Chapter 5 Summary of Findings, Conclusion and Policy Suggestions 129
5.2 Summary of Findings
5.2.1 Institutional Environment: Interstate Differences
i. The Market Sizes of Indian states vary widely. Per capita NSDP, which is one of the components of the size of the market, varies from fifteen thousand five hundred six (15506) to one lakh thirty seven thousand four hundred one (137401). Similarly, the percentage of the population living in the urban region differs from ten percent (10.112) to sixty six percent (65.893). These differences across the regions finally lead to the variability in the opportunities for the entrepreneurial activities in terms of the relative opportunity scores.
ii. The credit environment is also quite different across the Indian states. The credit- deposit ratio of the scheduled banks is as low as 17.72 and high up to 121.75.
Interestingly, there are only five states (Andhra Pradesh, Maharashtra, Punjab, Rajasthan and Tamil Nadu) out of 28 which have a Credit Deposit ratio higher than the all India average (78.9).
iii. The Gross Enrolment Ratio in higher education in India is 23 and there are 13 states having the values less than this average. But, there are some states like Tamil Nadu having a GER of 43.
iv. The study finds huge differences in terms of the accessibility of the masses to the various sources of information (Computer with Internet, Television, and Radio) across the states of India.
v. In terms of the security of lives and property against physical and economic offences, Indian states show different performances. There are some states like Kerala having a crime rate of 197, in terms of the physical crimes; on the other hand, there is a state like Nagaland having a crime rate of only eleven. Similarly, while in Tamil Nadu, there is about seventy percent recovery of the stolen property, in Manipur only five percent of the stolen property could be recovered.
Some states with better opportunity condition have a worse security environment, at the same time there are states having both better opportunity and security condition.
vi. The overall institutional environmental view is different from the individual performances in terms of the various indicators. These differences are seen among the states irrespective of geography and location of the state. It is further observed that while a state performs extremely well in certain indicators, its performances are not satisfactory in others. One cannot say that states with higher average institutional quality scores perform better in all respects than that of states with lower average institutional quality scores.
vii. Every region or states has its own strengths and weaknesses. However, any state can improve its entrepreneurial climate and thereby entrepreneurial performance
by addressing specific ‘bottlenecks’. Thus, the detailed information about the performances of the states in terms of the various indicators is important.
5.2.2 Institutional Environment and Industries (Factories)
i. The series of PFB adjusted institutional quality scores shows a positive and significant relationship with the series of number of factories per million populations. On the basis of the results obtained in the regression analysis, it is observed that the institutional environmental quality influences the entrepreneurial level of a state in a significant manner.
ii. In the regression analysis with different control variables, the institutional quality score yields a statistically significant positive coefficient suggesting that a better institutional environment is always important for entrepreneurship. It appears as a significant determinant of entrepreneurship measured through the number of factories per million populations.
iii. The bootstrap linear regression results are not significantly different from the ordinary least squares regression therefore; they validate the general OLS results.
iv. While all the sub-indices (index of opportunity, index of availability and index of security) show a positive effect on the number of factories per million populations, the environment of availability has the maximum effect with higher significance level.
v. The panel regression technique (Between Regressions) also indicates that the differences in institutional quality between the states of India significantly influence the number of factories between them.
5.2.3 Institutional Environment and MSMEs
i. A positive and significant association is found between the series of institutional quality scores and the series of number of MSMEs per million populations across the various states of India.
ii. On the basis of the results obtained in the OLS regression analysis, it is observed that the institutional environmental quality influences the entrepreneurial level (Number of MSMEs) significantly through the cross-sections of the Indian states.
iii. On the basis of the regression results with different control variables, it is found that the institutional quality score yields a statistically significant positive coefficient. Control variables do not decline the significance of the better institutional environment quality. Though some variables show positive coefficients with respect to the number of MSMEs, they are not significant.
iv. In the bootstrap linear regression results, the significance level of institutional environment quality as a determinant of the number of MSMEs goes down (from 5% to 10%).
v. Both the opportunity and the availability appear as significant factors in the determination of the number of MSMEs in a region or state in the OLS regression.
However, when bootstrap regression is used; it is only the availability, which appears as significant factor. On the other side, index of security though has a positive impact, does not appear as a significant factor in the determination of the number of MSMEs.
vi. The availability of credit, education and the information are more consistent and important factor in the development of the entrepreneurship in any region either in the form of factories or in the form of MSMEs.
vii. The panel regressions indicate that the differences in institutional quality between the states of India are significant in determining the differences in entrepreneurship among them in terms of the number of MSMEs.
Thus, both the objectives of the study: (1) To have an overview of the institutional environment differences across the states of India in the context of entrepreneurship and (2) To examine the relationship between the quality of institutions and the entrepreneurship in India across its states, are fulfilled through this study.