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! ]

Long-Run Forecasting in Multicointegrated Systems

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Siliverstovs, Boriss () (DIW Berlin)
Engsted, Tom () (Department of Finance, Aarhus School of Business)
Haldrup, Niels () (University of Aarhus)

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

Abstract

In this paper long-run forecasting of multicointegrating variables is investigated. Multicointegration

typically occurs in dynamic systems involving both stock and flow variables whereby a common feature

in the form of shared stochastic trends is present across different levels of multiple time series.

Hence, the effect of imposing this ”common feature” restriction on out-of-sample evaluation and forecasting

accuracy of such variables is of interest. In particular, we compare the long-run forecasting

performance of the multicointegrated variables between a model that correctly imposes the ”common feature” restrictions and a (univariate) model that omits these multicointegrating restrictions completely.

We employ different loss functions based on a range of mean square forecast error criteria,

and the results indicate that different loss functions result in different ranking of models with respect to their infinite horizon forecasting performance. We consider loss functions using a standard trace

mean square forecast error criterion (penalizing the forecast errors of flow variables only), and a loss function evaluating forecast errors of changes in both stock and flow variables. The latter loss function is based on the triangular representation of cointegrated systems and was initially suggested by Christoffersen and Diebold (1998). It penalizes deviations from long-run relations among the flow variables through cointegrating restrictions. We present a new loss function which further penalizes

deviations in the long run relationship between the levels of stock and flow variables. It is derived from the triangular representation of multicointegrated systems. Using this criterion, system forecasts from a model incorporating multicointegration restrictions dominate forecasts from univariate models.

The paper highlights the importance of carefully selecting loss functions in forecast evaluation of models involving stock and flow variables.

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://www.asb.dk/~tom/siliverstovsengstedhaldrup.pdf
Our checks indicate that this address may not be valid because: 404 Not Found. If this is indeed the case, please notify (Helle Vinbaek Stenholt)
File Format: application/pdf
File Function:
Download Restriction: no

Publisher Info
Paper provided by University of Aarhus, Aarhus School of Business, Department of Business Studies in its series Finance Working Papers with number 02-14.

Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Length: 26 pages
Date of creation: 09 May 2002
Date of revision:
Handle: RePEc:hhb:aarfin:2002_014

Contact details of provider:
Postal: The Aarhus School of Business, Fuglesangs Allé 4, DK-8210 Aarhus V, Denmark
Fax: + 45 86 15 19 43
Web page: http://www.asb.dk/about/departments/bs.aspx
More information through EDIRC

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

Related research
Keywords: Common Features; Multicointegration; Forecasting; VAR models;

Other versions of this item:

This paper has been announced in the following NEP Reports: 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. Elliott, Graham & Komunjer, Ivana & Timmermann, Allan G, 2003. "Estimating Loss Function Parameters," CEPR Discussion Papers 3821, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
  2. Haldrup, Neils, 1998. " An Econometric Analysis of I(2) Variables," Journal of Economic Surveys, Blackwell Publishing, vol. 12(5), pages 595-650, December. [Downloadable!] (restricted)
  3. Leachman, Lori L, 1996. "New Evidence on the Ricardian Equivalence Theorem: A Multicointegration Approach," Applied Economics, Taylor and Francis Journals, vol. 28(6), pages 695-704, June. [Downloadable!] (restricted)
  4. Engsted, Tom & Haldrup, Niels, 1999. " Multicointegration in Stock-Flow Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(2), pages 237-54, May. [Downloadable!] (restricted)
    Other versions:
  5. Engle, Robert F. & Yoo, Byung Sam, 1987. "Forecasting and testing in co-integrated systems," Journal of Econometrics, Elsevier, vol. 35(1), pages 143-159, May. [Downloadable!] (restricted)
  6. Engsted, Tom & Gonzalo, Jesus & Haldrup, Niels, 1997. "Testing for multicointegration," Economics Letters, Elsevier, vol. 56(3), pages 259-266, November. [Downloadable!] (restricted)
    Other versions:
  7. Boriss Siliverstovs, . "Multicointegration in US consumption data," Economics Working Papers 2001-6, School of Economics and Management, University of Aarhus. [Downloadable!]
    Other versions:
  8. Campbell, John Y & Shiller, Robert J, 1987. "Cointegration and Tests of Present Value Models," Journal of Political Economy, University of Chicago Press, vol. 95(5), pages 1062-88, October. [Downloadable!] (restricted)
    Other versions:
  9. Clements, M.P. & Hendry, D., 1992. "On the Limitations of Comparing Mean Square Forecast Errors," Economics Series Working Papers 99138, University of Oxford, Department of Economics.
  10. Anindya Banerjee & Lynne Cockerell & Bill Russell, 2001. "An I(2) analysis of inflation and the markup," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 221-240. [Downloadable!]
  11. Phillips, P C B, 1991. "Optimal Inference in Cointegrated Systems," Econometrica, Econometric Society, vol. 59(2), pages 283-306, March. [Downloadable!] (restricted)
    Other versions:
  12. Peter F. Christoffersen & Francis X. Diebold, 1997. "Cointegration and Long-Horizon Forecasting," NBER Technical Working Papers 0217, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
    Other versions:
  13. Clements, M.P. & Hendry, D.F., 1992. "Forecasting in Cointegrated Systems," Economics Series Working Papers 99139, University of Oxford, Department of Economics.
  14. Clements, Michael P & Hendry, David F, 1995. "Forecasting in Cointegration Systems," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(2), pages 127-46, April-Jun. [Downloadable!] (restricted)
  15. Granger, C W J & Lee, T H, 1989. "Investigation of Production, Sales and Inventory Relationships Using Multicointegration and Non-symmetric Error Correction Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 4(S), pages S145-59, Supplemen. [Downloadable!] (restricted)
  16. Engsted, T. & Johansen, S., 1997. "Granger's Representation Theorem and Multicointegration," Economics Working Papers eco97/15, European University Institute.
Full references

Cited by:
(explanations, 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. Osmani Teixeira de Carvalho Guillén & João Victor Issler & George Athanasopoulos, 2005. "Forecasting Accuracy and Estimation Uncertainty Using VAR Models with Short- and Long-Term Economic Restrictions: A Monte-Carlo Study," Monash Econometrics and Business Statistics Working Papers 15/05, Monash University, Department of Econometrics and Business Statistics. [Downloadable!]
    Other versions:
  2. Haldrup, Niels, . "Empirical analysis of price data in the delineation of the relevant geographical market in competition analysis," Economics Working Papers 2003-9, School of Economics and Management, University of Aarhus. [Downloadable!]
  3. Holler, Manfred & Skott, Peter, . "The importance of setting the agenda," Economics Working Papers 2003-8, School of Economics and Management, University of Aarhus. [Downloadable!]
  4. Nielsen, Morten Oe., . "Local Empirical Spectral Measure of Multivariate Processes with Long Range Dependence," Economics Working Papers 2002-16, School of Economics and Management, University of Aarhus. [Downloadable!]
Statistics
Access and download statistics

Did you know? Each page is provided with a technical contact, in case something is not right with the supplied information. See under "publisher info".

This page was last updated on 2009-11-25.


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.