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Partial effects in non-linear panel data models with correlated random effects

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  • Jason Abrevaya
  • Yu-Chin Hsu

Abstract

SummaryNonlinearity and heterogeneity are known to cause difficulties in estimating and interpreting partial effects. This paper provides a systematic characterization of the various partial effects in nonlinear panel data models that might be of interest to empirical researchers. The interpretation of the partial effects depends upon (i) whether the distribution of unobserved heterogeneity is treated as fixed or allowed to vary with covariates, and (ii) whether one is interested in particular covariate values or an average over such values. The characterization covers partial-effects concepts already in the literature but also includes new concepts for partial effects. A simple panel probit design highlights that the different partial effects can be quantitatively very different.

Suggested Citation

  • Jason Abrevaya & Yu-Chin Hsu, 2021. "Partial effects in non-linear panel data models with correlated random effects," The Econometrics Journal, Royal Economic Society, vol. 24(3), pages 519-535.
    • Handle: RePEc:oup:emjrnl:v:24:y:2021:i:3:p:519-535.
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    References listed on IDEAS

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    Cited by:

    1. Victor Aguirregabiria, 2023. "Dynamic demand for differentiated products with fixed-effects unobserved heterogeneity," The Econometrics Journal, Royal Economic Society, vol. 26(1), pages 1-25.
    2. Victor Aguirregabiria & Jesus Carro, 2021. "Identification of Average Marginal Effects in Fixed Effects Dynamic Discrete Choice Models," Working Papers tecipa-701, University of Toronto, Department of Economics.
    3. Cavit Pakel & Martin Weidner, 2023. "Bounds on Average Effects in Discrete Choice Panel Data Models," Papers 2309.09299, arXiv.org, revised May 2024.
    4. Cecilia ALEXANDRI & Corina SAMAN & Bianca PAUNA, 2024. "Heterogeneity in the agricultural sector and its implications for modeling viability," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 144-157, December.
    5. Laura Liu & Alexandre Poirier & Ji-Liang Shiu, 2021. "Identification and Estimation of Partial Effects in Nonlinear Semiparametric Panel Models," Papers 2105.12891, arXiv.org, revised Jul 2024.

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