Generalized nonparametric deconvolution with an application to earnings dynamics

Stéphane Bonhomme and Jean-Marc Robin

No CWP03/08, CeMMAP working papers from Centre for Microdata Methods and Practice, Institute for Fiscal Studies

Abstract:

In this paper,we construct a nonparametric estimator of the distributions of latent factors in linear independent multi-factor models under the assumption that factor loadings are known. Our approach allows to estimate the distributions of up to L(L+1)/2 factors given L measurements. The estimator works through empirical characteristic functions. We show that it is consistent, and derive asymptotic convergence rates. Monte-Carlo simulations show good finite-sample performance, less so if distributions are highly skewed or leptokurtic. We finally apply the generalized deconvolution procedure to decompose individual log earnings from the PSID into permanent and transitory components.

JEL-codes: C13 C14 (search for similar items in EconPapers)
Date: 2008-02-08
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (24)

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Related works:
Journal Article: Generalized Non-Parametric Deconvolution with an Application to Earnings Dynamics (2010)
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Persistent link: https://EconPapers.repec.org/RePEc:ifs:cemmap:03/08

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