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Partisan Conflict and Income Distribution in the United States: A Nonparametric Causality-in-Quantiles Approach

Author

Listed:
  • Mehmet Balcilar

    (Eastern Mediterranean University)

  • Seyi Saint Akadiri

    (Montpellier Business School)

  • Rangan Gupta

    (University of Pretoria)

  • Stephen M. Miller

    (University of Nevada, Las Vegas)

Abstract

This study examines the predictive power of a partisan conflict index on income inequality. Our study adds to the existing literature by using the newly introduced nonparametric causality-in-quantile testing approach to examine how political polarization in the Unites States affects several measures of income inequality and distribution overtime. The study uses annual time-series data from 1917-2013. We find evidence of a causal relationship running from partisan conflict to income inequality, except at the upper end of the quantiles. The study suggests that a reduction in partisan conflict will lead to a more equal income distribution.

Suggested Citation

  • Mehmet Balcilar & Seyi Saint Akadiri & Rangan Gupta & Stephen M. Miller, 2017. "Partisan Conflict and Income Distribution in the United States: A Nonparametric Causality-in-Quantiles Approach," Working papers 2017-11, University of Connecticut, Department of Economics.
  • Handle: RePEc:uct:uconnp:2017-11 Note: Stephen Miller is the corresponding author
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    References listed on IDEAS

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    More about this item

    Keywords

    Partisan Conflict; Income Distribution; Quantile Causality;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration

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