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We develop a Bayesian method for heterogeneous variable selection in both linear and nonlinear panel data models, where variable selection takes place at the individual level and non-zero parameters are allowed to differ across individuals. Each individual-specific parameter is either zero or comes from a Dirichlet process mixture of multivariate normals. For inference, we develop an efficient MCMC sampler. In a Monte Carlo study, we show that our method accurately captures complex continuous cross-sectional heterogeneity and individual-specific variable selection, features standard approaches fail to capture jointly. An application on data from a discrete choice experiment on food choices shows that accounting for heterogeneous variable selection and non-normal continuous heterogeneity uncovers substantial variable non-attendance and an improved out-of-sample fit

Author

Listed:
  • Anoek Castelein

    (Erasmus University Rotterdam)

  • Stan Koobs

    (Erasmus University Rotterdam)

  • Dennis Fok

    (Erasmus University Rotterdam)

  • Richard Paap

    (Erasmus University Rotterdam)

Abstract

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Suggested Citation

  • Anoek Castelein & Stan Koobs & Dennis Fok & Richard Paap, 2020. "We develop a Bayesian method for heterogeneous variable selection in both linear and nonlinear panel data models, where variable selection takes place at the individual level and non-zero parameters are allowed to differ across individuals. Each indi," Tinbergen Institute Discussion Papers 20-061/III, Tinbergen Institute, revised 05 Mar 2026.
    • Handle: RePEc:tin:wpaper:20200061
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    References listed on IDEAS

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    Keywords

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    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

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