This paper puts forward kernel ridge regression as an approach for forecasting with many predictors that are related … overfitting. We extend the kernel ridge regression methodology to enable its use for economic time-series forecasting, by …

-series techniques to distinct time series of regional data may then become a sub-optimal forecasting strategy. In the field of regional … forecasting of socio-economic variables, both linear and non-linear models have recently been applied and evaluated. However … spatial structure that is required for the estimation of spatial models improves the forecasting performance of non …

forecasting range. Next, additional forecasts are computed, by combining the NN methodology with Shift-Share Analysis (SSA). Since …-of-sample forecasting ability of the models is evaluated by means of several appropriate statistical indicators. …

five major OECD countries, namely United States, Germany, United Kingdom, The Netherlands and Japan, the other forecasting … relevant for forecasting 12 months ahead. …