Isenberg School of Management 890M - Economics Models in Marketing

This course aims to provide an overview of the methodological toolkit available to empirical researchers who are interested in making causal inference using quasi-experimental data. In marketing, randomized experimentation represents the gold standard for making causal inference using empirical data. In an ideal setting, we would randomly assign participants to different groups to receive varying types or levels of treatment. Nonetheless, there are many marketing-relevant settings where researchers do not have access to experimental data, or where running such experiments is too expensive or infeasible. Additionally, ethical considerations frequently preclude randomly assigning treatments, such as instances where it could lead to harm or deprive participants of necessary care, as in the case of life-saving treatments or medications. When randomization of treatment is not possible, one may have to rely on enhanced "statistical rigor" to compensate for the deficiencies in "design rigor."

Open to doctoral School of Management students only.