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Estimating Heterogeneous Effects in Static Binary Response Panel Data Models

Author

Listed:
  • Anastasia Semykina

    (Department of Economics, Florida State University)

Abstract

This paper considers estimating heterogeneous effects in panel data models when the outcome is binary. We argue that a common practice of splitting the sample and performing estimation separately for each subsample results in inconsistent estimators of heterogeneous parameters. The paper presents methods that account for a possibility of nonrandom sorting and produce consistent estimators of causal effects in two or more heterogeneous sub-populations. Monte Carlo simulations show that considered methods perform well in finite samples. As an empirical application, the paper studies gender differences in job satisfaction by occupation type.

Suggested Citation

  • Anastasia Semykina, 2022. "Estimating Heterogeneous Effects in Static Binary Response Panel Data Models," Working Papers wp2022_11_01, Department of Economics, Florida State University.
    • Handle: RePEc:fsu:wpaper:wp2022_11_01
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    File URL: https://coss.fsu.edu/econpapers/wpaper/wp2022_11_01.pdf
    File Function: First version, 2022-11
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    More about this item

    Keywords

    binary response; heterogeneous effects; nonrandom sorting;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions

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