Advanced Search
MyIDEAS: Login

Forecasting and Decision Theory

Contents:

Author Info

  • Granger, Clive W.J.
  • Machina, Mark J.

Abstract

When forecasts of the future value of some variable, or the probability of some event, are used for purposes of ex ante planning or decision making, then the preferences, opportunities and constraints of the decision maker will all enter into the ex post evaluation of a forecast, and the ex post comparison of alternative forecasts. After a presenting a brief review of early work in the area of forecasting and decision theory, this chapter formally examines the manner in which the features of an agent's decision problem combine to generate an appropriate decision-based loss function for that agent's use in forecast evaluation. Decision-based loss functions are shown to exhibit certain necessary properties, and the relationship between the functional form of a decision-based loss function and the functional form of the agent's underlying utility function is characterized. In particular, the standard squared-error loss function is shown to imply highly restrictive and not particularly realistic properties on underlying preferences, which are not justified by the use of a standard local quadratic approximation. A class of more realistic loss functions ("location-dependent loss functions") is proposed.

Download Info

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://www.sciencedirect.com/science/article/B7P5J-4JSMTWJ-5/2/706989958db66c1c1838643030710537
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.

Bibliographic Info

as in new window

This chapter was published in:

  • G. Elliott & C. Granger & A. Timmermann (ed.), 2006. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 1, number 1, January.
    This item is provided by Elsevier in its series Handbook of Economic Forecasting with number 1-02.

    Handle: RePEc:eee:ecofch:1-02

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

    Related research

    Keywords:

    Find related papers by JEL classification:

    References

    No references listed on IDEAS
    You can help add them by filling out this form.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as in new window

    Cited by:
    1. : Roman Kozhan & Mark Salmon, 2010. "The information Content of a Limit Order Book:the Case of an FX Market," Working Papers wpn10-05, Warwick Business School, Finance Group.
    2. Janus, Thorsten & Riera-Crichton, Daniel, 2013. "International gross capital flows: New uses of balance of payments data and application to financial crises," Journal of Policy Modeling, Elsevier, vol. 35(1), pages 16-28.
    3. Timmermann, Allan G, 2005. "Forecast Combinations," CEPR Discussion Papers 5361, C.E.P.R. Discussion Papers.
    4. Manganelli, Simone, 2006. "A new theory of forecasting," Working Paper Series 0584, European Central Bank.
    5. Teräsvirta, Timo, 2005. "Forecasting economic variables with nonlinear models," Working Paper Series in Economics and Finance 598, Stockholm School of Economics, revised 29 Dec 2005.
    6. Oliver Williams & Stephen Satchell, 2011. "Social welfare issues of financial literacy and their implications for regulation," Journal of Regulatory Economics, Springer, vol. 40(1), pages 1-40, August.
    7. Shapoval, A., 2010. "Prediction problem for target events based on the inter-event waiting time," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(22), pages 5145-5154.
    8. Zhang, Xinyu & Lu, Zudi & Zou, Guohua, 2013. "Adaptively combined forecasting for discrete response time series," Journal of Econometrics, Elsevier, vol. 176(1), pages 80-91.

    Lists

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

    Statistics

    Access and download statistics

    Corrections

    When requesting a correction, please mention this item's handle: RePEc:eee:ecofch:1-02. 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: (Zhang, Lei).

    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.