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! ]

Forecasting with Breaks

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Clements, Michael P.
Hendry, David F.

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

Abstract

A structural break is viewed as a permanent change in the parameter vector of a model. Using taxonomies of all sources of forecast errors for both conditional mean and conditional variance processes, we consider the impacts of breaks and their relevance in forecasting models: (a) where the breaks occur after forecasts are announced; and (b) where they occur in-sample and hence pre-forecasting. The impact on forecasts depends on which features of the models are non-constant. Different models and methods are shown to fare differently in the face of breaks. While structural breaks induce an instability in some parameters of a particular model, the consequences for forecasting are specific to the type of break and form of model. We present a detailed analysis for cointegrated VARs, given the popularity of such models in econometrics. We also consider the detection of breaks, and how to handle breaks in a forecasting context, including ad hoc forecasting devices and the choice of the estimation period. Finally, we contrast the impact of structural break non-constancies with non-constancies due to non-linearity. The main focus is on macro-economic, rather than finance, data, and on forecast biases, rather than higher moments. Nevertheless, we show the relevance of some of the key results for variance processes. An empirical exercise `forecasts' UK unemployment after three major historical crises.

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.sciencedirect.com/science/article/B7P5J-4JSMTWJ-H/2/e17d009c73049240317e03f537ebebdd
File Format:
File Function:
Download Restriction: Full text for ScienceDirect subscribers only

As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

Publisher Info
Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
This chapter was published in: G. Elliott & C. Granger & A. Timmermann (ed.) , Elsevier, chapter 12, pages 605-657, 2006.

This item is provided by Elsevier in its series Handbook of Economic Forecasting with number 1-12.

Handle: RePEc:eee:ecofch:1-12

Contact details of provider:
Web page: http://www.elsevier.com/wps/find/bookseriesdescription.cws_home/BS_HE/description

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

Related research
This chapter was published in the following book, which is listed on IDEAS:
G. Elliott & C. Granger & A. Timmermann (ed.), 2006. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 1, number 1, September. [Downloadable!] (restricted)
Keywords:

Find related papers by JEL classification:
B0 - Schools of Economic Thought and Methodology - - General

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. Pesaran, M.H. & Pick, A., 2008. "Forecasting Random Walks Under Drift Instability," Cambridge Working Papers in Economics 0814, Faculty of Economics, University of Cambridge. [Downloadable!]
    Other versions:
  2. Kirstin Hubrich & David F. Hendry, 2005. "Forecasting Aggregates by Disaggregates," Computing in Economics and Finance 2005 270, Society for Computational Economics. [Downloadable!]
  3. David F. Hendry & Kirstin Hubrich, 2006. "Forecasting economic aggregates by disaggregates," Working Paper Series 589, European Central Bank. [Downloadable!]
    Other versions:
  4. Issler, João Victor & Lima, Luiz Renato Regis de Oliveira, 2007. "A Panel Data Approach to Economic Forecasting: The Bias-Corrected Average Forecast," Economics Working Papers (Ensaios Economicos da EPGE) 642, Graduate School of Economics, Getulio Vargas Foundation (Brazil). [Downloadable!]
    Other versions:
  5. Elliott, Graham & Timmermann, Allan G, 2007. "Economic Forecasting," CEPR Discussion Papers 6158, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
    Other versions:
  6. Clements, Michael P. & Galvão, Ana Beatriz & Kim, Jae H., 2006. "Quantile Forecasts of Daily Exchange Rate Returns from Forecasts of Realized Volatility," The Warwick Economics Research Paper Series (TWERPS) 777, University of Warwick, Department of Economics. [Downloadable!]
    Other versions:
Statistics
Access and download statistics

Did you know? You may want to explore EconPapers, which displays the same data as IDEAS in a different way.

This page was last updated on 2009-11-6.


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.