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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
    Related URLs:
    Depositing user: Pure Administrator
    Date Deposited: 08 Jun 2012 14:15
    Last modified: 27 Mar 2014 21:43
    URI: http://strathprints.strath.ac.uk/id/eprint/39966

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