Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp017w62f821k
 Title: Estimating a Censored Dynamic Panel Data Model with an Application to Earnings Dynamics Authors: Hu, Luojia Keywords: panel datacensored regressionearnings dynamics Issue Date: 1-Mar-2000 Citation: Econometrica , Vol. 70, No. 6 (Nov., 2002) Series/Report no.: Working Papers (Princeton University. Industrial Relations Section) ; 435 Abstract: This paper proposes a method for estimating a censored panel data model with a lagged latent dependent variable and individual-speciﬁc ﬁxed effects. The main insight is to trim observations in such a way that a certain symmetry, which was destroyed by censoring, is restored. Based on the restored symmetry, orthogonality conditions are constructed and GMM estimation is implemented. The estimation method is used to study earnings dynamics, using matched data from the Current Population Survey and Social Security Administration (CPS- SSA) Earnings Record for a sample of men who were born in 1930-39 and living in the South dining the period of 1957-73. The SSA earnings are top-coded at the maximum social security taxable level. Although linear GMM estimation yields no difference in earnings dynamics by race, the earnings process for white men appears to be more persistent than that for black men (conditional on individual heterogeneity) after censoring is taken into account. URI: http://arks.princeton.edu/ark:/88435/dsp017w62f821k Related resource: http://links.jstor.org/sici?sici=0012-9682%28200211%2970%3A6%3C2499%3AEOACDP%3E2.0.CO%3B2-B Appears in Collections: IRS Working Papers

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