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Estimation of Nonlinear Models with Mismeasured Regressors Using Marginal Information

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Yingyao Hu and Geert Ridder

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Abstract

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 shown to be $\sqrt{n}$ 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 The Johns Hopkins University,Department of Economics in its series Economics Working Paper Archive with number 554.

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Date of creation: Jun 2009
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Handle: RePEc:jhu:papers:554

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