Interpreting Tests of School VAM Validity
Author(s)Walters, Christopher; Angrist, Joshua; Hull, Peter Davenport; Pathak, Parag
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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).
DepartmentMassachusetts Institute of Technology. Department of Economics
American Economic Review
American Economic Association (AEA)
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.
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