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- Oscar Jorda (2007): Inference for Impulse Responses
Poor identification of individual impulse response coefficients does not necessarily mean that animpulse response is imprecisely estimated. This paper introduces a three-pronged approach on howto communicate uncertainty of impulse response estimates: (1) withWald tests of joint significance;(2) with conditional t-tests of individual marginal coefficient significance; and (3) with fan chartsbased on the percentiles of the joint Wald statistics. The paper also shows how to anchor theimpulse response analysis with a priori economic restrictions that can be formally tested and usedto tighten structural identification. These methods are universal and do not depend on how theimpulse responses are estimated.
RePEc:cda:wpaper:201 Save to MyIDEAS - Jonas E. Arias & Juan F. Rubio-Ramirez & Daniel F. Waggoner (2020): Uniform Priors for Impulse Responses
Although the prior distributions of individual impulse responses induced by the conventional method may be nonuniform, they typically do not drive the posteriors if one does not condition on the reduced-form parameters. Importantly, when the focus is on joint inference, the uniform prior over the set of orthogonal matrices is not only sufficient but also necessary for inference based on a uniform joint prior distribution over the identified set for the vector of impulse responses. We also propose variants of the conventional method to conduct inference based on a uniform joint prior distribution for the vector of impulse responses. We generalize our results to vectors of objects of interest beyond impulse responses.
RePEc:fip:fedpwp:94737 Save to MyIDEAS - Oscar Jorda (2003): Model-Free Impulse Responses
This paper introduces methods for computing impulse response functions that do not require specification and estimation of the unknown dynamic multivariate system itself. ... Therefore, these methods are a natural alternative to estimating impulse responses from VARs.
RePEc:cda:wpaper:305 Save to MyIDEAS - Oscar Jorda (2004): Model-Free Impulse Responses
This paper introduces methods for computing impulse response functions that do not require specification and estimation of the unknown dynamic multivariate system itself. ... Therefore, these methods are a natural alternative to estimating impulse responses from VARs.
RePEc:wpa:wuwpma:0403016 Save to MyIDEAS - Oscar Jorda (2004): Model-Free Impulse Responses
This paper introduces methods for computing impulse response functions that do not require specificationand estimation of the unknown dynamic multivariate system itself. ... Therefore, these methods are a natural alternative toestimating impulse responses from VARs.
RePEc:cda:wpaper:87 Save to MyIDEAS - Peter Reusens & Christophe Croux (2015): Real or nominal variables, does it matter for the impulse response?
This paper analyzes impulse response functions of vector autoregression models for variables that are linearly transformed. These impulse responses are equal to the linear transformation of the original impulse responses only if the shocks are equal to the linear transformation of the original shocks.
RePEc:ete:kbiper:485168 Save to MyIDEAS - Hiroyuki Kawakatsu (2022): Local projection variance impulse response
This paper specifies a semiparametric variance impulse response function using realized variances. The news impact and impulse responses are estimated using local projection methods using least squares and external instruments. Compared to impulse responses estimated from parametric GARCH type models, semiparametric local projection responses show less persistence though the estimates are quite noisy.
RePEc:spr:empeco:v:62:y:2022:i:3:d:10.1007_s00181-021-02063-x Save to MyIDEAS - HAFNER, Christian & HERWARTZ, Helmut (2001): Volatility impulse response functions for multivariate GARCH models
We introduce a new concept of impulse response functions tracing the effects of independent shocks on volatility through time. ... Theoretical properties of volatility impulse response functions are derived and compared with conditional moment profiles introduced by Gallant, Rossi and Tauchen (1993) for semi-nonparametric models. In an empirical study of a bivariate foreign exchange rate series we use volatility impulse response functions to compare alternative parametric volatility specifications.
RePEc:cor:louvco:2001039 Save to MyIDEAS - Jörg Breitung & Ralf Brüggemann (2019): Projection estimators for structural impulse responses
In this paper we provide a general framework for linear projection estimators for impulse responses in structural vector autoregressions (SVAR). ... Furthermore, we propose a generalized least squares (GLS) version of the projections that performs similarly to the conventional (iterated) method of estimating impulse responses by inverting the estimated SVAR representation into the MA(∞) representation. Monte Carlo experiments indicate that the proposed OLS projections perform similarly to Jord`a’s (2005) projection estimator but enables us to apply standard inference on the estimated impulse responses. The GLS versions of the projections provide estimates with much smaller standard errors and confidence intervals whenever the horizon h of the impulse responses gets large.
RePEc:knz:dpteco:1905 Save to MyIDEAS - Tom Doan (undated): RATS program to replicate Hafner-Herwartz volatility impulse response functions
Replication file for Hafner and Herwartz(2006), "Volatility impulse responses for multivariate GARCH models: An exchange rate illustration", Journal of International Money and Finance, vol 25, no 5, 719-740.
RePEc:boc:bocode:rtz00183 Save to MyIDEAS