IDEAS home Printed from https://ideas.repec.org/a/bpj/sndecm/v1y1996i1nda1.html
   My bibliography  Save this article

Forecasting Using First-Available Versus Fully Revised Economic Time-Series Data

Author

Listed:
  • Swanson Norman

    (Department of Economics Pennsylvania State University)

Abstract

First-reported monthly and quarterly time-series data on nine macroeconomic variables from 1960-1993 are given. Features of this so-called "unrevised" or "first-reported data" are discussed, and the data is compared with standard "fully revised" data using Granger causality tests. For the purposes of real-time forecasting, as well as comparing professional forecasts with traditional econometric forecasts, the use of unrevised (or, even better, "real-time") data has a number of advantages over the use of fully revised data.

Suggested Citation

  • Swanson Norman, 1996. "Forecasting Using First-Available Versus Fully Revised Economic Time-Series Data," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 1(1), pages 1-20, April.
    • Handle: RePEc:bpj:sndecm:v:1:y:1996:i:1:n:da1
    DOI: 10.2202/1558-3708.1012
    as

    Download full text from publisher

    File URL: https://doi.org/10.2202/1558-3708.1012
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.
    File URL: https://libkey.io/10.2202/1558-3708.1012?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    More about this item

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C59 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Other
    • C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bpj:sndecm:v:1:y:1996:i:1:n:da1. See general information about how to correct material in RePEc.

    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.

    We have no bibliographic references for this item. You can help adding them by using 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 RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Golla (email available below). General contact details of provider: https://www.degruyter.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.