About: Bayesian vector autoregression

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In statistics and econometrics, Bayesian vector autoregression (BVAR) uses Bayesian methods to estimate a vector autoregression (VAR) model. BVAR differs with standard VAR models in that the model parameters are treated as random variables, with prior probabilities, rather than fixed values. The general idea is to use informative priors to shrink the unrestricted model towards a parsimonious naïve benchmark, thereby reducing parameter uncertainty and improving forecast accuracy. This type model can be estimated with Eviews, Stata, Python or R Statistical Packages.

Attributes	Values
rdfs:label	Bayesian vector autoregression (en)
rdfs:comment	In statistics and econometrics, Bayesian vector autoregression (BVAR) uses Bayesian methods to estimate a vector autoregression (VAR) model. BVAR differs with standard VAR models in that the model parameters are treated as random variables, with prior probabilities, rather than fixed values. The general idea is to use informative priors to shrink the unrestricted model towards a parsimonious naïve benchmark, thereby reducing parameter uncertainty and improving forecast accuracy. This type model can be estimated with Eviews, Stata, Python or R Statistical Packages. (en)
dcterms:subject	Multivariate time series Bayesian statistics
Wikipage page ID	20484241 (xsd:integer)
Wikipage revision ID	1070309896 (xsd:integer)
Link from a Wikipage to another Wikipage	Bayesian econometrics Bayesian inference Multivariate time series Python (programming language) University of Minnesota Stata Statistics Macroeconomic model Dynamic stochastic general equilibrium Prior probability Random variable Bayesian statistics Econometrics Eviews R (programming language) Shrinkage (statistics) Multilevel model Overfitting Vector autoregression Robert Litterman
Link from a Wikipage to an external page	https://www.commerce.gov/data-and-reports/economic-indicators/release-schedule https://books.google.com/books%3Fid=muorJ6FHIiEC&pg=PA223%7Cref=none
sameAs	Bayesian vector autoregression Bayesian vector autoregression Bayesian vector autoregression
dbp:wikiPageUsesTemplate	dbt:Cite_book dbt:Reflist dbt:Econometrics-stub
has abstract	In statistics and econometrics, Bayesian vector autoregression (BVAR) uses Bayesian methods to estimate a vector autoregression (VAR) model. BVAR differs with standard VAR models in that the model parameters are treated as random variables, with prior probabilities, rather than fixed values. Vector autoregressions are flexible statistical models that typically include many free parameters. Given the limited length of standard macroeconomic datasets relative to the vast number of parameters available, Bayesian methods have become an increasingly popular way of dealing with the problem of over-parameterization. As the ratio of variables to observations increases, the role of prior probabilities becomes increasingly important. The general idea is to use informative priors to shrink the unrestricted model towards a parsimonious naïve benchmark, thereby reducing parameter uncertainty and improving forecast accuracy. A typical example is the shrinkage prior, proposed by Robert Litterman (1979) and subsequently developed by other researchers at University of Minnesota, (i.e. Sims C, 1989), which is known in the BVAR literature as the "Minnesota prior". The informativeness of the prior can be set by treating it as an additional parameter based on a hierarchical interpretation of the model. In particular, the Minnesota prior assumes that each variable follows a random walk process, possibly with drift, and therefore consists of a normal prior on a set of parameters with fixed and known covariance matrix, which will be estimated with one of three techniques: Univariate AR, Diagonal VAR, or Full VAR. This type model can be estimated with Eviews, Stata, Python or R Statistical Packages. Recent research has shown that Bayesian vector autoregression is an appropriate tool for modelling large data sets. (en)
prov:wasDerivedFrom	wikipedia-en:Bayesian_vector_autoregression?oldid=1070309896&ns=0
page length (characters) of wiki page	5811 (xsd:nonNegativeInteger)
foaf:isPrimaryTopicOf	wikipedia-en:Bayesian_vector_autoregression
is Link from a Wikipage to another Wikipage of	Nowcasting (economics) Dynamic stochastic general equilibrium Bayesian Vector Autoregression List of statistics articles List of things named after Thomas Bayes Vector autoregression BVAR Bayesian VAR
is Wikipage redirect of	Bayesian Vector Autoregression BVAR Bayesian VAR
is foaf:primaryTopic of	wikipedia-en:Bayesian_vector_autoregression

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