This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

Business surveys modelling with Seasonal-Cyclical Long Memory models

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Laurent Ferrara () (DGEI-DAMEP - Banque de France)
Dominique Guegan () (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Panthéon-Sorbonne - Paris I, EEP-PSE - Ecole d'Économie de Paris - Paris School of Economics - Ecole d'Économie de Paris)

Additional information is available for the following registered author(s):

Abstract

Business surveys are an important element in the analysis of the short-term economic situation because of the timeliness and nature of the information they convey. Especially, surveys are often involved in econometric models in order to provide an early assessment of the current state of the economy, which is of great interest for policy-makers. In this paper, we focus on non-seasonally adjusted business surveys released by the European Commission. We introduce an innovative way for modelling those series taking the persistence of the seasonal roots into account through seasonal-cyclical long memory models. We empirically prove that such models produce more accurate forecasts than classical seasonal linear models.

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. 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://halshs.archives-ouvertes.fr/docs/00/28/37/10/PDF/ferrara_guegan_survey.pdf
File Format: application/pdf
File Function:
Download Restriction: no

Publisher Info
Paper provided by HAL in its series Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) with number halshs-00283710_v1.

Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Length:
Date of creation: 2008
Date of revision:
Publication status: Published, Economics Bulletin, 2008, 3, 29, 1-10
Handle: RePEc:hal:cesptp:halshs-00283710_v1

Note: View the original document on HAL open archive server: http://halshs.archives-ouvertes.fr/halshs-00283710/en/
Contact details of provider:
Web page: http://hal.archives-ouvertes.fr/

For technical questions regarding this item, or to correct its listing, contact: (CCSD).

Related research
Keywords: business surveys; seasonality; long memory models; forecasting;

Other versions of this item:

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.:
  1. Sofia C. Olhede, 2004. "Large-sample properties of the periodogram estimator of seasonally persistent processes," Biometrika, Oxford University Press for Biometrika Trust, vol. 91(3), pages 613-628, September.
  2. Angelini, Elena & Camba-Mendez, Gonzalo & Giannone, Domenico & Reichlin, Lucrezia & Rünstler, Gerhard, 2008. "Short-term Forecasts of Euro Area GDP Growth," CEPR Discussion Papers 6746, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
    Other versions:
  3. Baillie, Richard T., 1996. "Long memory processes and fractional integration in econometrics," Journal of Econometrics, Elsevier, vol. 73(1), pages 5-59, July. [Downloadable!] (restricted)
  4. Dominique Guegan, 2003. "A prospective study of the k-factor Gegenbauer processes with heteroscedastic errors and an application to inflation rates," Post-Print halshs-00201314_v1, HAL. [Downloadable!]
  5. Laurent Ferrara & Dominique Guegan & Zhiping Lu, 2008. "Testing fractional order of long memory processes : a Monte Carlo study," Documents de travail du Centre d'Economie de la Sorbonne b08012, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne. [Downloadable!]
    Other versions:
  6. Laurent Ferrara, 2007. "Point and interval nowcasts of the Euro area IPI," Applied Economics Letters, Taylor and Francis Journals, vol. 14(2), pages 115-120. [Downloadable!] (restricted)
  7. Wilfredo Palma & Ngai Hang Chan, 2005. "Efficient Estimation of Seasonal Long-Range-Dependent Processes," Journal of Time Series Analysis, Blackwell Publishing, vol. 26(6), pages 863-892, November. [Downloadable!] (restricted)
  8. Franses, Philip Hans & Ooms, Marius, 1997. "A periodic long-memory model for quarterly UK inflation," International Journal of Forecasting, Elsevier, vol. 13(1), pages 117-126, March. [Downloadable!] (restricted)
  9. Luis A. Gil-alana, 2006. "Testing Seasonality in the Context of Fractionally Integrated Processes," Annales d'Economie et de Statistique, ADRES, issue 81, pages 03, Janvier-M. [Downloadable!]
  10. Ray, Bonnie K., 1993. "Long-range forecasting of IBM product revenues using a seasonal fractionally differenced ARMA model," International Journal of Forecasting, Elsevier, vol. 9(2), pages 255-269, August. [Downloadable!] (restricted)
  11. Ferrara, Laurent & Guegan, Dominique, 2001. "Forecasting with k-Factor Gegenbauer Processes: Theory and Applications," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 20(8), pages 581-601, December.
  12. Josu Artech & Peter M Robinson, 1998. "Semiparametric Inference in Seasonal and Cyclical Long Memory Processes - (Now published in Journal of Time Series Analysis, 21 (2000), pp.1-25.)," STICERD - Econometrics Paper Series /1998/359, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE. [Downloadable!]
  13. Laurent Ferrara & Dominique Guegan, 2006. "Fractional seasonality: Models and Application to Economic Activity in the Euro Area," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00185370_v1, HAL. [Downloadable!]
Full references

Statistics
Access and download statistics

Did you know? RePEc also has a blog.

This page was last updated on 2009-12-4.

This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.