This course will feature 5 2-hour lectures.

Module description: 
The course aims to introduce the key concepts and state-of-art methods for causal inference from randomized experiments and observational studies under the potential outcome framework. We will cover different situations corresponding to different assumptions concerning the assignment mechanism. We will discuss inference under different modes of inference including design (randomization)based, frequentist and Bayesian in fully or partially identified settings. We will discuss the design and analysis of experimental designs and the design and analysis of observational studies with regular assignment mechanisms where the unconfoundedness assumption is assumed to hold. We will introduce irregular assignment mechanisms discussing strategies for dealing with experimental studies with noncompliance and other complications, introducing the principal stratification framework. We will introduce some alternative identification and estimation strategies in observational settings, such as changes in changes and synthetic control methods.
We will use R for the practical sessions held by the TAs.

Learning outcomes
By the end of the course, students will be able to:
•             Identify appropriate econometric and statistical methods  to address causal questions in economics.
•             Master experimental and observations methods for causal inference.
•             Design and evaluate empirical strategies for causal inference.
•             Implement causal inference methodology.
•             Interpret and critically assess empirical research in microeconometrics using the tools covered in the course.
•             Being able to identify, assess and overcome threats for identification and interpretation of causal effects, such as interference, data dependance, missing data, post-treatment complications.
•             Translate theoretical understanding of econometric and statistical techniques into practical data analysis using statistical software.

Assessment  
•    Two take-home assignment (40% each)
•    Participation in class (20%)