IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this paper or follow this series

Forecasting disaggregates by sectors and regions : the case of inflation in the euro area and Spain

  • Gabriel Pino

    ()

  • Juan de Dios Tena

    ()

  • Antoni Espasa

    ()

We study the performance of different modelling strategies for 969 and 600 monthly price indexes disaggregated by sectors and geographical areas in Spain, regions, and in the EA12, countries, in order to obtain a detailed picture of inflation and relative sectoral prices through geographical areas for each economy, using the forecasts from those models. The study also provides a description of the spatial cointegration restrictions which could be useful for understanding price setting within an economy. We use spatial bi-dimensional vector equilibrium correction models, where the price indexes for each sector are allowed to be cointegrated with prices in neighbouring areas using different definitions of neighbourhood. We find that geographical disaggregation forecasts are very reliable on a regional level in Spain as they improve the forecasting accuracy of headline inflation relative to alternative methods. Geographical disaggregation forecasts are also reliable for the EA12 but only because derived headline inflation forecasting is not significantly worse than alternative forecasts. These results show that regional analysis within countries is appropriate in the euro area. These highly disaggregated forecasts can be used for competitive and other type of macro and regional analysis

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://e-archivo.uc3m.es/bitstream/10016/16969/1/ws130807.pdf
Download Restriction: no

Paper provided by Universidad Carlos III, Departamento de Estadística y Econometría in its series Statistics and Econometrics Working Papers with number ws130807.

as
in new window

Length:
Date of creation: May 2013
Date of revision:
Handle: RePEc:cte:wsrepe:ws130807
Contact details of provider: Postal: C/ Madrid, 126 - 28903 GETAFE (MADRID)
Phone: 6249847
Fax: 6249849
Web page: http://portal.uc3m.es/portal/page/portal/dpto_estadistica

More information through EDIRC

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. Imbs, Jean & Mumtaz, Haroon & Ravn, Morten O & Rey, Hélène, 2003. "PPP Strikes Back: Aggregation and the Real Exchange Rate," CEPR Discussion Papers 3715, C.E.P.R. Discussion Papers.
  2. Christoffersen, Peter F & Diebold, Francis X, 1998. "Cointegration and Long-Horizon Forecasting," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(4), pages 450-58, October.
  3. Francis X. Diebold & Robert S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
  4. Schumacher, Christian & Breitung, Jörg, 2008. "Real-time forecasting of German GDP based on a large factor model with monthly and quarterly data," International Journal of Forecasting, Elsevier, vol. 24(3), pages 386-398.
  5. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501, March.
  6. Joseph Beaulieu, J. & Miron, Jeffrey A., 1993. "Seasonal unit roots in aggregate U.S. data," Journal of Econometrics, Elsevier, vol. 55(1-2), pages 305-328.
  7. David F. Hendry & Kirstin Hubrich, 2011. "Combining Disaggregate Forecasts or Combining Disaggregate Information to Forecast an Aggregate," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(2), pages 216-227, April.
  8. Giacomini, Raffaella & Granger, Clive W. J., 2004. "Aggregation of space-time processes," Journal of Econometrics, Elsevier, vol. 118(1-2), pages 7-26.
  9. Todd E. Clark, 2006. "Disaggregate evidence on the persistence of consumer price inflation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(5), pages 563-587.
  10. M. Hashem Pesaran, 2004. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," CESifo Working Paper Series 1331, CESifo Group Munich.
  11. Pesaran, M.H. & Smith, R., 1992. "Estimating Long-Run Relationships From Dynamic Heterogeneous Panels," Cambridge Working Papers in Economics 9215, Faculty of Economics, University of Cambridge.
  12. Jon Faust & John H. Rogers & Jonathan H. Wright, 2000. "News and noise in G-7 GDP announcements," International Finance Discussion Papers 690, Board of Governors of the Federal Reserve System (U.S.).
  13. Guenter W. Beck & Kirstin Hubrich & Massimiliano Marcellino, 2009. "Regional inflation dynamics within and across euro area countries and a comparison with the United States," Economic Policy, CEPR;CES;MSH, vol. 24, pages 141-184, 01.
  14. Jean Boivin & Serena Ng, 2003. "Are More Data Always Better for Factor Analysis?," NBER Working Papers 9829, National Bureau of Economic Research, Inc.
  15. Juan de Dios Tena & Antoni Espasa & Gabriel Pino, 2010. "Forecasting Spanish Inflation Using the Maximum Disaggregation Level by Sectors and Geographical Areas," International Regional Science Review, , vol. 33(2), pages 181-204, April.
  16. Franses, Philip Hans, 1991. "Seasonality, non-stationarity and the forecasting of monthly time series," International Journal of Forecasting, Elsevier, vol. 7(2), pages 199-208, August.
  17. Osborn, Denise R, et al, 1988. "Seasonality and the Order of Integration for Consumption," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 50(4), pages 361-77, November.
  18. Aron, Janine & Muellbauer, John, 2012. "Improving forecasting in an emerging economy, South Africa: Changing trends, long run restrictions and disaggregation," International Journal of Forecasting, Elsevier, vol. 28(2), pages 456-476.
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:cte:wsrepe:ws130807. 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: ()

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.