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Nonlinearity in medical expenditures: a new semiparametric approach


  • Yanqin Fan
  • Dong Li
  • Qi Li


Research in empirical health economics has found that the relationship between medical expenditures and age, income and other variables can be highly nonlinear. Moreover, men and women can have quite different medical expenditure patterns due to their differences in life expectancy. Thus it may be difficult to find an appropriate parametric model to capture the highly complicated nonlinearity in medical expenditures, and introducing a simple gender dummy variable in a parametric model may not reveal all the medical expenditure differences between men and women. This study takes a semiparametric approach. In particular, an additive partially linear specification is employed to study the relationship between medical expenditures and age, income, gender and other individual characteristics. Using data from the National Medical Expenditure Survey, the results indicate that the semiparametric approach taken in this study is very promising. They confirm that medical expenditures are nonlinear in income and age, and that men and women have quite different medical expenditure patterns.

Suggested Citation

  • Yanqin Fan & Dong Li & Qi Li, 2004. "Nonlinearity in medical expenditures: a new semiparametric approach," Applied Economics, Taylor & Francis Journals, vol. 36(9), pages 911-916.
  • Handle: RePEc:taf:applec:v:36:y:2004:i:9:p:911-916
    DOI: 10.1080/0003684042000233122

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    References listed on IDEAS

    1. David M. Cutler & Louise Sheiner, 1998. "Demographics and Medical Care Spending: Standard and Non-Standard Effects," NBER Working Papers 6866, National Bureau of Economic Research, Inc.
    2. Ai, Chunrong & McFadden, Daniel, 1997. "Estimation of some partially specified nonlinear models," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 1-37.
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    Cited by:

    1. Hupfeld, Stefan, 2009. "Rich and healthy--better than poor and sick?: An empirical analysis of income, health, and the duration of the pension benefit spell," Journal of Health Economics, Elsevier, vol. 28(2), pages 427-443, March.
    2. Paradiso, Antonio & Kumar, Saten & Lucchetta, Marcella, 2014. "Investigating the US consumer credit determinants using linear and non-linear cointegration techniques," Economic Modelling, Elsevier, vol. 42(C), pages 20-28.

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