Bayesian model averaging in the instrumental variable regression model
Koop, Gary and Leon-Gonzalez, Roberto and Strachan, Rodney (2012) Bayesian model averaging in the instrumental variable regression model. Journal of Econometrics, 171 (2). 237–250. ISSN 0304-4076 (http://personal.strath.ac.uk/gary.koop/kls4.pdf)
Full text not available in this repository.Request a copyAbstract
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 flexible and can be easily adapted to analyze any of the different 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.
ORCID iDs
Koop, Gary ORCID: https://orcid.org/0000-0002-6091-378X, Leon-Gonzalez, Roberto and Strachan, Rodney;-
-
Item type: Article ID code: 39966 Dates: DateEventDecember 2012PublishedSubjects: Social Sciences > Economic Theory Department: Strathclyde Business School > Economics Depositing user: Pure Administrator Date deposited: 08 Jun 2012 13:15 Last modified: 17 Nov 2024 02:17 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/39966