A Minimum Power Divergence Class of CDFs and Estimators for Binary Choice Models
AbstractThe Cressie-Read (CR) family of power divergence measures is used to identify a new class of statistical models and estimators for competing explanations of the data in binary choice models. A large flexible class of cumulative distribution functions and associated probability density functions emerge that subsumes the conventional logit model, and forms the basis for a large set of estimation alternatives to traditional logit and probit methods. Asymptotic properties of estimators are identified, and sampling experiments are used to provide a basis for gauging the finite sample performance of the estimators in this new class of statistical models.
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Bibliographic InfoPaper provided by Department of Agricultural & Resource Economics, UC Berkeley in its series Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series with number qt7bc2828q.
Date of creation: 08 Jul 2008
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binary choice models and estimators; conditional moment equations; squared error loss; Cressie-Read statistic; information theoretic methods; minimum power divergence;
Other versions of this item:
- Mittelhammer, Ronald C. & Judge, George G, 2008. "A minimum power divergence class of CDFs and estimators for binary choice models," CUDARE Working Paper Series 1059, University of California at Berkeley, Department of Agricultural and Resource Economics and Policy.
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- Kenneth Train, 2003.
"Discrete Choice Methods with Simulation,"
Online economics textbooks,
SUNY-Oswego, Department of Economics, number emetr2, Spring.
- McFadden, Daniel L., 1984. "Econometric analysis of qualitative response models," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 24, pages 1395-1457 Elsevier.
- Gabler, Siegfried & Laisney, Francois & Lechner, Michael, 1993. "Seminonparametric Estimation of Binary-Choice Models with an Application to Labor-Force Participation," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(1), pages 61-80, January.
- Smith, Richard J., 2007.
"Efficient information theoretic inference for conditional moment restrictions,"
Journal of Econometrics,
Elsevier, vol. 138(2), pages 430-460, June.
- Richard Smith, 2005. "Efficient information theoretic inference for conditional moment restrictions," CeMMAP working papers CWP14/05, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Han, Aaron K., 1987. "Non-parametric analysis of a generalized regression model : The maximum rank correlation estimator," Journal of Econometrics, Elsevier, vol. 35(2-3), pages 303-316, July.
- Cosslett, Stephen R, 1983. "Distribution-Free Maximum Likelihood Estimator of the Binary Choice Model," Econometrica, Econometric Society, vol. 51(3), pages 765-82, May.
- Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
- Klein, R.W. & Spady, R.H., 1991.
"An Efficient Semiparametric Estimator for Binary Response Models,"
70, Bell Communications - Economic Research Group.
- Klein, Roger W & Spady, Richard H, 1993. "An Efficient Semiparametric Estimator for Binary Response Models," Econometrica, Econometric Society, vol. 61(2), pages 387-421, March.
- Newey, Whitney K, 1991.
"Uniform Convergence in Probability and Stochastic Equicontinuity,"
Econometric Society, vol. 59(4), pages 1161-67, July.
- Newey, W.K., 1989. "Uniform Convergence In Probability And Stochastic Equicontinuity," Papers 342, Princeton, Department of Economics - Econometric Research Program.
- Pedro Gozalo & Oliver Linton, 1994. "Local Nonlinear Least Squares Estimation: Using Parametric Information Nonparametrically," Cowles Foundation Discussion Papers 1075, Cowles Foundation for Research in Economics, Yale University.
- Manski, Charles F., 1975. "Maximum score estimation of the stochastic utility model of choice," Journal of Econometrics, Elsevier, vol. 3(3), pages 205-228, August.
- Yuan, Ke-Hai & Jennrich, Robert I., 1998. "Asymptotics of Estimating Equations under Natural Conditions," Journal of Multivariate Analysis, Elsevier, vol. 65(2), pages 245-260, May.
- Horowitz, Joel L, 1992. "A Smoothed Maximum Score Estimator for the Binary Response Model," Econometrica, Econometric Society, vol. 60(3), pages 505-31, May.
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