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Negative Control Falsification Tests for Instrumental Variable Designs

Author

Listed:
  • Oren Danieli
  • Daniel Nevo
  • Itai Walk
  • Bar Weinstein
  • Dan Zeltzer

Abstract

The validity of instrumental variable (IV) designs is typically tested using two types of falsification tests. We characterize these tests as conditional independence tests between negative control variables -- proxies for unobserved variables posing a threat to the identification -- and the IV or the outcome. We describe the conditions that variables must satisfy in order to serve as negative controls. We show that these falsification tests examine not only independence and the exclusion restriction, but also functional form assumptions. Our analysis reveals that conventional applications of these tests may flag problems even in valid IV designs. We offer implementation guidance to address these issues.

Suggested Citation

  • Oren Danieli & Daniel Nevo & Itai Walk & Bar Weinstein & Dan Zeltzer, 2023. "Negative Control Falsification Tests for Instrumental Variable Designs," Papers 2312.15624, arXiv.org, revised Apr 2025.
  • Handle: RePEc:arx:papers:2312.15624
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    References listed on IDEAS

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    1. Raj Chetty & John N. Friedman & Jonah E. Rockoff, 2014. "Measuring the Impacts of Teachers I: Evaluating Bias in Teacher Value-Added Estimates," American Economic Review, American Economic Association, vol. 104(9), pages 2593-2632, September.
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    More about this item

    JEL classification:

    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation
    • C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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