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Implementing weak-instrument robust tests for a general class of instrumental-variables models

Author

Listed:
  • Keith Finlay

    () (Tulane University)

  • Leandro M. Magnusson

    () (Tulane University)

Abstract

We present a minimum distance approach for conducting hypothesis testing in the presence of potentially weak instruments. Under this approach, we propose size-correct tests for limited dependent variable models with endogenous explanatory variables such as endogenous tobit and probit models. Addition- ally, we extend weak-instrument tests for the linear instrumental-variables model by allowing for variance–covariance estimation that is robust to arbitrary het- eroskedasticity or intracluster dependence. We invert these tests to construct confidence intervals on the coefficient of the endogenous variable. We also provide a postestimation command for Stata, called rivtest, for computing the tests and estimating confidence intervals. Copyright 2009 by StataCorp LP.

Suggested Citation

  • Keith Finlay & Leandro M. Magnusson, 2009. "Implementing weak-instrument robust tests for a general class of instrumental-variables models," Stata Journal, StataCorp LP, vol. 9(3), pages 398-421, September.
  • Handle: RePEc:tsj:stataj:v:9:y:2009:i:3:p:398-421
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    References listed on IDEAS

    as
    1. Andrews, Donald W.K. & Moreira, Marcelo J. & Stock, James H., 2007. "Performance of conditional Wald tests in IV regression with weak instruments," Journal of Econometrics, Elsevier, vol. 139(1), pages 116-132, July.
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    More about this item

    Keywords

    rivtest; ivregress; ivprobit; ivtobit; condivreg; ivreg2; weak instruments; endogenous tobit; endogenous probit; two-stage least squares; hypothesis testing; confidence intervals;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • 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
    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions

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