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63 results, from 31
  • Refereed essays Web of Science

    An Alternative Bootstrap for Proxy Vector Autoregressions

    We propose a new bootstrap algorithm for inference for impulse responses in structural vector autoregressive models identified with an external proxy variable. Simulations show that the new bootstrap algorithm provides confidence intervals for impulse responses which often have more precise coverage than and similar length to the competing moving-block bootstrap intervals. An empirical example shows ...

    In: Computational Economics 62 (2023), S. 1857–1882 | Martin Bruns, Helmut Lütkepohl
  • Refereed essays Web of Science

    Heteroscedastic Proxy Vector Autoregressions

    In proxy vector autoregressive models, the structural shocks of interest are identified by an instrument. Although heteroscedasticity is occasionally allowed for in inference, it is typically taken for granted that the impact effects of the structural shocks are time-invariant despite the change in their variances. We develop a test for this implicit assumption and present evidence that the assumption ...

    In: Journal of Business & Economic Statistics 40 (2022), 3, S. 1268-1281 | Helmut Lütkepohl, Thore Schlaak
  • Refereed essays Web of Science

    Comparison of Local Projection Estimators for Proxy Vector Autoregressions

    Different local projection (LP) estimators for structural impulse responses of proxy vector autoregressions are reviewed and compared algebraically and with respect to their small sample suitability for inference. Conditions for numerical equivalence and similarities of some estimators are provided. Two generalized least squares (GLS) projection estimators are found to be more accurate than the other ...

    In: Journal of Economic Dynamics & Control 134 (2022), 104277, 17 S. | Martin Bruns, Helmut Lütkepohl
  • Refereed essays Web of Science

    Testing Identification via Heteroskedasticity in Structural Vector Autoregressive Models

    Tests for identification through heteroskedasticity in structural vector autoregressive analysis are developed for models with two volatility states where the time point of volatility change is known. The tests are Wald-type tests for which only the unrestricted model, including the covariance matrices of the two volatility states, has to be estimated. The residuals of the model are assumed to be from ...

    In: The Econometrics Journal 24 (2021), 1, S. 1-22 | Helmut Lütkepohl, Mika Meitz, Aleksei Netšunajev, Pentti Saikkonen
  • Refereed essays Web of Science

    Qualitative versus Quantitative External Information for Proxy Vector Autoregressive Analysis

    A major challenge for proxy vector autoregressive analysis is the construction of a suitable external instrument variable or proxy for identifying a shock of interest. Some authors construct sophisticated proxies that account for the dating and size of the shock while other authors consider simpler versions that use only the dating and signs of particular shocks. It is shown that such qualitative (sign-)proxies ...

    In: Journal of Economic Dynamics & Control 127 (2021), 104118, 17 S. | Lukas Boer, Helmut Lütkepohl
  • Refereed essays Web of Science

    Inference in Partially Identified Heteroskedastic Simultaneous Equations Models

    Identification through heteroskedasticity in heteroskedastic simultaneous equations models (HSEMs) is considered. The possibility that heteroskedasticity identifies structural parameters only partially is explicitly allowed for. The asymptotic properties of the identified parameters are derived. Moreover, tests for identification through heteroskedasticity are developed and their asymptotic distributions ...

    In: Journal of Econometrics 218 (2020), 2, S. 317-345 | Helmut Lütkepohl, George Milunovich, Minxian Yang
  • Refereed essays Web of Science

    Structural Vector Autoregressive Models with More Shocks Than Variables Identified via Heteroskedasticity

    In conventional structural vector autoregressive models it is assumed that there are at most as manystructural shocks as there are variables in the model. It is pointed out that heteroskedasticity can beused to identify more shocks than variables. Results are provided that allow a researcher to assesshow many shocks can be identified from specific forms of heteroskedasticity.

    In: Economics Letters 195 (2020), 109458, 4 S. | Helmut Lütkepohl
  • Refereed essays Web of Science

    Bayesian Inference for Structural Vector Autoregressions Identified by Markov-Switching Heteroskedasticity

    In this study, Bayesian inference is developed for structural vector autoregressive models in which the structural parameters are identified via Markov-switching heteroskedasticity. In such a model, restrictions that are just-identifying in the homoskedastic case, become over-identifying and can be tested. A set of parametric restrictions is derived under which the structural matrix is globally or ...

    In: Journal of Economic Dynamics & Control 113 (2020), 103862 | Helmut Lütkepohl, Tomasz Wozniak
  • Refereed essays Web of Science

    Constructing Joint Confidence Bands for Impulse Response Functions of VAR Models: A Review

    Methods for constructing joint confidence bands for impulse response functions which are commonly used in vector autoregressive analysis are reviewed. While considering separate intervals for each horizon individually still seems to be the most common approach, a substantial number of methods have been proposed for making joint inferences about the complete impulse response paths up to a given horizon. ...

    In: Econometrics and Statistics 13 (2020), S. 69-83 | Helmut Lütkepohl, Anna Staszewska-Bystrova, Peter Winker
  • Refereed essays Web of Science

    Bootstrapping Impulse Responses of Structural Vector Autoregressive Models Identified through GARCH

    Different bootstrap methods and estimation techniques for inference for structural vector autoregressive (SVAR) models identified by generalized autoregressive conditional heteroskedasticity (GARCH) are reviewed and compared in a Monte Carlo study. The bootstrap methods considered are a wild bootstrap, a moving blocks bootstrap and a GARCH residual based bootstrap. Estimation is done by Gaussian maximum ...

    In: Journal of Economic Dynamics & Control 101 (2019), S. 41-61 | Helmut Lütkepohl, Thore Schlaak
63 results, from 31
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