In the evolving landscape of statistical, econometric, and data science advancements, a significant number of innovative methodologies remain untapped by applied research. There is a disconnect between cutting-edge econometric tools and relevant economic questions addressing societies’ most pressing concerns. This in-person Workshop seeks to address this gap and establish research collaboration between data scientists, experts in the causal inference literature, and applied researchers who better understand the empirical contexts, objectives, and challenges faced by policymakers. In the spirit of working across multiple disciplines and employing a variety of methodologies, the DSI Causal Inference Emerging Data Science Program is in collaboration with the Forward Society (FOS) Lab. 

This Workshop is part of the Causal Inference Emerging Data Science Program that aims to facilitate cross-disciplinary exchange, where applied researchers from different disciplines can present their research questions and methodological issues. In turn, data science and causality researchers explore new and existing methods while promoting their research agendas.  

Join us in-person at the Workshop to foster collaborative exploration, amplifying the impact of causal inference and data science research on real-world policy challenges. 

Program