Uncertain Short-Run Restrictions and Statistically Identified Structural Vector Autoregressions

Sascha A. Keweloh

Papers from arXiv.org

Abstract: This study proposes a combination of a statistical identification approach with potentially invalid short-run zero restrictions. The estimator shrinks towards imposed restrictions and stops shrinkage when the data provide evidence against a restriction. Simulation results demonstrate how incorporating valid restrictions through the shrinkage approach enhances the accuracy of the statistically identified estimator and how the impact of invalid restrictions decreases with the sample size. The estimator is applied to analyze the interaction between the stock and oil market. The results indicate that incorporating stock market data into the analysis is crucial, as it enables the identification of information shocks, which are shown to be important drivers of the oil price.

Date: 2023-03, Revised 2024-04
New Economics Papers: this item is included in nep-ecm, nep-ene, nep-ets and nep-knm
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Citations: View citations in EconPapers (1)

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