Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
Factor price markdowns are a key object of interest when studying monopsony power. In this article, we test the performance of “production approaches” to estimate factor price markdowns, which have been used increasingly often in the literature. We evaluate the performance of these estimators under various data-generating processes using Monte Carlo simulations. We discuss the commonly made assumptions in this class of estimators, and we address the methodological challenges involved with relaxing these assumptions, such as departing from Hicks neutrality, allowing for nonsubstitutable inputs, and allowing for various types of labor market conduct.