We compare the predictive ability of Bayesian methods which deal simultaneously with model uncertainty and correlated regressors in the framework of cross-country growth regressions. In particular, we assess methods with 'spike and slab' priors combined with different prior specifications for the slope parameters in the slab. Our results indicate that moving away from Gaussan g-priors towards Bayesian ridge, LASSO or elastic net specifications has clear advantages for prediction when dealing with datasets of (potentially highly) correlated regressors, a pervasive characteristic of the data used hitherto in the econometric literature
This paper examines the robustness of explanatory variables in cross-country economic growth regress...
The paper provides a proof of consistency of the ridge estimator for regressions where the number of...
markdownabstract__Abstract__ Time varying patterns in US growth are analyzed using various univar...
We compare the predictive ability of Bayesian methods which deal simultaneously with model uncertain...
We propose a method to deal simultaneously with model uncertainty and cor-related regressors in line...
We investigate the issue of model uncertainty in cross-country growth regressions using Bayesian Mod...
CHAPTER 1:The default g-priors predominant in Bayesian Model Averaging tend to over-concentrate post...
textabstractRegression analyses of cross-country economic growth data are complicated by two main fo...
Ciccone and Jarociński (American Economic Journal: Macroeconomics 2010; 2: 222-246) show that infere...
This paper discusses likelihood-based estimation of linear panel data models with general predetermi...
Recent research on macroeconomic growth has been focused on resolving several key issues, two of whi...
We consider the problem of variable selection in linear regression models. Bayesian model averaging ...
I use the adaptive elastic net in a Bayesian framework and test its forecasting performance against ...
In macroeconomics, predicting future realisations of economic variables is the central issue for pol...
France, for hospitality during the preparation of this paper. The views expressed in this study are ...
This paper examines the robustness of explanatory variables in cross-country economic growth regress...
The paper provides a proof of consistency of the ridge estimator for regressions where the number of...
markdownabstract__Abstract__ Time varying patterns in US growth are analyzed using various univar...
We compare the predictive ability of Bayesian methods which deal simultaneously with model uncertain...
We propose a method to deal simultaneously with model uncertainty and cor-related regressors in line...
We investigate the issue of model uncertainty in cross-country growth regressions using Bayesian Mod...
CHAPTER 1:The default g-priors predominant in Bayesian Model Averaging tend to over-concentrate post...
textabstractRegression analyses of cross-country economic growth data are complicated by two main fo...
Ciccone and Jarociński (American Economic Journal: Macroeconomics 2010; 2: 222-246) show that infere...
This paper discusses likelihood-based estimation of linear panel data models with general predetermi...
Recent research on macroeconomic growth has been focused on resolving several key issues, two of whi...
We consider the problem of variable selection in linear regression models. Bayesian model averaging ...
I use the adaptive elastic net in a Bayesian framework and test its forecasting performance against ...
In macroeconomics, predicting future realisations of economic variables is the central issue for pol...
France, for hospitality during the preparation of this paper. The views expressed in this study are ...
This paper examines the robustness of explanatory variables in cross-country economic growth regress...
The paper provides a proof of consistency of the ridge estimator for regressions where the number of...
markdownabstract__Abstract__ Time varying patterns in US growth are analyzed using various univar...