Normalization, probability distribution, and impulse responses
When impulse responses in dynamic multivariate models such as identified VARs are given economic interpretations, it is important that reliable statistical inferences be provided. Before probability assessments are provided, however, the model must be normalized. Contrary to the conventional wisdom, this paper argues that normalization, a rule of reversing signs of coefficients in equations in a particular way, could considerably affect the shape of the likelihood and thus probability bands for impulse responses. A new concept called ML distance normalization is introduced to avoid distorting the shape of the likelihood. Moreover, this paper develops a Monte Carlo simulation technique for implementing ML distance normalization.
|Date of creation:||1997|
|Contact details of provider:|| Postal: 1000 Peachtree St., N.E., Atlanta, Georgia 30309|
Web page: http://www.frbatlanta.org/
More information through EDIRC
|Order Information:|| Email: |
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Ben S. Bernanke & Mark Gertler & Mark Watson, 1997.
"Systematic Monetary Policy and the Effects of Oil Price Shocks,"
Brookings Papers on Economic Activity,
Economic Studies Program, The Brookings Institution, vol. 28(1), pages 91-157.
- Bernanke, Ben S. & Gertler, Mark & Waston, Mark, 1997. "Systematic Monetary Policy and the Effects of Oil Price Shocks," Working Papers 97-25, C.V. Starr Center for Applied Economics, New York University.