This paper considers the problem of prediction in a panel data regression model with spatial auto-correlation in the … context of a simple demand equation for liquor. This is based on a panel of 43 states over the period 1965-1994. The spatial …

. 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 …

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 …

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 …

-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 …

(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. …

relative to industrial production and orders in Germany. Although we find evidence that forecast characteristics based on real …-time and final data releases differ, we also observe minimal impacts on the relative forecasting performance of indicator …