Uncovering Value Drivers of High Performance Soccer Players

Maribel Serna Rodríguez, Andrés Ramírez Hassan, Alexander Coad

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

This article tries to uncover the drivers of soccer players’ market value in the five major European soccer leagues taking into account model uncertainty (variable selection) in a framework with 35 billion potential models. For this purpose, we use a hedonic regression framework and implement Bayesian model averaging (BMA) through Markov chain Monte Carlo model composition (MC3). To deal with endogeneity issues, instrumental variable Bayesian model averaging (IVBMA) is implemented as well. We find very strong, and robust evidence, that the most important value drivers are player’s performance, participation in the national team (senior and under-21), age, and age squared.

Original languageEnglish
Pages (from-to)819-849
Number of pages31
JournalJournal of Sports Economics
Volume20
Issue number6
DOIs
Publication statusPublished - 2019 Aug 1
Externally publishedYes

Keywords

  • BMA
  • IVBMA
  • MC
  • soccer
  • value drive

ASJC Scopus subject areas

  • Economics, Econometrics and Finance (miscellaneous)

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