A generalized method of moments estimator for structural vector autoregressions based on higher moments
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Date
2019-09-11
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Abstract
I propose a generalized method of moments estimator for structural vector
autoregressions with independent and non-Gaussian shocks. The shocks are
identified by exploiting information contained in higher moments of the
data. Extending the standard identification approach, which relies on the
covariance, to the coskewness and cokurtosis allows to identify and
estimate the simultaneous interaction without any further restrictions. I
analyze the finite sample properties of the estimator and apply it to
illustrate the simultaneous interaction between economic activity, oil and
stock prices.
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Keywords
non-gaussian, independence, identifcation, oil prices, stock returns