Empirical Research Seminar

This course guides you through the process of empirical research in applied microeconomics, from selecting research ideas and appropriate methods, through collecting data, to submitting your final paper to a journal. We won’t talk about these steps, we will do these steps together. Each student and instructor completes a paper during the two terms of the course, which they submit at the end of the course to peer-reviewed journals.

Learning outcomes

• A complete, finished paper, submitted to a peer reviewed journal.
• Applicable, hands-on experience with how empirical research is done:
  • select a research idea
  • review the literature
  • collect data
  • select appropriate tools and methods
  • iterate through analysis
  • ensure reproducibility
  • write and present results

Learning activities and teaching methods

There are weekly writing goals that are share both in writing and discussed in class. Active participation is required throughout the term. Peer review is important, practice giving and receiving constructive feedback.

During the first term, we meet weekly and have weekly writing assignments. These are discussed in class. In the second term, you report on the milestones and problems with your work.

Assessment

• Participation in class discussions: 20 percent
• Written assignments for each class: 30 percent
• Evaluation from peers: 20 percent
• Final paper: 30 percent

The two terms are graded together.

Course contents

First term

1. What is your favorite empirical paper? Write 2-300 words about why that paper is great.
2. Bring a research question and a dataset. Don’t worry if they are vague, we will discuss them together.
3. Write an aspirational introduction. This is 5-600 words explaining what your paper does and why it is great; if everything goes well in your research.
4. Research design and estimable equation. How do you identify the measure the quantity / identify the effect you are interested in?
5. Look for the smoking gun. Discuss early evidence suggesting there is something to your story.
6. Modeling framework and literature. Place your (aspirational) results in the context of existing work.

Second term

1. Presenting regression results.
2. Visualizing patterns in your data.

Four classes are dedicated to feedback on your continued work.