Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
Results from the incentive literature suggest that performance measures are often distorted, eliciting dysfunctional and unintended responses. The existence of these responses, however, is difficult to demonstrate in practice because this behavior is typically hidden from the researcher. We present a simple model showing that one can test for the existence of distortions by estimating the change in the association between a performance measure and the true goal of the organization with the measure's introduction. Using data from a public-sector organization, we find evidence consistent with the existence of distortions. We draw implications for the selection of performance measures. Copyright by the President and Fellows of Harvard College and the Massachusetts Institute of Technology.