[Research Seminar 2019.02.08]Impulse-Response Analysis with Proxy VariablesSpeaker : Eul Noh (Ph.D.) University of California, San Diego
This paper suggests an efficient and simple regression-based approach for consistent estimation of dynamic effects of structural shocks in vector autoregressions (VAR) with proxy variables for the shocks. First, we show that given a serially uncorrelated proxy variable correlated only with current structural shock of interest, the existing Proxy Structural VAR (Proxy-SVAR) approach using the proxy as an instrument variable yields an unbiased estimator of the shape of the impulse-response function (IRF) if and only if the proxy does not have any direct forecasting ability in the VAR. Second, we prove that in the linear model, the shape of the IRF can be consistently estimated by adding the current and past values of the proxy variable in the VAR regardless of its direct forecasting ability or measurement error. Third, we show both theoretically and empirically that the formulation in Gertler and Karadi (2015) misestimates the effect of a monetary policy shock. Applying our unrestricted approach to GK’s specification results in a substantially different conclusion from the Proxy-SVAR. Our approach is more efficient than other regression-based methods because the IRF is computed from a regression employing all relevant information from data.