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.
Group analysis projects that are assigned will use the Python data science software suite. Students will be asked to take 12 hours of individual, introductory online instruction, imparting basic Python software skills. 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. If you do have some economics experience, you are encouraged to assist those of your peers who do not. 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.
Every student will be asked to participate in two group 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 microeconomic topic. In addition, each student will be asked to complete pass/fail problem sets, to take a midterm, and submit a final project. The group presentations will each count for 15% of the final grade, the problem sets for 20%, the midterm for 20%, and the final project for 30%.