|
Activity Number:
|
360
|
|
Type:
|
Invited
|
|
Date/Time:
|
Wednesday, August 1, 2007 : 8:30 AM to 10:20 AM
|
|
Sponsor:
|
Business and Economics Statistics Section
|
| Abstract - #307682 |
|
Title:
|
Structural Vector Autoregressions: Theory and Application
|
|
Author(s):
|
Dan Waggoner*+ and Tao Zha
|
|
Companies:
|
Federal Reserve Bank of Atlanta and Federal Reserve Bank of Atlanta
|
|
Address:
|
1000 Peachtree Street NE, Atlanta, GA, 30309-3904,
|
|
Keywords:
|
Identification ; Efficient Algorithm ; Nonlinear Restrictions ; Orthonormal Transformation
|
|
Abstract:
|
Identification for simultaneous multiple-equation models is an important issue. Typically, there is no formal way of checking whether a structural VAR model is identified or not. In this paper we develop a new and easily implementable necessary and sufficient condition for the exact identification of a SVAR model. We also develop a sufficient condition for overidentification. Both theorems apply to models with both linear and some nonlinear restrictions on the structural parameters. Moreover, we derive efficient MCMC algorithms to implement sign and long-run restrictions in SVARs. Using our methods, four well-known identification schemes are used to study whether monetary policy has changed in the Euro area since the introduction of the European Monetary Union.
|
