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Financial Development and Income Inequality: Is There Any Financial Kuznets Curve in Iran?

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Abstract

This paper deals with the investigation of the relationship between financial development and income inequality in case of Iran. In doing so, we have applied the ARDL bounds testing approach to examine the long-run relationship in the presence of structural break in the series. The unit root properties have been tested by applying Zivot and Andrews (in J Bus Econ Stat 10:251–270, 1992) and Clemente et al. (in Econ Lett 59, 175–182, 1998) structural break tests. The VECM Granger causality approach is used to detect the direction of the causal relationship between financial development and income inequality. Moreover, Greenwood–Jovanovich (GJ) hypothesis has also been tested for Iranian economy. Our results confirm the long run relationship between the variables. Furthermore, financial development reduces income inequality. Economic growth worsens income inequality, but inflation and globalization improve income distribution. Finally, GJ hypothesis is found as well as U-shaped relationship between globalization and income inequality in case of Iran. This study might provide new insights for policy makers to reduce income inequality by making economic growth more fruitful for poor segment of population and directing financial sector to provide access to financial resources of poor individuals at cheaper cost.

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Notes

  1. Khan et al. (2014) reported that agricultural growth decreases rural poverty in Pakistan.

  2. Zaman et al. (2012) reported that financial indicators improve human development via stimulating economic activity in Pakistan.

  3. Botswana, Ivory Coast, Cameroon, Egypt, Ethiopia, Ghana, Kenya, Lesotho, Morocco, Madagascar, Mauritania, Mauritius, Malawi, Nigeria, Senegal, Sierra Leone, South Africa, Tanzania, Tunisia, Uganda, Zambia and Zimbabwe.

  4. Argentina, Armenia, Australia, Austria, Barbados, Belarus, Belgium, Bolivia, Botswana, Bulgaria, Canada, Chile, China, Colombia, Costa Rica, Croatia, Cyprus, Czech Republic, Denmark, Dominican Republic, Ecuador, El Salvador, Estonia, Finland, France, Gabon, Georgia, Germany, Greece, Guatemala, Honduras, Hungary, Ireland, Israel, Italy, Japan, Kazakhstan, Kenya, Kyrgyzstan, Latvia, Lesotho, Lithuania, Luxembourg, Macedonia, Malta, Mauritius, Mexico, Moldova, Nepal, Netherlands, New Zealand, Nicaragua, Norway, Panama, Paraguay, Peru, Poland, Portugal, Romania, Russia, Serbia and Montenegro, Slovakia, Slovenia, South Africa, South Korea, Spain, Sweden, Switzerland, Tajikistan, Turkey, Ukraine, United Kingdom, United States, Uzbekistan, Venezuela and Zambia.

  5. Algeria, Bangladesh, Bolivia, Cameroon, Chile, Colombia, Ecuador, Egypt, Ghana, Guatemala, India, Indonesia, Jamaica, Jordan, Kenya, Korea, Madagascar, Malawi, Malaysia, Mexico, Morocco, Pakistan, Peru, Philippines, Papua New Guinea, Senegal, South Africa, Sri Lanka, Syria, Thailand, Trinidad and Tobago, Turkey, Uruguay, Venezuela, Zimbabwe.

  6. The structural breaks are based on Clemente et al. (1998).

  7. The dummy for structural breaks in based on Clemente et al. (1998) unit root test.

  8. The first of these involves a plot of the cumulative sum (CUSUM) of recursive residuals against the order variable and checking for deviations from the expected value of zero. The CUSUMSQs have expected values ranging in a linear fashion from zero at the first-ordered observation to one at the end of the sampling interval if the null hypothesis is correct. In both the CUSUM and CUSUMSQ tests, the points at which the plots cross the confidence lines give some in diction of value(s) of the ordering variable associated with parameter change.

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Authors and Affiliations

  1. Department of Management Sciences, COMSATS Institute of Information Technology, Lahore, Pakistan

    Muhammad Shahbaz

  2. Faculty of Economics and Business Management, Universiti Sultan ZainalAbidin, 21300, Kuala Terengganu, Terengganu, Malaysia

    Nanthakumar Loganathan

  3. Faculty of Applied Economics, Faculty of Management, ICFAI University, Tripura, Kamalghat, West Tripura, Sadar, 799210, Tripura, India

    Aviral Kumar Tiwari

  4. Department of Economics, University Putra Malaysia, 43400, Serdang, Selangor, Malaysia

    Reza Sherafatian-Jahromi

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  1. Muhammad Shahbaz
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  2. Nanthakumar Loganathan
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Shahbaz, M., Loganathan, N., Tiwari, A.K. et al. Financial Development and Income Inequality: Is There Any Financial Kuznets Curve in Iran?. Soc Indic Res 124, 357–382 (2015). https://doi.org/10.1007/s11205-014-0801-9

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