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Wild bootstrap tests for IV regression

Author

Listed:
  • Russell Davidson

    (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique, CIREQ - Centre interuniversitaire de recherche en économie quantitative, Department of Economics [Montréal] - McGill University = Université McGill [Montréal, Canada])

  • James Mackinnon

    (Department of Economics - Queen's University [Kingston, Canada])

Abstract

We propose a wild bootstrap procedure for linear regression models estimated by instrumental variables. Like other bootstrap procedures that we have proposed elsewhere, it uses efficient estimates of the reduced-form equation(s). Unlike them, it takes account of possible heteroskedasticity of unknown form. We apply this procedure to t tests, including heteroskedasticity-robust t tests, and to the Anderson-Rubin test. We provide simulation evidence that it works far better than older methods, such as the pairs bootstrap. We also show how to obtain reliable confidence intervals by inverting bootstrap tests. An empirical example illustrates the utility of these procedures.

Suggested Citation

  • Russell Davidson & James Mackinnon, 2009. "Wild bootstrap tests for IV regression," Working Papers halshs-00443550, HAL.
    • Handle: RePEc:hal:wpaper:halshs-00443550
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00443550
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    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General

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