IDEAS home Printed from https://ideas.repec.org/p/hrv/faseco/33192198.html
   My bibliography  Save this paper

Estimating turning points using large data sets

Author

Listed:
  • Watson, Mark W.
  • Stock, James H.

Abstract

Dating business cycles entails ascertaining economy-wide turning points. Broadly speaking, there are two approaches in the literature. The first approach, which dates to Burns and Mitchell (1946), is to identify turning points individually in a large number of series, then to look for a common date that could be called an aggregate turning point. The second approach, which has been the focus of more recent academic and applied work, is to look for turning points in a few, or just one, aggregate. This paper examines these two approaches to the identification of turning points. We provide a nonparametric definition of a turning point (an estimand) based on a population of time series. This leads to estimators of turning points, sampling distributions, and standard errors for turning points based on a sample of series. We consider both simple random sampling and stratified sampling. The empirical part of the analysis is based on a data set of 270 disaggregated monthly real economic time series for the US, 1959–2010.

Suggested Citation

  • Watson, Mark W. & Stock, James H., 2014. "Estimating turning points using large data sets," Scholarly Articles 33192198, Harvard University Department of Economics.
    • Handle: RePEc:hrv:faseco:33192198
    as

    Download full text from publisher

    File URL: http://dash.harvard.edu/bitstream/handle/1/33192198/Estimating%20Turning%20Points.pdf
    Download Restriction: no
    ---><---

    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:hrv:faseco:33192198. 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: Office for Scholarly Communication (email available below). General contact details of provider: https://edirc.repec.org/data/deharus.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.