Welfare Added? Optimal Teacher Assignment with Value-Added Measures
We study how teacher "value added" should inform optimal teacher-assignment policy. Our welfare-theoretic framework illustrates (1) how theoretically optimal assignments leverage variation in teachers' impacts both across student types and across different outcomes, and (2) how empirically optimal assignments trade off improved targeting from estimating richer student heterogeneity against increasing misallocation risk. In practice, optimal assignments use limited student types (only lagged achievement) and multiple outcomes (not just math). Even after correcting for policy overfitting, assignments raise average present-value earnings by $2,800 and increase lower-achieving students' earnings by 70-156% more than benchmark value-added policies that assume that teacher effects are homogeneous across students, that allow for heterogeneous effects across students but for a single subject, or teacher deselection.
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Copy CitationTanner S. Eastmond, Michael Ricks, Julian Betts, and Nathan Mather, "Welfare Added? Optimal Teacher Assignment with Value-Added Measures," NBER Working Paper 34768 (2026), https://doi.org/10.3386/w34768.Download Citation