Template-Type: ReDIF-Paper 1.0
Author-Name: Gary Koop
Author-Name-First: Gary
Author-Name-Last: Koop
Author-Email: gary.koop@strath.ac.uk
Author-Workplace-Name: Department of Economics, University of Strathclyde
Author-Name: Roberto  Leon-Gonzalez
Author-Name-First: Roberto 
Author-Name-Last: Leon-Gonzalez
Author-Email: rlg@grips.ac.jp.
Author-Workplace-Name: National Graduate Institute for Policy Studies
Author-Name: Rodney Strachan
Author-Name-First: Rodney
Author-Name-Last: Strachan
Author-Email: rodney.strachan@anu.edu.au
Author-Workplace-Name: The Australian National University
Title: Bayesian Model Averaging in the Instrumental Variable Regression Model*
Abstract: This paper considers the instrumental variable regression model when there is uncertainty about the set of instruments, exogeneity restrictions, the validity of identifying restrictions and the set of exogenous regressors. This uncertainty can result in a huge number of models. To avoid statistical problems associated with standard model selection procedures, we develop a reversible jump Markov chain Monte Carlo algorithm that allows us to do Bayesian model averaging. The algorithm is very ?exible and can be easily adapted to analyze any of the di¤erent priors that have been proposed in the Bayesian instrumental variables literature. We show how to calculate
the probability of any relevant restriction (e.g. the posterior probability that over-identifying restrictions hold) and discuss diagnostic checking using the posterior distribution of discrepancy vectors. We illustrate our methods in a returns-to-schooling application.
Length: 49 pages
Creation-Date: 2011-04
Revision-Date: 
Publication-Status: 
File-URL: http://www.strath.ac.uk/media/1newwebsite/departmentsubject/economics/research/researchdiscussionpapers/2011/11-12_Final.pdf
File-Format: Application/pdf
Number: 1112
Classification-JEL: FC11, C30
Keywords: Bayesian, endogeneity, simultaneous equations, reversible jump Markov chain Monte Carlo.
Handle: RePEc:str:wpaper:1112