Essay: Financial development and income inequality in India

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  • Subject area(s): Finance essays
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  • Published on: November 15, 2017
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The Research Paper “Financial development and income inequality in India: an application of ARDL approach” published in The International Journal Of Social Economics by Madhu Sehrawat and AK Giri from the Department of Economics and Finance, Birla Institute of Technology and Science, Pilani, India, have carried out a pioneering work in the finding out the relationship between “Financial development and Income Inequality” and “Financial Development and inequality reduction” through employing various Statistical methods, mainly Auto Regressive Distributed Lag(ARDL) and other methods such as ADF, DF-GLS, KPSS and several more.
 
2.0 OBJECTIVES AND RESEARCH QUESTIONS

2.1 The main objective of the paper as mentioned earlier is to examine the relationship between financial development and income inequality in India mostly utilising the annual date from the period of 1982-2012.The main purpose though as claimed by Sherawat and Giri is that there is a deficit of study in this field that has made a clear comparison between bank based and market based indicator of financial development in India and that of examining the relationship between finance and income inequality, where this paper has employed Gini Coefficient in the study as a delegate for the measurement of inequality for India mainly using the techniques of ARDL for co integration along with GJ hypothesis to provide short run and long run dynamics for India.

2.2 The major Research Questions faced by the researchers being., Does the Inverse Relation between Income Inequality and Financial development hold true for India? If it does then, What could be the relative effect of major economic Indicators such as GDP , Inflation Rate, Trade and CPI on the Income Inequality? The research tries to methodically solve and answer these questions long with many other.

3.0 METHODOLOGY

3.1 The researchers followed the methodology of co integrating of the model specification and data with the ARDL technique, where the model specification is the Gini Coefficient(GINI) which measures the inequality in the income which is derived from a statistical summation of various Variable factors which include Real GDP per capita which represents the size of the economic activity and a deputy for the growth momentum of the economy, Consumer price index as a delegate for Consumer price and TRADE((Exports+ Imports)/GDP) which helps in capturing the impact of trade openness on inequality of income and Financial Deepening where its impact is considered on steady state distribution of income.

3.2 The methodological process is continued further where the above mentioned model specifications is further worked upon by using the tool of Greenwood and Jovanovic Hypothesis (GJ Hypothesis), where the hypothesis asserts that the fixed costs associated with financial accessibility from the institutions prevent low income individuals from benefitting from them, where the hypothesis assumes that poor individuals save less and thus accumulating wealth more slowly, where therefore the gulf between various income groups gradually widens which increases income.

3.3 After the usage of GJ hypothesis the data is now co-integrated with ARDL where it empirically analyses the long run relationship and interaction of income inequality with financial development and other control variables. the ARDL method is adopted for three main reasons. Firstly, the bound test is simple as opposed to other multivariate co-integration techniques and also allows co-integrating relationship to be estimated by Ordinary Least Squared(OLS) once the lag order is selected.Secondly, the bound test procedure does not require the pre testing of the variables included in the model for unit root, where otherwise the predictive power will be lost. Third, the test is relatively more efficient in small sample data sizes as is the case of this study. The error correction method integrates the short run dynamics with long run equilibrium without losing long run information.

4.0 RESULTS AND FINDINGS

4.1 After the usage of the above mentioned methods, the variables of Credit, Financial Development, CPI, GDP and Trade to that of GINI Co-efficient indicated that there was an observed that bank-based financial deepening, inflation, trade and economic growth indicators leads to income inequality, but that is not the case of the Vice- versa .i.e., Income inequality doesn’t lead to the aforementioned factors. But, also there was no evidence found between market based financial deepening and Inequality in India. The researchers argue this could be due to the non- availability of data of Stock Exchanges except that of Bombay Stock Exchange(BSE), where the data of market based financial deepening is only partial nature as it has considered only the market capitalisation of Bombay stock exchange. The measure also suffers from the limitation of excluding funds raised in the primary segment of the capital market due to non-availability of data for the entire period of 1982- 2012.

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