Trade, Technology, and Industrial Policy in a Global Economy, Using Python-WB
This class will teach the key economic concepts underlying real world trade and technology policies, as practiced in today’s global economy, using a suite of widely used non-proprietary, open, data science software tools applied to real world data.
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 throughout the rest of your careers). Second, the class is designed to teach international economic policy 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. This course, and the online course modules, assume no prior software experience. An introductory microeconomics class, or equivalent, is a prerequisite for this class.
The Python software packages we will use are components in the most widely used, non-proprietary, open data science software platform, and readily allow access to excellent data visualization and analysis capabilities handling even the largest public datasets. The same software platform can also be integrated with, and run, R and Stata statistical analysis code.
Every student will participate in two formal group project presentations to the class. These exercises will be oral presentations of student analyses and solutions to a detailed policy analysis problem based on the particulars of a real world economic topic. In addition, each student will be asked to complete individual problem sets, to take an individual midterm, and to submit an individual final project.
Selected excerpts from anonymous student comments about last year’s class:
“The course was quite a surprise package, as it was difficult to blend teaching a programming language along with the learning of economic concepts. But Prof. Flamm pulled it off effortlessly. He had his content so well prepared that it was practically laid out to us for us to absorb and learn. He leveraged technology (Juptyr notebooks, python programming tools etc) and made best use of the ZOOM platform and virtual learning to create a learning environment. So glad to have taken the course.”
“Dr. Flamm did a good job of finding ways to incorporate Python into an International Economics format.”