Forecasting with many predictors is of interest, for instance, in macroeconomics and finance. This paper compares two methods for dealing with many predictors, that is, principal component regression (PCR) and principal covariate regression (PCovR). The forecast performance of these methods is...

This paper is concerned with time series forecasting in the presence of a large number of predictors. The results are of interest, for instance, in macroeconomic and financial forecasting where often many potential predictor variables are available. Most of the current forecast methods with many...

This paper is concerned with time series forecasting in the presence of a large number of predictors. The results are of interest, for instance, in macroeconomic and financial forecasting where often many potential predictor variables are available. Most of the current forecast methods with many...

We start from the assertion that a useful monetary policy design should be founded on more realistic assumptions about what policymakers can know at the time when policy decisions have to be made. Since the Taylor rule - if used as an operational device - implies a forward looking behaviour, we...

In this paper, we document the forecasting performance of estimated basic dynamic stochastic general equilibrium (DSGE) models and compare this to extended versions which consider alternative expectation formation assumptions and financial frictions. We also show how standard model features,...

A structural break is viewed as a permanent change in the parameter vector of a model. Using taxonomies of all sources of forecast errors for both conditional mean and conditional variance processes, we consider the impacts of breaks and their relevance in forecasting models: (a) where the...

This study attempts to determine the degree to which the state of the macroeconomy can be used to create a mutual fund investment strategy that consistently outperforms the S&P 500. By quantifying how systematic economic factors affect the relative performance of different fund strategies...

This paper evaluates the influence of central bank's projections and narrative signals provided in the summaries of its Inflation Report on the expectations of professional forecasters for inflation and GDP growth in the case of Mexico. We use the Latent Dirichlet Allocation model, a textmining...

The modelling of stock market volatility is considered to be important for practitioners and academics in finance due to its use in forecasting aspects of future returns. The GARCH class models have now firmly established themselves as one of the foremost techniques for modelling volatility in...

Wirtschaftsprognosen sollen die Unsicherheit bezüglich der zukünftigen wirtschaftlichen Entwicklung mindern und Planungsprozesse von Regierungen und Unternehmen unterstützen. Empirische Studien bescheinigen ihnen jedoch in aller Regel ein unbefriedigendes Qualitätsniveau. Auf der Suche nach...