A Bayesian Look at American Academic Wages: The Case of Michigan State University
Résumé
The paper investigates academic wage formation inside Michigan State University and develops tools in order to detect the presence of possible superstars. We model wage distributions using a hybrid mixture formed by a lognormal distribution for regular wages and a Pareto distributions for higher wages, using a Bayesian approach, particularly well adapted for inference in hybrid mixtures. The presence of superstars is detected by studying the shape of the Pareto tail. Contrary to usual expectations, we did found some evidence of superstars, but only when recruiting Assistant Professors. When climbing up the wage ladder, superstars disappear. For full professors, we found a phenomenon of wage compression as if there were a higher bound, which is just the contrary of a superstar phenomenon. Moreover, a dynamic analysis shows that many recruited superstars did not fulfill the university expectations as either they were not promoted or left for lower ranked universities.
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