Identifying distributional characteristics in random coefficients panel data models

Manuel Arellano () and Stéphane Bonhomme

No CWP22/09, CeMMAP working papers from Centre for Microdata Methods and Practice, Institute for Fiscal Studies

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.

New Economics Papers: this item is included in nep-ecm
Date: 2009-08
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http://cemmap.ifs.org.uk/wps/cwp2209.pdf (application/pdf)

Related works:
Working Paper: IDENTIFYING DISTRIBUTIONAL CHARACTERISTICS IN RANDOM COEFFICIENTS PANEL DATA MODELS (2009)
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Persistent link: http://EconPapers.repec.org/RePEc:ifs:cemmap:22/09

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