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Inference for Impulse Responses under Model Uncertainty

Lenard Lieb () and Stephan Smeekes ()

Papers from arXiv.org

Abstract: In many macroeconomic applications, confidence intervals for impulse responses are constructed by estimating VAR models in levels - ignoring cointegration rank uncertainty. We investigate the consequences of ignoring this uncertainty. We adapt several methods for handling model uncertainty and highlight their shortcomings. We propose a new method - Weighted-Inference-by-Model-Plausibility (WIMP) - that takes rank uncertainty into account in a data-driven way. In simulations the WIMP outperforms all other methods considered, delivering intervals that are robust to rank uncertainty, yet not overly conservative. We also study potential ramifications of rank uncertainty on applied macroeconomic analysis by re-assessing the effects of fiscal policy shocks.

Date: 2017-09, Revised 2019-10
New Economics Papers: this item is included in nep-ecm
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Working Paper: Inference for Impulse Responses under Model Uncertainty (2017) Downloads
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