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Estimating log models: to transform or not to transform?

Manning, Willard G, Mullahy, John·2001·Journal of Health Economics
DOI 10.1016/s0167-6296(01)00086-8
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  • The bias in the re-transformation can be even more significant in the presence of heteroscedasticity.

    “The bias in the re-transformation can be even more significant in the presence of heteroscedasticity, see Manning and Mullahy (2001).”

    From Clearance Pricing Optimization for a Fast-Fashion Retailer (2012) · cites this paper as Manning and Mullahy (2001)

    The Abstract (page unavailable) says heteroscedasticity can lead to appreciable bias for some estimators, including in a discussion of estimators based on log outcomes. The available passage does not specifically establish that retransformation bias becomes greater under heteroscedasticity. (LLM, conf=0.73)

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Research works printed but not linked: 15

  1. Blough, 1999, Modeling risk using generalized linear models, Journal of Health Economics, 18, 153, 10.1016/S0167-6296(98)00032-0 · DOI
  2. Cameron, A.C., Trivedi, P.K., 1998. Regression Analysis of Count Data. Cambridge University Press, Cambridge. · DOI
  3. D’Agostino, 1973, Tests for departure from normality: empirical results for the distribution of b2 and b1, Biometrika, 60, 613
  4. Duan, 1983, Smearing estimate: a nonparametric retransformation method, Journal of the American Statistical Association, 78, 605, 10.2307/2288126 · DOI
  5. Duan, N., Manning, W.G., et al., 1983. A comparison of alternative models for the demand for medical care. Journal of Business and Economics Statistics 1, 115–126. · DOI
  6. Gourieroux, 1984, Pseudo-maximum likelihood methods: applications to Poisson models, Econometrica, 52, 701, 10.2307/1913472 · DOI
  7. Jones, A., 2000. Health econometrics. In: Culyer, A., Newhouse, J. (Eds.), Handbook of Health Economics. Elsevier, Amsterdam.
  8. McCullagh, P., Nelder, J.A., 1989. Generalized Linear Models, 2nd Edition. Chapman & Hall, London. · DOI · Paper page
  9. Manning, 1998, The logged dependent variable, heteroscedasticity, and the retransformation problem, Journal of Health Economics, 17, 283, 10.1016/S0167-6296(98)00025-3 · DOI
  10. Manning, 1987, Monte Carlo evidence on the choice between sample selection and two-part models, Journal of Econometrics, 35, 59, 10.1016/0304-4076(87)90081-9 · DOI
  11. Manning, W.G., Newhouse, J.P., et al., 1987b. Health insurance and the demand for medical care: evidence from a randomized experiment. American Economic Review 77 (3), 251–277.
  12. Mullahy, 1998, Much ado about two: reconsidering retransformation and the two-part model in health econometrics, Journal of Health Economics, 17, 247, 10.1016/S0167-6296(98)00030-7 · DOI
  13. Newhouse, J.P., et al., 1993. Free for all: health insurance, medical costs, and health outcomes. In: The Results of the Health Insurance Experiment. Harvard University Press, Cambridge.
  14. Park, 1966, Estimation with heteroscedastic error terms, Econometrica, 34, 888, 10.2307/1910108 · DOI
  15. Wooldridge, 1991, On the application of robust, regression-based diagnostics to models of conditional means and conditional variances, Journal of Econometrics, 47, 5, 10.1016/0304-4076(91)90076-P · DOI

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Metadata

Authors
Manning, W. G., & Mullahy, J.
Venue
Journal of Health Economics
Publisher
Elsevier BV
Published
2001-07
Volume
20
Issue
4
Pages
461-494
ISSN
0167-6296
DOI
10.1016/s0167-6296(01)00086-8
Cited by
1,790
References
0
Language
en
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)

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