Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/29791
Authors: 
Girardin, Eric
Kholodilin, Konstantin Arkadievich
Year of Publication: 
2009
Series/Report no.: 
DIW Discussion Papers 938
Abstract: 
In this paper, we make multi-step forecasts of the annual growth rates of the real GRP for each of the 31 Chinese provinces simultaneously. Beside the usual panel data models, we use panel models that explicitly account for spatial dependence between the GRP growth rates. In addition, the possibility of spatial effects being different for different groups of provinces (Interior and Coast) is allowed. We find that both pooling and accounting for spatial effects helps substantially improve the forecast performance compared to the benchmark models estimated for each of the provinces separately. It was also shown that effect of accounting for spatial dependence is even more pronounced at longer forecasting horizons (the forecast accuracy gain as measured by the root mean squared forecast error is about 8% at 1-year horizon and exceeds 25% at 13- and 14-year horizon).
Subjects: 
Chinese provinces
forecasting
dynamic panel model
spatial autocorrelation
group-specific spatial dependence
JEL: 
C21
C23
C53
Document Type: 
Working Paper

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