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Regional unemployment forecasts with spatial interdependencies

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  • Schanne, N.
  • Wapler, R.
  • Weyh, A.

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.

Suggested Citation

  • Schanne, N. & Wapler, R. & Weyh, A., 2010. "Regional unemployment forecasts with spatial interdependencies," International Journal of Forecasting, Elsevier, vol. 26(4), pages 908-926, October.
    • Handle: RePEc:eee:intfor:v:26:y::i:4:p:908-926
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    More about this item

    Keywords

    Forecasting practice Labour-market forecasting Macroeconomic forecasting Regional forecasting Time series;

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
    • O18 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Urban, Rural, Regional, and Transportation Analysis; Housing; Infrastructure

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