IDEAS home Printed from https://ideas.repec.org/h/spr/sptchp/978-3-030-76646-7_6.html
   My bibliography  Save this book chapter

Structural Time-Series Model

In: Empirical Regional Economics

Author

Listed:
  • Richard S. Conway

    (Dick Conway and Associates)

Abstract

The Puget Sound Forecasting Model is a structural time-series model of the greater Seattle area. Its foremost objective is to produce accurate predictions. The model generates quarterly forecasts over two and ten-year periods. Since 1993 the forecasts have been reported in The Puget Sound Economic Forecaster, a quarterly newsletter on the regional economy. Principal variables predicted by the model include personal income, employment (18 categories), the unemployment rate, the consumer price index, population, retail sales, housing permits, the average home price, and the apartment vacancy rate. As a means of minimizing prediction error, the model combines a structural regression model (one with explanatory variables) with a time-series (ARIMA) model of the residuals.

Suggested Citation

  • Richard S. Conway, 2022. "Structural Time-Series Model," Springer Texts in Business and Economics, in: Empirical Regional Economics, chapter 0, pages 139-167, Springer.
    • Handle: RePEc:spr:sptchp:978-3-030-76646-7_6
    DOI: 10.1007/978-3-030-76646-7_6
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    More about this item

    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:spr:sptchp:978-3-030-76646-7_6. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.