UC Davis

We apply "value-added" models to estimate the effects of teachers on an outcome they cannot plausibly affect: student height. When fitting commonly estimated models to New York City data, we find that the standard deviation of teacher effects on height is nearly as large as that for math and reading, raising potential concerns about value-added estimates of teacher effectiveness. We consider two explanations: non-random sorting of students to teachers and idiosyncratic classroom-level variation. We cannot rule out sorting on unobservables, but find students are not sorted to teachers based on lagged height. The correlation in teacher effects estimates on height across years and the correlation between teacher effects on height and teacher effects on achievement are insignificant. The large estimated "effects" for height appear to be driven by year-to-year classroom by teacher variation that is not often separable from true effects in models commonly estimated in practice. Reassuringly for use of these models in research settings, models which disentangle persistent effects from transient classroom-level variation yield the theoretically expected effects of zero for teacher value added on height.