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- Cao, Bolong & Sun, Yixiao (2011): Asymptotic distributions of impulse response functions in short panel vector autoregressions
This paper establishes the asymptotic distributions of the impulse response functions in panel vector autoregressions with a fixed time dimension. ... The asymptotic dependence calls for variance correction for the orthogonalized impulse response functions. Simulation results show that the variance correction improves the coverage accuracy of both the asymptotic confidence band and the studentized bootstrap confidence band for the orthogonalized impulse response functions.
RePEc:eee:econom:v:163:y:2011:i:2:p:127-143 Save to MyIDEAS - HAFNER, Christian & HERWARTZ, Helmut (1998): Volatility impulse response functions for multivariate GARCH models
We investigate the structural implications of two alternative models for the response of the conditional (co-)variances to independent shocks. The impulse response analysis, adopted to volatility models, appears to be a convenient methodology to obtain information on the interaction of financial series. We define volatility impulse response functions and provide an empirical analysis for a bivariate exchange rate series. For the analyzed series, the impulse response function of the correlation reveals strong discrepancies between the estimated diagonal and BEKK models.
RePEc:cor:louvco:1998047 Save to MyIDEAS - Gregorio Impavido (2015): SVARSIRF: Stata module to compute structural impulse response function after SVAR
svarsirf calculates the SVAR structural impulse response function (SIRF) and its asymptotic standard errors (SE).
RePEc:boc:bocode:s458060 Save to MyIDEAS - Neville Francis & Michael T. Owyang & Daniel Soques (2023): Impulse Response Functions for Self-Exciting Nonlinear Models
We calculate impulse response functions from regime-switching models where the driving variable can respond to the shock. Our focus is on nonlinear vector autoregressions with a variety of specifications for the transition function used throughout the literature. Using Monte Carlo simulations with different misspecifications, we identify the conditions under which impulse response function estimates exhibit significant bias. Furthermore, we extend the concept of model-average impulse responses to this nonlinear context and demonstrate their robustness to model misspecification.
RePEc:fip:fedlwp:96679 Save to MyIDEAS - Cavicchioli, Maddalena (2023): Impulse response function analysis for Markov switching var models
We exactly derive the regime-dependent impulse response functions for a Markov switching vector autoregression (VAR) model in terms of neat matrix expressions in closed form. ... Using such a representation, the regime-dependent impulse response function analysis can be processed with respect to either an asymmetric discrete shock or to a symmetric continuous shock.
RePEc:eee:ecolet:v:232:y:2023:i:c:s0165176523003828 Save to MyIDEAS - Barbara Rossi (Duke) & Elena Pesavento (Emory) (2004): Small sample confidence intervals for multivariate impulse response functions at long horizons
Existing methods for constructing confidence bands for multivariate impulse response functions depend on auxiliary assumptions on the order of integration of the variables. ... The goal of this paper is to propose a simple method for constructing confidence bands for impulse response functions that are robust to the presence of highly persistent processes. We do so by using alternative approximations based on local-to-unity asymptotic theory and by allowing the lead time of the impulse response function to be a fixed fraction of the sample size.
RePEc:ecm:nawm04:364 Save to MyIDEAS - Rossi, Barbara & Pesavento, Elena (2004): Small Sample Confidence Intervals for Multivariate Impulse Response Functions at Long Horizons
Existing methods for constructing confidence bands for multivariate impulse response functions depend on auxiliary assumptions on the order of integration of the variables. ... The goal of this Paper is to propose a simple method for constructing confidence bands for impulse response functions that is not pointwise and that is robust to the presence of highly persistent processes. The method uses alternative approximations based on local-to-unity asymptotic theory and allows the lead time of the impulse response function to be a fixed fraction of the sample size.
RePEc:cpr:ceprdp:4536 Save to MyIDEAS - Stefan Bruder & Michael Wolf (2017): Balanced bootstrap joint confidence bands for structural impulse response functions
Constructing joint confidence bands for structural impulse response functions based on a VAR model is a difficult task because of the non-linear nature of such functions. We propose new joint confidence bands that cover the entire true structural impulse response function up to a chosen maximum horizon with a prespecified probability (1 − α), at least asymptotically.
RePEc:zur:econwp:246 Save to MyIDEAS - Karamé, F. (2012): An algorithm for generalized impulse-response functions in Markov-switching structural VAR
We transpose the Generalized Impulse-Response Function (GIRF) developed by Koop et al. (1996) to Markov-Switching structural VARs.
RePEc:eee:ecolet:v:117:y:2012:i:1:p:230-234 Save to MyIDEAS - Montes-Rojas Gabriel (2022): Estimating Impulse-Response Functions for Macroeconomic Models using Directional Quantiles
A multivariate vector autoregressive model is used to construct the distribution of the impulse-response functions of macroeconomics shocks. ... The distribution of the responses can then be obtained by using uniformly distributed random vectors.
RePEc:bpj:jtsmet:v:14:y:2022:i:2:p:199-225:n:1 Save to MyIDEAS