Course Description

This course focuses on regression methods for cross-section and panel data.  In the first half of the course, we will focus on widely used econometric methods appropriate for linear and nonlinear models, with an emphasis on nonlinear models.  Topics include generalized least squares, weighted least square, instrumental variable, maximum likelihood, and discrete dependent variable models.

In the second half of the course, we will study estimation methods for limited dependent variables as well as commonly applied econometric methods for panel data. These models are nonlinear in nature. Topics include censored and truncated models, Tobit, two-part model, sample-selection model, fixed effects and random effects models, and other relevant advanced topics. We focus on empirical applications in general, but the course will involve theories and derivations necessary to understand issues surrounding the methodology.

Course Objectives: (1) be able to choose appropriate estimation method and perform estimation and testing in nonlinear model settings; (2) basic understanding of asymptotic theories and assumptions; (3) familiar with panel data, discrete dependent variable, and limit dependent variable estimation methods; (4) achieve proficiency in statistical software to carry out empirical investigation.