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CONVERGENCE AMONG THE STATES OF INDIA IN THE TIME PERIOD FROM
1980 TO 1999
A THESIS PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF ARTS
UNIVERSITY OF FLORIDA
TABLE OF CONTENTS
L IS T O F T A B L E S ........ ............ .. .. ...... .. ...................................................... iii
ABSTRACT ............... ................... ......... .............. iv
1 IN TR OD U CTION ............................................... .. ......................... ..
L iteratu re R ev iew ................................................................ 1
E conom ic B ackground........... ............................................................... ....... .... .... 5
2 THEORETICAL PASSAGE ......................................................... .............. 10
3 T E ST O F H Y P O T H E SIS ................................................................ ..................... 16
Regression Specification ................................ ......... ........... ............... 16
Discussion and Interpretation of Empirical Analysis .............................................21
4 C O N C L U SIO N ......... ......................................................................... ........ .. ..... .. 35
L IST O F R EFE R E N C E S ............................................................................ .............. 37
B IO G R A PH IC A L SK E TCH ..................................................................... ..................40
LIST OF TABLES
3-1. Sum m ary of V ariables ........... ........................................................ ............... 19
3-2. Determinants of PCNSDP from 1980 to 1999. ................................. ...............21
3-3. Determinants of PCNSDP from 1980 to 1989. ................................. ...............22
3-4. Determinants of PCNSDP from 1990 to 1999. ................................. ...............23
3-5. Determinants of GROSDP from 1980 to 1999............ ...................... ...............24
3-6. Determinants of GROSDP from 1980 to 1989............................... ............... 25
3-7. Determinants of GROSDP from 1990 to 1999............ ...................... ...............26
Abstract of Thesis Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Master of Arts
CONVERGENCE AMONG THE STATES OF INDIA IN THE TIME PERIOD FROM
1980 TO 1999
Chair: Bin Xu
Major Department: Economics
The present study uses the neoclassical growth model as a framework to study a
sample of 14 states of India, in the period from 1980 to 1999. The empirical findings
show a result of convergence among the states' Per Capita Net State Domestic Product in
the period from 1980 to 1999. The results do not show conclusively that the level of
convergence in PCNSDP increased in the time period from 1990 to 1999 due to the
change in economic and political policy during the early 1990s. The study finds six
statistically significant determinants of economic growth. A state run by a high quality
government and endowed with human capital as well as infrastructure has the
foundations from which to grow. An increase in investment creates job openings, which
stimulates economic growth. Non-developmental government expenditure going towards
the military, social services and past interest payment on debt holds back a state's growth
The paper uses a sample of 14 states of India in the period from 1980 to 1999 to find
the determinants of PCNSDP (Per Capita Net SDP). The same sample is then used to
determine whether the PCNSDP of the 14 states is converging or diverging. Having
regressed GROSDP (Annual Growth Rate of SDP) against six explanatory variables, I
find a result of convergence among the states PCNSDP in the period from 1980 to 1999.
The results do not show conclusively that the level of convergence in PCNSDP increased
in the time period from 1990 to 1999 due to the change in economic and political policy
during the early 1990's. A state run by a high quality government and endowed with
human capital as well as infrastructure has the foundations from which to grow. An
increase in investment creates job openings, which stimulates economic growth. Non-
developmental government expenditure going towards the military, social services and
past interest payment on debt holds back a states growth potential.
An important economic question is whether poor countries or regions tend to converge
toward rich ones. In neoclassical growth models for closed economies, as presented by
Ramsey (1928), Solow (1956), Cass (1965) and Koopmans (1965), the per capital growth
rate tends to be inversely related to the starting level of output or income per person. The
assumption of diminishing returns to capital implicit in the neoclassical production
function leads to the prediction that the rate of return to capital is very large when the
stock of capital is small and vice versa.
To understand how fast, and to what extent the per capital income of a particular
economy is likely to catch up to the average of per capital income across economies, P-
convergence is used. There is absolute P-convergence if the coefficient on initial income,
denoted 0, is negative and statistically significant. Absolute convergence is the natural
rate at which the states PCNSDP are converging. When some additional variables are
included in the regression to control for heterogeneities across states, there is conditional
P-convergence if the coefficient on initial income is negative and statistically significant.
Conditional convergence in relation to absolute convergence shall have a larger P value
because conditional convergence is able to increases the rate of convergence by focusing
on the significant variables. A second approach used in the literature to measure
convergence, which is not used in this paper is a-convergence. There is a-convergence if
the standard deviation across states tends to decline over time. To understand how the
distribution of per capital income across economies has behaved in the past, or is likely to
behave in the future, a-convergence is used.
Several studies of high-income economies undertaken during the 1990's, for the US,
Japan, and regions within Western Europe, found evidence for strong convergence
among regions and states (Barro and Sala-I-Martin 1995). When examining the simple
relationship between the per capital growth rate and initial per capital product, the
estimates of 0 are around one percent for the sample of twenty OECD countries and near
zero percent for the sample of ninety-eight heterogeneous countries (Barro and Sala-I-
Martin 1991). The technological and institutional differences across regions within a
country or across similar countries are smaller justifying a test for absolute convergence.
We find evidence of convergence for a sample of ninety-eight countries from 1960
to 1985 only in a conditional sense, that is, only if we hold constant variables such
as initial school enrollment rates and the ratio of government consumption to GDP
(Barro and Sala-I-Martin 1992).
The literature studying growth rates between the Indian states has found evidence of
both convergence and divergence. Dholakia (1994) analyzed 20 Indian states over the
period of 1960-90 and found marked tendencies of convergence of long-term State
Domestic Product (SDP). Interestingly, Dholakia found that 1980 was the year when
several lagging states began growing and the leading states began to stagnate. Cashin
and Sahay (1996) studied a longer time period from 1961-91 and found similar results to
Dholakia of absolute convergence in a study of 20 states. Ahluwalia (2001) showed that
whilst Punjab and Haryana were the two richest states in 1990-91, their growth rates of
per capital SDP in the 1990's was not only lower than that in the 1980's, but also in both
cases fell below the national average. Consistent with the convergence argument, he also
showed that the poorer states per capital SDP growth rates did not lag behind, but rather
performed well, particularly for the states of Rajasthan and Madhya Pradesh.
Chaudhury (1974) studied state income inequalities between 1950-70 and found that
the degree of state income inequality had remained unchanged. Majumdar and Kapoor
(1980) was one of the first studies to suggest that there had been a steady increase in the
inter-state income inequalities between the years of 1962-76. Recent studies by Rao,
Shand and Kalirajan (1999) have found per capital SDP in the Indian states have tended to
diverge rather than converge. Dasgupta et al. (2000) used a similar approach to Rao and
also found a distinct tendency for the Indian states to have diverged during the period
Cashin and Sahay (1996) argues convergence, whilst Rao et al. (1999) argues
divergence for a similar time period. Rao et al. used a smaller sample of 14 major states,
whilst Cashin and Sahay included the special category hill states of Assam, Himachal
Pradesh, Jammu and Kashmir, Manipur and Tripura as well as the union territory of
Delhi. Rao et al. calculated average annual growth rate for six time periods which where
all fifteen year intervals. In contrast Cashin and Sahay calculated average annual growth
rate for each year during his sample. The study presented here uses a sample of fourteen
states, and calculates average annual growth rate.
Basu (2002) studied government quality and how it affects growth rates between the
Indian states. The significance of this paper comes from its creation of a Quality of
Governance Index (QGOI) which shall be used here as an explanatory variable. Basu's
research was limited to creating a QGOI and showing that the quality of government does
significantly affect growth rates among the sixteen states used in his study.
Stern's 1991 growth determinants paper reviews previous theoretical growth work,
and then puts forth a general model explaining economic growth. Part of Stem's
explanation of economic growth was human capital, quality of infrastructure and
government organization; from Stem's model the foundation of the paper presented here
is built. A similar cross sectional regression equation used by Sala-I-Martin in his growth
research is used in this empirical analysis.
Chapter 2 puts forward a deductive theoretical argument as to what is causing the
disparities in SDP. Chapter 3 is the empirical test of the theoretical argument and
hypothesis put forward in Chapter 2. The empirical results are discussed and interpreted
in Chapter 3 and a conclusion follows in Chapter 4.
Mahatma Ghandi led India to independence from the British rule in 1947. Having
gained independence, India was given greater responsibility in making economic and
political decisions. Jawaharlal Nehru pushed the National Indian Congress to implement
Nehruvian socialism as the development strategy for India from the years of 1950 to
1980. The policy was aimed at achieving economic self-sufficiency by industrialization.
The industrialization was different from that seen in other countries because a highly
protected import-substitution approach was used. This approach was typified by high
levels of protectionism against foreign competition, mistrust of foreign investors, public-
sector domination of industry and a highly centralized allocation of resources. The
resulting economy became bound in a web of bureaucracy, subsidies and price controls
that effectively served to deaden innovation and progress. "Protectionism isolated India
from the rest of the world, and the country's share of world trade declined from 2 percent
in the 1950s to less than half of one percent in the late 1980s"
The policy approach employed between 1950 and 1980 brought the Indian economy
on the verge of a great fall, and in 1984 the government began borrowing from the World
Bank. India is one of the oldest members of the World Bank having joined in 1944.
It is the World Bank's largest single borrower, with cumulative lending of about
$44 billion as of June 1998 in market-based loans from the International Bank for
Reconstruction and Development (IBRD), and development credits from the
International Development Association (IDA), the World Bank affiliate that
provides interest-free loans to economies with low per-capita incomes
The World Bank leant money on the condition that India adopts a moderate liberalized
strategy. Support for liberalization grew all through the 1980s. Liberalization came up
against powerful resistance from interest groups, and the lack of strong political
leadership meant that little progress toward liberalization was seen.
Central government borrowing exceeded five percent of GDP because public
expenditure was growing faster than revenue in the 1980's. The government had to
borrow to pay for the subsidies, which reached twelve percent of GDP in 1990. The
subsidies were going to the agricultural sectors to pay the farmers who were receiving
below market price for their produce. The budget deficit increased as the savings and
investment gap widened. Finally, "in 1991, the economy was on the verge of bankruptcy,
with only two weeks worth of foreign exchange reserves and a current account deficit of
minus three percent of GDP" (IMF, 1995).
The IMF had a standby arrangement facility with India in 1991 and leant $2.3bn to
help India avoid an economic crisis. The IMF forced changes in the economic policies
implemented by India since achieving independence in 1947. Cuts in public expenditure
on export subsidies, health and education were seen to reduce the budget deficit. The
economic policies used in the past forty years had failed and gradually a new approach to
managing the Indian economy was being forced into place by mounting international
"India's economic reforms began in 1991 when a newly elected Congress
government, facing an exceptionally severe balance of payments crisis, embarked on a
program of short term stabilization combined with a longer term program of
comprehensive structural reforms" (Sachs, Varshney and Bajpai 1999, 26). In 1991 the
government's new liberalization approach attempted to curb the trade deficit, by
attracting foreign direct investment and increasing exports. East Asia used export-
oriented growth, which helped them grow much faster than India. East Asian GDP
growth rates averaged around eight percent in the 1980s. Export oriented growth policies
such as opening up their economies, specializing in exports, and attracting Japanese
investment when the yen appreciated explains the East Asian's increased GDP growth
India attempted to insert itself back into the world economy in 1991 through the
expansion of its export trade. To boost exports the rupee was devalued by nineteen
percent in 1991. The devaluation caused exports to accelerate from eight point six
percent growth per year in 1986 to fifteen percent in 1995. The devaluation of the Rupee
made Indian exports relatively cheaper and the demand for the relatively cheaper Indian
goods increased. Those holding the Rupee at the time of the devaluation suffered
because now their savings were worth less than before the devaluation. The Rupee now
had less foreign purchasing power causing Indian imports to decrease.
The IMF had recently helped India avoid bankruptcy, and now demanded India start
changing the policies they had implemented post 1947. The states were literally forced
by the IMF to relinquish control of some public sector enterprises and to encourage
private enterprises to grow. Much of the industrial licensing system such as the "license-
permit Raj" used to protect the undeveloped Indian economy was broken up. Electricity,
power, steel and communications were now areas opened up to private sector investment.
These new sectors became more efficient under private control and the owners of these
newly privatized industries made profits.
The changing approach of policy now allowed foreign investors in the 1990's to own
major shares in companies. Red tape was cut making it easier to set up new businesses
and allow foreign investment. Many aspects of business decision-making by the
government were dismantled as more sectors became privatized. By 1998 direct foreign
investment totaled $3.2 billion, which is an investment level twenty five times greater
than that seen when India was a protectionist country.
In 1993, a market-determined exchange rate was introduced. Up until 1993, India had
used a fixed exchange rate for the rupee. The new floating exchange rate allows for
greater control over the economy by the government using monetary policy. By 1993
capital markets had become liberalized and more transparent to encourage foreign
investors. Import quotas were converted to tariffs, which opened up the Indian trade
policy. "The maximum tariff was lowered from four hundred percent in 1991 to thirty
five percent by 1998" (WTO 1998, 21).
The reforms of the 1990's had stabilized the Indian economy. Privatization helped
end the balance of payments crisis. The Indian foreign exchange reserves in 1991 were at
an all time low of $lbn and in contrast toward the end of 1996, the foreign exchange
reserves rose to $20bn. The reserves increased because non-resident Indians began
investing in India and the IMF had increased the capital flow. The end to protectionism
and the rise of liberalization in the 1990's is happening slowly in India. India's
capitalistic private sector had been the most controlled by the government in the non-
socialist world. Regulation still remains a problem in financial and agricultural sectors
because India previously had a heavily regulated economy. "Bound" tariffs are
maximum tariff rates committed in the WTO on agricultural goods. The Bound tariff
ceilings remain high, ranging from lone hundred and fifty percent to three hundred
percent. "In reality, applied rates for 1997/98 are considerably lower, averaging twenty
six percent for the sector, with a peak of forty five percent," (WTO 1998, 12). The
twenty six percent tariff on agricultural goods being imported artificially distorts the
market and creates less incentive for the Indian farmers to become more productive and
"India's increased openness and integration with the world economy have been
important factors in explaining the healthy economic growth in the 1990s." (WTO 1998,
14). Economic stagnation between 1950 and 1980 has proven economic development
under import-substitution industrialization is not a good path toward economic
development. The Soviet Union collapse showed Communism was not an effective
strategy for growth. The Austrian economists Mises and Hayek started the socialist
calculation debate in 1920. The Austrian economists had predicted that socialism would
not be sustainable in the long run. In the past seven years, liberalization and domestic
restructuring has helped India develop at five to six percent per annum.
The theoretical passage is first used to show the origins of the model and equations
later used in the empirical analysis. The work of Robert Barro and other economists in
the growth field have identified a substantial number of variables that are partially
correlated with the rate of economic growth. The basic methodology used by Sala-I-
Martin (1997) to identify the determinants of growth consists of running cross-sectional
regressions of the form:
y= + Px1+ 02X2 + .....+ PnXn + (1)
The vector of rates of economic growth is y, and x...... Xn are the vectors of
explanatory variables. "Variables like the initial level of income, the investment rate,
various measures of education, some policy indicators, and many other variables have
been found to be significantly correlated with growth in regressions like (1)" (Sala-1-
Martin 1997, 178).
The simplified neoclassical production function has only two inputs, physical capital,
K(t), and labor, L(t). The production function takes the form:
Y(t) = F[K(t), L(t), t] (2)
The flow of output produced at time "t" is represented by Y(t).
The neoclassical model assumes diminishing returns to capital, exogenous
technological progress, full employment, a fixed relationship between the labor
force and population, and exogenous growth of population. With respect to
preferences, the model assumes that the saving rate derives from the choices made
by utility-maximizing households over an infinite horizon (Barro and Sala-I-Martin
Economists have extended the notion of technology to include natural resources, such
as geography, fertile land, and the availability of minerals, as well as governmental
policies that effect property rights, the provision of infrastructure services, tax rates, and
Barro and Sala-I-Martin (1991) showed that the transitional growth process in the
neoclassical model can be approximated as:
(1/T). log(yit/yi,t T)= Xi* + 1og(yAi*/yAi,t T). (1 e-T)/T + uit (3)
The economy is indexed by "i", "t" indexes time, yit is per capital output, xi* is the
steady state per capital growth rate, yAi is output per effective worker, yA^* is the steady-
state level of output per effective worker, T is the length of the observation interval, the
coefficient p is the rate of convergence, and uit is an error term. The higher P, the greater
the responsiveness of the average growth rate to the gap between log(yAi*) and log(yAi,t
T), that is, the more rapid the convergence to the steady state. The model implies
conditional convergence in that, for given xi and yAi*, the growth rate is higher the lower
y i,t -T.
The second function of the theoretical passage is to show the relevance of each
variable to be used in the empirical analysis and from these variables deduce a testable
hypothesis. India has developed at a rapid speed over the past ten years, but still shows
many signs ofunderdevelopment. The birth rate is high with the population growing at a
rate of one point five percent a year. India ranks second in the world in terms of
population, and seventh in terms of land area. Population growth generally initiates
economic growth, but when population growth is at a very high rate, economic growth is
Education has long been seen as a key concept in curtailing population and aiding
economic growth. There is no public schooling system set up to ensure each child attains
a minimum education level. CIA figures state the literacy rate to be thirty seven percent
for women and sixty five percent for males. The literacy rate for women is very low,
because tradition holds that women do not necessarily need to be educated. The norm for
many Indian girls is to work around the house until marriage.
The occupational structure of the labor force is related to the education level. India
remains an agriculture-based society. CIA figures from 1995 show the distribution of the
Indian work force: sixty seven percent agriculture, seventeen percent service and sixteen
percent industry. Both the industrial and service sector is growing at a rate of six percent
a year, but it is going to take decades for the majority of the Indian work force to move
from farm work into industrial and service work.
A lack of education leads to poverty because most uneducated people are paid very
little for their work. "More than a third of the population is too poor to be able to afford
an adequate diet, and market surveys indicate that fewer than five percent of all
households had an annual income equivalent to $2,300 or more in 1995-96"
(http://www.cia.gov/cia). Data collected by the CIA in the year 2000 show that thirty
five percent of the Indian population lives below the poverty line. Poverty figures like
that seen in India in the year 2000 were seen in the U.S. before FDR's New Deal policy
was set in place in the 1930's. Most of the population only makes enough to live day to
day and therefore are not able to save money. Due to a lack of savings, India is not able
to develop advanced credit facilities. "The rapid growth of population in India has been
associated with a worsening man-to-land ratio, the growth of landlessness, and the
concentration of landholdings in the hands of a few" (Jannuzi 1989, 111).
For a long time it has been thought that having rich people was good for economic
development, and that the government should actually help keep these people rich
through such things as tax breaks. Investment stimulates growth in many ways,
particularly by creating jobs. Rather than investing money, the rich actually carry out an
act known as capital flight, which hinders the national economy. If a high percentage of
the money, which is made in India is not spent or invested in the domestic economy, then
many economic problems arise. Foreign direct investment (FDI) stimulates the economy
by investing money earned abroad into the Indian economy.
Growth begins in urban areas, which is where most of the well-developed
infrastructure in a state is found. Cities are the focus of government, with great
percentages of income collected in tax revenues being distributed in cities. This leads to
better health care and education facilities in relation to that found in rural areas. The
Indian government has not been creating jobs in the rural areas, which means the
population in the rural areas have to move to where the jobs are being created.
Individuals that work earn income that is eventually spent in the domestic economy
stimulating economic growth. The perception among the Indian population is that cities
have a lot of jobs. In reality there simple aren't enough jobs in the city, and if the
government were to create more jobs, then for each job created, ten more people
immigrate to the city in search for that one job.
The availability of transport and communication facilities is correlated with urbanized
areas and hence is also an explanatory variable of growth. India has recently begun
developing its poor infrastructure, which has aided in economic growth because
infrastructure helps trade occur. When a manufacturing firm decides to build a new
factory, the location and transportation system is a key factor driving any company's
choice. Once a firm has built its factory in a particular state the manufacturing process
Government expenditure on such things as education and infrastructure creates
economic growth. Non-developmental and social services expenditure by the
government hinders economic growth. Government debt caused by unnecessary and
excessive spending on such things as the military hinders economic growth. Since
achieving independence in 1947, India and Pakistan have been in dispute over Kashmir.
Figures analyzed by the BBC set expenditure on the war at ten billion for India and 4
billion dollars for Pakistan a year. "It is estimated that the bill to keep Indian troops on
the remote Siachen glacier amounts to $700,000 a day" (http://news.bbc.co.uk). As
fighting continues, India may encounter some economic problems, as tax money is not
invested in the country, but into the military. There are many alternate ways of spending
the ten billion dollars allocated to the military each year.
The quality of a state government effects economic growth. A high quality
government is able to control crime rates, riots and industrial disputes, which in turn
creates stability in the economy. One of the problems India faces is with its government
and other people who enforce laws. The system appears to be democratic but often votes
are bought or other forms of corruption occur. Low quality government is easily
susceptible to corruption. Few people pay taxes in a poorly set up non-progressive tax
system. India does not have the tax base it should for a country of its size simply due to
the amount of illegal activity taking place. A larger tax base and a decrease in corruption
would help India educate more of its population, and provide better health care.
From analyzing the deductive theoretical argument, six hypothesized theoretical
constructs of PCNSDP exist. A state run by a high quality government and endowed
with human capital as well as infrastructure has the foundations from which to grow. An
increase in investment creates job openings, which stimulates economic growth. Non-
developmental government expenditure going towards the military, social services and
past interest payment on debt holds back a states growth potential.
TEST OF HYPOTHESIS
The purpose of this statistical exercise is to explain the differing growth rates of a
sample of fourteen states in the time period from 1980 to 1999. The hypothesized
variables explaining the growth rates of SDP are: human capital, infrastructure, quality of
government, government expenditure, investment and employment. The basic
methodology used to explain PCNSDP consists of running regressions of the form:
Yit = Po + 6i + 6t + 31Xlit + P2X2it + ... + PnXnit + Eit (4)
This linear equation method is appropriate for running regressions and has been used
in previous growth work (1) by many other economists. PCNSDP is represented by Y
where "i" is the state and "t" is the year. Xnit are the six explanatory variables for each
state and year. The coefficients of each explanatory variable are Pn, whilst E is an error
term. State and time fixed effects are represented by 6i and 6t respectively.
The basic methodology used to explain GROSDP consists of running regressions of
Zit = ao + 6i + 6t + laYio + 2Xlit + 3X2it + .... + anXnit + rlit (5)
GROSDP is represented by Zit. The variable Yio denotes PCNSDP in the initial year.
The coefficients of each explanatory variable are an, whilst ri is an error term.
The sample consists of fourteen of India's states, which account for ninety-five
percent of the total population. The fourteen states cover 2.7 million square kilometers,
which amounts to eighty-three percent of India's total land area. The smaller states such
as Goa and Delhi were excluded from the analysis. The northern states of Jammu and
Kashmir were excluded because the on going war makes it difficult for accurate data
collection. Other states were excluded because of gaps in the data sources used in the
empirical analysis. Using fourteen of the states shall capture a good cross section of all
of India's states because only five percent of the total population is not being included in
The dependent variable PCNSDP was taken from the Directorates of Economics and
Statistics of Respective Governments, which were compiled in the annual Economic
Surveys. The dependent variable GROSDP was calculated by:
Zit = In (Yit+i) In (Yit) (6)
Two of the explanatory theoretical concepts use Census data. Literacy rate (LIT) has
always been an accepted measure of education level by economists. LIT has always been
an accepted measure of human capital in the field of economics. The variable WORK
measures the percentage of the total population that works, and was also taken from the
Census Reports. The production function used in this paper is comprised of six
explanatory variables, which equal the left hand sides SDP. Dividing both sides by labor
deals with the endogneity problem of the WORK variable and results in PCNSDP now
equaling the production function.
A states infrastructure is comprised of many things such as airports, ports and roads.
The data used in the empirical analysis only measured roads and did not measure all
possible types of infrastructure. ROADS capture the theoretical concept of infrastructure
relatively well. The Ministry of Surface Transport in the 1996 and 1986 reports calculate
the kilometers of highway in each state. Using this measure would not take into account
different area sizes of each state and would be a useless measure. The area of highway
was divided by the area of the state for all fourteen states to calculate the variable
The quality of government is measured using QGOI data for each state created by
Basu (2002). The lower the quality of a states government, the higher the level of
corruption found in that state. The QGOI scale ranges from 0 to 16, with 16 representing
a government of the highest quality. QGOI is a function of: crime rates, riots, industrial
disputes, strikes, Gini index and the debt to income ratio. The QGOI corresponds well to
measuring the theoretical concept of government corruption.
The annual Combined Finance and Revenue Accounts contain state government
expenditure. EXPEND is a function of money spent on: social services, economic
services, development and non-development. Total government expenditure was divided
by NSDP (Net State Domestic Product) so as to avoid the effect of larger states having
greater EXPEND values.
Loans sanctioned by State Financial Corporations are used as a proxy for investment
because it is difficult to find state level investment data. The total amount of loans given
out in each state was divided by NSDP to create the variable INVEST. The data is
created by the Industrial Development Bank of India and is compiled in the annual
Combined Finance and Revenue Accounts. Loan data have been used in other similar
studies and are a reasonable proxy for the theoretical construct of investment. To test
whether Loans sanctioned by State Financial Corporations is a good proxy for
investment, I calculated the correlation between INVEST and Total National Investment
data for each of the twenty years, and found an R-squared value of 0.9494.
Table 3-1. Summary of Variables.
Variable No. Obs Mean Std. Dev Min Max
GROSDP 266 0.1182838 0.0703775 -.0613505 0.3679864
PCNSDP 280 6231.386 5083.667 878 23398
LIT 280 60.217 13.33567 38.48 90.92
EXPEND 224 0.1785047 0.0331068 0.1175275 0.336864
QGOI 280 6.633714 2.726396 0 10
ROADS 280 0.8681745 0.994643 0.19334 5.18382
WORK 280 38.36339 5.019369 30.88 46.04
INVEST 196 0.0052828 0.0027581 0.0002606 0.0145365
INVEST has only 196 observations, whilst EXPEND has only 224 observations
because the data is only available up to the year 1993 and 1995 respectively. All the
variables have a positive value apart from GROSDP, which sometimes is negative
representing a decline in a states growth rate.
The regression equation to calculate the determinants of PCNSDP is:
Yit = Po + 6i + 6t + P0LITit + p2EXPENDit+ p3QGOIit+ 04ROADSit + p5WORKit
+ 06INVESTit + Eit (7)
Whilst the regression equation to calculate the determinants of GROSDP is:
Zit = ao + 6i + 6t + aiYio + a2LITit + a3EXPENDit + a4QGOIit + asROADSit +
a6WORKit + a7INVESTit + rfit (8)
A low QGOI government is inefficient and holds back growth. As a state government
increases its power and control, a more stable environment is created which should
positively affect growth rates. Part of creating a more stable environment is developing
human capital. As LIT increases the economy of a state can diversify into new sectors
and grow. Increasing LIT has a positive impact not only on growth but the quality of life
in each state. An educated population tends to move out of the rural areas into the urban
areas where there are many more amenities and job opportunities. Factories tend to
locate in urban areas because of the more developed infrastructure. As ROADS increase
it is expected that more factories move into that area stimulating growth.
Expenditure on items such as maintenance of the organs of the state, administration
services, pensions and interest payments are types of non-development expenditure.
Excessive government debt holds back the economy because greater percentages of the
budget are spent on repaying debt rather than spending on the economy to stimulate
growth. An increase in non-developmental expenditure shall impact growth rates in a
negative way. Expenditure on education, health, various other social services and
economic services are types of developmental expenditure. An increase in
developmental expenditure should theoretically increase the growth rate. EXPEND is
comprised of both developmental and non-developmental government expenditure. The
balance of both types of expenditure that shall influence whether EXPEND has a positive
or negative impact on growth. From looking at the EXPEND data, it can be seen that a
greater percentage is spent on non-development, which implies that EXPEND should
have a negative effect on growth rate. Previous analysis by Barro has "found that the
ratio of real government consumption expenditure to real GDP had a negative association
with growth and investment" (Barro 1991, 430).
Increasing investment should theoretically have a positive effect on growth rates. As
INVEST increases, it shall stimulate the economy and create jobs. WORK shall have a
positive effect on growth rates because as more people work, more money shall be spent
and circulated through the economy.
The process of convergence is quickened by movements of people out of areas
where ratios of capital to workers are low-and hence wage rates and levels of per
capital income are also low-to areas where they are high (Barro and Sala-I-Martin
Discussion and Interpretation of Empirical Analysis
The empirical research finds that the six explanatory variables upon which the
hypothesis of this paper is based, do significantly explain the differing PCNSDP between
the states for the three time periods, which are analyzed. All six of the explanatory
variables have the expected hypothesized sign.
Table 3-2. Determinants of PCNSDP from 1980 to 1999.
(l a) (2a) (3a) (4a)
LIT 142.96 144.21 21.29 0.3179
(10.001)*** (7.577)*** (1.825)* (0.012)
EXPEND -15488.42 -17737.75 -13261.98 -9564.51
(-3.597)*** (-5.022)*** (-5.199)*** (-3.892)***
QGOI 305.53 430.31 256.34 264.48
(6.344)*** (5.146)*** (6.6)*** (6.102)***
ROADS 1446.29 1895.97 236.76 421.36
(6.126)*** (5.250)*** (1.501) (1.436)
WORK 50.3 410.29 137.31 281.8
(1.812)* (5.818)*** (4.93)*** (6.952)***
INVEST 64593.69 91429.35 101100.8 103760.4
(1.291) (1.952)* (3.904)*** (4.314)***
Constant -5620.53 -22398.87 3038.88 -2790.46
(-4.936) (-10.339) (2.139) (-1.067)
Time Effect Yes Yes
State Effect Yes Yes
No. Obs 196 196 196 196
R-squared 0.5142 0.6886 0.7867 0.955
t-value appears in parenthesis
S Significance at the 0.10 level
S ** Significance at the 0.05 level
S *** Significance at the 0.01 level
All tests are two-tailed.
Table 3-3. Determinants of PCNSDP from 1980 to 1989.
(Ib) (2b) (3b) (4b)
LIT 76.71 93.17 107.1 132.93
(9.148)*** (5.325)*** (11.331)***
Table 3-4. Determinants of PCNSDP from 1990 to 1999.
(Ic) (2c) (3c) (4c)
LIT 119.77 37.82 27.3 42.48
(5.424)*** (1.567) (1.749)* (1.964)*
EXPEND -21248.57 -9308.67 -14449.2 -9582.65
(-3.348)*** (-1.996)** (-3.141)*** (-2.156)*
QGOI 383.58 429.83 459.03 513.67
(6.149)*** (3.312)*** (4.334)*** 4.451)***
ROADS 562.8 586.7 237.3 103.19
(2.185)** (1.847)* (1.034) (1.931)*
WORK 24.85 247.36 70.92 111
(1.661)* (2.717)*** (1.750)* (1.661)*
INVEST 10369.23 238396.1 5375.73 28613.47
(1.991)** (2.289)** (2.081)** (2.405)**
Constant 6519.71 -3133.82 1029.71 5236.64
(3.010) (-1.149) (1.102) (1.299)
Time Effect yes Yes
State Effect Yes Yes
No. Obs 56 56 56 56
R-squared 0.4817 0.5557 0.8207 0.8445
Tables 3-2, 3-3 and 3-4 show the results of equation (7). Regression (1) uses the
ordinary least-squares (OLS) method for fitting a regression line. The panel data set used
in the empirical analysis replicates the observations across both states and time periods.
A fixed-effects approach uses the variation in explanatory variables over time to identify
regression coefficients. A fixed effect estimator controls for state-invariant determinants
and is used in (2). Time fixed effects control for time-invariant determinants, such as
cultural factors and is used in (3). Regression (4) controls for both time-invariant, and
state-invariant determinants by using both time, and state fixed effects.
Table 3-5. Determinants of GROSDP from 1980 to 1999.
(5a) (6a) (7a) (8a) (9a)
PCNSDP 0 -1.23e-06 -.000013 -.000027 -7.54e-06 -.00003
(-1.669)* (-4.032)*** (-5.964)*** (-1.345) (-3.316)***
LIT 0.002339 0.004384 0.001701 0.006683
(3.156)*** (3.374)*** (2.363)** (2.256)**
EXPEND -.500067 -.860475 -.585777 -.91722
(-2.677)*** (-3.767)*** (-2.354)** (-3.189)***
QGOI 0.002378 0.011668 0.001244 0.013733
(1.058) (2.188)** (0.547) (2.532)**
ROADS 0.031754 0.027279 0.027168 0.050273
(2.970)*** (1.183) (2.705)*** (1.514)
WORK 0.001788 0.007578 0.002152 0.010319
(1.512) (1.663)* (1.898)* (1.987)**
INVEST 1.32446 5.849269 0.992275 6.216752
(0.631) (2.029)** (0.501) (2.217)**
Constant 0.110297 0.187723 0.677908 0.176682 0.928707
(15.834) (3.686) (4.177) (0.018) (2.651)
Time Effect Yes Yes
State Effect Yes Yes
No. Obs 266 182 182 182 182
R-squared 0.008 0.1234 0.176 0.3203 0.3937
F-statistic 2.13 3.5 6.28 4.02 3.02
Table 3-6. Determinants of GROSDP from 1980 to 1989.
(5b) (6b) (7b) (8b) (9b)
-0.0000117 -0.0000252 -0.0000251 -0.0000288 -0.0000472
(-2.347)** (-2.655)*** (-2.055)** (-2.404)** (-2.671)***
0.002599 0.001504 0.002626 0.005209
(-2.201)** (0.609) (2.045)** (1.662)
-5.99e-06 -4.58e-06 -1.21e-06 -9.52e-06
(-1.834)* (-1.467) (-1.171) (-1.992)**
0.003202 0.002945 0.003346 0.004322
(1.765)* (1.303) (1.863)* (1.972)**
0.032314 0.010399 0.033985 0.05029
(1.783)* (1.993)** (1.731)* (2.005)**
0.001889 0.000581 0.001272 0.000931
(1.218) (2.134)** (2.888)*** (2.238)**
3.850545 6.987681 1.476478 3.89648
(1.278) (1.719)* (1.510) (1.992)**
0.073672 0.096471 0.13424
(-4.864) (1.687) (0.587)
Table 3-7. Determinants of GROSDP from 1990 to 1999.
(5c) (6c) (7c) (8c) (9c)
PCNSDP 0 -1.16e-06 -0.0000129 -0.0000247 -0.0000156 -0.0000551
(-1.985)** (-1.683)* (-1.762)* (-1.936)* (-2.693)**
0.002737 0.003122 0.001712 0.004822
(1.77)* (1.338) (1.981)* (1.945)*
-2.79e-06 -.000021 -1.57e-06 -1.75e-06
(-1.682)* (-1.265) (-1.779)* (-2.094)**
0.004234 0.006734 0.005647 0.007134
(1.744)** (2.005)** (1.731)* (2.134)**
0.024 0.051503 0.019423 0.071636
(1.688)* (1.288) (1.843)* (2.250)**
0.001785 0.004521 0.002562 0.007209
(1.753)* (1.705)* (1.747)* (1.755)*
1.427096 16.62934 3.277358 17.03527
(1.427) (1.798)* (1.699)* (1.936)*
0.610512 0.010339 0.573957
(2.382) (0.098) (1.035)
Table 3-5, 3-6 and 3-7 show the results of equation (8). Regression (5) tests for
absolute convergence. Regression (6) uses OLS to begin the tests for conditional
convergence. A state fixed effect is used in (7) and a time fixed effect is used in (8).
Regression (9) combines the approach of (7) and (8) by using both a state and time fixed
The natural rate at which the states PCNSDP are converging is seen in regression (5).
Regressions (5a), (5b) and (5c) all have negative and statistically significant t-values,
which demonstrate the existence of absolute 0-convergence. Comparing the regression
coefficients of (5b) and (5c) leads to the conclusion that absolute convergence amongst
the states is highest in the period from 1980 to 1989.
The t-values of PCNSDP in regressions (6) through (9) are all negative and
significant, which shows conditional convergence of the states PCNSDP levels. The
coefficients of regression (6) through (9) are all greater than the coefficient of regression
(5), which shows that adding additional variables increases the level of convergence in
PCNSDP. Comparing the regression coefficients of (6) through (8) in Tables 3-6 and 3-7
leads to the conclusion that conditional convergence amongst the states is highest in the
period from 1980 to 1989. Regressions (9b) and (9c) include both state and time fixed
effects which shows conditional convergence is greater in the period from 1990 to 1999.
The results do not show conclusively that the level of convergence in PCNSDP increased
in the time period from 1990 to 1999 due to the change in economic and political policy
during the early 1990's. Changes in economic and political policy do not have an
immediate effect on PCNSDP because of time lags. Time lags may explain why
convergence in PCNSDP levels is not always greater in the 1990 to 1999 time period
when compared to the 1980 to 1989 time period.
The empirical results show that human capital is one of the key determinants of
growth. LIT had a positive coefficient and was statistically significant in all the
regressions. Development data shows that ninety nine point nine percent of all U.S.
children are enrolled in primary school education. The contrasting figure for children
enrolled in primary school in India is only seventy seven point two percent.
The education system available in India's states is very good but expensive. Children
are generally educated at private schools, where parents pay the tuition. Those parents in
the lower income brackets are unable to give their children the opportunity to move up in
social stature. The children of the poor are destined for a seemingly unending cycle of
poverty they were born into. India does not have the capacity to create a publicly funded
education system, so a school system of two layers needs to be created. The first layer
shall comprise of the present schools that those who can afford attend. The second layer
comprises of schools with not so many amenities, but is financed by the government.
The focus of the government-funded schools would be to educate all children to a
standard that allows young adults to enter the work force. Unemployment shall decrease,
as the educated work force shall be able to use entrepreneurial spirit and enter markets
previously not seen in India. If the work force becomes educated other firms apart from
simple manufacturing firms shall want to locate in India, which will bring about a greater
demand on the educated population.
Kerala stands out for its relatively high level of development. In Kerala there are
many universities and religion affiliated schools that educate the children at no cost to the
parents. Literacy rates in Kerala are much greater than those found in the rest of India
because every child has the opportunity to attend school. Educating the population is not
sufficient by itself to create long-term economic growth. Kerala accounts for three point
four percent of India's population, however fifty percent of the countries migration
occurs from the young educated population leaving Kerala. Without the educated, a
country stands no real chance of advancing economically because they have a population
unable to carry out the high technology jobs.
Education is the key to decreasing the rate at which the states population is growing.
Kerala has shown that education can bring population growth rates down to zero percent
and this is what the other states need to focus on. Policies need to be created and
implemented in India to control the growing population. World Development data shows
the contraceptive prevalence rate in India to be only forty one percent, in contrast to the
seventy one percent rate of the United States.
The empirical analysis found that as crime rates, riots, industrial disputes and
corruption decreased, a states growth rate increased. QGOI was significant in almost all
the regressions and consistently had a positive t-value.
Public sector employees maybe unproductive because of low and declining civil
service salaries and promotions unconnected to performance. Workers become corrupt
when wages are not paid fully or on time and this is the fault of the government. Budget
funds needed to pay for wages maybe delayed because of the inefficient politicians. The
motivation to remain honest may be further weakened if senior officials and political
leaders use public office for private gain. Currently there is no employee protection
system for those who report the corrupt employees.
The cost of corruption cannot be measured, but is often interpreted. Recently the
World Bank complied data predicting the level of corruption found in India. The report,
according to informed sources said that, "because of widespread corruption, two to three
per cent of the country's $1.805 trillion GDP is lost annually". The report goes further by
stating "had there been some control on corruption, the country's present per capital
income of $350 would have been increased to $750".
The World Bank has formulated an anti corruption approach:
GI & AC = F (KI, LE, CA) (9)
Equation (9) shows that government improvement and anti corruption programs are a
function of knowledge, information, political leadership and collective action. The
World Bank has set out three primary functions to decrease corruption. For corruption to
decrease the Indian population must take collective action to end it, and not carry on
supporting corruption for their own benefits. Collective action is fundamental in putting
new election laws in place. The population has to be educated and made to understand
the long run negative effects and costs of corruption for them to begin demanding an end
in corruption. The Indian political leadership and quality of government can only be
changed through the ballet box.
In the future, Madhya Pradesh should experience a larger increase in PCNSDP
because of the states large step toward democracy compared to all the other states. A
state that allows political freedom shall increase the quality of its government by
allowing the population to use their democratic vote. In the long run Madhya Pradesh's
change toward democracy should increase growth, but to what extent is extremely
difficult to measure. In 1994 Madhya Pradesh was the first state to conduct elections to
panchayats. The result was to take power away from the representatives and hand it to
the people directly. The state government of Madhya Pradesh has moved from a directly
administrative roll to a supervisory roll.
Data on real annual average growth rates of per capital GSDP bear testimony to the
fact that four out of five states that are more policy reform oriented (with the
exception of Andhra Pradesh) are also the fastest growing states in India in the
post-reform period (Bajpai and Sachs, 1999).
Bihar, Uttar Pradesh, Madhya Pradesh and Orissa have lagged behind in both policy
reform and growth of PCNSDP.
The variable WORK was statistically significant in all regressions and had a positive
t-value. With the large population India already has, something has to be done to create
jobs. Addressing the issue of technology, India needs to focus on using labor-intensive
rather than capital-intensive technologies. An un-educated person may have a job, but
often it is not well paying enough to keep the individual above the countries nationally
established poverty line.
Financial and High-Tech services such as communications and information
technology industries are reliant on a well-educated work force. These industries also
require telephone and Internet connections, which are all characteristics of urban areas.
Urban areas have a higher quality of life that attracts the highly skilled mobile workers.
Maharashtra has the most well developed service industry among all fourteen states, with
the countries financial center and other important IT based industries being located within
the state. Tamil Nadu, Karnataka and Andhra Pradesh have relatively large service
sectors in relation to the other ten states. As the population becomes more educated,
Kerala has seen the majority of its population move from the primary sector to the
tertiary sector, which is a similar kind of movement to that seen in developed countries.
The Green Revolution dating from 1965 to the early 1980's created many jobs and
initiated agricultural-led- productivity growth. Irrigation and extensive fertilizer use
helped increase wheat and paddy rice yields. The Green Revolution was primarily in the
states of Haryana and Punjab, which have an ideal agro-climate. This short-lived burst in
agriculture led growth has not occurred in the period from 1980-99.
Agriculture jobs are seasonal and a village or town cannot survive on agriculture
alone. In an attempt to revive growth in rural areas, China has adopted a policy trying to
attract large manufacturing firms to these areas. China has remedied this problem by
attracting big corporations to Chinese towns and villages so as to absorb the surplus
labor. Corporations set up production plants in towns where the population can do both
farming and manufacturing work. The best example of this type of export led growth is
the arrival ofNike to the East Coast of China. In this situation the whole town is based
around Nike; almost all residents in the surrounding areas work in the factory. Most of
the villagers work at Nike during the day and go to the farm at night to make sure
everything is all right. Having factories locate in small towns and villages has created the
incentive needed to keep the rural population from migrating.
Urban areas have relatively well developed infrastructure networks in relation to rural
areas. ROADS hypothesized positive relationship with growth rate was supported in the
results. Theoretically, the more money allocated by states to building up infrastructure,
the faster a state should grow. Well-developed infrastructure attracts firms to locate in a
particular state because infrastructure helps businesses.
INVEST had a positive relationship with growth rate which was statistically
significant in most of the regressions. The states giving out more loans grew faster
because the money from loans was invested back into the state stimulating the states
economic growth. The poor economic performance of Kerala can be attributed to
insufficiency of investment, both private and public largely due to the failure of the
government to implement policies effective in encouraging private investment. Private
investment in Kerala is the lowest in comparison with all of the other states. Historically
the state's government has had a hostile attitude toward foreign investment. The lack of
policy development by the state government results in very low FDI. Due to a lack of
FDI, manufacturing only accounted for fifteen point five percent of Kerala's SDP in
The expected coefficient sign of EXPEND was difficult to predict because it depended
on the proportion of non-developmental to developmental expenditure. The variable
EXPEND was statistically significant in all regressions and had a constant negative
impact on both PCNSDP and GROSDP. For EXPEND to have had a negative sign, it
would imply that the majority of states spend more on non-development than
The government spends almost half of its Non-Plan Expenditure budget on interest
payments. This payment is only going toward paying interest on the debt and not the
principal of the debt. In the long run economic growth is stifled because thirty three
percent of the budget is not being put back into the Indian economy. The proportion of
the budget allocated to subsidies is being put back into the economy. The amount of
money allocated to subsidies has decreased since 1947, but it still remains a substantial
portion of budget expenditures. The social services expenditure of 6,187 Crore Rupees
represents money allocated to education and health. A comparison made between the
money allocated toward defense and that allocated toward health and education, shows
only one seventh of the money allocated to defense is allocated toward education and
health. Money should be allocated to education instead of the military because allocating
money to education would have a long run multiplier effect upon economic growth
Rajasthan had an extremely high PCNSDP in the 1981-1990 time period, but after
1991 Rajasthan was no longer seen as the fastest growing state. Even though Rajasthan
received the highest per capital transfers and grants from the union government among the
four BIMARU states, and was one of the top recipients of federal transfers of all states,
this alone does not account for the high growth rates. Orissa received the second largest
per capital transfers, and was still the slowest growing state in the 1981-1990 period. The
other factors that help explain the high growth rate of Rajasthan are the rapid
electrification of the state and the building on the Command Canal in 1980 to help
agriculture. Rajasthan was also a beneficiary of the Green Revolution, which
contributed to the SDP just as the increased tourism did during this time. Raj asthan's
tourist industry has grown at the fastest rate among all fourteen states because of the
popularity of visits to Jaipur and Udaipur and the states proximity to Delhi.
Orissa is located on the coast but experiences some of the lowest PCNSDP. Orissa's
agricultural sector and economy suffer greatly from frequent flood devastation. The state
is one of the most well endowed with resources in relation to the other states. Orissa is
primarily an agricultural state despite its resource endowments. For this reason the poor
agricultural performances year after year hinders the SDP and growth rate. An important
factor that maybe explaining Orissa's low PCNSDP is the fact that twenty five percent of
the states population is tribal. Tribal populations are generally associated with lower
social indicators in health and education, and suffer social and political exclusion.
India abandoned the protectionist approach advocated between 1947 and 1990. The
liberalization approach has increased the rate at which India is developing. The new
approach has set the foundations from which good economic and political policy can be
created to help the states of India grow. Throughout the 1990's India has had many
economic problems, which have been resolved using foreign aid.
Theoretically, the relatively more urbanized states should experience economic
growth faster than states that have a greater proportion of its population in rural areas.
Urban areas have more of the variables that are both positively correlated and help
initiate growth. Well-developed educational facilities are concentrated in urban areas.
As the students finish their education and begin participation in the work force, they
should theoretically find well paying jobs in urbanized areas. The job openings occur as
the city and its infrastructure grows through government expenditure, attracting new
businesses into the area. New businesses invest in the state economy, which stimulates
economic growth. Urban areas cannot efficiently develop if the state government is of a
low quality because of government inefficiencies. If government expenditure is not used
to build roads, schools and other infrastructure, the growth process shall be hindered.
The empirical evidence from a sample of 14 states, in the time period from 1980 to
1999 supports the theoretical argument. The six explanatory variables LIT, EXPEND,
QGOI, ROADS, WORK and INVEST explain significantly the determinants of growth.
A state run by a high quality government and endowed with human capital as well as
infrastructure has the foundations from which to grow. The balance of investment and
state expenditure are key determinants of both job creation and economic growth. The
empirical results show that both absolute and conditional convergence among the states
PCNSDP exists. The results do not show conclusively that the level of convergence in
PCNSDP increased in the time period from 1990 to 1999 due to the change in economic
and political policy during the early 1990's.
The study implies the government role should be to develop human capital and
infrastructure through development expenditure. Job creation is both the role of the
government through developmental expenditure, and the population through investment.
The study implies the primary role of the population should be to increase the quality of
government by use of their democratic vote.
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My family originates from the state of Gujarat in India. I was born and raised in
England and moved to the United States in March of 1998. I graduated from the
University of Texas at Dallas with a Bachelor of Arts in economics and finance in August
of 2001. Currently I am at the University of Florida studying towards a Master of Arts in