Add to ORKGThis paper builds on a simple unified representation of shrinkage Bayes estimators based on hierarchical Normal-Gamma priors. Various popular penalized least squares estimators for shrinkage and selection in regression models can be recovered using this single hierarchical Bayes formulation. Using 129 U.S. macroeconomic quarterly variables for the period 1959 -- 2010 I exhaustively evaluate the forecasting properties of Bayesian shrinkage in regressions with many predictors. Results show that for particular data series hierarchical shrinkage dominates factor model forecasts, and hence it becomes a valuable addition to existing methods for handling large dimensional data
The paper addresses the issue of forecasting a large set of variables using multi-variate models. In...
In linear regression problems with many predictors, penalized regression techniques are often used t...
In the last years a growing °ow of information in the ¯eld of macroeconomy has been collected in ve...
This paper builds on a simple unified representation of shrinkage Bayes estimators based on hierarch...
This paper builds on a simple unified representation of shrinkage Bayes estimators based on hierarch...
This paper considers Bayesian regression with normal and double-exponential priors as forecasting me...
Vector autoregressive (VAR) models are frequently used for forecasting and impulse response analysis...
Sparsity is a standard structural assumption that is made while modeling high-dimensional statistica...
Large Bayesian VARs with stochastic volatility are increasingly used in empirical macroeconomics. Th...
The paper provides a proof of consistency of the ridge estimator for regressions where the number of...
In this paper, we forecast EU-area inflation with many predictors using time-varying parameter model...
In this paper, we forecast EU-area inflation with many predictors using time-varying parameter model...
In macroeconomics, predicting future realisations of economic variables is the central issue for pol...
We propose a novel Bayesian method for dynamic regression models where both the values of the regres...
The paper addresses the issue of forecasting a large set of variables using multivariate models. In ...
The paper addresses the issue of forecasting a large set of variables using multi-variate models. In...
In linear regression problems with many predictors, penalized regression techniques are often used t...
In the last years a growing °ow of information in the ¯eld of macroeconomy has been collected in ve...
This paper builds on a simple unified representation of shrinkage Bayes estimators based on hierarch...
This paper builds on a simple unified representation of shrinkage Bayes estimators based on hierarch...
This paper considers Bayesian regression with normal and double-exponential priors as forecasting me...
Vector autoregressive (VAR) models are frequently used for forecasting and impulse response analysis...
Sparsity is a standard structural assumption that is made while modeling high-dimensional statistica...
Large Bayesian VARs with stochastic volatility are increasingly used in empirical macroeconomics. Th...
The paper provides a proof of consistency of the ridge estimator for regressions where the number of...
In this paper, we forecast EU-area inflation with many predictors using time-varying parameter model...
In this paper, we forecast EU-area inflation with many predictors using time-varying parameter model...
In macroeconomics, predicting future realisations of economic variables is the central issue for pol...
We propose a novel Bayesian method for dynamic regression models where both the values of the regres...
The paper addresses the issue of forecasting a large set of variables using multivariate models. In ...
The paper addresses the issue of forecasting a large set of variables using multi-variate models. In...
In linear regression problems with many predictors, penalized regression techniques are often used t...
In the last years a growing °ow of information in the ¯eld of macroeconomy has been collected in ve...