Gender Differences in Labour Force Participation
in India: An Analysis of NSS data
Ferrell Patel 0387946
ECON-3046EL-01
Professor Charles Daviau
Abstract: - The purpose of the article is to research and review the descriptive
statistical analysis of women’s work force participation to the labour force
comparing it to men’s participation work force participation to the labour force as
obtained from the NSS (National Sample Survey) 55th round survey of
Employment and Unemployment and comparing it with NSS 60th round survey.
The article also conducts various econometric estimations from the survey. The
article focuses on the variables that impact for the work participation rate.
The Labour force participation of women is an interesting topic for the labour
market studies. All over the world we can see that there is a participation rate
difference of male and female in the labour force. Generally male participation rate
dominates over the female participation rate in labour force even though generally
female puts in more hours of work which is not included in labour force such as
household work and various other activities.
The Participation rate of female and male in the labour force is further divided into
two which is rural male, rural female and urban male, urban female. The code 93
with Usual principal status is also consider which means that the attended to
domestic duties and was also engaged in free collection of goods (vegetables,
roots, firewood, cattle feed, etc.), sewing, tailoring, weaving, etc. for household
use. The household income is also a variable for change in the work force
participation rate. For males and females from the 55th round of NSS it can be said
that with the rising of mpce (per capita monthly expedite) there is declining in
work force participation rate.
The household income is also a variable for the work participation rate. With the
increase in standard of living of the bottom 80% of the rural and urban population
there is decreasing of work labour participation. However, there is increase in the
work participation rate of the top20% of the female workers in urban population as
they are highly educated and most of the members of family bring in the income
for the household. There is also a clear difference in participation rate of female in
urban and rural areas. In urban areas the work participation rate of female is more
than that of the rural. Education is also a variable in the work for participation rate.
The work participation rate graphs with rural and urban male and females with
education are quite interesting as there are many shifts in the graph. The work
force participation rate for the rural females and male can be seen declining with
the increase of education. But the decreasing of participation rate in female is
much higher than that of male. The difference overall in participation rate for rural
male is around 20% while in rural female is around 35%. But for the urban female
graph we can see that there is a bell-shaped curve first as the education increases
the work force employment rate decreases till secondary education but then for the
urban female having higher education then secondary the work force employment
rate increases. Similarly, it seen in urban male graph have a bell-shaped curve, but
the variation is very negligible. The education has a major impact on female work
participation rate than that of male in both the urban and rural areas.
One of the reasons for such low rates for women labour force participation in India
is also because the women’s paid labour is called upon only when men’s labour is
exhausted as India having large population has an excess supply of labour. Social
factor is also a reason for the low rate for women in labour force participation
Because women, and men, are socialized to look upon reproductive work within
the domestic sphere as the primary responsibility of women, it is expected that for
the average woman, domestic responsibilities take precedence over her insertion
into the labour market. The socialization process here generally starts fairly early
in life to ensure that the young girl is not mentally tuned to, or encouraged to, enter
the labour market productively in preference to her domestic duties. Even if
women are required to be inducted into the market by virtue of increasing
tightening of labour demand brought about by structural economic changes, or
because of the pressing need for augmenting family incomes, by the time that call
comes, the average woman would already have been at a disadvantage, being at the
receiving end of unequal opportunities for acquiring the employment. As the
employer thinking that women have to take the burden of household work and then
come to work, they will prefer to hire male worker then a female worker.
The research paper uses the large survey instrument such as NSS that have
valuable information which is not replicated or can’t be replicated to small surveys
or in surveys that are geared to women activities. the paper uses NSS data to try to
understand how far this body of data can be stretched to analyses some of the
questions that have been plaguing researchers on patterns of female labour force
participation in India. The research paper divides the NSS data into many branches
like literacy (which is further divided into seven grades categories), demographic
variables, Age, Martial status, Household size, regional variables, Per capita
household expenditures and social class.
The research paper has also done some additional activities using the NSS data and
three hypotheses were tested:
1) Controlling for levels of household income along with other social and
demographic variables, the more secure is husband’s income, the lower is the
probability of a women entering the labour force.
2) Controlling for levels of household income and other social and demographic
variables, if the husband is in self-employment, the probability on the wife’s labour
force participation will, be higher.
3) Other things remaining the same, the farther apart the wife is from her husband
in terms of educational qualifications, the lower will be the probability that the
wife will enter the labour force.
Earnings Functions were estimated separately for male and female both in rural
and urban areas for only those members of the labour force for whom earnings data
were available. These included regular wage and salary earners and casual
workers. The basic earnings function for both sexes were specified as logarithm of
wages per day as a function of age, age squared, various levels of education of the
worker and a constant term. The basic equation is as follows:
Ln(w) = a + ß(1) (age) +ß (age*2) + ß(3) (edu) + €
(1)
Initially this equation was estimated separately only for the subsets of male and
female workers in the labour market for whom NSS supplies information on
earnings. The results are summarized below:
Rural:
Difference between Estimated male and female wages = 0.5729
= 0.2271(Characteristic Effect) + 0.3458 (Discrimination Effect)
= 39.6 % + 60.4 %
Urban:
Difference between estimated male and female wages=0.3669
=0.047692(Characteristic Effect) + 0.319268(Discrimination Effect)
= 12.99 % + 87.01 %
It can be seen from the equation that the estimate of gender based ‘discrimination’
turns out to be very high in both rural and urban areas, over 60 % in rural and over
87 % in urban areas.
Conclusion: - The Employment Unemployment data collected by NSS have many
criticisms as many people have argued that the instrument used to measure the data
is inadequate for capturing kind of work majority of women does in the informal
sector and as unpaid family labour and other such work.
The other problem with the NSS data used in this paper is the paucity, and clear
absence for men and women information on earnings. Without this information
there is no sensible economic analysis of demand and supply behavior.