-year horizon). -- Chinese provinces ; forecasting ; dynamic panel model ; spatial autocorrelation ; group-specific spatial … provinces simultaneously. Beside the usual panel data models, we use panel models that explicitly account for spatial dependence … shown that effect of accounting for spatial dependence is even more pronounced at longer forecasting horizons (the forecast …

each of the 31 Chinese provinces simultaneously. Beside the usual panel data models, we use panel models that explicitly … longer forecasting horizons (the forecast accuracy gain as measured by the root mean squared forecast error is about 8% at …

provinces simultaneously. Beside the usual panel data models, we use panel models that explicitly account for spatial dependence … shown that effect of accounting for spatial dependence is even more pronounced at longer forecasting horizons (the forecast …

works in the field are based on either cross-sectional or fixed-effects estimates. We propose the estimation of convergence … in per-capita GDP across European regions by making use of panel-data models extended to include spatial error … autocorrelation (Anselin, 1988; Elhorst, 2003). This will allow us to extend the traditional beta-convergence model to include a …

. Our further contribution to the literature is that next to the usual panel data models such as pooled and within models we … advantage of the panel dimension, given the short sample for which the data are available, and hence gain efficiency and … differences existing between the German regions, in particular between East and West Germany. Our main finding is that pooling …

favour a similar economic performance among adjacent regions. Therefore, proper forecasting of socio-economic variables, such … as employment, requires an understanding of spatial (or spatio-temporal) autocorrelation effects associated with a … deal with the analysis of and accounting for spatial autocorrelation by means of spatial filtering t! echniques for data …

provinces simultaneously. Beside the usual panel data models, we use panel models that explicitly account for spatial dependence … shown that effect of accounting for spatial dependence is even more pronounced at longer forecasting horizons (the forecast …

(states) simultaneously. Beside the usual panel data models, such as pooled and fixed-effects models, we apply panel models … even more pronounced at longer forecasting horizons (the forecast accuracy gain as measured by the root mean squared … spatial dependence structure into regional forecasting models, especially, when long-term forecasts are made. …

(states) simultaneously. Beside the usual panel data models, such as pooled and fixed-effects models, we apply panel models … even more pronounced at longer forecasting horizons (the forecast accuracy gain as measured by the root mean squared … spatial dependence structure into regional forecasting models, especially, when long-term forecasts are made. …