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The purpose of this paper is to examine the relationship between financial development and income inequality in India using annual data from 1982-2012.

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.

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.

The present recommend for appropriate economic and financial reforms focussing on financial inclusion to reduce income inequality in India.

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.

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?

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.

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.

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.

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.