English, Article, Journal or magazine article edition: Aggregation of Space-Time Processes Raffaella Giacomini; Clive W.J. Granger

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Bookmark: http://trove.nla.gov.au/version/73487
Physical Description
  • preprint
Language
  • English

Edition details

Title
  • Aggregation of Space-Time Processes
Author
  • Raffaella Giacomini
  • Clive W.J. Granger
Physical Description
  • preprint
Notes
  • In this paper we compare the relative efficiency of different methods of forecasting the aggregate of spatially correlated variables. Small sample simulations confirm the asymptotic result that improved forecasting performance can be obtained by imposing a priori constraints on the amount of spatial correlation in the system. One way to do so is to aggregate forecasts from a Space-Time Autoregressive model (Cliff et al., 1975), which offers a solution to the 'curse of dimensionality' that arises when forecasting with VARs. We also show that ignoring spatial correlation, even when it is weak, leads to highly inaccurate forecasts. Finally, if the system satisfies a 'poolability' condition, there is a benefit in forecasting the aggregate variable directly.
  • RePEc:cdl:ucsdec:2001-07
  • In this paper we compare the relative efficiency of different methods of forecasting the aggregate of spatially correlated variables. Small sample simulations confirm the asymptotic result that improved forecasting performance can be obtained by imposing a priori constraints on the amount of spatial correlation in the system. We also show that ignoring spatial correlation, even when it is weak, leads to highly inaccurate forecasts.
  • Spatial correlation, aggregation, forecast efficiency, space-time models, VAR
  • RePEc:boc:bocoec:582
Language
  • English
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