In this paper, we ask whether it is possible to forecast gross value-added (GVA) and its sectoral subcomponents at the … regional level. With an autoregressive distributed lag model we forecast total and sectoral GVA for one German state (Saxony … usage of different forecast pooling strategies and factor models. Our results show that we are able to increase forecast …

desired policy goals. This paper develops a group of models to forecast inflation for Argentina, which includes autoregressive … can improve the forecast ability of the univariate autoregressive benchmark’s model of inflation. The Giacomini-White test … indicates that a BVAR performs better than the benchmark in all forecast horizons. Statistical differences between the two BVAR …

-markup theory can help to forecast inflation. We first review the relative performance of different predictors in forecasting h …

This paper evaluates the real-time forecast performance of alternative Bayesian Vector Autoregressive (VAR) models for … models with more flexible error covariance structures forecast GDP growth and inflation better than the standard VAR, while …

exploit many predictors, and this chapter surveys these methods. The first group of methods considered is forecast combination … (forecast pooling), in which a single forecast is produced from a panel of many forecasts. The second group of methods is based … increasingly precise as the number of series increases) can be used to forecast individual economic variables. The third group of …

. Forecast errors for the period 2000-2008 show an excess of autocorrelation and a statistically significant bias at the end of … the sample. We take advantage of the bias and autocorrelation structure of the forecast errors to build new and more …