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Estimation of Average Marginal Effects in Multiplicative Unobserved Effects Panel Models

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  • Robert S. Martin

Abstract

In multiplicative unobserved efffects panel models for nonnegative dependent variables, estimation of average marginal effects would seem problematic with a large cross section and few time periods due to the incidental parameters problem. While fixed effects Poisson consistently estimates the slope parameters of the conditional mean function, marginal effects generally depend on the unobserved heterogeneity. However, I show that a class of fixed effects averages is consistent and asymptotically normal with only the cross section growing. This implies researchers can estimate average treatment effects in levels as opposed to settling for average proportional effects.

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  • Robert S. Martin, 2017. "Estimation of Average Marginal Effects in Multiplicative Unobserved Effects Panel Models," Economic Working Papers 497, Bureau of Labor Statistics.
    • Handle: RePEc:bls:wpaper:497
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    Cited by:

    1. Jeffrey M Wooldridge, 2023. "Simple approaches to nonlinear difference-in-differences with panel data," The Econometrics Journal, Royal Economic Society, vol. 26(3), pages 31-66.
    2. Nicholas Brown & Jeffrey Wooldridge, 2023. "More Efficient Estimation of Multiplicative Panel Data Models in the Presence of Serial Correlation," Working Paper 1497, Economics Department, Queen's University.
    3. Cäcilia Lipowski & Ralf A. Wilke & Bertrand Koebel, 2022. "Fertility, economic incentives and individual heterogeneity: Register data‐based evidence from France and Germany," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(S2), pages 515-546, December.

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    More about this item

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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