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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

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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 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.

Item type: Article
ID code: 39966
Keywords: Bayesian , endogeneity, simultaneous equations, reversible jump , Markov chain, Economic Theory, History and Philosophy of Science, Economics and Econometrics, Applied Mathematics
Subjects: Social Sciences > Economic Theory
Department: Strathclyde Business School > Economics
Depositing user: Pure Administrator
Date Deposited: 08 Jun 2012 13:15
Last modified: 18 Jun 2015 02:47
Related URLs:
URI: http://strathprints.strath.ac.uk/id/eprint/39966

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