Syllabus
AEM 7010: Doing Applied Economics Research, Spring 2026
The official course syllabus PDF will be linked here.
Course summary
AEM 7010 introduces practical skills for doing applied economics research. The course covers four areas across eight 75-minute sessions: trends in economic research, reproducibility, version control with Git and GitHub, and AI tools for coding.
This site documents the last quarter of the class.
This course provides exposure to a wide variety of basic skills necessary for conducting high-quality research in applied economics. This includes defining a research question, primary and secondary data collection, principles of academic writing and presentation, research ethics, basic coding and data management, as well as project management. This course is meant to help students transition from coursework to the independent research they undertake starting at the end of the first year of the Ph.D. program. Some of the topics (e.g., coding) are only covered at an overview level with the expectation that those requiring a deeper knowledge will take further coursework.
What you will be able to do
By the end of these eight sessions you will be able to:
- Build and document reproducible research workflows.
- Track changes to your R scripts and research code using Git.
- Back up your work on GitHub and collaborate with co-authors through pull requests.
- Tag specific versions of your code for paper submissions and replication packages.
- Use AI coding assistants responsibly in research, with verification.
- Document and disclose AI use in a way that meets journal and replication standards.
Logistics
- Term: Spring 2026, last quarter of the class.
- Meeting times: Mondays and Wednesdays, 75-minute sessions.
- First meeting: Wednesday, April 8, 2026.
- Last meeting: Monday, May 4, 2026.
- Credits: 3 credits, S/U.
- Corequisite: ECON 6090.
- Instructors: Prof. Ariel Ortiz-Bobea (sessions 1, 4 to 8). Lars Vilhuber, AEA Data Editor (sessions 2 and 3).
Schedule
The course meets twice a week: Mondays and Wednesdays. Sessions 2 and 3 are guest-led by Lars Vilhuber, AEA Data Editor. The other six are taught by Ariel Ortiz-Bobea.
- 1. Wed, Apr 8 Trends in Economic ResearchReproducibility expectations, the data revolution, and the rise of AI tools.
- 2. Mon, Apr 13 Reproducibility IFoundations and what top journals require. With Lars Vilhuber.
- 3. Wed, Apr 15 Reproducibility IIReplication packages in practice. Restricted data and computational environments. With Lars Vilhuber.
- 4. Mon, Apr 20 Git FundamentalsThe core Git workflow on your own computer.
- 5. Wed, Apr 22 GitHub and CollaborationPush, pull, branches, pull requests, tags for replication packages.
- 6. Mon, Apr 27 AI Tools I: ChatA mental model of LLMs. Live demo of a chat-driven scrape.
- 7. Wed, Apr 29 AI Tools II: CoworkAgentic desktop AI that can see your files and run code.
- 8. Mon, May 4 AI Tools III: Claude CodeA code-native agent inside a git project.
Before each session
Each session has a short Before class note at the top of its page. Read it the day before. The first one to check is for Session 4, which assumes you have completed the Setup page.
Grading and expectations
Attendance is expected at every session. Each session lists short tasks under Before class, In class, and After class. Completing these is what builds the practical fluency the course is designed to deliver.
Before you begin
Two short setup steps before Session 4: install Git, R, and an editor. Details on the Setup page.