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

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).

[1]  Jonathan Gruber,et al.  The Consumption Smoothing Benefits of Unemployment Insurance , 1994 .

[2]  H. Ichimura,et al.  SEMIPARAMETRIC LEAST SQUARES (SLS) AND WEIGHTED SLS ESTIMATION OF SINGLE-INDEX MODELS , 1993 .

[3]  N. Kiefer.  Economic Duration Data and Hazard Functions , 1988 .

[4]  Tony Lancaster,et al.  Generalised residuals and heterogeneous duration models: With applications to the Weilbull model , 1985 .

[5]  R. Sherman,et al.  Rank estimators for monotonic index models , 1998 .

[6]  Gilbert MacKenzie,et al.  The Statistical Analysis of Failure Time Data , 1982 .

[7]  David R. Cox,et al.  Regression models and life tables (with discussion , 1972 .

[8]  Francis W. Horvath,et al.  Keeping Time: An Analysis of Errors in the Measurement of Unemployment Duration , 1984 .

[9]  Thomas M. Stoker,et al.  Semiparametric Estimation of Index Coefficients , 1989 .

[10]  A. Atkinson,et al.  Unemployment Compensation and Labor Market Transitions: A Critical Review , 1991 .

[11]  J. Hausman,et al.  Misclassification of the dependent variable in a discrete-response setting , 1998 .

[12]  J. Hausman,et al.  Flexible parametric estimation of duration and competing risk models , 1990 .

[13]  Jason Abrevaya.  Leapfrog estimation of a fixed-effects model with unknown transformation of the dependent variable , 1999 .

[14]  R. Sherman.  The Limiting Distribution of the Maximum Rank Correlation Estimator , 1993 .

[15]  J. Poterba,et al.  Unemployment Benefits and Labor Market Transitions: A Multinomial Logit Model with Errors in Classification , 1995 .

[16]  N. Mathiowetz,et al.  Out of Work, Out of Mind: Response Errors in Retrospective Reports of Unemployment , 1988 .

[17]  Hal S. Sider.  Unemployment Duration and Incidence: 1968-82 , 1985 .

[18]  Aaron K. Han.  Non-parametric analysis of a generalized regression model: the maximum rank correlation estimator , 1987 .

[19]  Tony Lancaster,et al.  The Econometric Analysis of Transition Data. , 1992 .

[20]  Bruce D. Meyer.  Unemployment Insurance and Unemployment Spells , 1988 .

[21]  J. Kalbfleisch,et al.  The Statistical Analysis of Failure Time Data , 1980 .