Access

You are not currently logged in.

Access your personal account or get JSTOR access through your library or other institution:

login

Log in to your personal account or through your institution.

If you need an accessible version of this item please contact JSTOR User Support

Estimating Continuous-Time Processes Subject to Time Deformation: An Application to Postwar U.S. GNP

James H. Stock
Journal of the American Statistical Association
Vol. 83, No. 401 (Mar., 1988), pp. 77-85
DOI: 10.2307/2288921
Stable URL: http://www.jstor.org/stable/2288921
Page Count: 9
  • Get Access
  • Download ($14.00)
  • Cite this Item
If you need an accessible version of this item please contact JSTOR User Support
Estimating Continuous-Time Processes Subject to Time Deformation: An Application to Postwar U.S. GNP
Preview not available

Abstract

A class of time series models is presented in which variables evolve on a data-based rather than calendar time scale. The discrete calendar-time model thus obtained exhibits time-varying parameters and conditional heteroscedasticity. Using a procedure based on the Kalman filter, univariate models are estimated for postwar U.S. real gross national product (GNP) and short- and long-term interest rates. The results indicate significant time scale nonlinearities.

Page Thumbnails

  • Thumbnail: Page 
77
    77
  • Thumbnail: Page 
78
    78
  • Thumbnail: Page 
79
    79
  • Thumbnail: Page 
80
    80
  • Thumbnail: Page 
81
    81
  • Thumbnail: Page 
82
    82
  • Thumbnail: Page 
83
    83
  • Thumbnail: Page 
84
    84
  • Thumbnail: Page 
85
    85