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Heteroskedasticity-Robust Elasticities in Logarithmic and Two-Part Models

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  • Tom Hertz

Abstract

Logarithmic models are widely used to study highly skewed positive outcomes, either alone or in combination with an equation that first distinguishes between zero and non-zero values (the two part model). A well-known drawback of such models is that to obtain marginal effects that pertain to the arithmetic mean, rather than the mean of logs, we must exponentiate, and this retransformation is complicated in the presence of heteroskedasticity. This paper presents a simple method for correcting estimated elasticities for the effects of heteroskedasticity, in both log-linear and log-log (constant elasticity) equations. An example, drawing on Bulgarian farm survey data, demonstrates that this correction leads to significantly different estimates of the elasticity of expenditures on agricultural inputs with respect to land area and the age of the household head.

Suggested Citation

  • Tom Hertz, 2007. "Heteroskedasticity-Robust Elasticities in Logarithmic and Two-Part Models," Working Papers 2007-19, American University, Department of Economics.
    • Handle: RePEc:amu:wpaper:1907
    DOI: 10.17606/nh01-wr03
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    File URL: https://doi.org/10.17606/nh01-wr03
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    References listed on IDEAS

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    1. Mullahy, John, 1998. "Much ado about two: reconsidering retransformation and the two-part model in health econometrics," Journal of Health Economics, Elsevier, vol. 17(3), pages 247-281, June.
    2. John Mullahy, 1998. "Much Ado About Two: Reconsidering Retransformation and the Two-Part Model in Health Economics," NBER Technical Working Papers 0228, National Bureau of Economic Research, Inc.
    3. Tom Hertz, 2009. "The effect of nonfarm income on investment in Bulgarian family farming," Agricultural Economics, International Association of Agricultural Economists, vol. 40(2), pages 161-176, March.
    4. Duan, Naihua, et al, 1984. "Choosing between the Sample-Selection Model and the Multi-part Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(3), pages 283-289, July.
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    1. Toni Mora & Joan Gil & Antoni Sicras-Mainar, 2015. "The influence of obesity and overweight on medical costs: a panel data perspective," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 16(2), pages 161-173, March.
    2. Jay Dev Dubey, 2021. "Measuring Income Elasticity of Healthcare-Seeking Behavior in India: A Conditional Quantile Regression Approach," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(4), pages 767-793, December.
    3. Toni Mora & Joan Gil & Antoni Sicras-Mainar, 2012. "The Influence of BMI, Obesity and Overweight on Medical Costs: A Panel Data Approach," Working Papers 2012-08, FEDEA.
    4. Uehleke, Reinhard, 2016. "The role of question format for the support for national climate change mitigation policies in Germany and the determinants of WTP," Energy Economics, Elsevier, vol. 55(C), pages 148-156.
    5. Toni Mora & Joan Gil & Antoni Sicras-Mainar, 2012. "The Influence of BMI, Obesity and Overweight on Medical Costs: A Panel Data Approach," Working Papers 2012-08, FEDEA.

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