• Topics in Data Analytics in R/Stata ECON 258

With data analytics being an important skill, the goal of this class is to provide hands-on experience for students to be confident enough to continue learning on their own especially on the job or during graduate school. No coding experience is necessary. The course is divided into three sections: 1) Learning the basic coding syntax, data cleaning, manipulation, graphs, and tables, 2) intuition of causal inference models, and 3) machine learning models.

The course focuses more on intuition and hands-on coding rather than being too theoretical on econometrics/machine learning. Learning to code is difficult for two reasons: first, students need to get used to the coding language; second, students need to connect ideas with data. The second is what I emphasize. How would one come up with a question that could be explored in the data? Students receive code and (messy) data every week. Each code starts with a question and a game plan. Group work is common where students are asked to develop their own questions and see whether they can answer the question using the data.

• Markets and Institutions through Experimentation ECON 395

This course explores key ideas from influential economic scholars surrounding topics in politics, economics, and legal institutions. Students can “experience” the theory at work through an experiment each week. We delve into the works of Anthony Downs (median voter theorem), Elinor Ostrom (tragedy of the commons), Ronald Coase (property rights), and George Akerlof (a market for lemons) among others.

On Tuesdays, students participate in a classroom experiment followed by group and class discussions. Students are nudged to discover the results of the experiment themselves through discussion prompts. On Thursdays, a more traditional lecture is given on the scholar and theory underlying the experiment.

Discussion encourages students to relate real-life observations to the classroom experiment as well as identifying realistic or unrealistic features of the experiment. At the end of the course, students work in groups to investigate an institutional problem, relate the problem with material discussed in class, and suggest a solution. Problems that students chose ranged from smaller problems of “How to make class registration more efficient?” to larger public policy issues such as “What vaccine distribution structure would be more efficient?”

Other courses taught:

• Principles of Macroeconomics ECON 102

• Intermediate Introduction to Statistics and Econometrics ECON 451