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
Englisch

Bibliographic citation
Series: cemmap working paper ; No. CWP22/09

Classification
Wirtschaft
Single Equation Models; Single Variables: Panel Data Models; Spatio-temporal Models
Subject
panel data
random coefficients
multiple effects
nonparametric identification
Mathematik

Event
Geistige Schöpfung
(who)
Arellano, Manuel
Bonhomme, Stéphane
Event
Veröffentlichung
(who)
Centre for Microdata Methods and Practice (cemmap)
(where)
London
(when)
2009

DOI
doi:10.1920/wp.cem.2009.2209
Handle
Last update
10.03.2025, 11:43 AM CET

Data provider

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Object type

  • Arbeitspapier

Associated

  • Arellano, Manuel
  • Bonhomme, Stéphane
  • Centre for Microdata Methods and Practice (cemmap)

Time of origin

  • 2009

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