The class is about estimating microeconometric models. The class has an applied emphasis: how econometrics can help us understand the incentives of agents in markets for technology, health, insurance and others. The class covers a variety of econometric methods, from veteran parametric methods to frontier methods (nonparametrics, partial identification). We analyze models that address issues that arise frequently in empirical work. The class begins with models that have Limited Dependent Variables (i.e., certain limitations are imposed on the dependent variable) such as Probit, Logit, Ordered Probit, and Censored Regression models. We then discuss the important problem of sample selection and study practical methods for solving it. The class then turns to discuss Discrete Choice Models and, if time permits, structural modeling techniques.
Spring
2016