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Causal Effects in Matching Mechanisms with Strategically Reported Preferences

Author

Listed:
  • Marinho Bertanha
  • Margaux Luflade
  • Ismael Mourifié

Abstract

A growing number of central authorities use assignment mechanisms to allocate students to schools in a way that reflects student preferences and school priorities. However, most real-world mechanisms incentivize students to strategically misreport their preferences. In this paper, we provide an approach for identifying the causal effects of school assignment on future outcomes that accounts for strategic misreporting. Misreporting may invalidate existing point-identification approaches, and we derive sharp bounds for causal effects that are robust to strategic behavior. Our approach applies to any mechanism as long as there exist placement scores and cutoffs that characterize that mechanism’s allocation rule. We use data from a deferred acceptance mechanism that assigns students to more than 1,000 university–major combinations in Chile. Matching theory predicts that students’ behavior in Chile should be strategic because they can list only up to eight options, and we find empirical evidence consistent with such behavior. Our bounds are informative enough to reveal significant heterogeneity in graduation success with respect to preferences and school assignment.

Suggested Citation

  • Marinho Bertanha & Margaux Luflade & Ismael Mourifié, 2024. "Causal Effects in Matching Mechanisms with Strategically Reported Preferences," NBER Working Papers 32434, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:32434
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    1. Justine S. Hastings & Christopher A. Neilson & Seth D. Zimmerman, 2013. "Are Some Degrees Worth More than Others? Evidence from college admission cutoffs in Chile," NBER Working Papers 19241, National Bureau of Economic Research, Inc.
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    More about this item

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation

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