A Misspecification-Robust Impulse Response Estimator

Abstract

This paper proposes an alternative methodology to estimating impulse response function. The proposed method does not impose parametric restrictions on the estimated impulse response function as the conventional method does. Instead, the impulse responses are estimated by regressing the series of interest on the residuals obtained from prior-stage “long autoregression”. Our Monte Carlo simulations demonstrate that the proposed estimator is capable of capturing the shapes of a wide range of impulse response functions without requiring that a correctly specified model be used in estimating the innovations. On the other hand, the inference under the conventional impulse response estimator can be quite misleading if the estimation models are misspecified. The advantage of the proposed impulse response estimator over the conventional one is most relevant when the true impulse response function exhibits rich dynamics, but the size of the sample proscribes the use of large-order estimation models.