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Estimation of Nonlinear Models with Mismeasured Regressors Using Marginal Information

  • Yingyao Hu
  • Geert Ridder

We consider the estimation of nonlinear models with mismeasured explanatory variables, when information on the marginal distribution of the true values of these variables is available. We derive a semi-parametric MLE that is is shown to be pn consistent and asymptotically normally distributed. In a simulation experiment we find that the finite sample distribution of the estimator is close to the asymptotic approximation. The semi-parametric MLE is applied to a duration model for AFDC welfare spells with misreported welfare benefits. The marginal distribution of the correctly measured welfare benefits is obtained from an administrative source.

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Paper provided by Institute of Economic Policy Research (IEPR) in its series IEPR Working Papers with number 05.39.

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Length: 57 pages
Date of creation: Oct 2005
Date of revision:
Handle: RePEc:scp:wpaper:05-39
Contact details of provider: Phone: (213) 740-3521
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Web page: http://www.usc.edu/dept/LAS/economics/IEPR/

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