4 August 2023
Causal Inferenceonline course
Learn a number of state-of-the-art tools to establish causal relations in the social sciences, with a focus on intuition.
Need to know
You should have a good understanding of linear regression, including interactions, some understanding of panel data, and some knowledge of R.
To start, we will delve into the challenges of establishing causality in the social sciences. You will gain an understanding of the fundamental problem of causal inference and the potential outcomes framework, which provide a solid foundation for making causal claims in research. Through detailed discussions and examples, you will also learn about experiments — how they work, why they are important, and how they can help establish causal relations in social science research.
You will learn about instrumental variables (IVs), discussing their assumptions, how to estimate them, and replicate previous work that uses this method. You will also briefly discuss ideas on how to find good IVs.
Learn about difference-in-differences (DIDs), discussing their assumptions, how to estimate them, and replicate previous work that uses this method. We will also briefly discuss the recent explosion of literature using this topic and some thoughts on how to navigate it.
You have the opportuntity to explore regression discontinuity designs (RDDs), discussing their assumptions, and how to estimate them. You will replicate previous work that uses this method and discuss fuzzy RDDs and how they connect to instrumental variables.
You will learn about causal inference as a way of thinking. Good causal work is not just grounded in solid knowledge of estimation. It requires the ability to think of potential pitfalls of different designs, and to be ingenious in finding identification strategies. You will learn some techniques that make this easier, and we'll discuss how to apply the methods learned over the week to the topics in which each participant is interested.
How the course will work online
The course is structured into five live Zoom sessions, each lasting 2.5 hours each day. The course provides a safe and collaborative environment for discussing students' work and published research. Our ultimate goal is to make the course useful, and the final session will focus on specific topics of interest to each student.
Throughout the course, we will frequently discuss each student's research. You will be provided with methodological and applied readings to deepen your understanding of the methods we learn. We will also spend substantial time replicating previous work using R, which will give you the confidence to interpret software output for each method we discuss.
Vicente Valentim is Postdoctoral Prize Research Fellow at Nuffield College, University of Oxford. Vicente studies how democracies generate norms against behaviour associated with authoritarianism, how those norms are sustained, and how they erode.
Researchers, professional analysts, and advanced students.
This introductory course on causal inference techniques will teach you state-of-the-art tools for establishing causal relations in the social sciences. Emphasising intuition, the course will equip you to deepen your knowledge of these methods independently and engage with the methodological debate surrounding them. You will learn popular methods of causal inference in the social sciences and how to apply them to research topics of interest, giving you a strong foundation for further study.
You can earn up to four credits for attending this course.
3 ECTS credits – Attend 100% of live sessions and engage fully with class activities.
4 ECTS credits – Attend 100% of live sessions, engage fully with class activities and complete a post-class assignment.
GBP 478: ECPR Member
EUR 956: ECPR Non-Member
Funding applications for the 2023 ECPR Summer School in Research Methods and Techniques are now closed.
For more details on funding opportunities for ECPR's other events, please visit our website.