Forecasting Euro Area Macroeconomic Variables with Bayesian Adaptive Elastic Net
نویسنده
چکیده
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.
منابع مشابه
Bayesian Quantile Regression with Adaptive Elastic Net Penalty for Longitudinal Data
Longitudinal studies include the important parts of epidemiological surveys, clinical trials and social studies. In longitudinal studies, measurement of the responses is conducted repeatedly through time. Often, the main goal is to characterize the change in responses over time and the factors that influence the change. Recently, to analyze this kind of data, quantile regression has been taken ...
متن کاملForecasting Euro-Area Macroeconomic Variables Using a Factor Model Approach for Backdating
We suggest to use a factor model based backdating procedure to construct historical Euro-area macroeconomic time series data for the pre-Euro period. We argue that this is a useful alternative to standard contemporaneous aggregation methods. The paper investigates for a number of Euro-area variables whether forecasts based on the factorbackdated data are more precise than those obtained with st...
متن کاملAdaptive Learning and Macroeconomic Inertia in the Euro Area*
This article aims to study the determinants of macroeconomic inertia in the euro area. To this end, it estimates a simple monetary DSGE model with private-sector learning, but which also includes more structural sources of inertia, such as habit formation in consumption and inflation indexation. Economic agents are assumed to form nearrational expectations and to learn the model parameters over...
متن کاملCombining Country-Specific Forecasts when Forecasting Euro Area Macroeconomic Aggregates
European Monetary Union (EMU) member countries’ forecasts are often combined to obtain the forecasts of the Euro area macroeconomic aggregate variables. The aggregation weights which are used to produce the aggregates are often considered as combination weights. This paper investigates whether using different combination weights instead of the usual aggregation weights can help to provide more ...
متن کاملForecasting with DSGE Models
In this paper we review the methodology of forecasting with log-linearised DSGE models using Bayesian methods. We focus on the estimation of their predictive distributions, with special attention being paid to the mean and the covariance matrix of h-steps ahead forecasts. In the empirical analysis, we examine the forecasting performance of the New Area-Wide Model (NAWM) that has been designed f...
متن کامل