanding India both interesting and acutely challenging at the
same time.
It is against the backdrop of this challenge that one could
place the world of Parth Saurabh’s Pokhar Ke Dunu Paar
(2022). Pokhar is the third film to have come out of what is
informally being called the “Darbhanga New Wave,” and
aptly captures the interpersonal complexities of mofussil modernity. The film is framed like a snippet out of a big
diary and provides a window into the lives of a couple who
had eloped from their hometown, only to come back during
the COVID-19 lockdown. It documents the struggles of Sumit and Priyanka, played brilliantly by Avinash Jha and
Tanya Jha Khan, as they discover the economic shock of the
pandemic, which now threatens to tear the idealism that had
fired their elopement. Sumit is an entitled wastrel who seeks
solace for his indolence in the company of his old friends.
Economic & Political Weekly
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may 4, 2024
vol lIX no 18
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73
POSTSCRIPT
CINEMA
Priyanka who has just finished her school and dreams of
the party office, toxic friendships, and Priyanka’s longing to
going to the University of Delhi for further studies is perennirejoin her family do well to drive home this critique. Two, at
ally perturbed by the taken-for-granted attitude of Sumit.
the heart of Pokhar lies a vehement critique of the romantic
Indian film-makers have generally plotted love in the trope
theory of love. Since the advent of romanticism in the 18th
of “rebellious romance,” given the centrality of monogamous
century, our notions of love have entirely been shaped by the
marriage and caste patriarchy in India. The idea of the
core concerns of this body of thought. As the philosopher
“chosen one” sits at the heart of their concern. Mainstream
Alain de Botton points out, the belief that once we meet our
Hindi cinema, more specifically, has been predestined “soul mate,” all our sorrows, issues of
At the heart of
occupied with portraying struggles of finding,
loneliness, carnal desires, and material hardships
Pokhar lies a
confessing, and accomplishing love in the face of
will be over has been a recipe for emotional disaster.
vehement critique
societal hardships. The theme of sustaining roWe fail to recognise the inherent imperfectability
of the romantic
mance, once the revolt is over and there is “no enand emotional fragility of human characters. We
theory of love
emy” to fight, has remained relatively marginal. In
fail to understand that we will not find everythe film, Priyanka pleads with her father to accept their
thing in one person. Counter-intuitively, Botton suggests: to
union. Sumit longs for the carefree time that he has lost. The
truly love someone, one needs to get over the nostalgia that
portrayal of the post-rebellion romance is something that has
gets us into a relationship in the first place. In the film, this is
remained an underexplored thematic of mainstream Indian
exemplified in Sumit’s constant harking back to his tales of rocinema, which Pokhar attends to.
mantic heroism, which blurs his vision to grapple with the
One of the aspects that sets apart the Darbhanga wave of
practical concerns of sustaining a relationship. A healthy and
film-making has been to show the limitations of human
post-romantic vision of love can only be sustained if it is muagency in the face of structural barriers that are thrown in
tually educative. Curiously enough, constant references to
the wake of economic transformation. This invariably transeducation remain an unrealised subtext in the film.
lates into the dislocation of the protagonist from human to
Gamak Ghar inaugurated the Darbhanga New Wave by
non-human actors—say, a house in Gamak Ghar (2019), the
documenting the traumatic impact of rapid urbanisation
lack of economic mobility in a small town in Dhuin (2022), or
and migration on the village-based joint family structure
masculinity in the wake of economic hardship in Pokhar. The
and its resultant nuclearisation. By bringing to the fore the
result of this is that films of this cinematic wave are able to
contradictions that now threaten the visions of the romantic
elevate themselves from being fictional narratives to being
nuclear family itself, Pokhar Ke Dunu Paar seems to have
musings on the existential crises thrown up by social change.
come full circle.
Cinematic devices such as choosing a certain aspect ratio,
Supriy Ranjan (ranjan.supriy@gmail.com) is a visiting faculty at the National Law School
long cuts, colour palettes and metaphors of buildings, transof India University and a PhD candidate at the Centre for Political Studies, Jawaharlal
portation, and trains further reinforce this.
Nehru University, New Delhi.
Modernity makes a sharp distinction between associational and ascriptive forms of relationships and subscribes
LAST LINES
that modern individualism and its due freedom can flourish
only when it is foundationally anchored in the norms of reciprocity in civil society. Traditional forms of relationships
such as family, caste, kinship, and religion are identified as
the biggest enemies that suffocate the individual. Bollywood’s portrayals of romance have done their best to establish this normative vision where the villain is often the
father, the caste headmen, or the religious community.
In contrast, the framing of Pokhar is bereft of any such
element. The protagonists are without surnames, often a
marker of ascriptive identity in India. In its place, there is an
abundance of various forms of associational relationships—
friendships, partnership networks (which Sumit constantly
talks about), and even a political party (the couple lives in
a party office).
By consciously emplotting Pokhar in this unusual manner,
the film makes two larger points. One, a modernist framing
of freedom and civic life is not without its pitfalls. This is
especially so in a context where the material foundations of
associational life are not secured. The dilapidated state of
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vol lIX no 18
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