AEM 6850 - Empirical Methods for Applied Economists

Fall. 3 credits. Letter grades only (no audit).

Prerequisite: AEM 6120 or higher.

A. Michuda.

The course introduces students to various empirical methods and practices necessary to conduct applied research and analysis in microeconomics in a data-rich world. The course format is hands-on and students will conduct most of their work on computers in Python. Students will be graded on 1- participation, 2- weekly empirical exercises and 3- final project (chosen by the student). Topics covered include: 1- basics of Python programming 2- efficient coding practices for replication, teamwork and debugging 3- data gathering and manipulation (APIs and scraping) 4- effective data visualization 5- basic analysis of spatial data and networks 6- numerical methods (Monte Carlo simulations, bootstrapping techniques).

Outcome 1: Students will become proficient in basic programming in a statistical software.

Outcome 2: Students will be capable of gathering, manipulating and visualizing various types of data.

Outcome 3: Students will employ numerical methods in applied research.

Outcome 4: Students will apply techniques for analyzing original economic questions.