This paper studies the relationship between university institutional autonomy (both formal and informal) and their performance and efficiency using multi-stage empirical methodology. First, we measure an “autonomy-in-use” index, and then we employ Data Envelopment Analysis in order to...

School rankings based on value-added (VA) estimates are subject to prediction errors, since VA is defined as the difference between predicted and actual performance. We introduce a more flexible random forest (RF), rooted in the machine learning literature, to minimize prediction errors and to...