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Computing Marginal Effects In The Box-Cox Model

  • Jason Abrevaya

This paper considers computation of fitted values and marginal effects in the Box-Cox regression model. Two methods, 1 the “smearing” technique suggested by Duan (see Ref. [10]) and 2 direct numerical integration, are examined and compared with the “naive” method often used in econometrics.

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File URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-120015789
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Article provided by Taylor & Francis Journals in its journal Econometric Reviews.

Volume (Year): 21 (2002)
Issue (Month): 3 ()
Pages: 383-393

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Handle: RePEc:taf:emetrv:v:21:y:2002:i:3:p:383-393
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  1. Wooldridge, Jeffrey M, 1992. "Some Alternatives to the Box-Cox Regression Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 33(4), pages 935-55, November.
  2. Amemiya, Takeshi & Powell, James L., 1981. "A comparison of the Box-Cox maximum likelihood estimator and the non-linear two-stage least squares estimator," Journal of Econometrics, Elsevier, vol. 17(3), pages 351-381, December.
  3. Manning, Willard G., 1998. "The logged dependent variable, heteroscedasticity, and the retransformation problem," Journal of Health Economics, Elsevier, vol. 17(3), pages 283-295, June.
  4. Poirier, Dale J & Melino, Angelo, 1978. "A Note on the Interpretation of Regression Coefficients within a Class of Truncated Distributions," Econometrica, Econometric Society, vol. 46(5), pages 1207-09, September.
  5. Showalter, Mark H, 1994. "A Monte Carlo Investigation of the Box-Cox Model and a Nonlinear Least Squares Alternative," The Review of Economics and Statistics, MIT Press, vol. 76(3), pages 560-70, August.
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