Robust inference in structural VARs with long-run restrictions

Abstract : Long-run restrictions are a very popular method for identifying structural vector autoregressions, but they suffer from weak identi fication when the data is very persistent, i.e., when the highest autoregressive roots are near unity. Near unit roots introduce additional nuisance parameters and make standard weak-instrument-robust methods of inference inapplicable. We develop a method of inference that is robust to both weak identi fication and strong persistence. The method is based on a combination of the Anderson-Rubin test with instruments derived by fi ltering potentially non-stationary variables to make them near stationary. We apply our method to obtain robust con fidence bands on impulse responses in two leading applications in the literature.
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Guillaume Chevillon, Sophocles Mavroeidis, Zhaoguo Zhan. Robust inference in structural VARs with long-run restrictions. 2016. ⟨hal-01459344⟩

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