Nonlinear time series models have become fashionable tools to describe and forecast a variety of economic time series … reasons for this finding is that inappropriate model selection criteria and forecast evaluation criteria are used. In this … found to perform better in out-of-sample forecasting than a benchmark linear model. An empirical illustration for US GDP …

be used as actuals in current forecast evaluation. We allow for structural changes in the regression parameters to …

we analyse some recent developments from that perspective. The literature on forecast evaluation predominantly assumes … two forecasts in which: (i) the two forecasts are generated from two distinct econometric models; (ii) one forecast is … generated from an econometric model and the other is obtained as a combination of a model, the other forecast, and intuition …

Macroeconomic forecasting is not an easy task, in particular if future growth rates are forecasted in real time. This … reported by the Conference Board. Not surprisingly, all forecast methods improve considerably if `ex post' data are used, after …

(p) model for all forecast horizons and different AR models for different horizons. Representation, estimation and forecasting …

This article proposes a modified method for the construction of diffusion indexes in macroeconomic forecasting using … models with smaller forecast errors than previously used methods. …

forecasting study. We include both single equation and multiple equation methods. A VAR model in first differences with and … considered. For longer forecast horizons, however, the periodic and seasonal cointegration models are better. When comparing …

most beneficial to forecast quality for immediate horizons (as very recent events are not in the model) and for further … other conjectures. We also document that the forecast horizon that is the most important for supply chain management here … entails the heaviest adjustment by the experts. Unfortunately, that additional adjustment harms forecast accuracy. …