Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
Value-added models (VAMs) are increasingly used to measure school effectiveness. Yet, random variation in school attendance is necessary to test the validity of VAMs and to guide the selection of models for measuring causal effects of schools. In this paper, I use random assignment from a public school choice lottery to test the predictive power of VAM specifications. In VAMs with minimal controls and two or more years of prior data, I fail to reject the hypothesis that school effects are unbiased. Overall, many commonly used VAMs are accurate predictors of student achievement gains.