Regional unemployment forecasts with spatial interdependencies

Norbert Schanne (), R. Wapler and A. Weyh

International Journal of Forecasting, 2010, vol. 26, issue 4, 908-926

Abstract: 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.

Keywords: Forecasting; practice; Labour-market; forecasting; Macroeconomic; forecasting; Regional; forecasting; Time; series (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (34)

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Related works:
Working Paper: Regional unemployment forecasts with spatial interdependencies (2008)
Working Paper: Regional employment forecasts with spatial interdependencies (2007)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:26:y::i:4:p:908-926

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