OSE data science

This course introduces students to basic microeconometric methods. The objective is to learn how to make and evaluate causal claims. By the end of the course, students should be able to apply each of the methods discussed and critically evaluate research based on them. Throughout the course we will make heavy use of Python and its SciPy ecosystem as well as Jupyter Notebooks.

• Lectures
• Problem sets
• Handouts
• Projects
• Partners
• Organization

Textbooks

                                                                                         

We use the book The effect: an introduction to research design and causality by Nick Huntington-Klein and Causal inference: the mixtape by Scott Cunningham throughout the course.

Reviews

• Athey, S., Imbens, G. (2017). The state of applied econometrics: causality and policy evaluation , Journal of Economics Perspectives, 31(2), 3-32.

• Abadie, A., Cattaneo, M.D. (2018). Econometric methods for program evaluation , Annual Review of Economics, 10, 465-503.

Powered by

                                                                       

We gratefully acknowledge funding by the Federal Ministry of Education and Research (BMBF) and the Ministry of Culture and Science of the State of North Rhine-Westphalia (MKW) as part of the Excellence Strategy of the federal and state governments.