Public event

Data Science Brown Bag: A General Design-Based Framework and Estimator for Randomized Experiments

Join us for a talk by Fredrik Sävje from Yale University as he introduces a new design-based framework for causal inference in randomized experiments. 


Abstract from the speaker: 

We describe a new design-based framework for drawing causal inference in randomized experiments. Causal effects in the framework are defined as linear functionals evaluated at potential outcome functions. Knowledge and assumptions about the potential outcome functions are encoded as function spaces. This makes the framework expressive, allowing experimenters to formulate and investigate a wide range of causal questions. We describe a class of estimators for estimands defined using the framework and investigate their properties. The construction of the estimators is based on the Riesz representation theorem. We provide necessary and sufficient conditions for unbiasedness and consistency. Finally, we provide conditions under which the estimators are asymptotically normal, and describe a conservative variance estimator to facilitate the construction of confidence intervals for the estimands.

About the speaker:

Fredrik Sävje is an Assistant Professor of political science and Resident Fellow at the Institution of Social and Policy Studies at Yale.  He received his PhD in economics from Uppsala University in 2015 and was a Post-doctoral Fellow in the departments of political science and statistics at UC Berkeley.

Bring your own lunch bag! Light pastries and drinks will be available in case you forget to bring it. 

The Data Science Brown Bag Series is an informal and interactive gathering where participants bring their own brown bag lunch and engage in discussions on research and insights the field of data and computational social science (light pastries and drinks will be available if you forget your lunch bag!). 

The series provides a platform for data enthusiasts, researchers, and practitioners to share their experiences, best practices, and emerging methodologies and research in using data science to analyze and understand social and political phenomena. The brown bag talk series is for anyone interested in data science and social science to network, learn, and share ideas in a casual and friendly setting.

Contact person

  • William Lowe, Senior Research Scientist
  • Huy Ngoc Dang, Manager of Data Science Lab & Programme Coordinator of Master of Data Science for Public Policy