English, Article, Journal or magazine article edition: Long term regional forecasting with spatial equation systems Wolfgang Polasek; Richard Sellner; Wolfgang Schwarzbauer

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Bookmark: http://trove.nla.gov.au/version/145136
Physical Description
  • preprint
Language
  • English

Edition details

Title
  • Long term regional forecasting with spatial equation systems
Author
  • Wolfgang Polasek
  • Richard Sellner
  • Wolfgang Schwarzbauer
Physical Description
  • preprint
Notes
  • Long-term predictions with a system of dynamic panel models can have tricky properties since the time dimension in regional (cross) sectional models is usually short. This paper describes the possible approaches to make long-term-ahead forecast based on a dynamic panel set, where the dependent variable is a cross-sectional vector of growth rates. Since the variance of the forecasts will depend on number of updating steps, we compare the forecasts behavior of a aggregated and a disaggregated updating procedure. The cross section of the panel data can be modeled by a spatial AR (SAR) or Durbin model, including heteroscedasticity. Since the forecasts are non-linear functions of the model parameters we show what MCMC based approach will produce the best results. We demonstrate the approach by a example where we have to predict 20 years ahead of regional growth in 99 Austrian regions in a space-time dependent system of equations.
  • RePEc:rim:rimwps:10-07
Language
  • English
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