Regression modelQuasi-experimental / causal inference

Robust Instrumental Variables Estimation

Robust Instrumental Variables estimation extends standard IV and two-stage least squares (2SLS) by guarding against weak-instrument bias and non-standard inference. Methods such as the Anderson-Rubin test, Limited Information Maximum Likelihood (LIML), and the Conditional Likelihood Ratio test provide valid confidence sets and hypothesis tests even when instruments are weak or only partially identified, making IV inference reliable in settings where standard 2SLS breaks down.

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Sources

  1. Stock, J. H., Wright, J. H., & Yogo, M. (2002). A survey of weak instruments and weak identification in generalized method of moments. Journal of Business and Economic Statistics, 20(4), 518-529. DOI: 10.1198/073500102288618658
  2. Andrews, I., Stock, J. H., & Sun, L. (2019). Weak instruments in instrumental variables regression: Theory and practice. Annual Review of Economics, 11, 727-753. DOI: 10.1146/annurev-economics-080218-025643

Related methods

ScholarGateRobust Instrumental Variables (Robust Instrumental Variables Estimation). Retrieved 2026-06-04 from https://scholargate.app/en/causal-inference/robust-instrumental-variables