## INTRODUCTION

for India for a 31 year period starting from 1980-1981 up to 2010-2011 on six independent

variables: Gross Domestic Capital Formation, Net Domestic Savings, Exports, Employment,

## Gross Enrolment Ratio and Imports.

MOTIVE

Macroeconomic theory suggests that aggregate demand depends on economy’s investment,

savings, exports and imports. We have gone off the beaten track and included two

unconventional variables- the employment in the public and organized private sector and the

gross enrolment ratio. Our objective behind this has been to show how the spread of

education sector and increased employment opportunities affect the annual growth rate of

## GDP and to find out if it has had a significant impact on the economic growth of India in the

past few years.

## The reason that we have taken the data of our variables from the 1980s rather

than the 1991, post liberalization, when the major economic reforms took place is because

since 1980, India’s economic growth rate has more than doubled, rising from 1.7 percent (in

per-capita terms) in 1950-1980 to 3.8 percent in 1980-2000.India’s economic performance

during the first three decades since independence was christened the “Hindu” rate of growth,

a term connoting a disappointing but not disastrous outcome, and playing to the cliché of the

acquiescence in the present that the religion supposedly imbues, because of a greater

emphasis on the hereafter. Many studies have attributed the 1991 reforms for the spurge in

economic growth but as we have studied in or 2nd year that trigger for India’s economic

growth was an attitudinal shift on the part of the national government in 1980 in favor of

private business. The rhetoric of the reigning Congress Party until that time had been all

about socialism and pro-poor policies. When Indira Gandhi returned to power in 1980, she re-

aligned herself politically with the organized private sector and dropped her previous

rhetoric. The national government’s attitude towards business went from being outright

hostile to supportive. Indira Gandhi’s switch was further reinforced, in a more explicit

manner, by Rajiv Gandhi following his rise to power in 1984. This, in our view, was the key

change that unleashed the animal spirits of the Indian private sector in the early1980s. The

change in India in the early 1980s is accordingly best described as pro-business rather than

pro-market. Easing restrictions on capacity expansion for incumbents, removing price

controls, and reducing corporate taxes (all of which took place during the 1980s) are

examples of pro-business policies, while trade liberalization (which did not take place in any

significant form until the 1990s) is the archetypal market-oriented policy. This shift from the

socialist policies to the pro-business policies led to the economic boom after the 1980s which

were only sustained by the liberalization of the 1990s. Therefore, we aim to study the growth

of India and how the economic factors affect the annual growth rate of GDP from the 1980s

rather than 1990s, as has been done in the literature survey that we have found.

## DATA AND MODEL SPECIFICATIONS

Source - The data for the dependent and all the independent variables was obtained for the 31

Reserve Bank of India. We have taken the annual growth rate of GDP as our dependent

variable and have regressed it on six independent variables,

- GROSS DOMESTIC CAPITAL FORMATION

## Gross domestic capital formation is the addition to the capital stock within the domestic

territory of a country during a year. The surplus of production over consumption during a

economy, the faster an economy can grow its aggregate income. Increasing an economy's

capital stock also increases its capacity for production, which means an economy can produce

more. Therefore we expect a positive relationship between gross domestic capital formation

and rate of annual GDP growth because higher domestic capital formation leads to higher

investment which in turn leads to an increase in the aggregate demand.

- NET DOMESTIC SAVINGS

## Net Domestic Savings are calculated as GDP less final consumption expenditure (total

consumption).Therefore, more savings means more investment, which implies increase in

production, which leads to more demand for factor inputs, which results in more income,

which implies more demand, that leads to more investment, leading to rapid economic

growth, this again leads to increased savings. It should be noted that sustained low saving

relative to investment translates into persistent current account deficit and a deteriorating

international investment position.

- EXPORTS

## Export growth may affect output growth through positive externalities on non-exports,

through the creation of more efficient management styles, improved production techniques,

increased scale economies, improved allocated efficiency, and better ability to generate

dynamic comparative advantage. If there are incentives to increase investment and improve

technology this would imply a productivity differential in favor of the export sector (in other

words, marginal factor productivities are expected to be higher in the export sector than in the

other sectors of the economy). It is thus argued that an expansion of exports, even at the cost

of other sectors, will have a net positive effect on the rest of the economy.

- EMPLOYMENT IN PUBLIC AND ORGANISED PRIVATE SECTOR

## The relationship between unemployment and GDP is called Okun's law. It is the association

of a higher national economic output with the decrease in national unemployment. This is

because in order to increase the economic output of a country, people will need to go back to

work, thus lowering unemployment. Historically, a 1 percent decrease in GDP has been

associated with a slightly less than 2-percentage-point increase in the unemployment rate.

## Employment growth has a positive and significant impact on growth rate of GDP, but some

of the effects take a few quarters to be fully felt.

- GROSS ENROLLMENT RATIO

## The Gross Enrolment Ratio (GER) is a statistical measure used in the education sector. The

United Nations uses it to determine the number of students enrolled in school at several

different grade levels to be able to compute an education index for different countries. A

combined gross enrolment ratio (CGER), incorporating all three levels of education, is used

member states. The expected impact of a higher gross employment ratio on the growth rate of

## GDP is positive because in order to promote economic and industrial development in a

country, the essential requirement is the capacity to develop skilled manpower of good

quality in adequate number.

- IMPORTS

## A good or service brought into one country from another is called imports. Along with

exports, imports form the backbone of international trade. The higher the value of imports

entering a country, compared to the value of exports, the more negative that country's balance

of trade becomes. Therefore according to the economic theory, an increase in the amount of

imports as compared to the amount of exports of that country will lead to a negative growth

in the gross domestic product of that country. That’s why we expect a negative relationship

between the imports and growth rate of GDP in our regression analysis.

## METHODOLOGY

We plotted the annual growth rate of GDP for India over the 31 year period with respect to

each of the independent variables and the scatter that we obtained had the following shape-

## We converted our entire sample data set into log 10 and again plotted the scatter diagram and

we got the following scatter plot:

## Only a straight line could best fit into scatter plot thus obtained. Thus we reached the

conclusion that the functional form of our model was double log.

## SCATTER PLOT

MODEL AND RESULTS

The software that we used was Microsoft Excel 2007. As proved earlier the functional form

of our model is a double log model. This implies that the regression line obtained would be

analogous to the following:

Y = AX1B1. X2B2 .X3B3 .X4B4 .X5B5 . X6B6

## Where,

X1 – Rate of Gross Domestic Capital Formation (in %)

X2 – Net Domestic Savings (in Billions)

X3 – Exports (in Billions)

X4 – Employment in the public and organized private sector (in Millions)

X5 – Gross Enrolment Ratio (for both boys and girls between the ages of 6-14)

X6 – Imports (in Billions)

Taking log on both sides of the equation, we would get

Log Y = log A + B1 log X1 + B2 log X2 + B3 log X3 + B4 log X4 + B5 log X5 + B6 log X6

Now taking log A = B0 , we get

Log Y = B0 + log X1 + B2 log X2 + B3 log X3 + B4 log X4 + B5 log X5 + B6 log X6

## DESCRIPTIVE STATISTICS

- Multiple R is the correlation between the actual and the predicted values of the

dependent variable which in our case is the annual growth rate of GDP.

The value of the multiple R statistics is coming out to be .8076 or 80.76%

- R2 is the coefficient of determination. It gives the explanatory power of the regression

line i.e. the percentage of variations in the total sum of squares (TSS) which is

explained by the regression.

## Another way of interpreting R2 is the percentage of variations in the

actual and predicted values of the dependent variable that is explained by the

regression of the dependent variable on the independent variables jointly.

The R2 value obtained for the model is .652 which implies that 65.02% of the

variations in the TSS are explained by the regression. This value is sufficiently high.

- Adjusted R2 is used to compensate for the addition of variables in the model. As more

independent variables are added to the original model, unadjusted R2 will rise

indicating that a greater percentage of variations are explained by the regression.

variables in the model. The adjusted R2value is .565 or 56.5% (approx)

## EXPLAINATION OF ANOVA TABLE

- The sum of squares due to regression is .653. This is also called the explained sum of

squares or ESS.

## The mean sum of squares given in the 4th column is the sum of squares divided by the

numerator degrees of freedom i.e. ( k-1 ) , ‘k’ being the number of independent

variables including the intercept term.

The degrees of freedom here is 7-1=6

So the mean sum of squares is 0.653/6 = 0.1088

- The residual sum of squares or RSS is 0.348

## The mean sum of squares is the RSS divided by the denominator degrees of freedom

i.e. (n-k ) , ‘k’ being the number of independent variables including the intercept term

and ‘n’ being the sample size.

The degree of freedom is 31-7 = 24

The mean sum of squares is 0.348/24 = 0.01513

- The last row gives the total sum of squares which is the sum total of explained sum

of squares (ESS) and residual sum of squares (RSS).

- The 5th column gives the Fcal value for the model :

Fcal = ESS/(k-1)

## RSS/ (n-k)

= 7.504

## INTERPRETATION OF THE MODEL

log GROWTH RATE = 3.06599 +2.52338 log GDCF+0.9348 log D_SAV+1.29033 log

EXPORTS+2.2260007 log EMPLOYMENT+4.45250 log GER+0.490416 log IMPORTS

## The slope coefficients in multiple regression are referred to as the partial regression

coefficients. They capture the effect of a particular independent variable on the dependent

variable when all other variables are kept constant.

## Since our model is a double log model, the partial regression slope coefficients

are also called the partial elasticity coefficients. They measure the relative or percentage

change in the dependent variable due to a relative or percentage change in one of the

independent variables, when all others are kept constant.

- B1 = 2.523

## An increase in the rate of gross domestic capital formation (GDCF ) by 1% increases the

annual growth rate of GDP by 2.523%, all other Xi’s remaining constant. The partial

elasticity coefficient of the annual growth rate of GDP w.r.t the rate of GDCF is

2.523.

## This is backed by macroeconomic theory as an increase in the GDCF or investment will lead

have a positive impact on the growth rate of GDP.

- B2 = 0.935

## An increase in the net domestic savings by 1% increases the annual growth rate of GDP by

0.935%, all other Xi’s remaining constant.

The partial elasticity coefficient of the annual growth rate of GDP w.r.t net domestic savings

is 0.935.

## An increase in savings would mean an increase in the funds available to b transformed into

gross capital formation which would again have a positive impact on the annual growth rate

of GDP.

- B3 = 1.290

## An increase in the exports by 1% increases the annual growth rate of GDP by 1.29%, all

other Xi’s remaining constant.

The partial elasticity coefficient of the annual growth rate of GDP w.r.t exports is 1.29.

## This is inconsistent with economic theory that states that expansion of exports, even at the

cost of other sectors will have a positive impact on the economy.

- B4 = 2.226

## An increase in the employment in the public and organised private sector by 1% increases the

annual growth rate of GDP by 2.226%, all other Xi’s remaining constant.

The partial elasticity coefficient of the annual growth rate of GDP w.r.t the employment in

the public and organised private sector is 2.226.

- B5 = 4.453

## An increase in the gross enrolment ratio by 1% increases the annual growth rate of GDP by

4.453%, all other Xi’s remaining constant.

The partial elasticity coefficient of the annual growth rate of GDP w.r.t the gross enrolment

ratio is 4.453.

## The expected impact of a higher gross enrolment ratio on the country’s GDP is positive

because in order to promote industrial and economic development, the population has to be

literate. Again the effect is consistent.

- B6 = -0.490

## An increase in the imports by 1% decreases the annual growth rate of GDP by 0.490%, all

other Xi’s remaining constant.

The partial elasticity coefficient of the annual growth rate of GDP w.r.t imports is -0.490.

## Again this is consistent with economic theory which states that an increase in imports will

have a negative impact on the growth rate of GDP.

## HYPOTHESIS TESTING

- TESTS OF SIGNIFICANCE

- FOR B1

HO : B1 = 0

## HA : B1 is not equal to 0

The p- value is 0.029967.

## This means that the null will be rejected at 5%, 10% and 25% levels of significance. This

means that the rate of GDCF has a significant impact on the annual growth rate of GDP in

## India.

- FOR B2

HO : B2 = 0

## HA : B2 is not equal to 0

The p- value is 0.230416.

## The null will not be rejected at 1%, 5% or 10% levels of significance.

But the null will be rejected at 25% level of significance.

This means that net domestic savings have a significant impact on the annual growth rate of

GDP in India.

A possible reason why the null was rejected at 25% instead of the conventionally

used levels of significance is because of the existence of a high degree of multi collinearity in

the data set.

## There was the existence of a strong linear relationship between net domestic savings and

GDCF and exports.

- FOR B3

HO : B3 = 0

## HA : B3 is not equal to 0

The p- value is 0.100676.

## The null hypothesis is rejected at 25% level of significance which implies that exports do

have a significant impact on the annual growth rate of GDP in India.

## We think that this result can be again attributed to multicollinearity and the fact that India has

been running a trade deficit for the time period we have considered.

- FOR B4

HO : B4 =0

## HA : B4 is not equal to 0

The p- value is 0.023244.

## The null is rejected at 5%, 10% as well as 25% levels of significance indicating that

employment does have a significant impact on the annual growth rate of GDP in India.

- FOR B5

HO : B5 = 0

## HA : B5 is not equal to 0

The p- value is 0.000558.

## The null hypothesis is rejected at 1%, 5%, 10% as well as 25% levels of significance.

This implies that the gross enrolment ratio does have a significant impact on the annual

growth rate of GDP in India.

- FOR B6

HO : B6 = 0

## HA : B6 is not equal to 0

The p- value is 0.343266 which is very high and is not rejected even at 25% level of

significance. This means that imports doesn’t have a significant impact on the annual growth

rate of GDP in India. Imports are thus insignificant.

- JOINT TEST OF SIGNIFICANCE

HO : R2 = 0

## HA : R2 is not equal to 0

The joint test of significance or the F-test tests the null hypothesis which states that the

independent variables jointly do not have a significant impact on the dependent variable,

against the alternative which states that the independent variables jointly have a significant

impact on the dependent variable.

Numerator degrees of freedom = (k-1) = 7-1 = 6. Denominator degrees of freedom = (n-k) =

31-7 = 24. The tabulated F-statistic at is significant at 5% and 10% level of significance:

## The independent variables are also jointly significant

CONCLUSION

We found that Gross Domestic Capital Formation, Net Domestic Savings, Exports,

Employment in the public and organised private sectors and Gross Enrolment Ratio have had

a significant impact on the annual growth rate of GDP for India during the period considered.

## All the above variables are significant at 25% level of significance and a few of them are

significant at levels of significance as low as 1% and 5%, indicating a good fit.

## The results for all the independent variables are consistent with economic theory except for

imports which came out to be insignificant. This was a surprising result as imports have a

negative effect on a country’s GDP according to macroeconomic theory. Dropping imports

which is why we chose to include imports in our final model despite its insignificance. We

observed a very high degree of multicollinearity between the imports and the rest of the

independent variables, its value ranging from 95% to 99%. We thus concluded that it was

possible that the presence of a high degree of multicollinearity in the data set and a small

sample size could have been the possible reasons as to why imports didn’t have a significant

impact on India’s GDP. On the whole, we found that India’s GDP has seen an upward trend

in the time period considered except for a few years in between when it experienced a

downward trend.This can be attributed to the ever increasing rate of GDCF, net domestic

savings, exports, employment and the gross enrolment ratio.

## Work Cited

“Gross Fixed Capital Formation in Infrastructure, 2013.” Planning Commission of India.

4 Aug. 2014. <http://planningcommission.nic.in/data/datatable/0814/table_40.pdf>

“Capital Formation by Type of Assets and by Type of Institution (in Rs. Crore) and Rates

w.r.t. Expenditure on GDP”. Planning Commission of India. 4 Aug. 2014.

<http://planningcommission.nic.in/data/datatable/0814/table_27.pdf>

“Rate of Growth of GDP by Industry of Origin at Factor Cost & at 2004-05 Prices.” Planning

Commission of India. 4 Aug. 2014.

<http://planningcommission.nic.in/data/datatable/0814/table_12.pdf>

“Selected Socio-Economic Statistics India, 2011.” Government of India Ministry of Statistics

and Programme Implementation. October 2011.

<http://mospi.nic.in/mospi_new/upload/sel_socio_eco_stats_ind_2001_28oct11.pdf>

“India - Macro-economic Summary: 1999-00 to 2013-14.” Planning Commission of India.

31 May. 2014. <http://planningcommission.nic.in/data/datatable/0814/table_1.pdf>

“Report on Employment & Unemployment Survey 2011-2012.” Government of India,

Ministry of Labour & Employment. 13 Nov 14.

<http://labourbureau.nic.in/rep_1.pdf>

“Domestic Savings by Type of Institution and % Rate of Savings to GDP.” Planning

Commission of India. 4 Aug. 2014.

<http://planningcommission.nic.in/data/datatable/0814/table_28.pdf>

APPENDICES

Summary Statistics: