Bayesian model averaging in the instrumental variable regression model

Gary Koop, Roberto Leon-Gonzalez and Rodney Strachan

Journal of Econometrics, 2012, vol. 171, issue 2, 237-250

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 such as exogeneity or over-identification. We illustrate our methods in a returns-to-schooling application.

Keywords: Bayesian; Endogeneity; Simultaneous equations; Reversible jump Markov chain Monte Carlo (search for similar items in EconPapers)
JEL-codes: C11 C30 (search for similar items in EconPapers)
Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (39)

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Related works:
Working Paper: Bayesian Model Averaging in the Instrumental Variable Regression Model (2012)
Working Paper: Bayesian Model Averaging in the Instrumental Variable Regression Model (2011)
Working Paper: Bayesian Model Averaging in the Instrumental Variable Regression Model (2011)
Working Paper: Bayesian Model Averaging in the Instrumental Variable Regression Model* (2011)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:171:y:2012:i:2:p:237-250

DOI: 10.1016/j.jeconom.2012.06.005

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