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Technical skills

The skills listed here are things you might have learned in your classes or from prior experience (see sections on coursework and prior experience). We encourage you to emphasize these skills in your cover letter or other pieces of your application, giving examples of times that you have employed these skills either inside or outside of the classroom.

If you’re interested in further developing your technical skills, check out our list of resources. For an example of how you can use these skills as an RA, check out our coding example.

  • Some understanding of causal inference
  • Comfort with at least one of the following languages in order to clean, manage, visualize, and analyze data (e.g. run linear regressions)
    • Stata
    • R
    • Python
    • MATLAB
  • Familiarity with principles of programming
  • Ability to use LaTeX


  • Ability to manipulate large datasets or databases (e.g., in SAS or SQL)
  • Knowledge of the command line interface
  • Mapping skills (could be in ArcGIS, qGIS, Python, R, etc.)
  • Knowledge of fancy data visualization packages or libraries
    • R: ggplot2
    • Python: matplotlib
    • JavaScript: D3
  • Skills to do structural estimation (e.g., in MATLAB or Julia)
  • Ability to use Git or other version control softwares