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Identifying the effect of a mis-classified, binary, endogenous regressor

Author

Listed:
  • Francis J. DiTraglia

    (Department of Economics University of Oxford)

  • Camilo Garcia-Jimeno

    (Federal Reserve Bank of Chicago)

Abstract

This paper studies identification of the effect of a mis-classified, binary, endogenous regressor when a discrete-valued instrumental variable is available. We begin by showing that the only existing point identification result for this model is incorrect. We go on to derive the sharp identified set under mean independence assumptions for the instrument and measurement error. The resulting bounds are novel and informative, but fail to point identify the effect of interest. This motivates us to consider alternative and slightly stronger assumptions: we show that adding second and third moment independence assumptions suffices to identify the model.

Suggested Citation

  • Francis J. DiTraglia & Camilo Garcia-Jimeno, 2020. "Identifying the effect of a mis-classified, binary, endogenous regressor," Papers 2011.07272, arXiv.org.
    • Handle: RePEc:arx:papers:2011.07272
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    References listed on IDEAS

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