AEM 6850

Empirical Methods for Applied Economists

Course Description

Course information provided by the 2026-2027 Catalog.

The course introduces students to a practical toolkit to enhance empirical economic research in a data-rich, AI-assisted world. The format is hands-on. Students learn in R, building a versioned, reproducible research portfolio on GitHub. The course teaches workflows and tools that are becoming essential to modern empirical research without covering inference. Grading is based on (1) participation, (2) weekly empirical exercises, and (3) a final project. Topics covered include: (1) programming foundations in R; (2) version control, project structure, and reproducibility (git, GitHub, renv, Quarto); (3) responsible use of AI coding tools, verification practices, and disclosure standards; (4) data acquisition (APIs, web scraping, databases); (5) data wrangling and visualization; (6) basic spatial data analysis; and (7) research workflow and communication.

Prerequisites AEM 6120 or higher.

Last 4 Terms Offered 2025FA, 2025SP, 2023FA, 2022FA

Learning Outcomes

• Build a reproducible research project in R.
• Acquire, wrangle, and visualize tabular and spatial data.
• Use, verify, and disclose AI tools in empirical research.
• Plan and communicate a small empirical project in a public repository.

View Enrollment Information