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
Hauptverfasser: Schanne, N., Wapler, R., Weyh, A.
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container_title International journal of forecasting
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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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