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Semiparametric Estimation Of Regression Models For Panel Data

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Joel L. Horowitz (Univ. of Iowa)
Marianthi Markatou

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Abstract

Linear models with error components are widely used to analyze panel data. Some applications of these models require knowledge of the probability densities of the error components. Existing methods handle this requirement by assuming that the densities belong to known parametric families of distributions (typically the normal distribution). This paper shows how to carry out nonparametric estimation of the densities of the error components, thereby avoiding the assumption that the densities belong to known parametric families. The nonparametric estimators are applied to an earnings model using data from the Current Population Survey. The model's transitory error component is not normally distributed. Use of the nonparametric density estimators yields estimates of the probability that individuals with low earnings will become high earners in the future that are much lower than the estimates obtained under the assumption of normally distributed error components. JEL Classification: C13, C14, C23

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Paper provided by EconWPA in its series Econometrics with number 9309001.

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Length: 24 pages
Date of creation: 23 Sep 1993
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Handle: RePEc:wpa:wuwpem:9309001

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Find related papers by JEL classification:
C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Estimation
C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Semiparametric and Nonparametric Methods
C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data

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  1. Chamberlain, Gary, 1984. "Panel data," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 22, pages 1247-1318 Elsevier. [Downloadable!] (restricted)
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. John F. Geweke & Michael P. Keane, 1997. "An empirical analysis of income dynamics among men in the PSID: 1968-1989," Staff Report 233, Federal Reserve Bank of Minneapolis. [Downloadable!]
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  2. Javier Alvarez & Manuel Arellano, 2004. "Robust Likelihood Estimation Of Dynamic Panel Data Models," Working Papers wp2004_0421, CEMFI. [Downloadable!]
  3. 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, Yale University. [Downloadable!]
  4. Stéphane Bonhomme & Jean-Marc Robin, 2008. "Generalized nonparametric deconvolution with an application to earnings dynamics," CeMMAP working papers CWP03/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies. [Downloadable!]
  5. Magnac, Thierry & Roux, Sébastien, 2007. "Dynamique des salaires dans une cohorte," IDEI Working Papers 436, Institut d'Économie Industrielle (IDEI), Toulouse. [Downloadable!]
  6. Laura Hospido, 2007. "Modelling heterogeneity and dynamics in the volatility of individual wages," Banco de España Working Papers 0738, Banco de España. [Downloadable!]
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  7. William C. Horrace & Christopher F. Parmeter, 2008. "Semiparametric Deconvolution with Unknown Error Variance," Center for Policy Research Working Papers 104, Center for Policy Research, Maxwell School, Syracuse University. [Downloadable!]
  8. Geert Ridder & Yingyao Hu, 2004. "Estimation of Nonlinear Models with Measurement Error Using Marginal Information," Econometric Society 2004 North American Summer Meetings 21, Econometric Society. [Downloadable!]
  9. Stéphane Bonhomme & Jean-Marc Robin, 2008. "Assessing the equalizing force of mobility using short panels: France 1990-2000," CeMMAP working papers CWP02/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies. [Downloadable!]
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  10. Walter Sosa-Escudero & Mariana Marchionni & Omar Arias, 2006. "Sources of Income Persistence: Evidence from Rural El Salvador," Working Papers 0037, CEDLAS, Universidad Nacional de La Plata. [Downloadable!]
  11. Byeong Park & Robin C. Sickles & Leopold Simar, 2000. "Semiparametric Efficient Estimation of AR(1) Panel Data Models," Econometric Society World Congress 2000 Contributed Papers 1510, Econometric Society. [Downloadable!]
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  12. Carrasco, Marine & Florens, Jean-Pierre, 2002. "Spectral Method for Deconvolving a Density," IDEI Working Papers 138, Institut d'Économie Industrielle (IDEI), Toulouse. [Downloadable!]
  13. Yingyao Hu & Geert Ridder, 2005. "On Deconvolution as a First Stage Nonparametric Estimator," IEPR Working Papers 05.29, Institute of Economic Policy Research (IEPR). [Downloadable!]
  14. Oliver Linton & Yoon-Jae Whang, 2000. "Nonparametric Estimation with Aggregated Data," STICERD - Econometrics Paper Series /2000/397, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE. [Downloadable!]
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  15. Erich Battistin, 2002. "Errors in Survey Reports of Consumption Expenditures," 10th International Conference on Panel Data, Berlin, July 5-6, 2002 C4-2, International Conferences on Panel Data. [Downloadable!]
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  16. Isabel Proenca, 2005. "A Simple Deconvolving Kernel Density Estimator when Noise is Gaussian," Econometrics 0508006, EconWPA. [Downloadable!]
  17. Susanne M. Schennach, 2004. "Instrumental Variable Estimation of Nonlinear Errors-in-Variables Models," Econometric Society 2004 North American Summer Meetings 602, Econometric Society. [Downloadable!]
  18. Yingyao Hu & Geert Ridder, 2005. "Estimation of Nonlinear Models with Mismeasured Regressors Using Marginal Information," IEPR Working Papers 05.39, Institute of Economic Policy Research (IEPR). [Downloadable!]
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