Do former athletes make better managers? Evidence from a partially adaptive grouped-data regression model

Abstract

The goal of this paper is to introduce a partially adaptive estimator for the grouped-data regression model based on an error structure described by a mixture of two normal distributions. The model we introduce is easily estimated by maximum likelihood using the EM algorithm adapted from the work of Bartolucci and Scaccia (Comput Stat Data Anal 48:821-834, 2005). The partially adaptive estimator is applied to data used by Long and Caudill (Rev Econ Stat 73:525-531, 1991) to examine the impact of intercollegiate athletics on income. We estimate a variation of the original regression model and find that there is a considerable financial advantage for those male athletes now working in business management. This finding is consistent with the idea that athletes acquire team-building and organizational skills that are helpful in business.