to forecasting area-wide industrial production. To this end, we use various tests that are designed to compare competing …

In this paper we review the methodology of forecasting with log-linearised DSGE models using Bayesian methods. We focus … matrix of h-steps ahead forecasts. In the empirical analysis, we examine the forecasting performance of the New Area … scope for improving the NAWM's forecasting performance. For example, the model is not able to explain the moderation in wage …

indicators play a crucial role for forecasting regional GDP. Keywords: regional forecasting, forecast combination, factor models …

small set of macroeconomic fundamentals being relevant for forecasting. …

model used for the measurement of current and forecasting of the future customer profitability. Modern customer … research model uses RFM model to define forecasting variables and neural network, multivariate regression analysis and binary … logistic regression as forecasting methods. This paper shows the ways how proposed methods can be used in process of …

and forecasting as well as for "what-if" inferring suitable for entities of all sizes. In particular, it allows for …

priors entertained for all variables at all forecasting horizons. …

need to be included in a VAR if interest is in forecasting or impulse response analysis of a given set of variables. We … including the selected variables into VARs typically improves forecasting accuracy at short horizons. …