Please join the last Max Weber Programme's last Lecture before the summer with Prof. Imbens, Honorary Degree Awardee.
The quest to move beyond association and establish causation lies at the heart of empirical science. This talk traces the intellectual history of causal inference, from its foundational developments to the sophisticated methodological landscape of today. Central to this discussion is the randomized controlled experiment, long regarded as the gold standard for identifying causal effects. I will discuss how randomization holds such a privileged position through its ability to balance observed and unobserved confounders, and to yield unbiased estimates of treatment effects under minimal assumptions.
Drawing on a range of examples, both historical and contemporary, I will illustrate the remarkable power of randomized experiments to resolve questions that observational data alone cannot answer. Yet randomization, for all its virtues, is not a universal solution. Modern applied settings increasingly present challenges that classical experimental designs were not built to handle. These include interference between units, dynamic treatment regimes, and complex network structures. I will discuss recent advances in experimental design that have emerged in response to these challenges, offering new tools for causal identification in settings where traditional randomization falls short.
The talk aims to be accessible to a broad audience while conveying both the enduring value and the evolving frontier of experimental approaches to causal inference.
About the speaker:
Guido Imbens is a Dutch-American economist whose research concerns econometrics and statistics. He holds the Applied Econometrics Professorship in Economics at the Stanford Graduate School of Business at Stanford University. After graduating from Brown University Guido Imbens taught at Harvard University, UCLA, and UC Berkeley. He specialises in econometrics, and in particular, methods for drawing causal inferences. In 2021, Imbens was awarded half of the Nobel Memorial Prize in Economic Sciences jointly with Joshua Angrist "for their methodological contributions to the analysis of causal relationships".
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