This paper provides an empirical comparison of various selection and penalized regression approaches for forecasting with vector autoregressive systems. In particular, we investigate the effect of the system size as well as the effect of various prior specification choices on the relative and...

This paper proposes a new method for forecast selection from a pool of many forecasts. The method uses conditional information as proposed by Giacomini and White (2006). It also extends their pairwise switching method to a situation with many forecasts. I apply the method to the monthly...

Global vector autoregressions (GVARs) have several attractive features: multiple potential channels for the international transmission of macroeconomic and financial shocks, a standardized economically appealing choice of variables for each country or region examined, systematic treatment of...

Intermittent demand time series involve items that are requested infrequently, resulting in sporadic demand. Croston׳s method and its variants have been proposed in the literature to address this forecasting problem. Recently other novel methods have appeared. Although the literature provides...

We consider forecasting with factors, variables and both, modeling in-sample using Autometrics so all principal components and variables can be included jointly, while tackling multiple breaks by impulse-indicator saturation.  A forecast-error taxonomy for factor models highlights the impacts...

Several approaches for subset recovery and improved forecasting accuracy have been proposed and studied. One way is to apply a regularization strategy and solve the model selection task as a continuous optimization problem. One of the most popular approaches in this research field is given by...

The question of variable selection in a regression model is a major open research topic in econometrics. Traditionally two broad classes of methods have been used. One is sequential testing and the other is information criteria. The advent of large datasets used by institutions such as central...

In this paper we investigate the impact of data revisions on forecasting and model selection procedures. A linear ARMA model and nonlinear SETAR model are considered in this study. Two Canadian macroeconomic time series have been analyzed: the real-time monetary aggregate M3 (1977-2000), and...

Finding a good forecasting model in a data-rich environment is a complex problem which challenges forecasters and statistical methods. In such an environment, automated modelling strategies are necessary for an efficient use of the information in the data. In contrast to frequently applied...

Our results suggest that the anticipated path of China's Carbon Dioxide (CO2) emissions has dramatically increased over the last five years. The magnitude of the projected increase in Chinese emissions out to 2015 is several times larger than reductions embodied in the Kyoto Protocol. Our...