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Identifying Distributional Characteristics in Random Coefficients Panel Data Models

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Abstract

We study the identification of panel models with linear individual-specific coefficients, when T is fixed. We show identification of the variance of the effects under conditional uncorrelatedness. Identification requires restricted dependence of errors, reflecting a trade-off between heterogeneity and error dynamics. We show identification of the density of individual effects when errors follow an ARMA process under conditional independence. We discuss GMM estimation of moments of effects and errors, and introduce a simple density estimator of a slope effect in a special case. As an application we estimate the effect that a mother smokes during pregnancy on child’s birth weight.

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  • Manuel Arellano & Stéphane Bonhomme, 2009. "Identifying Distributional Characteristics in Random Coefficients Panel Data Models," Working Papers wp2009_0904, CEMFI.
  • Handle: RePEc:cmf:wpaper:wp2009_0904
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    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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