Forecasting Euro Area Macroeconomic Variables with Bayesian Adaptive Elastic Net

Sandra Stankiewicz ()
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Sandra Stankiewicz: Department of Economics, University of Konstanz, Germany

No 2015-12, Working Paper Series of the Department of Economics, University of Konstanz from Department of Economics, University of Konstanz

Abstract: I use the adaptive elastic net in a Bayesian framework and test its forecasting performance against lasso, adaptive lasso and elastic net (all used in a Bayesian framework) in a series of simulations, as well as in an empirical exercise for macroeconomic Euro area data. The results suggest that elastic net is the best model among the four Bayesian methods considered. Adaptive lasso, on the other hand, shows the worst forecasting performance. Lasso is generally better then adaptive lasso, but worse than adaptive elastic net. The differences in the performance of these models become especially large when the number of regressors grows considerably relative to the number of available observations. The results point to the fact that the ridge regression component in the elastic net is responsible for its improvement in forecasting performance over lasso. The adaptive shrinkage in some of the models does not seem to play a major role, and may even lead to a deterioration of the performance.

Keywords: Elastic net; Lasso; Bayesian; Forecasting (search for similar items in EconPapers)
JEL-codes: C11 C22 C53 (search for similar items in EconPapers)
Pages: 32 pages
Date: 2015-05-13
New Economics Papers: this item is included in nep-eec, nep-ets, nep-for, nep-mac and nep-ore
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Citations: View citations in EconPapers (1)

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