A Bayesian Look at American Academic Wages: The Case of Michigan State University

Majda Benzidia and Michel Lubrano

No 1628, AMSE Working Papers from Aix-Marseille School of Economics, France

Abstract: The paper investigates academic wage formation, taking as a benchmark the Michigan State University. 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. With this model, we test for the presence of superstars in the Pareto member by comparing inequality in the two members. We found some evidence of superstars when recruiting Assistant Professors. However, a dynamic analysis reveals that they have a higher rate of outing, and, if they stay, a lower rate of wage increase. For full professors, we found a phenomenon of wage compression as if there were a kind of higher bound, which is just the contrary of a superstar phenomenon.

Keywords: wage determination; academic market; superstars; tournaments theory; human capital; Mincer equation; Bayesian inference; hybrid mixtures (search for similar items in EconPapers)
JEL-codes: C10 C11 C46 J20 J24 J30 J45 (search for similar items in EconPapers)
Pages: 46 pages
Date: 2016-10
New Economics Papers: this item is included in nep-lma
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.amse-aixmarseille.fr/sites/default/files/_dt/2012/wp_2016_-_nr_28.pdf (application/pdf)

Related works:
Working Paper: A Bayesian Look at American Academic Wages: The Case of Michigan State University (2016)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:aim:wpaimx:1628

Access Statistics for this paper

More papers in AMSE Working Papers from Aix-Marseille School of Economics, France AMU-AMSE - 5-9 Boulevard Maurice Bourdet, CS 50498 - 13205 Marseille Cedex 1. Contact information at EDIRC.
Bibliographic data for series maintained by Gregory Cornu ().