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Testing the binomial fixed effects logit model, with an application to female labour supply.

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This study introduces a simplified method for binomial panel logit models, enhancing analysis of proportion data. The new approach improves estimation and includes a test for overdispersion in panel data regression.

Keywords:
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Area of Science:

  • Econometrics
  • Statistical Modeling

Background:

  • Regression models for proportions are common in applied research.
  • Standard models face challenges with nonlinearities and panel data structures.

Purpose of the Study:

  • To propose a simple implementation of the conditional maximum likelihood estimator for binomial panel logit models.
  • To investigate estimator properties under misspecification and develop a new overdispersion test.

Main Methods:

  • Conditional maximum likelihood estimation for binomial panel logit models.
  • Development and application of a novel overdispersion test for panel data.

Main Results:

  • A simplified implementation of the estimator is presented for standard statistical software.
  • Properties of the estimator under misspecification were analyzed.

Conclusions:

  • The proposed method offers a practical approach to analyzing proportion data in panel studies.
  • The new overdispersion test aids in model diagnostics for such data.