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High-dimensional linear models with many endogenous variables

Author

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  • Belloni, Alexandre
  • Hansen, Christian
  • Newey, Whitney

Abstract

High-dimensional linear models with endogenous variables play an increasingly important role in the recent econometric literature. In this work, we allow for models with many endogenous variables and make use of many instrumental variables to achieve identification. Because of the high-dimensionality in the structural equation, constructing honest confidence regions with asymptotically correct coverage is non-trivial. Our main contribution is to propose estimators and confidence regions that achieve this goal.

Suggested Citation

  • Belloni, Alexandre & Hansen, Christian & Newey, Whitney, 2022. "High-dimensional linear models with many endogenous variables," Journal of Econometrics, Elsevier, vol. 228(1), pages 4-26.
    • Handle: RePEc:eee:econom:v:228:y:2022:i:1:p:4-26
    DOI: 10.1016/j.jeconom.2021.06.011
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    References listed on IDEAS

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    Cited by:

    1. Eric Gautier & Christiern Rose, 2022. "Fast, Robust Inference for Linear Instrumental Variables Models using Self-Normalized Moments," Papers 2211.02249, arXiv.org, revised Nov 2022.

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    More about this item

    Keywords

    Honest confidence regions; Instrumental variables; High dimensional models;
    All these keywords.

    JEL classification:

    • C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • C39 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Other

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