Indiana University Bloomington

Economics E724
Topic: Introduction To Modern Bayesian Methods

Algebra Required: Yes
Calculus Required: Yes
Instructor: Tchernis
Syllabus: No Syllabus Avaliable
Keywords: Bayesian Econometrics
Description: The goals of the course are as follows: 1) To provide the students with an introduction to Bayesian econometric modeling and estimation methods. 2) To give the students a set of tools that will allow them to tackle complex econometric models, the estimation of which might be infeasible using classical methods. 3) To give the students sufficient opportunity to program the estimation algorithms covered in class ? much of the class will be based on learning by doing. 4) To give the students an opportunity to present and discuss published articles and their own work: each student will make two presentations in class ? one to lead the discussion of an article and one to present the final project.
Books: Gary Koop, Dale J. Poirier, and Justin L. Tobias (2007) ?Bayesian Econometrics,? Volume 12 of Econometric Exercises Series, Cambridge University Press. Recommended: Lancaster, T., (2004), ?An Introduction to Modern Bayesian Econometrics,? Blackwell Publishing. Koop, G., (2004), ?Bayesian Econometrics,? Wiley. Gelman, A., Carlin, J.B., Stern, H.S., and D.B. Rubin, (2004), ?Bayesian Data Analysis,? Second Edition, Chapman & Hall.
Substantive Orientation: Economics
Statistical Orientation: Bayesian
Applied/Theoretical: Applied
Software: MatLab
How Software is Used: Programing
Problem Sets: 30%
Presentation: 20%
Comments: 1. Participation and homework assignments: 30%; 2. Article presentation: 20%; 3. Project presentation: 20%; 4. Final paper: 30%