Topics in Microeconometrics
Description
This course provides an introduction to recent advances in methods for program and policy evaluation. Causal inference seeks to estimate the impacts of programs or policy interventions on outcome variables of interest. For example, labor economists are interested in estimating the causal effect of a training program on earnings.
We first discuss the general framework based on counterfactual outcomes and then cover the main methods available to the empirical researcher. For each method, we discuss key theoretical results, implementation issues and applications from leading research papers. We pay particular attention to the fact that the different methods make different assumptions about the mechanism based on which people are assigned to the program. We start with the assumption that program assignment is conditionally randomized. Suitable methods in this case include matching and regression methods. Then we discuss methods that rely on longitudinal information to recover causal effects. We further discuss instrumental variable methods that are suitable in the case of confounded assignment. The last part of the lecture covers the regression discontinuity design that exploits deterministic assignment rules generating discontinuities in the probability of receiving the program.
The course consists of weekly lectures and exercise sessions (6 ECTS credits in total), starting in the first week of the term.
See ILIAS for further information.