Causal Analysis for Policy and Business

Introduksjon

Please note that this is a preliminary course description. The final version will be published in June 2027.

As the volume of digital information grows exponentially, businesses and economists are increasingly turning to massive datasets for insights. Yet, more data does not guarantee better answers—especially when the goal is to understand cause and effect. This course offers a principled approach to empirical analysis, grounded in the potential outcomes framework. Focusing on applied microeconometrics, we examine how to draw credible conclusions from large-scale randomized trials and quasi-experiments, with real-world examples drawn from public policy, labor economics, finance, and marketing.

Kursets innhold

The course covers the following topics:

• Large-scale experimentation
• Local average treatment effects
• Treatment effect heterogeneity
• Regression discontinuity designs
• Supplementary analyses and replication
• High-dimensional data