A1044
Title: Asymptotically valid bootstrap inference for proxy SVARs
Authors: Carsten Jentsch - TU Dortmund University (Germany) [presenting]
Kurt Lunsford - Federal Reserve Bank of Cleveland (United States)
Abstract: Proxy structural vector autoregressions identify structural shocks in vector autoregressions with external variables that are correlated with the structural shocks of interest but uncorrelated with all other structural shocks. Asymptotic theory is provided for this identification approach under mild $\alpha$-mixing conditions that cover a large class of uncorrelated, but possibly dependent innovation processes. Consistency of a residual-based moving block bootstrap (MBB) is proven for inference on statistics such as impulse response functions and forecast error variance decompositions. The MBB serves as the basis for constructing confidence intervals when the proxy variables are strongly correlated with the structural shocks of interest. For the case of one proxy variable used to identify one structural shock, it is shown that the MBB can be used to construct confidence sets for normalized impulse responses that are valid regardless of proxy strength based on the inversion of the Anderson and Rubin statistic suggested in a prior study.