Hofmarcher, Paul, Crespo Cuaresma, Jesus, Grün, Bettina, Hornik, Kurt. 2011. Fishing Economic Growth Determinants Using Bayesian Elastic Nets. Research Report Series, Institute for Statistics and Mathematics, Report 113.
BibTeX
Abstract
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.
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Status of publication | Published |
---|---|
Affiliation | WU |
Type of publication | Working/discussion paper, preprint |
Language | English |
Title | Fishing Economic Growth Determinants Using Bayesian Elastic Nets |
Title of whole publication | Research Report Series, Institute for Statistics and Mathematics, Report 113 |
Year | 2011 |
URL | http://epub.wu.ac.at/3213/ |
Associations
- People
- Hofmarcher, Paul (Former researcher)
- Crespo Cuaresma, Jesus (Details)
- Grün, Bettina (Details)
- Hornik, Kurt (Details)
- Organization
- Institute for Statistics and Mathematics IN (Details)
- Department of Economics (Crespo Cuaresma) (Details)
- Research Institute for Computational Methods FI (Details)