The market for highly-skilled labor: Evidence from professional sports
In this project, we will study historical player transfer data from European professional football (n > 1,000,000 transfers). To supplement this analysis, we will also exploit data on player and team performance, team ownership and management, team finances, and player agents.
This is an UNPAID research project.
Faculty Advisor
- Professor: Wei Cai
- Center/Lab:
- Professor Cai’s research broadly investigates the role of information and incentives in shaping behavior, decision-making, and performance in complex contracting environments. She uses multiple research methods including statistical analyses of archival data sources, field experiments, and surveys. She closely collaborates with practitioners and collects unique data that can provide important managerial implications for the design of management control systems in shaping desirable organizational outcomes.
Project Timeline
- Earliest starting date: 9/6/21
- End date: 8/31/22
- Number of hours per week of research expected during Fall 2021: ~10
- Number of hours per week of research expected during Summer 2022: ~40
Candidate requirements
- Skill sets:
- Programming in R and Stata: e.g. Tidyverse, RMarkdown, Shiny
- Basic statistics and econometrics: producing and interpreting descriptive statistics and regressions, hypothesis testing, and causal inference
- Basic data science: network analysis, machine learning, data visualization
- Student eligibility:
freshman,sophomore,junior,senior, master’s - International students on F1 or J1 visa: eligible
- Academic Credit Possible: Yes