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Semiparametric Estimation with Mismeasured Dependent Variables: An Application to Duration Models for Unemployment Spells

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  • Jason Abrevaya
  • Jerry A. Hausman

Abstract

This paper considers mismeasurement of the dependent variable in a general linear index model, which includes qualitative choice models, proportional and additive hazard models, and censored models as special cases. The monotone rank estimator of Cavanagh and Sherman [1998] is shown to be consistent in the presence of any mismeasurement process that obeys a simple stochastic-dominance condition. The emphasis is on measurement error which is independent of the covariates, but extensions to covariate-dependent measurement error are also discussed. We consider the proportional hazard duration model in detail and apply the estimator to mismeasured unemployment duration data from the Survey of Income and Program Participation (SIPP).

Suggested Citation

  • Jason Abrevaya & Jerry A. Hausman, 1999. "Semiparametric Estimation with Mismeasured Dependent Variables: An Application to Duration Models for Unemployment Spells," Annals of Economics and Statistics, GENES, issue 55-56, pages 243-275.
    • Handle: RePEc:adr:anecst:y:1999:i:55-56:p:243-275
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