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

Listed author(s):
  • Shinhye Chang

    (University of Pretoria)

  • Rangan Gupta

    (University of Pretoria)

  • Stephen M. Miller

    (University of Nevada, Las Vegas and University of Connecticut)

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.

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File URL: http://web2.uconn.edu/economics/working/2016-14.pdf
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Paper provided by University of Connecticut, Department of Economics in its series Working papers with number 2016-14.

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Length: 26 pages
Date of creation: Sep 2016
Handle: RePEc:uct:uconnp:2016-14
Note: Stephen Miller is the corresponding author
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University of Connecticut 365 Fairfield Way, Unit 1063 Storrs, CT 06269-1063

Phone: (860) 486-4889
Fax: (860) 486-4463
Web page: http://www.econ.uconn.edu/

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