Spring 2022 - 59470 - PA 393K - Applied Microeconomics for Policy Analysis

Applied Microeconomics for Policy Analysis-WB

This class is designed to motivate learning microeconomic concepts by showing that they can be simply and practically applied to real world data, and to give you some first-hand experience in doing so. Much of the learning will be structured in the form of empirical economic analysis problems. In addition to completing individual exercises, every student will take an individual midterm examination, submit an individual final project, and join in two small-group analysis projects, with in-class presentation, discussion, and critique.

Assigned projects and problem sets will be undertaken using open source data science software. The Python software tools in which all students will gain some proficiency are part of the most widely used, non-proprietary, open data science software platform, and enable access to excellent data visualization and analysis tools capable of handling even the largest datasets. The same software platform can also be integrated with, and run, R and Stata statistical analysis code.

The intention is to make this class doubly valuable to a student interested in public policy. First, the class will introduce you to cutting edge data science tools that can be applied to real data for practical policy purposes (and hopefully both give you some advantages in post-graduation job markets and facilitate future acquisition of even more advanced skills over the rest of your careers). Second, the class is designed to teach economic concepts by showing that they can be simply and practically applied to real world data, and to give you some first- hand experience in doing this.

Students will be asked to complete 12 hours of individual, introductory, asynchronous online instruction in basic Python software skills prior to the third week of class. Examples worked in class and solutions posted online will use the Python data science software platform.

The class does not require a previous economics course or any previous computer programming experience. Time will be reserved for in-class laptop “empirical analysis clinics,” to provide you with real time feedback on conceptual or data analysis issues you may encounter.

Selected excerpts from anonymous student comments from last year’s class:

“I was really anxious about this course going into it because of the reputation economics has as a difficult subject and the programming-coding component of the course. But Dr. Flamm really walked us through the challenging aspects of the subject and helped us a lot with contextualizing these difficult concepts with a new set of skills that I'm sure I will find tons of use for in my future career. It was always a delight to hear Dr. Flamm lecture and interact with him in office hours and on days when students gave presentations and he got us thinking and asking questions about our research and presentation topics.”

“From someone who's not particularly strong in Econ and has never coded: I loved the CORE textbook. Digestible for non-econ folks. I appreciated your incorporation of your interests into the course; they were interesting topics for sure.…I very much appreciate you forcing us to learn Python. It is a practical skill that I think most students will be glad to know a bit about.”

“Flamm … adapted class well in terms of the requirements for Covid-19 it was not overwhelming but I did learn a lot of python coding which was cool.”

“Dr. Flamm…gave room for even a Zoom class to bond and his passion for economics is readily apparent.”

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