Structural vector autoregressions and information in moments beyond the variance

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This dissertation is concerned with the estimation of the simultaneous interaction in non- Gaussian SVAR models using generalized method of moments (GMM) estimators with higher- order moment conditions. The dissertation contributes to the literature by providing identification results using higher-order moment conditions derived from the assumption of independent structural shocks, by proposing modifications to the GMM estimation procedure to improve the small sample performance in the presence of higher-order moment conditions, and by developing a framework to combine traditional restriction based approaches with data-driven identification and estimation approaches.

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Structural vector autoregression, Identification, Non-Gaussian, Independent, GMM

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Vektor-autoregressives Modell, Nichtgaußscher Prozess

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