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Is neglected heterogeneity really an issue in binary and fractional regression models? A simulation exercise for logit, probit and loglog models

  • Ramalho, Esmeralda A.
  • Ramalho, Joaquim J.S.

Theoretical and simulation analysis is performed to examine whether unobserved heterogeneity independent of the included regressors is really an issue in logit, probit and loglog models with both binary and fractional data. It is found that unobserved heterogeneity has the following effects. First, it produces an attenuation bias in the estimation of regression coefficients. Second, although it is innocuous for logit estimation of average sample partial effects, it may generate biased estimation of those effects in the probit and loglog models. Third, it has much more deleterious effects on the estimation of population partial effects. Fourth, it is only for logit models that it does not substantially affect the prediction of outcomes. Fifth, it is innocuous for the size of Wald tests for the significance of observed regressors but, in small samples, it substantially reduces their power.

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Article provided by Elsevier in its journal Computational Statistics & Data Analysis.

Volume (Year): 54 (2010)
Issue (Month): 4 (April)
Pages: 987-1001

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Handle: RePEc:eee:csdana:v:54:y:2010:i:4:p:987-1001
Contact details of provider: Web page: http://www.elsevier.com/locate/csda

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  1. Chesher, Andrew & Peters, Simon, 1994. "Symmetry, Regression Design, and Sampling Distributions," Econometric Theory, Cambridge University Press, vol. 10(01), pages 116-129, March.
  2. J. S. Cramer, 2007. "Robustness of Logit Analysis: Unobserved Heterogeneity and Mis-specified Disturbances," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 69(4), pages 545-555, 08.
  3. Stoker, Thomas M, 1986. "Consistent Estimation of Scaled Coefficients," Econometrica, Econometric Society, vol. 54(6), pages 1461-81, November.
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  5. Leslie E. Papke & Jeffrey M. Wooldridge, 1993. "Econometric Methods for Fractional Response Variables with an Application to 401(k) Plan Participation Rates," NBER Technical Working Papers 0147, National Bureau of Economic Research, Inc.
  6. Yatchew, Adonis & Griliches, Zvi, 1985. "Specification Error in Probit Models," The Review of Economics and Statistics, MIT Press, vol. 67(1), pages 134-39, February.
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  8. Lee, Lung-Fei, 1982. "Specification error in multinomial logit models : Analysis of the omitted variable bias," Journal of Econometrics, Elsevier, vol. 20(2), pages 197-209, November.
  9. Esmeralda A. Ramalho & Joaquim Ramalho, 2010. "Alternative versions of the RESET test for binary response index models: a comparative study," CEFAGE-UE Working Papers 2010_09, University of Evora, CEFAGE-UE (Portugal).
  10. Chesher, Andrew, 1995. "A Mirror Image Invariance for M-Estimators," Econometrica, Econometric Society, vol. 63(1), pages 207-11, January.
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