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Closed-form estimation of a regression model with a mismeasured binary regressor and heteroskedasticity

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  • Liu, Yibin
  • Wu, Wenbin

Abstract

This paper finds that heteroskedasticity in nonclassical error-in-variable models leads to biased and inconsistent estimates when higher-order moments of data are used. A closed-form estimator is provided to correct this bias based on information from the first three moments.

Suggested Citation

  • Liu, Yibin & Wu, Wenbin, 2017. "Closed-form estimation of a regression model with a mismeasured binary regressor and heteroskedasticity," Statistics & Probability Letters, Elsevier, vol. 125(C), pages 202-206.
    • Handle: RePEc:eee:stapro:v:125:y:2017:i:c:p:202-206
    DOI: 10.1016/j.spl.2017.02.016
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    References listed on IDEAS

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    1. Chen, Xiaohong & Hu, Yingyao & Lewbel, Arthur, 2008. "Nonparametric identification of regression models containing a misclassified dichotomous regressor without instruments," Economics Letters, Elsevier, vol. 100(3), pages 381-384, September.
    2. Chen, Xiaohong & Hu, Yingyao & Lewbel, Arthur, 2008. "A note on the closed-form identification of regression models with a mismeasured binary regressor," Statistics & Probability Letters, Elsevier, vol. 78(12), pages 1473-1479, September.
    3. Xiaohong Chen & Han Hong & Denis Nekipelov, 2011. "Nonlinear Models of Measurement Errors," Journal of Economic Literature, American Economic Association, vol. 49(4), pages 901-937, December.
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