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Over-identified Doubly Robust identification and estimation

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  • Lewbel, Arthur
  • Choi, Jin Young
  • Zhou, Zhuzhu

Abstract

Consider two parametric models. At least one is correctly specified, but we do not know which. Both models include a common vector of parameters. An estimator for this common parameter vector is called Doubly Robust (DR) if it is consistent no matter which model is correct. We provide a general technique for constructing DR estimators (assuming the models are over identified). Our Over-identified Doubly Robust (ODR) technique is a simple extension of the Generalized Method of Moments. We illustrate our ODR with a variety of models. Our empirical application is instrumental variables estimation, where either one of two instrument vectors might be invalid.

Suggested Citation

  • Lewbel, Arthur & Choi, Jin Young & Zhou, Zhuzhu, 2023. "Over-identified Doubly Robust identification and estimation," Journal of Econometrics, Elsevier, vol. 235(1), pages 25-42.
  • Handle: RePEc:eee:econom:v:235:y:2023:i:1:p:25-42
    DOI: 10.1016/j.jeconom.2022.01.009
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    Cited by:

    1. Jiaming Mao & Jingzhi Xu, 2020. "Ensemble Learning with Statistical and Structural Models," Papers 2006.05308, arXiv.org.

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    More about this item

    Keywords

    Doubly Robust estimation; Generalized method of moments; Instrumental variables; Average Treatment Effects; Parametric models;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models

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