Instructor Rating Markets

Abstract

We describe the design of Instructor Rating Markets in which students trade on the ratings that will be received by instructors, with new ratings revealed every two weeks. The markets provide useful dynamic feedback to instructors on the progress of their class, while at the same time enabling the controlled study of prediction markets where traders can affect the outcomes they are trading on. More than 200 students across the Rensselaer campus participated in markets for ten classes in the Fall 2010 semester. We show that market prices convey useful information on future instructor ratings and contain significantly more information than do past ratings. The bulk of useful information contained in the price of a particular class is provided by students who are in that class, showing that the markets are serving to disseminate insider information. At the same time, we find little evidence of attempted manipulation of the liquidating dividends by raters. The markets are also a laboratory for comparing different microstructures and the resulting price dynamics, and we show how they can be used to compare market making algorithms.