  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.

Econometrics;Applications;Methodology