Data analysis is the basis of any evidence-based managerial decision-making. Data analysis is about recognizing patterns in data so that inferences about the real world can be made. The course teaches students about causal inference using selected methods of data creation, collection, and analysis. It draws on econometrics and statistical methods developed to estimate economic relationships, testing theoretical hypotheses and evaluating policies.
In particular, this course will provide a review of regression analysis including linear regression with multiple regressors, non-linear regression models and dummy variables. In addition the course will cover the methods of laboratory and field experiments, specific approaches to establish causal relations with observational data, such as Differences-in-Differences Regression and Regression Discontinuities. (We may also cover Instrumental Variables if there is time.)