IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Log in (now much improved!) to save this article

How helpful are spatial effects in forecasting the growth of Chinese provinces?

  • Eric Girardin
  • Konstantin A. Kholodilin

In this paper, we make multi-step forecasts of the annual growth rates of the real gross regional product (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 for. We find that both pooling and accounting for spatial effects help substantially to improve the forecast performance compared to the benchmark models estimated for each of the provinces separately. It is also shown that the 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 the 1‐year horizon and exceeds 25% at the 13‐ and 14‐year horizons). Copyright (C) 2010 John Wiley & Sons, Ltd.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://hdl.handle.net/10.1002/for.1193
Download Restriction: no

Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.

Volume (Year): 30 (2011)
Issue (Month): 7 (November)
Pages: 622-643

as
in new window

Handle: RePEc:jof:jforec:v:30:y:2011:i:7:p:622-643
Contact details of provider: Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

as in new window
  1. Badi Baltagi & Dong Li, 2006. "Prediction in the Panel Data Model with Spatial Correlation: the Case of Liquor," Spatial Economic Analysis, Taylor & Francis Journals, vol. 1(2), pages 175-185.
  2. Konstantin A. Kholodilin & Boriss Siliverstovs & Stefan Kooths, 2007. "A Dynamic Panel Data Approach to the Forecasting of the GDP of German Länder," Discussion Papers of DIW Berlin 664, DIW Berlin, German Institute for Economic Research.
  3. Long Gen Ying, 2003. "Understanding China’s recent growth experience: A spatial econometric perspective," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 37(4), pages 613-628, December.
  4. Lawrence R Klein & Wendy Mak, 2005. "Initial Steps in High-Frequency Modeling of China," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 40(1), pages 11-14, January.
  5. Meng, Bo & Chao, Qu, 2007. "Application of the Input-Output Decomposition Technique to China's Regional Economies," IDE Discussion Papers 102, Institute of Developing Economies, Japan External Trade Organization(JETRO).
  6. Herbert Brücker & Boriss Siliverstovs, 2006. "On the estimation and forecasting of international migration: how relevant is heterogeneity across countries?," Empirical Economics, Springer, vol. 31(3), pages 735-754, September.
  7. Simonetta Longhi & Peter Nijkamp, 2007. "Forecasting Regional Labor Market Developments under Spatial Autocorrelation," International Regional Science Review, SAGE Publishing, vol. 30(2), pages 100-119, April.
  8. Qin, Duo & Cagas, Marie Anne & Ducanes, Geoffrey & Magtibay-Ramos, Nedelyn & Quising, Pilipinas, 2008. "Automatic leading indicators versus macroeconometric structural models: A comparison of inflation and GDP growth forecasting," International Journal of Forecasting, Elsevier, vol. 24(3), pages 399-413.
  9. James H. Stock & Mark W. Watson, 1989. "New Indexes of Coincident and Leading Economic Indicators," NBER Chapters, in: NBER Macroeconomics Annual 1989, Volume 4, pages 351-409 National Bureau of Economic Research, Inc.
  10. Declan Curran & Michael Funke, 2006. "Taking the Temperature - Forecasting GDP Growth for Mainland China," Quantitative Macroeconomics Working Papers 20606, Hamburg University, Department of Economics.
  11. McCallum, John, 1995. "National Borders Matter: Canada-U.S. Regional Trade Patterns," American Economic Review, American Economic Association, vol. 85(3), pages 615-23, June.
  12. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Oxford University Press, vol. 58(2), pages 277-297.
  13. Sandra PONCET, 2002. "A Fragmented China. Measure and Determinants of Chinese Domestic Market Disintegration," Working Papers 200221, CERDI.
  14. Xubei Luo, 2005. "Growth spillover effects and regional development patterns : the case of Chinese provinces," Policy Research Working Paper Series 3652, The World Bank.
  15. Poncet, Sandra, 2003. "Measuring Chinese domestic and international integration," China Economic Review, Elsevier, vol. 14(1), pages 1-21.
  16. Badi H. Baltagi & James M. Griffin & Weiwen Xiong, 2000. "To Pool Or Not To Pool: Homogeneous Versus Hetergeneous Estimations Applied to Cigarette Demand," The Review of Economics and Statistics, MIT Press, vol. 82(1), pages 117-126, February.
  17. Aroca, Patricio & Guo, Dong & Hewings, Geoffrey J.D., 2006. "Spatial Convergence in China: 1952-99," Working Paper Series RP2006/89, World Institute for Development Economic Research (UNU-WIDER).
  18. Krister Sandberg, 2004. "Growth of GRP in Chinese Provinces. A Test for Spatial Spillovers," ERSA conference papers ersa04p596, European Regional Science Association.
  19. James H. Stock & Mark W. Watson, 2005. "Implications of Dynamic Factor Models for VAR Analysis," NBER Working Papers 11467, National Bureau of Economic Research, Inc.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:jof:jforec:v:30:y:2011:i:7:p:622-643. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Wiley-Blackwell Digital Licensing)

or (Christopher F. Baum)

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.