A.K. Giri

Financial development and economic growth: empirical evidence from India

Purpose - – The purpose of this paper is to examine the relationship between financial development and economic growth in India using annual data from 1982 to 2012. Design/methodology/approach - – The stationarity properties are checked by ADF, DF-GLS, KPSS and Ng–Perron unit root tests. The long- and short-run dynamics are examined by using the autoregressive distributed lag (ARDL) approach to co-integration. Findings - – The co-integration test confirms a long-run relationship in financial development and economic growth for India. The analysis of ARDL test results reveals that both bank-based and market-based indicators of financial development have a positive impact on economic growth in India. Hence, the results support the supply-leading hypothesis and highlight the importance of financial development in economic growth. The findings also indicate that the Indian bank-centric financial sector has the potential for economic growth through credit transmission. Research limitations/implications - – The present study recommends appropriate reforms in financial markets to attain sustainable economic growth. The findings are useful for policy-makers who want to maintain a parallel expansion of financial development and growth. Originality/value - – To date, there are hardly any studies that use both market-based and bank-based indicators as proxies of financial development and analyze their role in economic growth in India. So, the contribution of the paper is to fill this gap in literature.

The impact of financial development, economic growth and energy consumption on environmental degradation

Purpose – The purpose of this paper is to investigate the impact of financial development, economic growth and energy consumption on environment degradation for Indian economy by using the time series data for the period 1971-2011. Design/methodology/approach – The stationary properties of the variables are checked by ADF, DF-GLS, PP and Ng-Perron unit root tests. The long-run relationship is examined by implementing the Autoregressive Distributed Lag bounds testing approach to co-integration and error correction method (ECM) is applied to examine the short-run dynamics. The direction of the causality is checked by VECM framework and variance decomposition is used to predict exogenous shocks of the variables. Findings – The empirical evidence confirms the existence of long-run relationship among the variables. Financial development appears to increase environmental degradation in India. The main contributors to environmental degradation are: economic growth, energy consumption financial development and ur...

Financial development and income inequality in India: an application of ARDL approach

Purpose - – The purpose of this paper is to examine the relationship between financial development and income inequality in India using annual data from 1982-2012. Design/methodology/approach - – Stationarity properties of the series are checked by using ADF, DF-GLS, KPSS and Ng- Perron unit root tests. The paper applied the auto regressive distributed lag (ARDL) bound testing approach to co-integration to examine the existence of long run relationship; and error correction mechanism for the short run dynamics. Findings - – The co-integration test confirms a long run relationship between financial development and income inequality for India. The ARDL test results suggest that financial development, economic growth, inflation aggravates the income inequality in both long run and short run. However, trade openness reduces the gap between rich and poor in India. Research limitations/implications - – The present recommend for appropriate economic and financial reforms focussing on financial inclusion to reduce income inequality in India. Originality/value - – Till date, there is hardly any study that makes a clear comparison between market-based indicator and bank based indicator of financial development in India and those examining the relationship between finance and income inequality nexus. Further there is hardly any study to include gini coefficient as a proxy for inequality for India and apply ARDL techniques of co-integration, using the basic principles of GJ hypothesis and provide short run and long run dynamics for India. So the contribution of the paper is to fill these research gaps.

Financial development and poverty reduction in India: an empirical investigation

Purpose - – The purpose of this paper is to examine the relationship between financial sector development and poverty reduction in India using annual data from 1970 to 2012. The paper attempts to answer the critical question: does financial sector development lead to poverty reduction? Design/methodology/approach - – Stationarity properties of the series are checked by using Ng-Perron unit root test. The paper uses the Auto Regressive Distributed Lag (ARDL) bound testing approach to co-integration to examine the existence of long-run relationship; error-correction mechanism for the short-run dynamics and Granger non-causality test to test the direction of causality. Findings - – The co-integration test confirms a long-run relationship between financial development and poverty reduction for India. The ARDL test results suggest that financial development and economic growth reduces poverty in both long run and short run. The causality test confirms that there is a positive and unidirectional causality running from financial development to poverty reduction. Research limitations/implications - – This study implies that poverty in India can be reduced by financial inclusion and financial accessibility to the poor. For a fast growing economy with respect to financial sector development this may have far-reaching implication toward inclusive growth. Originality/value - – This paper is the first of its kind to empirically examine the causal relationship between financial sector development and poverty reduction in India using modern econometric techniques.

Financial development and poverty reduction: panel data analysis of South Asian countries

Purpose - – The purpose of this paper is to examine the contribution of financial development to poverty reduction in 11 South Asian developing countries using panel data set over the time period 1990-2012. Design/methodology/approach - – The stationarity properties are checked by using Levin-Lin-Chu and Im-Pesaran-Shin panel unit root tests. The paper applied the Pedroni’s panel co-integration test to examine the existence of long-run relationship. The coefficients of co-integration are examined by fully modified OLS (FMOLS) and the causal link is checked by panel causality test. Findings - – The empirical results of Pedroni co-integration test confirm a long-run relationship between financial development and poverty reduction in South Asian developing economies. The findings of FMOLS method confirm a strong and positive relationship between financial development, trade openness, inflation and poverty reduction. Results of panel causality test indicate that there is a unidirectional causality running from financial development to poverty reduction variable. Research limitations/implications - – The present study recommends appropriate economic and financial reforms focussing on financial inclusion to reduce poverty in selected South Asian economies. Originality/value - – This paper is the first of its kind to empirically examine the causal relationship between financial sector development and poverty reduction in South Asian economies using modern econometric techniques.

The relationship between financial development indicators and human development in India

Purpose - – The purpose of this paper is to examine the relationship between financial development indicators and human development in India using annual data from 1980-2012. Design/methodology/approach - – The Ng-Perron unit root test is used to check for the order of integration of the variables. The long run relationship and short run dynamics are examined by implementing the ARDL bounds testing approach to co-integration. Granger’s non-causality test and variance decomposition techniques are also used to examine the impact of financial development indicators on human development. Findings - – The results confirm a long run relationship among the variables. The results of granger non causality indicate that unidirectional causality runs from financial development indicators to human development index (HDI). The variance decomposition analysis shows that among all the financial indicators, broad money supply (M3) has the largest contribution to changes in human development in India. Research limitations/implications - – The present study recommends for appropriate reforms in financial market to attain sustainable human development in India. The findings will be useful for India’s policy makers, in order to maintain the parallel expansion of financial development and human development. Originality/value - – This paper is first of its kind to empirically examine the casual relationship between financial development indicators and human capital development proxied by HDI in India by using modern econometric techniques.

Financial Structure, Interest Rate, Trade Openness and Growth: Time Series Analysis of Indian Economy:

The aim of this study is to construct a financial development index for Indian economy and to examine the impact of financial development index and trade openness on economic growth in India using annual data from 1982 to 2014. The results of autoregressive distributed lag (ARDL) approach to co-integration confirm the long-run relationship between financial development index, trade openness and economic growth in Indian economy. The results of Granger non-causality show that there is a unidirectional causality running from financial development to economic growth and bi-directional causality runs between economic growth and trade openness. The analysis of variance decomposition shows that influence of trade openness exerts the largest influence, whose steady contribution level for economic growth changes approaches to 15.48 per cent in India.

Panel data analysis of financial development, economic growth and rural-urban income inequality: Evidence from SAARC countries

Purpose The purpose of this paper is to examine the relationship between financial development and rural-urban income inequality (INQ) in South Asian Association for Regional Cooperation (SAARC) countries using panel data from 1986-2012. Design/methodology/approach The stationarity properties are checked by the LLC and IPS panel unit root tests. The paper applied the Pedroni’s panel co-integration test to examine the existence of the long-run relationship and coefficients of co-integration are examined by fully modified ordinary least squares. The short-term and long-run causality is examined by panel Granger causality. Findings The results of Pedroni co-integration test indicate that there exists a long-run relationship among the variables. The findings suggest that financial development increases rural-urban inequality whereas trade openness reduces rural-urban inequality. The empirical results of panel Granger causality indicate evidence of short-run causality confirms that economic growth and financial development causes rural-urban INQ. Research limitations/implications The present study recommends for appropriate economic and financial reforms focusing on financial inclusion to reduce rural-urban INQ in SAARC countries. Financial policies geared toward agriculture and rural population should be adopted to reduce the prevailing rural-urban INQ in SAARC region. Originality/value Till date, there is hardly any study exploring the causal relationship between financial development and rural-urban INQ for SAARC countries by using panel co-integration and causality techniques. So the contribution of the paper is to fill these research gaps in the literature.

The Impact Of Macroeconomic Indicators On Indian Stock Prices: An Empirical Analysis

Abstract The purpose of the present study is to examine the long run and the short run relationship between stock price and a set of macroeconomic variables for Indian economy using annual data from 1979 to 2014. The long run relationship is examined by implementing the ARDL bounds testing approach to co-integration. VECM method is used to test the short and long run causality and variance decomposition is used to predict long run exogenous shocks of the variables. The results confirm a long run relationship among the variables. Evidence suggests that Economic growth, inflation and exchange rate influence stock prices positively. However, crude oil price influences the stock price negatively. This implies that the increase in oil price induces inflationary expectation in the mind of investors and hence stock prices are adversely affected. The VECM result indicates that short run and long run unidirectional causality running from economic growth and FDI to stock prices in India. The result of the variance decomposition shows that stock market development in India is mostly explained by its own shocks. The Government can take steps to control the crude oil price in India and Investors’ confidence has to be gained by boosting the economic growth of the economy through appropriate policy tools.

An empirical relationship between financial development indicators and human capital in some selected Asian countries

The purpose of this paper is to investigate the relationship between financial development indicators and human capital for Asian countries using the annual data from 1984-2013.,The stationarity of the variables are checked by Levin-Lin-Chu, Im-Pesaran-Shin, Fisher-type augmented Dickey-Fuller and Philips-Perron panel unit-root tests. The Pedroni’s and Kao’s panel co-integration approaches are employed to examine the long-run relationship among the variables. To estimate the coefficients of co-integrating vectors, both panel dynamic ordinary least squares (PDOLS) and fully modified ordinary least squares (FMOLS) techniques are used. The short-term and long-run causality is examined by panel granger causality.,The Pedroni’s and Kao’s co-integration approaches support the existence of the long-run relationship among the indicators of financial development, economic growth and human capital. The PDOLS and FMOLS estimators revealed that both financial development indicators and economic growth variable act as an important driver for the increase in human capital. The results of panel granger causality indicate that causality runs from indicators of financial development, economic growth and public spending on education to human capital.,There is hardly any study that examine the impact of financial development indicators and economic growth on human capital in Asian economies, therefore the present study fill the research gap in the literature.