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Bayesian vector autoregressions : estimation
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Miranda-Agrippino, Silvia and Ricco, Giovanni (2019) Bayesian vector autoregressions : estimation. In: Oxford Research Encyclopedia of Economics and Finance. Oxford University.
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WRAP-Bayesian-vector-autoregressions-estimation-Ricco-2018.pdf - Accepted Version Embargoed item. Restricted access to Repository staff only - Requires a PDF viewer. Download (770Kb) |
Official URL: https://doi.org/10.1093/acrefore/9780190625979.013...
Abstract
Vector autoregressions (VARs) are linear multivariate time-series models able to capture the joint dynamics of multiple time series. Bayesian inference treats the VAR parameters as random variables, and it provides a framework to estimate “posterior” probability distribution of the location of the model parameters by combining information provided by a sample of observed data and prior information derived from a variety of sources, such as other macro or micro datasets, theoretical models, other macroeconomic phenomena, or introspection.
In empirical work in economics and finance, informative prior probability distributions are often adopted. These are intended to summarize stylized representations of the data generating process. For example, “Minnesota” priors, one of the most commonly adopted macroeconomic priors for the VAR coefficients, express the belief that an independent random-walk model for each variable in the system is a reasonable “center” for the beliefs about their time-series behavior. Other commonly adopted priors, the “single-unit-root” and the “sum-of-coefficients” priors are used to enforce beliefs about relations among the VAR coefficients, such as for example the existence of co-integrating relationships among variables, or of independent unit-roots.
Item Type: | Book Item | ||||||
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Divisions: | Faculty of Social Sciences > Economics | ||||||
Publisher: | Oxford University | ||||||
Book Title: | Oxford Research Encyclopedia of Economics and Finance | ||||||
Official Date: | April 2019 | ||||||
Dates: |
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DOI: | 10.1093/acrefore/9780190625979.013.164 | ||||||
Status: | Peer Reviewed | ||||||
Publication Status: | Published | ||||||
Access rights to Published version: | Restricted or Subscription Access | ||||||
Date of first compliant deposit: | 11 October 2018 | ||||||
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