Structural Vector Autoregressions
Structural vector autoregressions (SVARs) are a multivariate, linear representation of a vector of observables on its own lags. SVARs are used by economists to recover economic shocks from observables by imposing a minimum of assumptions compatible with a large class of models. This article reviews the relation of SVARs to dynamic stochastic general equilibrium models, discusses the normalization, identification, and estimation of SVARs, and concludes with an assessment of the advantages and drawbacks of SVARs.
KeywordsBootstrap Dynamic stochastic general equilibrium models Estimation Identification Markov chain Monte Carlo methods Neoclassical growth theory Normalization Reduced-Form representation Sims, C. A. Structural vector autoregressions Vector autoregressions
JEL ClassificationsD4 D10
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