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 urbanization. The results also lend support to the existence of environmental Kuznets curves for Indian economy. Research limitations/implications – The present study suggests that environmental degradation can be reduced at the cost of economic growth or energy efficient technologies should be encouraged to enhance the domestic product with the help of financial sector by improving environmental friendly technologies from advanced economies. Originality/value – This paper proposes to make a contribution to the existing literature through examining the relationship between financial development and environmental degradation in Indian economy during 1971-2011 by employing modern econometric techniques.

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.

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.

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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.