Title of article :
Bayesian model averaging in the instrumental variable regression model
Author/Authors :
Koop، نويسنده , , Gary and Leon-Gonzalez، نويسنده , , Roberto and Strachan، نويسنده , , Rodney، نويسنده ,
Issue Information :
دوفصلنامه با شماره پیاپی سال 2012
Pages :
14
From page :
237
To page :
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 :
reversible jump Markov chain Monte Carlo , endogeneity , Simultaneous Equations , Bayesian
Journal title :
Journal of Econometrics
Serial Year :
2012
Journal title :
Journal of Econometrics
Record number :
2129184
Link To Document :
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