Department of Economics Seminar Series 



"Causal vs. Predictive Models, and Where Can We Use Machine Learning in Economics, Social and Health Sciences?"




Mutlu Yüksel

(Dalhousie University)



Date: April 29, 2024 (Monday)

Time: 16:30


Synchronous Online Seminar

MS Teams Platform


MS Teams Link

Meeting ID: 246 506 859 070

Passcode: ZyU89E


This presentation explores the integration of machine learning(ML) techniques into social sciences, with a specific focus on econometrics. It outlines core areas of econometrics, distinguishing between macro and micro-econometrics, and contrasting Frequentist and Bayesian approaches, while also introducing Rubin's causal model and other causal econometrics and ML methods. Machine learning's potential applications in social science research are highlighted, along with the methodological approaches involved. The discussion addresses critical concepts such as extrapolation versus prediction, emphasizing their relevance in economic and social research. The presentation explores into the differences between effect estimation and prediction. By incorporating examples and recommended resources, the presentation aims to equip social scientists with the knowledge to effectively leverage machine learning techniques in their research.

Last Updated:
25/04/2024 - 18:36