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Identifying Distributional Characteristics In Random Coefficients Panel Data Models

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  • Manuel Arellano

    () (CEMFI, Centro de Estudios Monetarios y Financieros)

  • Stéphane Bonhomme

    () (CEMFI, Centro de Estudios Monetarios y Financieros)

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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Bibliographic Info

Paper provided by CEMFI in its series Working Papers with number wp2009_0904.

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Date of creation: Aug 2009
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Handle: RePEc:cmf:wpaper:wp2009_0904

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Keywords: Panel data; random coefficients; multiple effects; nonparametric identification.;

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References

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Citations

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Cited by:
  1. Stéphane Bonhomme & Elena Manresa, 2012. "Grouped Patterns Of Heterogeneity In Panel Data," Working Papers wp2012_1208, CEMFI.
  2. Susanne Schennach, 2012. "Measurement error in nonlinear models- a review," CeMMAP working papers CWP41/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  3. Stefan Hoderlein & Yuya Sasaki, 2011. "On the role of time in nonseparable panel data models," CeMMAP working papers CWP15/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  4. Magnac, Thierry & Pistolesi, Nicolas & Roux, Sébastien, 2013. "Post schooling human capital investments and the life cycle variance of earnings," TSE Working Papers 13-380, Toulouse School of Economics (TSE).

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