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.
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Paper provided by Department of Economics, University of Leicester in its series Discussion Papers in Economics with number
06/5.
Length: Date of creation: Feb 2006 Date of revision: Handle: RePEc:lec:leecon:06/5
Contact details of provider: Postal: Department of Economics University of Leicester, University Road. Leicester. LE1 7RH. UK Phone: +44 (0)116 252 2887 Fax: +44 (0)116 252 2908 Email: Web page: http://www.le.ac.uk/economics/
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