Effects of “Export Promotion” and “Import Substitution” on Poverty, Inequality and
Growth in India: An analysis in "closed loop" Input-Output framework
DEBDAS BANDYOPADHYAY
DEPARTMENT OF STATISTICS
UNIVERSITY OF KALYANI
KALYANI 741235
WEST BENGAL
INDIA
Effects of Export Promotion and Import Substitution on Poverty, Inequality and
Growth in India: An analysis in "closed loop" Input-Output framework
DEBDAS BANDYOPADHYAY
DEPARTMENT OF STATISTICS
UNIVERSITY OF KALYANI
KALYANI 741235
WEST BENGAL
INDIA
1.Introduction
Choice between export promotion and import substitution
as two competing strategies of economic development has been subject matter
of discussion among policy makers. For a developing country, this choice is
crucial as each of them affect i)foreign exchange reserve, considered to be
one of the most important factors limiting growth, and ii)income distribution and poverty through their influence on the level and structure of output and prices. It is often suggested that for developing countries promotion of labour intensive manufacturing exports is a good strategy for reducing poverty1. Import substitution, on the other hand, is generally discouraged on the ground that most of substitution has been capital intensive
in nature and contributed relatively little towards reducing poverty and
income inequality. It has also been argued that, scope of import substitution being rather limited in agriculture where most of the poor earn their
income, capital intensive import substitution will worsen the relative position of the poor in the economy. It has been emphasised that countries
pursuing industrialisation through import substitution policy may have unfavourable impact on distribution of income distribution and poverty2.
Comparison between export promotion and import substitution strategies of development should ideally be done in a framework
that captures interrelationships among income distribution, poverty and
growth. Foreign trade affects growth and income distribution through their
impact on level and structure of output and prices. Income distribution
affects poverty and growth of an economy because import content of the
consumption goods of the poor being less than that of the rich, any redi1
For example, Ranis (1973), with reference to experience in Far- East countries, calls it a conventional wisdom
to export labour intensive manufacturing goods for reducing unemployment and poverty in labour surplus
developing countries.
2
See, for example, Krueger(1970), Kervis(1973) etc.
3
stribution in favour of the poor will ease foreign exchange constraint of
the economy and enhance growth. A number of studies estimate the effects of
income redistribution on poverty, growth and other macroeconomic variables
using a framework that captures one-way dependence of growth and poverty on
income redistribution (see, Pyatt(1972),Paukert, Skolka and Maton(1974),
Sinha et al(1979),Mohammed (1981)etc among others.)3. In this framework it
is assumed that hypothetical redistribution of household income neither
affects nor affected by distribution of personal income within each industry4. Consequently, the alternative level and structure of output leaves
the overall inequality in household income distribution unaltered although
it changes the level of average income in different fractile groups of households. This is mainly because household income distribution in this methodology is not derived from personal income generated within each industry.
These studies also ignore important factors like prices, inequality in wage
structure, food grain output constraints etc. that have profound effects on
income distribution, poverty and growth of a developing economy like India5.
In this paper we estimate and compare, for Indian economy,
the effects of export promotion and import substitution strategies of
economic development on poverty, income inequality, growth and other important macroeconomic variables using a model that captures two-way dependence
between
growth and income distribution. The model focuses on i) differ-
ential access to employment due to difference in skill characteristics
tics among socio-economic groups and resultant inequality in wage earning,
ii) different rules of price and output determination in food grain and
non-food grain sectors arising out of their different supply conditions6 and
iii) differential consumption and savings behaviour across income groups in
the economy. Moreover, the model endogenously determines the "poverty group" and their level and share of income as a function of level and structure of output and prices given the distribution of income between wage
3
Mohammed (1981), however, surpassed the scope of this model by using it for studying the impact of foreign
trade on income distribution. Thus although he assumes that "trade by bringing about higher level of employment
may reduce income inequality" (Mohammed (1981), pp132) , income distribution parameters are kept fixed
under alternative export-promotion and import substitution schemes. Export promotion and import substitution
strategies may, however, increase income inequality as shown in this paper.
4
A certain mapping between implicit personal income distribution and exogenous household distribution of
income under alternative hypothetical redistribution is assumed to exist, although it is not specified.
5
Tendulkar(1971) , the first “closed loop” model for Indian economy , considered both wage and non-wage
income while closing the model with respect to consumption . He, however, did not consider distribution of
wage earning as the paper was not concerned with redistributive exercises.
6
This basic dichotomy in output and price behaviour in underdeveloped countries is clearly spelt out in Robinson
and Eatwell(1974,pp145-157). Its empirical justification for Indian economy can be found in Chakrabarty(1970),
Maity(1975) among others.,
4
and profit and distribution of wage earning. These factors, which have important bearing on the level and share of income of the poor, have not been
formally combined together, to the best of our knowledge, in a model for
analysing and comparing the effects of ‘inward’ and ‘outward’ looking
foreign trade policies on income distribution, poverty, and growth of Indian economy.
Structural specification of the model is given in section 2.
Section 3 describes the database of the study. Empirical results obtained
by simulating the model with different export promotion and import substitution polices are analysed in section 4. Major conclusions emerging from
the study and limitations of the model used are listed in the final section.
2.The Model
The primary objective of the model is to consider the interdependence of output, price and income distribution in an economy for determining poverty, inequality and growth in a segmented economy. This interdependence can be best examined by segmenting the economy in to a number of
productive sectors and the population into a number of socio-economic groups.
Economy has a number of productive sectors of which the first sector, called food grain sector, uses Cobb-Douglas type production function while the production in rest of the sectors, called non-food grain
sectors, are characterised by Leontief technology. These sectors, which are
interdependent and differ in supply conditions, play an important role in
determining the prices and output economy. We assume that, in the ‘short
run’, food grain output is supply constrained and there are excess capacities in non-food grain sectors of the economy.
Population is divided in two groups viz. "poor" or "target
group" and "non-poor" or "non-target group"7. The two socio-economic groups
are linked with different productive sectors through income and consumption. The target group is linked with productive sectors through employment" and their income consists of only "wage" income8. The non-target group,
on the other hand, is linked with productive sectors via employment as well
7
Throughout the paper we shall use the terms ‘poor’ and ‘target group’ interchangeably.
5
as ownership of assets. Thus income of non-target group consists of wage
and profit income. These groups are also implicitly linked with each other
through commodity trade. Change in the level and pattern of consumption of
one group will change the level and share of income of the other group via
its impact on the level and structure of output and prices of the economy.
Impact of trade policies on poverty and other economic variables in our
model are transmitted mainly through these linkages. Given this segmentation of the economy and its linkages, the model determines level and share
of income of the poor, the level and structure of output, prices and growth
of the economy. Model Equations are grouped into a number of blocks viz.
Income Distribution and Poverty, Output and Employment, Prices, Private
Consumption, Import, and Investment and Growth. Unknown variables in a
Block are solved taking variables determined in other Blocks as given. The
model equations, given in Table-1, form a system of interdependent parts,
each part dealing with a particular aspect of the overall problem9.
2.1.1 Income Distribution and Poverty
Poverty group consist of households with per capita income
is less than or equal to the minimum per capita income (k0) required to meet
the poverty line aggregate consumption10. We assume poverty group households i) earn their income only through employment either as hired labour or
as self employed ii) have a common dependency ratio (db ) which is a constant (z* ) multiple of the overall dependency ratio of the economy11 and iii)
net savings
of the poverty group is zero. Under these assumptions, minimum
per capita income, k0 ,is the cost of poverty line consumption times the
dependency ratio of the poverty group (see eq.1 in Table-1). Given the sectoral output and price (determined in the next section), aggregate income
of the poor(Yb), determined from distribution of sectoral employment (Li)
over different wage classes as given by wage distribution matrix (eik),is
the total wage income up to k0 (eq.2). Number of persons in the target group
is equal to the target group employment (i.e. total employment up to wage
class ko) times dependency ratio (db). Poverty ratio () and per capita inc-
The employment for the “poor’ include employment both as hired labour and self-employment.
Correspondingly the term "wage" include contractual wage payment as well as earning from self -employment.
9
A schematic presentation of the working of the model is given in Fig.1.
10
This income definition only ensures the ability of the poor to buy the poverty line aggregate consumption but
may not guarantee poverty line normative consumption. For one possible treatment of the problem see Panda(
1992).
11
Over all dependency ratio of the economy has been defined as the number of persons , including the earner ,
per earning member of a household and is equal to total population (P *) divided by total employment (Li ).
8
6
Model Equations
Income Distribution and
(1)
k  d . p .
0
b
cb
(3)
Y
d
b
b
Investment and Growth
0
k0
n
( 2)
poverty :
( 22)
  eik. Li . wk
n
z*.( P*. /  Li)

U
j


( 23)
/(  . P*)
( 24)
I
i

j

 1} /

(5)
y
y
( 6)
y   e .L .w  y
b
n
a
s
i 1 k 
y
k
1
0

j
, j  1,2  n
25)
 xi 
 (x
, i  1,2,3,.......n
j
x ) , i  1,2,3,.....n
R  {v jc / v 0jc} , j  1 , 2 , 3 n
R
  v /v 
i

i
0
i
j
f
0
26)
j
j
j
Employment
 D. p
(a b) / c
1
n
w
a / c
1
.p
b / c
f
x  a .x  C  I
(9)
ij
j 1
a
Output and
1
k
 (1  t d ). y /(1   ). P*
a
x
i
ik
n
 b .U
i 1 k 1
(8)
j
i 1
(4)   d b .( eik. Li . wk ) / P*
(7 )
 .v

j
j
k0
n
b
j
j
 . v {(1 R j)
i 1 k 1
1
d
ij
j 1
j
i
 . xi  G i 
*
i
E M
, i  2,3, n
*
i
i
L  a .x . p / w
L   . x , i  2,3, n
(10)
1
(11)
1
i
i
1
1
i
Pr ice
(12)
(13)
(14)
(15)
p . x ( p , p , w )  x ( p , p )  0
p  (1   ).(1  t ).( m  l ) , j  2,3,...n
1s
1
1
j
m
l
j
1
f
j
j
n
j
n
j
n
d
ij
i 1
i
i
s
a . e . w

1
 a . p .(1  t )   a p

j
1d
j
jk
k 1
kj
i 1
m
ij
mi
(1  t mi)
, j  2,3,.....n
j  2,3,.......n
Demand :
Consumption :
(16)
(17)
(18)
(19)
( 20)
C  y /P
C  (1  s ) y / P
P  .P
P  (1   ). P
1
1
b
2
h
1
*
2
C
i
2
a
*
[
2
 P {a . p
m
m
i
m 1
m
i
n
 bi .(C   a j .
m
m
j 1
p
j
)}] ,
i  1,2,3...n
Im port
21)
M
i

n
a .x
j 1
m
ij
j
 hi (C i 
I
 Gi )
*
i
, i  1,2,3,....n
Dependency ratio of the poverty group is then a constant (z*) multiple of over all dependency ratio of the
economy. ( see eq.3).
7
Table-2
Notations
(Superscript ‘0’ refer to base year, superscript ‘m’ to population group ‘m’ and subscript ‘i’ to sector ‘i’)
A. Endogenous Variables
Percentage of poor
PCE for population group ‘m’
Agg. Private Consumption for sector ‘i’
Dependency ratio
Investment by sector of origin
Normative wage rate
Sector ‘i’ employment
Sector ‘i’ unit labour cost
Producer’s price for sector ‘i’ output
Size of population group ‘m’
CPI for poor
Unit material cost for sector ‘i’
Capacity growth rate of value added
Aggregate value-added growth rate
Investment by destination
Value-added for sector ‘i’
Sector ‘i’ output
Market supply of sector ‘1’ output
Change –in- stock
Aggregate income of the non-poor
Aggregate income of the poor
Per capita income of the non-poor
Per capita income for the poor yb
B. Parameters
Domestic and imported input coefficients aijd , aijm
Capital coefficient
bij
Parameters of LES for population mth gr. aim , bim
Parameters of agricultural production fn.
D,b,c
(i,k)th element of emp. distribution
e ik
Labour-output ratio for sector 'i'
i
Average import content of domestic demand hi
Li
Stock-flow conversion factor for sector ‘i’
i
li
pi
Sector 'i' investment fn. parameters
i , i i , i
P m Savings rate for the non-poor
sh
p m Direct tax rate
td
mi Indirect tax rate
ti
R i Mark-up for sector 'i'
i
R Import duty
tmi
Ui
Average wage rate in kth wage class
wk
Vi
Average wage rate in sector 'i'
wi
xi
Market demand sector ‘1’( base yr. price) x1d
x is
C. Exogenous Variables
x Export of sector ‘i’ output
Ei *
ya
Government consumption of sector ‘i’
Ci *
yb Population
P*
ya

cm
Ci
db
Ii
k0
ome of the poor (Yb ) are then determined in eqns.4&5. Aggregate income of
the non-target group (Ya) consists of wage income above k0 and profit income
(Yf) from which their per capita income (Ya) is determined eqs.6& 7).
2.1.2 Output, Price and Employment
Food grain output is determined from farmers' supply response
function taken as a function of food grain price(p1),average wage rate in
food grain sector (w1),and fertiliser price (pf)(eq.8)12. Its price is market
clearing type and is determined from eq.12 such that excess supply in the
food grain market (right hand expression of eqn.12) is zero. Non-food grain
sectors’ output are demand determined and obtained from input- output material balance equation (eqn.9) and their prices are determined by Kaleckian
type mark up pricing rule (eqn.13). Unit material cost(mj) and wage cost
12
Food grain supply response function depends upon many other variables. We, however, ignore such variables
and absorb their effects via the constant ‘D’. Further, fertiliser price, pf , in the supply response function is
obtained by applying indirect tax rate on the producers’ price as determined in the eq.13.
8
SCHEMATIC DIAGRAM OF THE WORKING OF THE MODEL
Wage rate &
WDM
PL
Income of poor & non-poor
% of people below PL
Domestic & Imported
Input-Output coeffs.
Supply Response Fn.
for AG
Output for AG
Sectoral
labor coeffs.
oe
Mkt supply
for AG
Prices of NAG
( I-O Model )
Sectoral mark up &
tax rates
Wage rate
& WDM
Sectoral private cons.
Prices for
AG
Pvt. cons. demand
for AG
LES
parameters
Sectoral
prices
Market demand for
AG
Sectoral Exports
Changein -stock
Imports
Output of
NAG
( I-O Model )
Sectoral gross Inv.
Sectoral Govt.
cons.
Sectoral Output
Output of AG
Sectoral Inv Functions
Fig.-1
Endogenous
Exogenous
AG : Agricultural goods, NAG : Non-agricultural goods, WDM : wage distribution matrix ,PL:
Poverty line
(lj) are blown up by mark up rate (j )and indirect tax rate(tj) to get the
sect-oral market price (eq.13)13. Material unit cost consists of domestic
and imported material input cost while wage cost depends upon labour coefficient(j) and distribution of sectoral employment over different wage classes (eqns.14&15). Employment in food grain sector is determined by factor
demand equation obtained from the first order condition of constrained profit maximisation problem in agriculture (eqn.10.). Employment in non-food
grain sectors are obtained by applying labour output ratio to sectoral output (eq.11).
13
Market supply for food grain, x1s (=x1 (p1, pf, w1) - a11.x1 ), is defined as food grain output net of food grain
inputs. Food grain producers own consumption are bought from market.
9
2.1.3 Demand
Demand for private consumption, investment, change-in-stock
and importare endogenously determined while Government consumption and exports are exogenous. Per Capita Consumption Expenditure (PCE) for the two
groups of population, C1 and C2, are determined from their respective per
capita income, Yb and Ya(eqns.16&17). Sectoral breakdown of PCE for the two
groups of population obtained through LES for the respective groups are
combined to arrive at private consumption vector for the entire population
(eqs. 18,19&20). Finally imports for intermediate and final use are determined in eq.21 using input-output import coefficient matrix (amij) and import coefficient of final demand hj. Investment and change-in-stock are related to output in eqns.22, 23 and 24. Investment requirement by sector of
destination (Uj), consists of replacement investment, net fixed investment
and an intercept term. Replacement investment is taken as a fixed proportion of sectoral value-added. Net investment is obtained through multisectoral version of accelerator principle (eq.21). If j is the investmentoutput gestation lag in sector j then net investment in sector 'j' is a
function of increase in value-added during gestation period. Assuming uniform distribution of investment over gestation period, net investment in
sector j is given by the last term of eq.21 where j is incremental capital
value-added ratio and Rj is the post base year value-added growth rate (eqn.
25). Thus sectoral investment in our model is demand driven. Investment by
origin for sector ‘i’ is determined from using capital coefficient matrix
(bij) (eq.22). Change-in-stock is obtained by applying stock-flow conversion
factor to output change (eqn.24). Finally aggregate growth rate is determined by eqn.25.
3.Data Base
The model is applied to twenty two sector Indian economy for
the year 1996-97(referred as Base Year)14. Operation of the model requires
point estimates of different technological, behavioural and policy parameers. Estimates of the parameters relating to consumption and investment functions, coefficients relating to material and labour inputs, imports, change in stock and the sectoral tax rates are taken from Eighth Plan Technical Note, Planning Commission(1995),Government of India (hereafter referred
10
as Tech. Note). Estimates of sectoral mark-up rates and policy parameters
like direct tax rate, household savings rate and corporate tax rate are taken from relevant issues of National Accounts Statistics and Annual Survey
of Industries, Government of India. All India poverty line (0) has been estimated from the estimates of rural and urban poverty line as given in Tech. Note under the assumption of lognormality of all India PCE (See Appendix A)15.
Initial estimate of sectoral employment distribution matrix,
taken from Labour Bureau (1973), National Council of Applied Economic Research (1975) and Roy (1979), is first corrected for changes in CPI for agricultural and industrial workers during intervening period and then made consistent to base year i)Mean monthly private consumption of people below
poverty line and their percentage and ii) sectoral total wage by an iterative method16
Estimates of parameters of food grain supply response function are taken from Kawagoe et al.(1985)(estimate 4). Intercept term(D) of
the supply function is so determined that food grain output obtained from
this function is same as that of the base year.
The point estimates are made consistent to base year structure of the economy so that given these point estimates and the exogenous
variables the model reproduces the observed base year structure the economy17. Base year values of the variables as reproduced by the model, referred as Basic Solution, are taken as historically given benchmark values
with which the changes under different policy scenarios are compared18.
Selected macroeconomic indicators under Basic Solution are presented in
Table-3
4. Empirical Analysis
Effects of foreign trade policies on poverty, inequality and other
macroeconomic variables may be studied by analyzing the quantitative impact
14
See Appendix for mapping of Tech. Note sector classification into our classification.
All India Poverty Line estimated is Rs .201 at 1996-97 prices.
16
See, Bandyopadhyay(1986) ,for details.
17
Different problems arise in the construction of consistent data base of an economy. See Taylor (1985),
Bandyopadhyay (1986) for details.
18
Units of goods are so chosen that sectoral prices are unity at the base year when the economy is assumed to be
at equilibrium. Also to maintain scale comparability, estimated changes under different policy scenario over the
Basic Solution are expressed per Rs. one million.
15
11
of volume and structure of different export promotion and import substitution schemes. In our model any change in volume and structure of export
and import disturbs the base year equilibrium of the economy and sets on a
chain reaction operating through changes in output, price, income distribution and poverty in the economy. The equilibrium is restored when aggregate savings equates with aggregate investment through changes in output,
prices income distribution, and poverty19.
Table-3
Selected Macroeconomic Indicators for Indian Economy, 1996-97
as reproduced by the Model+
Economic Indicator
Estimate Economic Indicator
1.
2.
3.
4.
5.
6.
7.
8.
9.
579087
494345
95096
159169
102287
112641
21.03
22.09
4.40
GDP
Private Consumption
Government Consumption@
Gross Investment
Export@
Import
Savings Rate(%)
Investment Rate (%)
Aggregate Growth
(Post 1996-97)
10. Per capita Income*
a) Poor
b) Non-poor
159.20
553.40
11.Per capita Cons8.
a) Poor
b) Non-poor
12. Poverty
a)Ratio(%)
b)Sen’s Index
13. Inequality(L.R.)
a) Income
b) Consumption
c) Wage
14.Dependency Ratio
a)Target Group
b) Overall
Estimate
159.29
482.15
26.34
15.24
0.259
0.225
0.347
4.13
4.89
@ Exogenous + Rs. Crores at 1991-92 prices * Rs. at 1991-92 prices
4.1 Effects of changes in level and structure of export.
Effects of volume and structure of exports are studied under
six alternatives as described in Table-4. While the first two alternatives
study the impact of change in volume of export in absence and presence of
food grain supply constraints in the economy the rest mainly analyze impact
of changes in structure of exports20. Macroeconomic impact of alternative
volume and structure of exports are given in Table-5. It is found that 10
percent increase in volume of exports, keeping the structure same as in the
19
Schematic diagram showing working of the model and an iterative procedure for its solution are given in the
Appendix..
20
For this we have divided the exporting sectors into two groups viz. traditional exports consisting of sectors like
agricultural food products, mining and textiles and non-traditional exports consisting of manufacturing sectors.
Their impacts are studied both in presence and absence of constraints in the food grain sector of the economy.
12
base year, increases private consumption, employment and growth respectively by 1.28, 1.32 and 1.40 percent when there is no food grain output constraint in the economy. However, in presence of food grain output constraint,
this favorable impact of increase in exports is much reduced as can be seen
from the results under alternatives 1 and 2. Increase in volume of ex-ports
also pushes up aggregate savings rate of by 1.30 per cent and pushes down
the rate of foreign savings by 2.00 per cent.
Table 4: Description of Alternative Export Promotion Schemes.
Case No.
1.
2.
3.
4.
5.
6.
Description of alternative cases.
Base year exports increased by 10 percent.
Case No.1 with food grain output fixed at
Basic Solution level.
10 per cent increase in traditional exports
Case No.3 with agricultural output fixed at
Basic Solution level.
10 percent increase in non-traditional exports.
Case 5 with food grain output fixed at Basic
solution level.
Analysis of impact of pattern of export, considered under
alternatives 3,4,5 and 6, show that export promotion of traditional sectors
have more favorable impact on private consumption, employment and growth
than that of non-traditional exports. This is because an increase in traditional export(Case no. 3)increase, consumption and growth by
0.49, 0.28
and 0.54 percents respectively. The corresponding increase non-traditional
exports are 0.32, 0.20 and 0.49 percents respectively. Moreover, it is seen
that increase in traditional export in presence of food grain output constraint has more detrimental effect on the economy than that of non-traditional export.
Effects of increase in volume and pattern of export on economic
condition of poor and non-poor are given in Table-6. Results show that
monthly per capita income and consumption of both poor and non-poor increases due to increase in volume of export but increase for the non-poor is
much higher than that of the poor. Thus we see that 10 percent increase in
export results in 1.55 per cent increase in income of the non-poor, the co-
13
rresponding increase for the poor being 1.00 per cent. (see case 1.). Moreover, even this positive impact on poor vanishes and the income of the poor
falls by 34 per cent in presence of food grain output constraint in the economy (see case 2.). This is because export promotion in presence of output
constraint causes demand pull increase in food grain prices which, in turn
results in overall price rise in the economy hurting the poor. Economic position of the non-poor, however, slightly improves (income of the non-poor
increases by 1.72 per cent) as a part of profit due to price rise accrues
Table 5: Change in Macroeconomic aggregates under
alternative Export Promotion Schemes21.
Case
No.
1.
2.
3.
4.
5
6.
Agg.
Growth
101.43
101.03
100.54
100.34
100.49
100.44
Private
Cons.
101.28
100.99
100.49
100.11
100.32
100.26
Employment
101.32
100.95
100.28
100.18
100.20
100.16
Savings
Ratio
Import
CPI
101.31
100.89
100.56
100.28
100.50
100.42
101.64
101.03
100.72
100.68
100.97
100.94
101.04
101.93
100.97
100.32
100.01
101.63
to the non-poor. Consequently, distribution of real income shifts against
the poor.22
Analysis of impact of pattern of export reveals that favor-able impact of
increase in traditional export is more than that of non- traditional export. Comparison of alternatives 3 and 5 show that 10 per cent increase in
traditional export increases the income of the poor and non poor by 0.25
and .06 per cent respectively. Comparison of alternatives 4 and 6, however,
show that expansion of traditional export in face of food grain output constraint hurts the poor more than the non-poor. Percentage of ‘poor’ and
Sen’s index of poverty decline as a result of export promotion, provided
there is no food grain output constraint in the economy (see Table-6). Thus
10 percent increase in volume of export reduces the percentage of poor by
1.21 percent and Sen’s index by 0.71 percent. However if there is food grain output constraint in the economy both the percentage of poor and Sen’s
index increase by 1.47 percent and 0.92 percent respectively due to 10.0
percent in volume of exports. Further, it may be seen that expansion of traditional export has more favorable impact on poverty than that of the nontraditional export. This is mainly because traditional exports originate
21
22
Expressed as percentage change, per Rs. million , over the Basic Solution level.
Note that increase in CPI for poor under case 3. is 1.14 per cent and the same for the non-poor is 1.08 per cent.
14
from such sectors which are more labor intensive and whose share of income
among poor than the industries from which non-traditional exports originate. However expansion of both traditional and non- traditional export
increase poverty in presence of food grain output constraint. Results on
impact of inequality due to increase in volume and changes in pattern of
export show export promotion accentuates income inequality. Thus we see
that 10 percent increase in export results in 0.92 and 0.57 percent of
income and consumption inequality. Further it is seen that inequality
Table 6: Change in Economic Profile of Target and Non-Target Group under
Alternative Export Promotion Schemes
Case
No.
1)
2)
3)
4)
5)
6)
Per capita income
Poor
Non-poor
100.95
100.12
100.25
99.70
100.06
99.91
101.55
101.72
100.85
101.22
100.98
100.15
Poverty Index
H. C.
Sen’s
98.79
99.01
99.01
101.34
99.24
99.88
99.29
100.01
99.68
100.40
99.75
100.32
Inequality(L.R)
Income Consumption
100.92
102.73
101.65
100.32
100.19
100.25
100.57
102.56
100.17
100.13
100.18
100.18
accentuating effect of non traditional export is more than that of traditional export.
4.2: Effects of changes in volume and structure of Import
Substitution.
In order to study the effect of import substitution we consider import
substitution in both intermediate as well as final use. Further, to compare
how structure of import substitution affect poverty, income inequality and
growth we consider the major import using sectors viz. petroleum, metal
products, machine tools and fertiliser industries. Different import
substitution schemes considered for analysis are given in Table-7.
Macroeconomic impacts of alternative import substitution schemes are given in Table-8. It is seen that 10 percent import substitution
in all sectors (Case no.1) increase consumption, employment and growth by
0.84, 0.94 and 0.98 percent respectively. Aggregate import requirement fall
by 4.76 percent whereas aggregate savings rate increase by 2.67 percent.
Thus we see that import substitution, in general, have favorable impact on
consumption, employment and growth, but this positive impact is much less
15
than that of corresponding increase in export. Comparison of results under
Cases 1 and 2, however, show presence of food grain output constraint in
the economy further reduces this positive impact. Comparison of results under Cases 4,5,6show varying macro economic impact of sectoral import substitution. Thus it is seen that import substitution in Petroleum sector has
maximum positive impact on consumption, employment and growth than the corresponding level of import substitution in other sectors of the economy.
Table 7: Description of Alternative Import Substitution Schemes.
Case No.
1.
2.
3.
4.
5.
6.
Description of Alternative Cases.
10 percent import substitution
Sectors.
Case 1 with output of sector 1
Solution level
10 percent import substitution
Sector
10 percent import substitution
in all importing
fixed at Basic
in Machine tools
in Petroleum Sector.
10 percent import substitution in Fertilizer sector
Sector.
10 percent import substitution in Electronics and
Communications.
Economic impact of import substitution, both overall as
well as sect-oral, on the poor and non-poor are presented in Table-9. It is
seen that due to 10 percent import substitution across the sectors, income
of the poor and non-poor increase respectively by 0.32 and 1.00 per cent.
Thus positive impact of import substitution on the income of the poor is
much less (almost one-third) than that of the non-poor. Moreover, comparison of results under Cases 1 and 2 show that the discriminatory effect of
import substitution on income of poor and non-poor increases in presence of
food grain output constraint in the economy. At the sectoral level, it is
seen that import substitution in Petroleum and communications sector has
comparatively larger positive impact on income of the poor than the other
sectors of the economy. This favourable impact of import substitution is,
however, much less than that of export promotion. Further, it may be seen
import substitution reduces poverty provided there is no food grain output
constraint in the economy. Finally, it is interesting to note that increase
in inequality due to import substitution is more than that of export promotion.
16
4.7 Growth-equity trade-off under “export promotion” and
“ Import substitution”: A Comparison
In recent years there have been a number of studies on the
link between poverty, inequality and growth23. Kuznets(1955) was first to
observe from cross country data that process of development has a tendency
to be accompanied by increase in inequality which was subsequently confirmed by Oshima(1962),Adelman and Morris(1973),Adelman(1974),Chenery and Syrquinn(1975) etc.
Recent empirical evidences, however, are far from unamb-
iguous24. In this section we compare “export promotion” and “import substitution” strategies of development in terms of growth-equity trade-off exhibited by them25.
Table 8: Change in Macroeconomic aggregates under
alternative Import substitution Schemes.
Case
No.
Agg.
growth
Private
Cons.
Employment
1.
2.
3.
4.
5.
6.
100.98
100.36
100.14
100.85
100.44
100.61
100.84
100.20
100.12
100.69
100.35
100.10
100.94
100.29
100.20
100.97
100.46
100.16
Savings
Ratio
102.76
102.98
100.79
101.31
100.89
100.82
Import
95.24
90.61
99.74
100.68
100.97
101.82
CPI
101.24
101.78
100.92
100.92
100.01
100.36
Following Ahluwalia(1974), we combine per capita consumption
level of poor and non-poor in to a single utility index using semilogarithmic Social Welfare Function. Per Capita Utility (PCU) under different “export promotion” and “import substitution” schemes and their percent change
over Basic Solution PCU, calculated under ‘equal weight’ and ‘poverty weight’ social welfare function, are given in Table- 1026.
It is seen that bo-
th “export promotion” and “import substitution’ show moderate growth-equity
trade–off under ‘equal weight’ SWF, its magnitude being lees for “export
promotion” than “import substitution”. However, under ‘poverty weight’ SWF,
magnitude of this trade-off is substantial for both strategies. It is also
23
See, Tendulkar and Jain(1955) , Deininger and Square(2000) among others.
For example, Mohammed(1981), Tendulkar and Jain(1995) and Deininger and Square(2000) found little
support for the so called “Kuznets hypothesis”.
25
A policy is said to exhibit unambiguous growth-equity trade-off if a positive growth effect of the policy is
accompanied with a decline in Per Capita Utility ( PCU) under both “equal weight” and “poverty weight” SWF
and vice-versa.
26
See Appendix , for details.
24
17
seen that growth-equity trade-off is more for traditional than non-traditional export and it increases when there is food grain output constraint in
the economy.
Table 9: Change in Economic Profile of Target and Non-target Groups
under Alternative Import Substitution Schemes.
Case
No.
1)
2)
3)
4)
5)
6)
Per capita income
Poor
Non poor
100.32
99.96
100.11
100.14
100.13
100.09
100.99
101.19
100.45
100.69
100.57
100.40
Poverty Index
H. C.
Sen’s
99.39
101.21
99.95
99.43
99.68
99.97
99.60
101.86
99.85
100.00
99.80
99.94
Inequality(L.R)
Income Consumption
101.07
101.69
100.16
100.35
100.32
100.48
101.02
101.92
100.15
100.29
100.27
100.34
5. Conclusions and Limitations
The paper estimates and compares the effects of “outward looking”(export promotion) and “inward looking” (import substitution) strategies of economic development on income distribution, poverty and growth
for Indian economy using a model that captures two way dependence between
growth and income distribution. Factors typically found in a developing country like India viz. “fix-flex” mode of output and price determination,
high wage inequality in wage earning and food grain output constraint. Endogenous determination of income distribution, poverty and growth considering the mentioned above factors is the novelty of our model which, to the
best of our knowledge, have so far not been used for analysing Indian trade
policies. Simulation of the model with different “export promotion’ and
‘import substitution” policies show i) export promotion, particularly for
traditional sectors, reduces poverty provided there is no food grain output
constraint in the economy, ii) poverty reducing effect of export promotion
is substantially more than that of import substitution, iii) both export
promotion and import substitution increases inequality, particularly when
there is food grain output constraint in the economy, but inequality accentuating effect of import substitution is
more than that of export prom-
otion and iv) both export promotion and import substitution exhibit growthequity trade-off but its magnitude is substantial and more for import substitution than that of export promotion particularly under the “poverty
weight” SWF. Thus our findings indicate that economic development through
export promotion is more effective than import substitution for “growth
18
with poverty reduction” provided there is no food grain output constraint
in the economy and one is ready to accept social cost due to higher level
of economic inequality.
Before concluding it is, however, necessary to point out some of the
important limitations of our study some of which may have substantial implications for ‘long run’ interpretations of our findings. First use of input output technology in non-agricultural sectors of the economy rules out
substitution possibilities among inputs in response to price changes under
Table-10:Percentage change in Per capita Utility Level
alternative Export Promotion and Import Substitution Schemes27.
Case
No.
Per capita utility (PCU)
(Export Promotion)
Per capita utility (PCU)
(Import Substitution)
Equal Weight Poverty Weight Equal Weight
1)
2)
3)
4)
5)
6)
100.66
100.70
100.45
100.55
100.70
100.72
101.61
101.72
101.05
101.30
102.50
102.78
100.82
100.98
101.36
101.22
101.52
101.62
Poverty Weight
102.50
102.87
101.61
101.32
101.14
101.96
different policy scenario. Secondly use of LES for estimating private consumption demand has well known limitations in capturing demand changes over
a long period. Thirdly endogenous determination of investment on the basis
of accelerator type relation ignores the direct effects of variables like
profit rate, price tax etc on investment28. Fourthly modelling of supply
response on for the food sector as a whole using only three explanatory
variables is restrictive. Finally distributional effects of trade policies
on choice of technology which may have considerable impact on poverty and
growth is not considered in the present study.
Basic Solution PCU level under “equal weight” and “poverty weight” SWF are 1.13 and 2.56 respectively.
In so far as investment in our model is demand driven, indirect effects of these variables on investment are
captured through demand.
27
28
19
APPENDIX
A: Determination of All India Poverty Line.
Let the all India poverty line to be estimated be x. Also let Fr and
Fu be distribution functions of per capita consumption expenditure in rural
and urban India. Then proportion of total expenditure, pj, having per capita
expend-iture xj or less is given by
p
j
 [ Pr . F r ( x j )  Pu . F u ( x j )] /( Pr  Pu ) (1)
where Pr and Pu are rural and urban populations. Now,if Fr and Fu are twopara-meter lognormal distribution functions with parameters (xr ,r) and (xu
,u) then
p
j

p .( y
r
jr
)
p .( y
u
ju
) (2)
where,
y  (1 /  ).  log( x / x )   / 2(3)
y  (1 /  ). log( x / x )   / 2(4)
p  P /( P  P ), p  P /( P  P )(5)
jr
r
ju
u
r
r
j
r
j
r
r
u
u
u
u
u
r
u
and  (.) is standard normal C.D.F. Now, let Qj be the aggregate share of
per capita consumption up to xj for the country as a whole, then
Q
j
x
 [ p . j x.d F r ( x) 
p . x d F ( x)] /( P.x )(6)
 [ p x .( y   )  p . x .( y   )] / P.x  (7)
r
r
j
u
0
r
r
rj
u
0
u
u
ju
u
where x is average per capita consumption expenditure for the country as a
who-le and P is the total population. Now if we assume that all India per
capita consumption expenditure follows two-parameter log normal
distribution with parameters x and  then we know the Lorentz ratio for the
per capita consumpt-ion expenditure is given by
L  2. ( / 2 )  1  (8)
Now L can be estimated from observed distribution of per capita consumption
expenditure and one such formula based upon Simpson’s 1/3rd rule is given by
n
L  1 ( p 
j 1
j
p
).(Q  Q ) (9)
j 1
j
j 1
where n is the number of expenditure class limits considered. Now, an
estimate of L as determined from (9) can be used in (8) to determine 
uniquely. The all India poverty line x can then be determined from the
eqs.(10) and (11).
   ( )  (10)
y  (1 /  ). log( x / x )   / 2 (11)
20
B: SOLUTION PROCEDURE FOR THE MODEL
In order to solve the Model we adopt an iterative procedure which directly follows from the logical structure of the model. We may
note that any change in policy parameter and/or exogenous variable disturbs
the model equilibrium and initiates an adjustment mechanism that works through changes in different endogenous variables in the model. The equilibrium is re established when aggregate savings equals aggregate investment.
The iterative procedure starts with some initial guess values of sectoral
output and prices and consists of the following steps:
i)
Estimate sectoral gross value added and calculate their rates of
growth(Rj )by eqn.26
ii)
Estimate sectoral employment(Li) by eqns.10 for sector 1 and by eqn.11
for i=2,3,...n.
iii)
Estimate per capita income and consumption of the ‘poor’ and ‘nonpoor’ (Yb, Ya ,C1, C2) by eqns. 5,7,16,17 after determining K0 ,db ,yb
and ya by eqns.1,3,4,2 and 6 respectively.
iv)
Estimate sectoral private consumption (Ci ) by eqn.20
v)
Estimate investment by origin ( Ui ) as well as destination(Ii) and
change in stock(Si) by eqns.22,23 and 24
vi)
Estimate terminal year sectoral import(Mi) by eqn.24
vii)
Estimate sectoral output(Xi) by eqns.8 for i=1 (or replace it by
exogenously given output if there is supply constraint) and by eqn.9
for i=2,..n.
viii)
Repeat step i) through vii) until the output vector converges. Then
proceed to step ix).
ix)
Using this output vector estimate sector 1 prices (pj) by eqn.12 and
use it for determining prices for rest of the sectors by eqn.13.
x)
Repeat step ix) till price vector converges.
xi)
Stop iteration when successive levels of output and price vectors differ by less than a given tolerance level.
Simultaneous convergence of output and price vectors ensures
savings-investment identity. This is checked under each policy scenario to
confirm validity of the solution procedure.
C: Welfare Evaluation of Alternative Policies
Welfare evaluation of alternative policies has been done using a social welfare function of semilogarithmic type where utility is written as a function of per capita consumption of the ‘poor’ and ‘non-poor’
(See Ahluwalia(1974)). Thus if Cb and Ca denote per capita consumption of
the ‘poor’ and ‘non-poor’ then social utility function is given by,
U = N1.1
21
log Cb + N2.2 log Ca
where N1 and N2 are the number of the ‘poor’ and the ‘non-poor’ and 1 and
2are weights. Using social utility function defined above we define two
alternative measures of per capita social utility, Ue and Up from a)”equal
weights” and b) “poverty weights” form of social utility function. The
‘equal weights” social utility index can be shown to be a measure of increase in welfare if we assume that the utility function is symmetric. The
“poverty weights” social utility index, on the other hand, provides a measure of welfare improvement when weights are different for different classes. Thus
Ue
= N1.log Cb + N2.log Ca  /N
Up
= N1.1. log Cb + N2.2.log Ca  /N
where N is the total population29.
D: Mapping of Tech. Note Sectors into 22 Sectors
Sector Name
1. Food grain
2. Non-food grain agriculture
3. Allied Agriculture
4. Food Manufacturing
5. Coal and Lignite
6. Crude petroleum and Natural gas
7. Other minerals
8. Textiles
9. Wood and Wood products
10. Paper and Paper Products
11. Leather and Leather products
29
Tech. Note
Sector No..
1 to 4
5 to 11
12 to 14
20 to 23
15
16
17 to 19
24 to 28
29
30
31
Sector Name
12. Rubber and .Plastic products
13. Petroleum and Coal products
14. Chemical Fertilizer
15. Other chemicals
16. Metal & Metal Products
17. Machine & Machine Tools
18. Electronic Equipment
19. Transport Equipment
20. Other Manufacturing
21. Construction & Electricity
22. Services
Tech Note
Sector No.
32,33
34,35
36
37 to 39
42,43
44 to 47
48,49
50 to 52
53
54,55
56 to 60
See Ahluwalia (1974) for method of deriving weights for ‘equal weights‘ and ‘poverty weights’ form of utility indices. In our study
weights are determined in such a way that they yield ‘poverty weights’ 0.6 and 0.4 for the target and non-target groups of population.
22
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