Random subspace methods are a novel approach to obtain accurate forecasts in high-dimensional regression settings. We provide a theoretical justification of the use of random subspace methods and show their usefulness when forecasting monthly macroeconomic variables. We focus on two approaches....

The first three factors resulting from a principal components analysis of term structure data are in the literature typically interpreted as driving the level, slope and curvature of the term structure. Using slight generalisations of theorems from total positivity, we present sufficient...

This paper puts forward a method to estimate average economic growth, andits associated confidence bounds, which does not require a formal decision onpotential unit root properties. The method is based on the analysis of eitherdifference-stationary or trend-stationary time series models,...

This paper analyses the relationship between organizational complexity ( the degree of detail of information necessary to correctly assign agents to positions), robustness (the relative loss of performance due to mis-allocated agents), and performance. More complex structures are not necessarily...

The empirical economic growth literature is criticized for its lack ofrobustness. For different definitions of robustness, conclusions vary from 'almost everycorrelation is fragile' to 'a substantial number of explanatory variables are robust.' Were-analyze the empirical results of the economic...