Abstract
This chapter investigates finance–growth relationship at district level and attempts to provide policy implications relating to access to financial services, hence, growth in local economy. The districts with higher financial development also experience higher growth rate of per capita gross district domestic product and per capita gross district domestic product (GDDP) during 2004–05 to 2010–11. We found relatively stronger effect of deposit than credit on economic growth that highlights the critical role of branch access in unbanked locations in district economy. Our findings implicate the importance of bottom-up approach of decision-making in which local financial conditions are as significant as financial development at macro-level financial development in the process of growth. Economic reforms played a significant role to this effect through various policy instruments meant for local economy. Banks and financial institutions became instrumental to foster savings and hence investments by providing better financial access to local people. This, in turn, augmented economic growth in local economy. While analysing the role of financial development, we also find positive and significant effect of human capital on growth that may activate alternative channels of growth and production which are less finance-intensive.
Samaresh Bardhan acknowledges invaluable contributions of Prof. Manoj Kumar Sanyal to teaching economics and shaping a better understanding of the subject. The author also acknowledges his unforgettable guidance, support, encouragement and extraordinary kindness.
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Notes
- 1.
Recognising importance of banks in development process, Government of India took several initiatives such as (i) bank nationalisation: 14 largest commercial banks were nationalised in 1969 and six more banks were nationalised in 1980, (ii) priority sector lending targets under which a fraction of bank credit is channelised towards agriculture and small-scale sector, (iii) branch licensing policy under which a bank, willing to open a branch in already banked location, is required to open four new branches in unbanked locations. Under priority sector lending programme, 40% of adjusted net bank credit is provided to priority sectors of agriculture and small-scale sector industry, and separate targets are fixed for different sectors.
- 2.
Even though states of Bihar and Uttar Pradesh were bifurcated in the year 2000, these states are still considered to be the most populous states of India.
- 3.
These inferences are drawn from our compiled data set.
- 4.
- 5.
Patrick (1966) characterised the finance–growth relationship in two hypotheses: demand-following and supply-leading. Under demand-following hypothesis, economic growth generates demand for financial services which leads to greater financial development; under supply-leading hypothesis, financial development leads to faster economic growth.
- 6.
In 1969, 14 of the largest commercial private sector banks were nationalised followed by another round of bank nationalisation of six banks in 1980; it was primarily done to ensure timely and cost-effective availability of banking services to all sections of the society.
- 7.
Sample consists of districts in twelve states of Andhra Pradesh, Assam, Bihar, Karnataka, Kerala, Madhya Pradesh, Maharashtra, Odisha, Punjab, Rajasthan, Uttar Pradesh and West Bengal. During the period under investigation, few new districts were created bifurcating existing districts. In order to maintain continuity in data set, we dropped those districts which were bifurcated or newly created during the study period.
- 8.
Gross district domestic product (GDDP) is defined as the money value of all goods and services produced during a given period of time, within the boundary of a district.
- 9.
Pradhan Mantri Jan Dhan Yojna (PMJDY) is scheme initiated by Prime Minister (Pradhan Mantri) of India for financial inclusion which is named on Public Money (Jan Dhan).
- 10.
Lower credit–deposit ratio may also indicate higher reserve requirements of RBI which leads to lower percentage of deposits, available for lending purposes as it happened during 1980s in Indian financial system.
- 11.
It is argued that district-level data across states are not strictly comparable. However, this problem is addressed partially by analysing available data state by state (Table 12.1). Indira et al. (2002) focused on income and poverty estimates at the district level and found that in some states, commodity producing sectors are considered as the sources of output in districts. In others states, both non-commodity producing sectors and commodity producing sectors are considered in order to get a measure of income and output. Services sector is also not considered due to non-availability of estimates of income accrued in a district. Due to these various conceptual differences, district-level data of GDP across states may not be strictly comparable.
- 12.
As bigger districts are expected to have higher number of crimes, we normalise the data by considering number of crimes per 100,000 populations such that meaningful comparisons can be obtained between districts of sample states.
- 13.
Net enrolment ratio (NER) is defined as ratio of number of children enrolled in school to total number of children in that age group. Number of enrolment in primary schools corresponds to enrolment in class I–V and upper primary enrolment includes enrolment in class VI–VIII. Although high enrolment is one of the policy targets of government, GER may be higher than 100 because of repeating students or underage students who are studying in higher classes as against their age category. Therefore, net enrolment ratio can be considered as a better proxy of human capital in comparison to GER.
- 14.
Land acquisition policy in a state very often prevents infrastructure projects to be initiated and its effective implementation takes a long time. One notable example is POSCO steel project by South Korean steel firm to be started in Jagatsinghpur district of Odisha, worth INR 510 billion. The Memorandum of Understanding (MoU) for the project was signed in 2005 and this project is yet to take off even by 2017.
Source: http://www.thehindu.com/news/national/other-states/in-odisha-fresh-row-brewing-over-posco-land/article18516063.ece (Accessed: 31st May, 2018).
- 15.
We also conducted state-specific panel GMM regression corresponding to Tables 12.3 and 12.4. However, we present the coefficient estimates on financial development (DEPOSIT, CREDIT and CDR) with 90% CI in Figs. 12.6 and 12.7 of Appendix. We observe results similar to those observed in Tables 12.3 and 12.4 with DEPOSIT appearing as most strongly associated with INCOME and are statistically significant in majority of states with mixed results for CDR.
- 16.
Two commonly used ways of reducing instrument counts are: reducing number of lags taken as instruments and second by collapsing the instruments suggested by Roodman (2009b). We preferred second option in this paper as there were lesser time points available to be used as instruments.
- 17.
In Tables 12.8 and 12.9 of Appendix, we reproduce results of Tables 12.3 and 12.4, applying two-step estimation procedure along with collapse option and observe no noticeable change in coefficient sign and significance in majority of the explanatory variables. Tables 12.10 and 12.11 show the results of one-step estimation, without using collapse option and included year dummies as the explanatory variable. This observation is based on the premise that certain changes in income per capita and growth may be driven solely be temporal pattern irrespective of the effects of explanatory variables. This again shows robustness of the results corresponding to positive and significant effect of deposit per capita on per capita income and growth. Credit–deposit ratio is still statistically insignificant, and credit is no longer remains statistically significant.
- 18.
- 19.
As on 23 May 2018. Source: www.pmjdy.gov.in (Accessed 31.5.2018).
- 20.
Source: https://globalfindex.worldbank.org/node (Accessed: 31.5.2018).
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Appendix
Appendix
See Tables 12.7, 12.8, 12.9, 12.10, 12.11 and Figs. 12.6, 12.7.
Note lndeposit: natural logarithm of district-wise deposit per capita; lncredit: natural logarithm of district-wise credit per capita; cdratio: credit-deposit ratio. Above coefficients correspond to state-specific panel GMM regression as specified in Table 12.3, only the coefficients of financial development are shown along with 90% confidence interval. As the data for Assam was available for one year, its panel estimation results are not available. Coefficient estimates are plotted using coefplot command (Jann 2014)
State-wise verses overall coefficient plots of financial development (a lndeposit, b lncredit, c cdratio) on growth.
Note lndeposit: natural logarithm of deposit per capita; lncredit: natural logarithm of credit per capita; and cdratio: credit-deposit ratio. Above coefficients correspond to state-specific panel GMM regression as specified in Table 12.4, only the coefficients of financial development are shown along with 90% confidence interval. As the data for Assam was available for one year, its panel estimation results are not available. Coefficient estimates are plotted using coefplot command of Jann (2014)
State-wise verses overall coefficient plots of financial development (a lndeposit, b lncredit, c cdratio) on income.
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Bardhan, S., Sharma, R. (2019). Does Local Financial Development Matter for Growth? Evidence from Indian Districts. In: Biswas, P., Das, P. (eds) Indian Economy: Reforms and Development. India Studies in Business and Economics. Springer, Singapore. https://doi.org/10.1007/978-981-13-8269-7_12
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