IDEAS home Printed from https://ideas.repec.org/h/pal/palchp/978-1-349-16092-1_2.html
   My bibliography  Save this book chapter

Effective Use of Econometric Models in Macroeconomic Policy Formulation

In: Optimal Control for Econometric Models

Author

Listed:
  • Gregory C. Chow

Abstract

At the beginning of each year, the Economic Report of the President of the United States makes projections of GNP in nominal and real terms for the coming year, the unemployment rate and the inflation rate, and states the major fiscal and monetary policies required to achieve these target rates. For example, the Report of January 1976 estimates real GNP to be 6 to 6.5 per cent higher in 1976 than in 1975 (p. 19), the unemployment rate to fall by almost a full percentage point and the inflation rate measured by the rise in the GNP deflator to be about 6 per cent (p. 24). The associated fiscal policies include a proposed Federal outlay in fiscal 1977 of $394 billion, a cut in taxes beginning in July 1976 of about $28 billion relative to what they would be under the 1974 law (p. 22). The rate of growth in the money supply M1, as announced by the Federal Reserve, ranges between 5 1/2 and 7 1/2 per cent, but the Report asserts that maintaining a rate of money growth at the upper limit of this range would hinder the progress toward lower inflation rates (pp. 21–2). Assuming that econometric models are being used for policy analysis, this paper presents a systematic approach to apply some recently developed techniques of stochastic control to improve the formulation of macroeconomic policies and the accompanying economic projections.

Suggested Citation

  • Gregory C. Chow, 1979. "Effective Use of Econometric Models in Macroeconomic Policy Formulation," Palgrave Macmillan Books, in: Sean Holly & Berç Rüstem & Martin B. Zarrop (ed.), Optimal Control for Econometric Models, chapter 2, pages 31-39, Palgrave Macmillan.
  • Handle: RePEc:pal:palchp:978-1-349-16092-1_2
    DOI: 10.1007/978-1-349-16092-1_2
    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.

    Citations

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


    Cited by:

    1. Rustem, Berc & Becker, Robin G. & Marty, Wolfgang, 2000. "Robust min-max portfolio strategies for rival forecast and risk scenarios," Journal of Economic Dynamics and Control, Elsevier, vol. 24(11-12), pages 1591-1621, October.

    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:pal:palchp:978-1-349-16092-1_2. 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.palgrave.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.