IDEAS home Printed from https://ideas.repec.org/a/bla/reesec/v15y1987i4p374-388.html
   My bibliography  Save this article

Forecasting Using Long‐Order Autoregressive Processes: An Example Using Housing Starts

Author

Listed:
  • Michael A. Sklarz
  • Norman G. Miller
  • Will Gersch

Abstract

A long autoregressive (AR) modeling procedure for monthly U.S. housing starts data is considered. Neither differencing to remove the trend, nor differencing to remove the seasonal component is required in this method. The model is fitted by a Householder transformation‐Akaike AIC criterion algorithm. Forecast performance is compared to that obtained by the Box‐Jenkins ARIMA method. The prediction error variance of the long AR model method tends to be smaller than the prediction error variance of the Box‐Jenkins model method. The long AR method is well suited for housing market time‐series which are characterized by both strong seasonal and slowly changing trend components.

Suggested Citation

  • Michael A. Sklarz & Norman G. Miller & Will Gersch, 1987. "Forecasting Using Long‐Order Autoregressive Processes: An Example Using Housing Starts," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 15(4), pages 374-388, December.
    • Handle: RePEc:bla:reesec:v:15:y:1987:i:4:p:374-388
    DOI: 10.1111/1540-6229.00438
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/1540-6229.00438
    Download Restriction: no
    File URL: https://libkey.io/10.1111/1540-6229.00438?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
    ---><---

    Citations

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


    Cited by:

    1. Tim Meyer, 2019. "On the Directional Accuracy of United States Housing Starts Forecasts: Evidence from Survey Data," The Journal of Real Estate Finance and Economics, Springer, vol. 58(3), pages 457-488, April.

    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:bla:reesec:v:15:y:1987:i:4:p:374-388. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/areueea.html .

    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.