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Opening a can of worms: the pitfalls of time-series regression analyses of income inequality

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  • Simon Parker

Abstract

This paper argues that time-series regression analysis is of only very limited use for understanding the determinants of income inequality. The argument is based on a combination of results from the time series econometrics literature and several characteristics of inequality itself, principally nonstationarity of the data in most inequality regression models, and the weak theoretical foundations underlying the models. A sample of postwar US data is used to illustrate the problems involved.

Suggested Citation

  • Simon Parker, 2000. "Opening a can of worms: the pitfalls of time-series regression analyses of income inequality," Applied Economics, Taylor & Francis Journals, vol. 32(2), pages 221-230.
  • Handle: RePEc:taf:applec:v:32:y:2000:i:2:p:221-230
    DOI: 10.1080/000368400322903
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    Cited by:

    1. Niko Gobbin & Glenn Rayp, 2008. "Different ways of looking at old issues: a time-series approach to inequality and growth," Applied Economics, Taylor & Francis Journals, vol. 40(7), pages 885-895.
    2. Gil-Alana, Luis A. & Škare, Marinko & Pržiklas-Družeta, Romina, 2019. "Measuring inequality persistence in OECD 1963–2008 using fractional integration and cointegration," The Quarterly Review of Economics and Finance, Elsevier, vol. 72(C), pages 65-72.

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