The Value of Structural Information in the VAR Model
Abstract
Economic policy decisions are often informed by empirical economic analysis. While the decision-maker is usually only interested in good estimates of outcomes, the analyst is interested in estimating the model. Accurate inference on the structural features of a model, such as cointegration, can improve policy analysis as it can improve estimation, inference and forecast efficiency from using that model. However, using a model does not guarantee good estimates of the object of interest and, as it assigns a probability of one to a model and zero to near-by models, takes extreme zero-one account of the ‘weight of evidence’ in the data and the researcher’s uncertainty. By using the uncertainty associated with the structural features in a model set, one obtains policy analysis that is not conditional on the structure of the model and can improve efficiency if the features are appropriately weighted. In this paper tools are presented to allow for unconditional inference on the vector autoregressive (VAR) model. In particular, we employ measures on manifolds to elicit priors on subspaces defined by particular features of the VAR model. The features considered are cointegration, exogeneity, deterministic processes and overidentification. Two applications - money demand in Australia, and a macroeconomic model of the UK proposed by Garratt, Lee, Persaran, and Shin (2002) are used to illustrate the feasibility of the proposed methods.Download Info
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Paper provided by Centre for Economic Research, Keele University in its series Keele Economics Research Papers with number KERP 2004/02.Length: 37 pages
Date of creation: Jan 2004
Date of revision:
Handle: RePEc:kee:kerpuk:2004/02
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Postal: Department of Economics, University of Keele, Keele, Staffordshire, ST5 5BG - United Kingdom
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Postal: Centre for Economic Research, Research Institute for Public Policy and Management, Keele University, Staffordshire ST5 5BG - United Kingdom
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Related research
Keywords: Posterior probability; Laplace approximation; Structural modelling; Cointegration; Exogeneity; Model averaging;Other versions of this item:
- Strachan, R.W. & Dijk, H.K. van, 2003. "The value of structural information in the VAR model," Econometric Institute Report EI 2003-17, Erasmus University Rotterdam, Econometric Institute.
- Rodney W. Strachan & Herman K. van Dijk, 2004. "The Value of Structural Information in the VAR Model," Econometric Society 2004 North American Summer Meetings 45, Econometric Society.
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
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Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.Cited by:
- Gary Koop & Simon M. Potter & Rodney W. Strachan, 2005.
"Reexamining the consumption-wealth relationship: the role of model uncertainty,"
Staff Reports
202, Federal Reserve Bank of New York.
- Gary Koop & Simon M. Potter & Rodney W. Strachan, 2008. "Re-Examining the Consumption-Wealth Relationship: The Role of Model Uncertainty," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(2-3), pages 341-367, 03.
- Gary Koop & Simon M. Potter & Rodney W. Strachan, 2005. "Re-examining the Consumption-Wealth Relationship: The Role of Model Uncertainty," Discussion Papers in Economics 05/3, Department of Economics, University of Leicester.
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