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Identification and Estimation of Structural-Change Models with Misclassification

Author

Listed:
  • Terence Tai-Leung Chong

    (The Chinese University of Hong Kong)

  • Kwan-To Wong

    (University of Hong Kong)

  • Melvin Hinich

    (University of Texas at Austin)

Abstract

Consider a simple change-point model with a binary regressor. We examine the consistency of the change-point estimator when the regressor is subject to misclassification. It is found that the time of change can always be identified. Further, special cases where the structural parameters can also be identified are discussed. Simulation evidence is provided.

Suggested Citation

  • Terence Tai-Leung Chong & Kwan-To Wong & Melvin Hinich, 2007. "Identification and Estimation of Structural-Change Models with Misclassification," Economics Bulletin, AccessEcon, vol. 3(36), pages 1-19.
    • Handle: RePEc:ebl:ecbull:eb-07c20004
    as

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    References listed on IDEAS

    as
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    4. Aprajit Mahajan, 2006. "Identification and Estimation of Regression Models with Misclassification," Econometrica, Econometric Society, vol. 74(3), pages 631-665, May.
    5. Poterba, James M & Summers, Lawrence H, 1995. "Unemployment Benefits and Labor Market Transitions: A Multinomial Logit Model with Errors in Classification," The Review of Economics and Statistics, MIT Press, vol. 77(2), pages 207-216, May.
    6. Levi, Maurice D, 1973. "Errors in the Variables Bias in the Presence of Correctly Measured Variables," Econometrica, Econometric Society, vol. 41(5), pages 985-986, September.
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    JEL classification:

    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables

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