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The absolute health income hypothesis revisited: A Semiparametric Quantile Regression Approach

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  • Thanasis Stengos

    ()
    (Department of Economics, University of Guelph)

  • Yiguo Sun

    ()
    (Department of Economics, University of Guelph.)

Abstract

This paper uses the 1998-99 Canadian National Population Health Survey (NPHS) data to examine the health-income relationship that underlies the absolute income hypothesis. To allow for nonlinearity and data heterogeneity, we use a partially linear semiparametric quantile regression model. Among more than dozen of socioeconomic variables, we find that family income, age and the food security status are the most important factors in explaining an individual’s overall functional health. The “absolute income hypothesis” is partially true; the negative aging effects appear more pronounced for the ill-healthy population than for the healthy population and when annual income is below 40,000 Canadian dollars.

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Bibliographic Info

Paper provided by University of Guelph, Department of Economics and Finance in its series Working Papers with number 0606.

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Length: 29 pages
Date of creation: 2006
Date of revision:
Handle: RePEc:gue:guelph:2006-6

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Cited by:
  1. Thanasis Stengos & Ximing Wu, 2006. "Information-Theoretic Distribution Test with Application to Normality," Working Papers 0604, University of Guelph, Department of Economics and Finance.
  2. Ignacio Moral-Arce & Stefan Sperlich & Ana Fernández-Saínz & Maria Roca, 2012. "Trends in the Gender Pay Gap in Spain: A Semiparametric Analysis," Journal of Labor Research, Springer, vol. 33(2), pages 173-195, June.

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