The course will be aiming at providing you with a thorough understanding and operational knowledge of the mostly commonly used methods to identify and estimate causal effects in economics. Most economic questions are, by their own nature, causal (e.g., the effect of the introduction of a minimum wage on the labor market, the impact of the adoption of a fiscal policy to boost consumption, etc.).
However, the data available to economists are, typically, non-experimental—i.e., they result from agents’ choices and market equilibria. Hence, identifying causal effects in economics poses specific challenges: correlation is not causation. The course will be designed so as to start by defining the concept of causality used throughout it and proceed by analyzing, both at the theoretical and applied level, different research designs and the corresponding econometric methods to identify causal effects: matching, regression, difference-in-differences, instrumental variables and regression discontinuity design.
This course is part of the “Labor, Development & Policy evaluation” Program. If you wish to follow this course, you need to enrol via the Program at this link.
