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Empirical Economics

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01.08.2016

Financial development and income inequality: a panel data approach

verfasst von: Sebastian Jauch, Sebastian Watzka

Erschienen in: Empirical Economics | Ausgabe 1/2016

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Abstract

We analyzed the link between financial development and income inequality for a broad unbalanced dataset of up to 138 developed and developing countries over the years 1960–2008. Using credit to GDP as a measure of financial development, our results reject theoretical models predicting a negative impact of financial development on income inequality measured by the Gini coefficient. Controlling for country fixed effects, possible endogeneity problems, GDP per capita and other control variables, we find that financial development increases income inequality. These results are robust to different measures of financial development, econometric specifications and control variables.

Vorheriger Artikel Evidence on copula-based double-hurdle models with flexible margins

Nächster Artikel A class of demand systems satisfying global regularity and having complete rank flexibility

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Demirgüç-Kunt et al. (2009) provide a brief overview of the relation between microfinance and income inequality and also cite studies that do not confirm that microfinance lowers inequality.

See, e.g., the monograph of Wilkinson and Pickett (2011) for an extensive discussion of the problems posed by high and rising inequality for modern economies and societies.

A more detailed discussion of these papers is available in an extended version of this research online.

Other datasets that claim to have a broad coverage and that are widely used in cross-country studies include different measures of the Gini, e.g., household consumption or income, household or per person levels and gross or net income. The Solt database is in that sense the most comprehensive standardized dataset on income inequality to our knowledge.

Table A.3 in the Online Appendix provides an overview of our measures for financial development and income inequality for all countries in our sample. Figure A.1 in the same Appendix provides a 3D chart of income inequality against GDP p.c. and financial development.

We have done various robustness checks using a limited dataset that excludes credit booms and financial centers. These checks confirmed our results. Please see our robustness section below.

We do acknowledge that these countries have shown excessive provision of private credit or serve as financial hubs. Excluding the 5 year term 2005–2009 does, however, not change the sign of the coefficients and has no substantial effect on the significance of our results.

See Tables A.1 and A.2 in the Online Appendix.

Detailed results are available in an extended Working Paper version of this research online at http://www.cesifo-group.de/de/ifoHome/publications/working-papers/CESifoWP/CESifoWPdetails?wp_id=17407941.

This is best shown by the French motto “liberté, egalité, fraternité” which of course includes equality. This motto shows that the origin of the legal system is not independent of inequality and that the legal system is therefore not a good instrument because it directly influences inequality. Legal origin may be a good instrument for financial development when studying growth, but it is not suitable for an investigation of the influence of financial development on inequality.

There are different approaches on how to proceed with yearly data. Yearly data may represent cyclical movements, whereas using a five-year average yields a more balanced panel, but at the same time means a loss in the number of observations. To compare the results of this larger and more suitable dataset with previous work, we focus on five-year averages. Most variables move slowly over time. Therefore, differences between five-year averages show more variation than yearly data and smooth the effect of business cycles. Yearly data and five-year averages lead to similar coefficients, and we therefore report five-year averages only.

See in particular the recent debate on long-term trends in inequality as initiated, e.g., by Piketty (2014). Please see also the discussion by Milanovic and Alvaredo in Finance and Development, IMF, Sept 2011.

We would like to thank a referee for pointing these robustness tests out to us. Results are available from the authors upon request.

This value ranges from 0.176 to 0.275 depending on the subsample and specification (see Table 3).

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Titel: Financial development and income inequality: a panel data approach
verfasst von: Sebastian Jauch
Sebastian Watzka
Publikationsdatum: 01.08.2016
Verlag: Springer Berlin Heidelberg
Erschienen in: Empirical Economics / Ausgabe 1/2016
Print ISSN: 0377-7332
Elektronische ISSN: 1435-8921
DOI: https://doi.org/10.1007/s00181-015-1008-x

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