Resource title

Fishing Economic Growth Determinants Using Bayesian Elastic Nets

Resource image

image for OpenScout resource :: Fishing Economic Growth Determinants Using Bayesian Elastic Nets

Resource description

We propose a method to deal simultaneously with model uncertainty and correlated regressors in linear regression models by combining elastic net specifications with a spike and slab prior. The estimation method nests ridge regression and the LASSO estimator and thus allows for a more flexible modelling framework than existing model averaging procedures. In particular, the proposed technique has clear advantages when dealing with datasets of (potentially highly) correlated regressors, a pervasive characteristic of the model averaging datasets used hitherto in the econometric literature. We apply our method to the dataset of economic growth determinants by Sala-i-Martin et al. (Sala-i-Martin, X., Doppelhofer, G., and Miller, R. I. (2004). Determinants of Long-Term Growth: A Bayesian Averaging of Classical Estimates (BACE) Approach. American Economic Review, 94: 813-835) and show that our procedure has superior out-of-sample predictive abilities as compared to the standard Bayesian model averaging methods currently used in the literature. (author's abstract) ; Series: Research Report Series / Department of Statistics and Mathematics

Resource author

Paul Hofmarcher, Jesus Crespo Cuaresma, Bettina GrĂ¼n, Kurt Hornik

Resource publisher

Resource publish date

Resource language


Resource content type


Resource resource URL

Resource license

Adapt according to the license agreement. Always reference the original source and author.