Corpus ID: 237593060

Algorithms for Inference in SVARs Identified with Sign and Zero Restrictions

  title={Algorithms for Inference in SVARs Identified with Sign and Zero Restrictions},
  author={Matthew Read},
I develop algorithms to facilitate Bayesian inference in structural vector autoregressions that are set-identified with sign and zero restrictions by showing that the system of restrictions is equivalent to a system of sign restrictions in a lower-dimensional space. Consequently, algorithms applicable under sign restrictions can be extended to allow for zero restrictions. Specifically, I extend algorithms proposed in Amir-Ahmadi and Drautzburg (2021) to check whether the identified set is… Expand

Figures and Tables from this paper

Robust Bayesian Analysis for Econometrics
We review the literature on robust Bayesian analysis as a tool for global sensitivity analysis and for statistical decision-making under ambiguity. We discuss the methods proposed in the literature,Expand


Inference for Vars Identified with Sign Restrictions
Methods of constructing error bands for impulse response functions of sign-restricted SVARs that are valid from a frequentist perspective are developed and a comparison of frequentist and Bayesian error bands in the context of an empirical application is provided. Expand
Structural Vector Autoregressions: Theory of Identification and Algorithms for Inference
Structural vector autoregressions (SVARs) are widely used for policy analysis and to provide stylized facts for dynamic general equilibrium models. Yet there have been no workable rank conditions toExpand
Robust Bayesian Inference in Proxy Svars
The robust Bayesian approach to inference in set-identified models proposed by Giacomini and Kitagawa (2018) is extended to proxy SVARs and new results on the frequentist validity of the approach are provided. Expand
A note on global identification in structural vector autoregressions
In a landmark contribution to the structural vector autoregression (SVARs) literature, RubioRamı́rez, Waggoner, and Zha (2010, ‘Structural Vector Autoregressions: Theory of Identification andExpand
Identification and inference with ranking restrictions
It is shown that ranking restrictions on impulse‐responses to sign restrictions help to identify productivity news shocks in the data using both a fully Bayesian conditional uniform prior and prior‐robust inference. Expand
Inference Based on Structural Vector Autoregressions Identified With Sign and Zero Restrictions: Theory and Applications
Algorithms to independently draw from a family of conjugate posterior distributions over the structural parameterization when sign and zero restrictions are used to identify structural vector autoregressions (SVARs) are developed. Expand
Delta-method inference for a class of set-identified SVARs
Abstract We study vector autoregressions that impose equality and/or inequality restrictions to set-identify the dynamic responses to a single structural shock. We make three contributions. First, weExpand
The Systematic Component of Monetary Policy in SVARs: An Agnostic Identification Procedure
In this paper, we identify monetary policy shocks in structural vector autoregressions (SVARs) by imposing sign and zero restrictions on the systematic component of monetary policy while leaving theExpand
Identification and Inference Under Narrative Restrictions
We consider semi-structural time series models subject to ‘narrative restrictions’, which are inequality restrictions on functions of the structural shocks in specific time periods (as inExpand
Why Agnostic Sign Restrictions are not Enough: Understanding the Dynamics of Oil Market VAR Models
Sign restrictions on the responses generated by structural vector autoregressive models have been proposed as an alternative approach to the use of exclusion restrictions on the impact multiplierExpand