Template-Type: ReDIF-Paper 1.0
Author-Name: Strachan, R.W.
Author-Name-Last: Strachan
Author-Name-First: Rodney
Author-Person: pst79
Author-Name: van Dijk, H.K.
Author-Name-Last: van Dijk
Author-Name-First: Herman
Author-Person: pva325
Title: Model uncertainty and Bayesian model averaging in vector autoregressive processes
Abstract: Economic forecasts and policy decisions are often informed by empirical analysis based on econometric models. However, inference based upon a single model, when several viable models exist, limits its usefulness. Taking account of model uncertainty, a Bayesian model averaging procedure is presented which allows for unconditional inference within the class of vector autoregressive (VAR) processes. Several features of VAR process are investigated. Measures on manifolds are employed in order to elicit uniform priors on subspaces defined by particular structural features of VARs. The features considered are the number and form of the equilibrium economic relations and deterministic processes. Posterior probabilities of these features are used in a model averaging approach for forecasting and impulse response analysis. The methods are applied to investigate stability of the “Great Ratios” in U.S. consumption, investment and income, and the presence and effects of permanent shocks in these series. The results obtained indicate the feasibility of the proposed method.
Creation-Date: 2006-02-03
File-URL: https://repub.eur.nl/pub/7446/ei2006-08.pdf
File-Format: application/pdf
Series: RePEc:ems:eureir
Number: EI 2006-08
Classification-JEL: C11, C32, C52
Keywords: Grassman manifold, cointegration, impulse response, model averaging, orthogonal group, posterior probability, stochastic trend, vector autoregressive model
Handle: RePEc:ems:eureir:7446