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Semiparametric estimation of employment duration models

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Author Info
Joel Horowitz
George Neumann
Abstract

There are a variety of economic areas, such as studies of employment duration and of the durability of capital goods, in which data on important variables typically are censored. The standard techinques for estimating a model from censored data require the distributions of unobservable random components of the model to be specified a priori up to a finite set of parameters, and misspecification of these distributions usually leads to inconsistent parameter estimates. However, economic theory rarely gives guidance about distributions and the standard estimation techniques do not provide convenient methods for identifying distributions from censored data. Recently, several distribution-free or semiparametric methods for estimating censored regression models have been developed. This paper presents the results of using two such methods to estimate a model of employment duration. The paper reports the operating characteristics of the semiparametric estimators and compares the semiparametric estimates with those obtained from a standard parametric model.

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Publisher Info
Article provided by Taylor and Francis Journals in its journal Econometric Reviews.

Volume (Year): 6 (1987)
Issue (Month): 1 ()
Pages: 5-40
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Handle: RePEc:taf:emetrv:v:6:y:1987:i:1:p:5-40

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Related research
Keywords: semiparametric estimation distribution-free estimation censored regression model duration analysis quantile estimation semiparametric generalized least squares estimation

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  1. Frank Gerhard & Nikolaus Hautsch, 2007. "A Dynamic Semiparametric Proportional Hazard Model," Studies in Nonlinear Dynamics & Econometrics, Berkeley Electronic Press, vol. 11(2), pages 1377-1377. [Downloadable!] (restricted)
    Other versions:
  2. Boockmann, Bernhard & Steffes, Susanne, 2007. "Seniority and Job Stability: A Quantile Regression Approach Using Matched Employer-Employee Data," ZEW Discussion Papers 07-014, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research. [Downloadable!]
  3. Bia, Michela, 2007. "The Propensity Score method in public policy evaluation: a survey," P.O.L.I.S. department's Working Papers 79, Department of Public Policy and Public Choice - POLIS. [Downloadable!]
  4. Bernd Fitzenberger & Ralf Wilke, 2006. "Using quantile regression for duration analysis," AStA Advances in Statistical Analysis, Springer, vol. 90(1), pages 105-120, March. [Downloadable!] (restricted)
    Other versions:
  5. R. Koenker & O. Geling, . "Reappraising Medfly Longevity: A Quantile Regression Survival Analysis," Sonderforschungsbereich 373 1999-53, Humboldt Universitaet Berlin.
  6. Bia, Michela & Mattei, Alessandra, 2007. "Application of the Generalized Propensity Score. Evaluation of public contributions to Piedmont enterprises," P.O.L.I.S. department's Working Papers 80, Department of Public Policy and Public Choice - POLIS. [Downloadable!]
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