Arbeitspapier
Identifying distributional characteristics in random coefficients panel data models
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.
- Language
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Englisch
- Bibliographic citation
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Series: cemmap working paper ; No. CWP22/09
- Classification
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Wirtschaft
Single Equation Models; Single Variables: Panel Data Models; Spatio-temporal Models
- Subject
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panel data
random coefficients
multiple effects
nonparametric identification
Mathematik
- Event
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Geistige Schöpfung
- (who)
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Arellano, Manuel
Bonhomme, Stéphane
- Event
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Veröffentlichung
- (who)
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Centre for Microdata Methods and Practice (cemmap)
- (where)
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London
- (when)
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2009
- DOI
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doi:10.1920/wp.cem.2009.2209
- Handle
- Last update
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10.03.2025, 11:43 AM CET
Data provider
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Arellano, Manuel
- Bonhomme, Stéphane
- Centre for Microdata Methods and Practice (cemmap)
Time of origin
- 2009