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Female athletic participation and income: evidence from a latent class model

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  • Steven B. Caudill
  • James E. Long
  • Franklin G. Mixon

Abstract

This paper introduces and applies an EM algorithm for the maximum-likelihood estimation of a latent class version of the grouped-data regression model. This new model is applied to examine the effects of college athletic participation of females on incomes. No evidence for an “athlete” effect in the case of females has been found in the previous work by Long and Caudill [12], Henderson et al. [10], and Caudill and Long [5]. Our study is the first to find evidence of a lower wage for female athletes. This effect is present in a regime characterizing 42% of the sample. Further analysis indicates that female athletes in many otherwise low-paying jobs actually get paid less than non-athletes.

Suggested Citation

  • Steven B. Caudill & James E. Long & Franklin G. Mixon, 2012. "Female athletic participation and income: evidence from a latent class model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(3), pages 477-488, June.
    • Handle: RePEc:taf:japsta:v:39:y:2012:i:3:p:477-488
    DOI: 10.1080/02664763.2011.596194
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    8. Steven Caudill & James Long, 2010. "Do former athletes make better managers? Evidence from a partially adaptive grouped-data regression model," Empirical Economics, Springer, vol. 39(1), pages 275-290, August.
    9. Hamparsum Bozdogan, 1987. "Model selection and Akaike's Information Criterion (AIC): The general theory and its analytical extensions," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 345-370, September.
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    Cited by:

    1. Bianca Biagi & Maria Giovanna Brandano & Steven B. Caudill, 2016. "Tourism and house prices in Italy," Tourism Economics, , vol. 22(5), pages 964-978, October.
    2. Jerome Segura III & Jonathan Willner, 2019. "Athleticism in NCAA D-III: It Ain’t Only Football That Matters," Journal of Sports Economics, , vol. 20(7), pages 929-958, October.

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