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 Use a Screen Reader

This content is available through Read Online (Free) program, which relies on page scans. Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.

Bayesian Semi-Nonparametric Arch Models

Gary Koop
The Review of Economics and Statistics
Vol. 76, No. 1 (Feb., 1994), pp. 176-181
Published by: The MIT Press
DOI: 10.2307/2109835
Stable URL: http://www.jstor.org/stable/2109835
Page Count: 6
  • Read Online (Free)
  • Download ($19.00)
  • Subscribe ($19.50)
  • Cite this Item
Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Bayesian Semi-Nonparametric Arch Models
Preview not available

Abstract

A Bayesian semi-nonparametric approach to ARCH models is developed with the advantage that small sample results are obtained even when the likelihood function is subject to nonlinear inequality constraints (as in the ARCH models used in this paper). The semi-nonparametric nature of the approach allows for the relaxation of the assumption of normal errors. An application and a small Monte Carlo study indicate that the methods we advocate are both feasible and necessary.

Page Thumbnails

  • Thumbnail: Page 
176
    176
  • Thumbnail: Page 
177
    177
  • Thumbnail: Page 
178
    178
  • Thumbnail: Page 
179
    179
  • Thumbnail: Page 
180
    180
  • Thumbnail: Page 
181
    181