Instructor: William Greene, New York University
DATES: MAY 29 - JUNE 2, 2007
LOCATION: AMERICAN UNIVERSITY
This class will deal with the analysis of static and dynamic panel and longitudinal data sets. Topics will include ‘fixed’ and ‘random’ effects. Both linear and nonlinear models will be reviewed and developed. Instrumental variables, maximum likelihood, generalized method of moments (GMM), two step estimation methods as well as MCMC will be studied and developed. Theoretical developments will focus on heterogeneity in models such as random parameter variation, and on techniques for optimization in the setting of nonlinear models. We will also consider numerous applications from the literature, including static and dynamic regression models, heterogeneous parameters models (e.g., Fama-Macbeth), random parameter variation, and specific nonlinear models such as binary and multinomial choice and models for count data.