Some convenient limit properties of usual information criteria are given for cointegrating rank selection. Allowing for a nonparametric short memory component and using a reduced rank regression with only a single lag, standard information criteria are shown to be weakly consistent in the choice...

Reduced rank regression (RRR) models with time varying heterogeneity are considered. Standard information criteria for selecting cointegrating rank are shown to be weakly consistent in semiparametric RRR models in which the errors have general nonparametric short memory components and shifting...

A number of recently published papers have focused on the problem of testing for a unit root in the case where the driving shocks may be unconditionally heteroskedastic. These papers have, however, assumed that the lag length in the unit root test regression is a deterministic function of the...

We use data generated by a macroeconomic DSGE model to study the relative benefits of forecast combinations based on forecast-encompassing tests relative to simple uniformly weighted forecast averages across rival models. Assumed rival models are four linear autoregressive specifications, one of...

This paper uses the adaptive LASSO estimator to determine the variables important for economic growth. The adaptive LASSO estimator is a computationally very simple procedure that performs at the same time both consistent parameter estimation and model selection. The methodology is applied to...

We investigate whether and to what extent multiple encompassing tests may help determine weights for forecast averaging in a standard vector autoregressive setting. To this end we consider a new test-based procedure, which assigns non-zero weights to candidate models that add information not...

This paper reports quarterly ex ante forecasts of macroeconomic activity for the U.S.A., Japan and Australia for the period 1995-1997. The forecasts are based on automated time series models of vector autoregressions (VAR's), reduced rank regressions (RRR's), error correction models (ECM's) and...