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A Minimum Power Divergence Class of CDFs and Estimators for the Binary Choice Model

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  • Ron Mittelhammer
  • George Judge

Abstract

The 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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Suggested Citation

  • Ron Mittelhammer & George Judge, 2009. "A Minimum Power Divergence Class of CDFs and Estimators for the Binary Choice Model," International Econometric Review (IER), Economic Research Association, vol. 1(1), pages 33-49, April.
    • Handle: RePEc:erh:journl:v:1:y:2009:i:1:p:33-49
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