Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/79380
Authors: 
Bonhomme, Stéphane
Robin, Jean-Marc
Year of Publication: 
2008
Series/Report no.: 
cemmap working paper, Centre for Microdata Methods and Practice CWP03/08
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.
Subjects: 
Factor models , nonparametric estimation , deconvolution , Fourier transformation , earnings dynamics
JEL: 
C13
C14
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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