Description

This course examines econometrics from a Bayesian perspective including linear and nonlinear regression, covariance structures, panel data, qualitative variable models, nonparametric and semiparametric methods, time series, Bayesian model averaging and variable selection. Bayesian methodology including Markov Chain Monte Carlo methods, hierarchical models, model checking, mixture models, empirical Bayes approaches, approximations, and computational issues and some attention to foundations.

Special Instructions: There will be different options in the course mixing theory and empirical work in different measures. Each student must choose one of these options by the fifth class meeting. Grading, assignments, units of credit, and the content of the final exam may vary among the options.

Prerequisites: Graduate level econometrics or equivalent.

This course is cross listed with the Public Policy Department (Same as PUBLPOL 303C).

• Number of Units: 1-6
• Course Number: 243

Recently Taught By:

• Jeff Strnad

All Public Policy courses:

• Advanced Legal Writing: Legislative Drafting and Analysis
• Bayesian Statistics and Econometrics
• Econometrics: Mathematical Methods
• Economic Analysis of Law
• Land Use
• Law and Public Policy Colloquium
• Legal Profession: Economics and Management of Pro Bono Practice
• Legislation
• Statistical Inference in Law