Causality between Per Capita Real GDP and Income Inequality in the U.S.: Evidence from a Wavelet Analysis

Shinhye Chang, Rangan Gupta and Stephen Miller
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Shinhye Chang: University of Pretoria

No 2016-14, Working papers from University of Connecticut, Department of Economics

Abstract: This study applies wavelet coherency analysis to examine the relationship between the U.S. per capita real GDP and six income inequality measures over the period 1917 to 2012. Wavelet analysis allows the simultaneous examination of correlation and causality between the two series in both the time and frequency domains. Our findings provide robust evidence of positive correlation between the growth and inequality across frequencies. Yet, directions of causality vary across frequencies and evolve with time. In the time-domain, the time-varying nature of long-run causalities implies structural changes in the two series. These findings provide a more thorough picture of the relationship between the U.S. per capita real GDP and inequality measures over time and frequency, suggesting important implications for policy makers.

Keywords: Income; Inequality; Wavelet analysis; U.S. (search for similar items in EconPapers)
JEL-codes: C49 D31 (search for similar items in EconPapers)
Pages: 26 pages
Date: 2016-09
Note: Stephen Miller is the corresponding author
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Citations: View citations in EconPapers (1)

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Related works:
Journal Article: Causality Between Per Capita Real GDP and Income Inequality in the U.S.: Evidence from a Wavelet Analysis (2018)
Working Paper: Causality between Per Capita Real GDP and Income Inequality in the U.S.: Evidence from a Wavelet Analysis (2015)
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Persistent link: https://EconPapers.repec.org/RePEc:uct:uconnp:2016-14

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