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Partially Adaptive Econometric Methods and the Modern Obesity Epidemic

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  • Scott A. Carson
  • James B. McDonald

Abstract

Assumptions about explanatory variables and errors are central in regression analysis. For example, the well-known method of ordinary least squares yields consistent and efficient estimators if the underlying error terms are independently, identically, and normally distributed. Additionally, the conditional distribution of the dependent variable is symmetric. The modern obesity epidemic is a well-known health dilemma where the BMI distribution was initially positively skewed but has become more symmetric, which may affect inferences about health and public resource allocation. This study applies partially adaptive estimation methods with flexible error distributions to account for possible skewness and leptokurtosis in the distribution of BMI.

Suggested Citation

  • Scott A. Carson & James B. McDonald, 2018. "Partially Adaptive Econometric Methods and the Modern Obesity Epidemic," CESifo Working Paper Series 7058, CESifo.
    • Handle: RePEc:ces:ceswps:_7058
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    References listed on IDEAS

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    7. Hansen, Bruce E, 1994. "Autoregressive Conditional Density Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 35(3), pages 705-730, August.
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    More about this item

    Keywords

    obesity epidemic; partially adaptive estimation; skewed generalized T distribution;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • D13 - Microeconomics - - Household Behavior - - - Household Production and Intrahouse Allocation
    • J13 - Labor and Demographic Economics - - Demographic Economics - - - Fertility; Family Planning; Child Care; Children; Youth

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