Assessing Rothstein's critique of teacher value-added models

Abstract

Value-added models of teacher effectiveness yield consistent estimates of teacher quality under the assumption that students are randomly assigned to classrooms conditional on ability. Rothstein (2010) tested and rejected this underlying sorting assumption, casting doubt on the usefulness of the value-added framework. In this paper, I illustrate that the falsification tests employed by Rothstein perform quite poorly in small samples and I propose an alternative testing strategy that is less sensitive to sample size. I also show that none of the proposed falsification tests works well when the achievement production function is misspecified. Finally, I return to the same North Carolina sample employed by Rothstein and retest the assumption of conditional random assignment. Once I account for the “smallness” of the data and allow teacher inputs to persist at reasonable rates, I fail to reject conditional random assignment.

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