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Optimal formula instruments

Author

Listed:
  • Kirill Borusyak
  • Peter Hull

Abstract

When estimating the effects of treatments defined by complex formulas, researchers often use simple functions of exogenous shocks as instruments. A leading example is “simulated instruments†for public policy eligibility, which capture variation in state-level policy generosity. We show how more powerful instruments can be constructed by incorporating heterogeneous shock exposure while using a recentering procedure to avoid bias. We characterize the asymptotically efficient instruments in this class and propose an algorithm for constructing feasible approximations to them. Compared to a simulated instrument approach, our approach yields a 44% smaller standard error on the private insurance crowd-out effect of Medicaid enrollment from the 2014 Affordable Care Act expansions.

Suggested Citation

  • Kirill Borusyak & Peter Hull, 2025. "Optimal formula instruments," CeMMAP working papers 09/25, Institute for Fiscal Studies.
  • Handle: RePEc:azt:cemmap:09/25
    DOI: 10.47004/wp.cem.2025.0925
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    References listed on IDEAS

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    5. Atila Abdulkadiroğlu & Joshua D. Angrist & Yusuke Narita & Parag A. Pathak, 2017. "Research Design Meets Market Design: Using Centralized Assignment for Impact Evaluation," Econometrica, Econometric Society, vol. 85, pages 1373-1432, September.
    6. David M. Cutler & Jonathan Gruber, 1996. "Does Public Insurance Crowd out Private Insurance?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 111(2), pages 391-430.
    7. Kirill Borusyak & Peter Hull, 2024. "Negative Weights Are No Concern in Design-Based Specifications," AEA Papers and Proceedings, American Economic Association, vol. 114, pages 597-600, May.
    8. Joshua D. Angrist, 1998. "Estimating the Labor Market Impact of Voluntary Military Service Using Social Security Data on Military Applicants," Econometrica, Econometric Society, vol. 66(2), pages 249-288, March.
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    Cited by:

    1. Yechan Park, 2026. "A Design-Based Approach to Testing and Inference in (Quasi-)Experiments with Spillovers," Papers 2607.08640, arXiv.org, revised Aug 2026.
    2. Christopher Carter & Adeline Delavande & Mario Fiorini & Peter Siminski & Patrick Vu, 2025. "Optimal Screening in Experiments with Partial Compliance," Papers 2512.09206, arXiv.org.

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    More about this item

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

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