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Generalized nonparametric deconvolution with an application to earnings dynamics

  • Stéphane Bonhomme
  • Jean-Marc Robin

    ()

    (Institute for Fiscal Studies and EUREQua, University of Paris 1)

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.

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File URL: http://cemmap.ifs.org.uk/wps/cwp308.pdf
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Paper provided by Centre for Microdata Methods and Practice, Institute for Fiscal Studies in its series CeMMAP working papers with number CWP03/08.

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Date of creation: Feb 2008
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Handle: RePEc:ifs:cemmap:03/08
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  17. Geweke, John & Keane, Michael, 2000. "An empirical analysis of earnings dynamics among men in the PSID: 1968-1989," Journal of Econometrics, Elsevier, vol. 96(2), pages 293-356, June.
  18. Li, Tong, 2002. "Robust and consistent estimation of nonlinear errors-in-variables models," Journal of Econometrics, Elsevier, vol. 110(1), pages 1-26, September.
  19. Gary CHAMBERLAIN & Keisuke HIRANO, 1999. "Predictive Distributions based on Longitudinal Earnings Data," Annales d'Economie et de Statistique, ENSAE, issue 55-56, pages 211-242.
  20. Peter Hall & Qiwei Yao, 2003. "Inference in components of variance models with low replication," LSE Research Online Documents on Economics 17701, London School of Economics and Political Science, LSE Library.
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