Title: Block Recursion and Structural Vector Autoregressions
Author: Zha, Tao
Author Affiliation: Federal Reserve Bank of Atlanta
Source: Journal of Econometrics, June 1999, v. 90, iss. 2, pp. 291-316
Publication Date: June 1999
Abstract: In applications of structural VAR modeling, finite-sample properties may be difficult to obtain when certain identifying restrictions are imposed on lagged relationships. As a result, even though imposing some lagged restrictions makes economic sense, lagged relationships are often left unrestricted to make statistical inference more convenient. This paper develops block Monte Carlo methods to obtain both maximum likelihood estimates and exact Bayesian inference when certain types of restrictions are imposed on the lag structure. These methods are applied to two examples to illustrate the importance of imposing restrictions on lagged relationships.
Descriptors: Time Series and Spectral Analysis
Econometric and Statistical Methods and Models: Multivariate Analysis, Statistical Information Theory, and Other Special Inferential Problems; Queuing Theory; Markov Chains
Inferential Problems in Simultaneous Equation Systems
Natural Resources--General
Conservation and Pollution
Energy
Econometric Methods: Multiple/Simultaneous Equation Models: Time-Series Models
Nonrenewable Resources and Conservation: Government Policy (includes OPEC policy)
ISSN: 03044076
Publication Type: Journal Article
Availability: http://www.elsevier.com/homepage/sae/econbase/econom/