Bayesian model averaging in the instrumental variable regression model
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...[Show more]
|Collections||ANU Research Publications|
|Source:||Journal of Econometrics|
|01_Koop_Bayesian_model_averaging_in_2012.pdf||515.62 kB||Adobe PDF||Request a copy|
|02_Koop_Bayesian_model_averaging_in_2012.pdf||446.24 kB||Adobe PDF||Request a copy|
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