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Generalized nonparametric deconvolution with an application to earnings dynamics

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  • Stéphane Bonhomme
  • Jean-Marc Robin

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

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.

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Bibliographic Info

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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References

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  1. Fatih Guvenen, 2007. "Learning Your Earning: Are Labor Income Shocks Really Very Persistent?," American Economic Review, American Economic Association, vol. 97(3), pages 687-712, June.
  2. Fatih Guvenen, 2007. "An Empirical Investigation of Labor Income Processes," NBER Working Papers 13394, National Bureau of Economic Research, Inc.
  3. Jean-Marc Robin & Stéphane Bonhomme, 2009. "Consistent Noisy Independent Component Analysis," Sciences Po publications info:hdl:2441/eu4vqp9ompq, Sciences Po.
  4. Li, Tong & Vuong, Quang, 1998. "Nonparametric Estimation of the Measurement Error Model Using Multiple Indicators," Journal of Multivariate Analysis, Elsevier, vol. 65(2), pages 139-165, May.
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Citations

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Cited by:
  1. Xiaohong Chen & Yingyao Hu, 2006. "Identification and Inference of Nonlinear Models Using Two Samples with Arbitrary Measurement Errors," Cowles Foundation Discussion Papers 1590, Cowles Foundation for Research in Economics, Yale University.
  2. Lance Lochner & Youngki Shin, 2014. "Understanding Earnings Dynamics: Identifying and Estimating the Changing Roles of Unobserved Ability, Permanent and Transitory Shocks," NBER Working Papers 20068, National Bureau of Economic Research, Inc.
  3. Manuel Arellano & Stéphane Bonhomme, 2009. "Identifying distributional characteristics in random coefficients panel data models," CeMMAP working papers CWP22/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  4. Susanne Schennach, 2013. "Convolution without independence," CeMMAP working papers CWP46/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  5. Marek Jarocinski & Albert Marcet, 2013. "Priors about Observables in Vector Autoregressions," UFAE and IAE Working Papers 929.13, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
  6. Jane Cooley Fruehwirth & Salvador Navarro & Yuya Takahashi, 2011. "How the Timing of Grade Retention Affects Outcomes: Identification and Estimation of Time-Varying Treatment Effects," University of Western Ontario, CIBC Centre for Human Capital and Productivity Working Papers 20117, University of Western Ontario, CIBC Centre for Human Capital and Productivity.
  7. Thierry Magnac & Sebastien Roux & Nicolas Pistolesi, 2013. "Post schooling human capital investments and the life cycle variance of earnings," 2013 Meeting Papers 426, Society for Economic Dynamics.
  8. Johanna Kappus & Gwennaelle Mabon, 2013. "Adaptive Density Estimation in Deconvolution Problems with Unknown Error Distribution," Working Papers 2013-31, Centre de Recherche en Economie et Statistique.
  9. Joel Horowitz, 2013. "Ill-posed inverse problems in economics," CeMMAP working papers CWP37/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  10. Johannes, Jan & Van Bellegem, Sébastien & Vanhems, Anne, 2011. "Convergence Rates For Ill-Posed Inverse Problems With An Unknown Operator," Econometric Theory, Cambridge University Press, vol. 27(03), pages 522-545, June.
  11. Evdokimov, Kirill & White, Halbert, 2012. "Some Extensions Of A Lemma Of Kotlarski," Econometric Theory, Cambridge University Press, vol. 28(04), pages 925-932, August.
  12. Jean-Marc Robin & Stéphane Bonhomme, 2009. "Consistent Noisy Independent Component Analysis," Sciences Po publications info:hdl:2441/eu4vqp9ompq, Sciences Po.
  13. Xiaohong Chen & Han Hong & Denis Nekipelov, 2011. "Nonlinear Models of Measurement Errors," Journal of Economic Literature, American Economic Association, vol. 49(4), pages 901-37, December.
  14. Nikolas Mittag, 2013. "A Method Of Correcting For Misreporting Applied To The Food Stamp Program," Working Papers 13-28, Center for Economic Studies, U.S. Census Bureau.

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