Regional unemployment forecasts with spatial interdependencies
We forecast unemployment levels for the 176 German labour-market districts on a monthly basis. Because of their small sizes, strong spatial interdependencies exist between these regional units. To account for these, as well as for the heterogeneity in the regional development over time, we apply dif...
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Veröffentlicht in: | International journal of forecasting 2010-10, Vol.26 (4), p.908-926 |
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creator | Schanne, N. Wapler, R. Weyh, A. |
description | We forecast unemployment levels for the 176 German labour-market districts on a monthly basis. Because of their small sizes, strong spatial interdependencies exist between these regional units. To account for these, as well as for the heterogeneity in the regional development over time, we apply different versions of a univariate spatial GVAR model. When comparing the forecast precision with that of univariate time series methods, we find that the spatial model does indeed perform better, or at least as well. Hence, the spatial GVAR model provides an alternative or complementary approach to commonly used methods in regional forecasting which do not consider regional interdependencies. |
doi_str_mv | 10.1016/j.ijforecast.2009.07.002 |
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subjects | Economic forecasting Economic models Forecasting practice Forecasting practice Labour-market forecasting Macroeconomic forecasting Regional forecasting Time series Interdependence Labor market Labour-market forecasting Macroeconomic forecasting Regional forecasting Studies Time series Unemployment |
title | Regional unemployment forecasts with spatial interdependencies |
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