An Alternative Bootstrap for Proxy Vector Autoregressions

Abstract

Abstract We propose a new bootstrap algorithm for inference for impulse responses in structural vector autoregressive models identified with an external proxy variable. Simulations show that the new bootstrap algorithm provides confidence intervals for impulse responses which often have more precise coverage than and similar length to the competing moving-block bootstrap intervals. An empirical example shows how the new bootstrap algorithm can be applied in the context of identifying monetary policy shocks.

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