In this paper, we compare two different variable selection approaches for linear regression models: Autometrics (automatic general-to-specific selection) and LASSO (?1-norm regularization). In a simulation study, we show the performance of the methods considering the predictive power (forecast...

The use of large datasets for macroeconomic forecasting has received a great deal of interest recently. Boosting is one possible method of using high-dimensional data for this purpose. It is a stage-wise additive modelling procedure, which, in a linear specification, becomes a variable selection...

We compare the forecasting performances of the classical and the Minnesota-type Bayesian vector autoregressive (VAR) models with those of linear (fixed-parameter) and nonlinear (time-varying parameter) VARs involving a stochastic search algorithm for variable selection, estimated using Markov...

This paper develops methods for automatic selection of variables in Bayesian vector autoregressions (VARs) using the Gibbs sampler. In particular, I provide computationally efficient algorithms for stochastic variable selection in generic linear and nonlinear models, as well as models of large...

This paper develops methods for automatic selection of variables in forecasting Bayesian vector autoregressions (VARs) using the Gibbs sampler. In particular, I provide computationally efficient algorithms for stochastic variable selection in generic (linear and nonlinear) VARs. The performance...

This paper develops methods for automatic selection of variables in Bayesian vector autoregressions (VARs) using the Gibbs sampler. In particular, I provide computationally efficient algorithms for stochastic variable selection in generic linear and nonlinear models, as well as models of large...

The use of large datasets for macroeconomic forecasting has received a great deal of interest recently. Boosting is one possible method of using high-dimensional data for this purpose. It is a stage-wise additive modelling procedure, which, in a linear specification, becomes a variable selection...

This paper is concerned with the problem of variable selection when the marginal effects of signals on the target variable as well as the correlation of the covariates in the active set are allowed to vary over time, without committing to any particular model of parameter instabilities. It poses...

The Mzansi intervention is a major initiative designed to provide banking services to the unbanked South African population. This study investigates the underlying variables that define the choice of a Mzansi account from a consumer perspective. Unlike previous studies, we do not assume that...