Interpreting Tests of School VAM Validity
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Angrist_Interpreting tests.pdf
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Author(s)
Walters, Christopher
Angrist, Joshua
Hull, Peter Davenport
Pathak, Parag
Date Issued
May 2016
Journal
American Economic Review
Publisher
American Economic Association (AEA)
Citation
Angrist, Joshua, Peter Hull, Parag Pathak, and Christopher Walters. “Interpreting Tests of School VAM Validity.” American Economic Review 106, no. 5 (May 2016): 388–392. ©2016 American Economic Association.
Version
Final published version
Abstract
We develop over-identification tests that use admissions lotteries to assess the predictive value of regression-based value-added models (VAMs). These tests have degrees of freedom equal to the number of quasi-experiments available to estimate school effects. By contrast, previously implemented VAM validation strategies look at a single restriction only, sometimes said to measure forecast bias. Tests of forecast bias may be misleading when the test statistic is constructed from many lotteries or quasi-experiments, some of which have weak first stage effects on school attendance. The theory developed here is applied to data from the Charlotte-Mecklenberg School district analyzed by Deming (2014).
MIT Department
Massachusetts Institute of Technology. Department of Economics
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1257/aer.p20161080
