A0232
Title: Inference in panel SVARs with cross-sectional dependence of unknown form
Authors: Lennart Empting - University of Duisburg-Essen (Germany)
Saskia Oeztuerk - Georg-August-Universität Göttingen (Germany) [presenting]
Simone Maxand - Europa-Universität Viadrina (Germany)
Konstantin Wagner - Humboldt University Berlin (Germany)
Abstract: Moving-block bootstrap procedures have become a preferred method to determine the sampling uncertainty of vector autoregressive (VAR) model estimation, most prominently visualized as confidence bands around impulse response functions (IRF). These inferential methods are extended for multivariate time series by the cross-section dimension and compile recursive-design moving-block bootstrap procedures for proxy-identified panel VAR models and their structural IRF. The procedures resample blocks of estimated error terms either in \textit{(i)} the temporal, \textit{(ii)} the cross-sectional, or \textit{(iii)} both dimensions jointly. Their asymptotic assessment and a finite-sample Monte-Carlo study both suggest the preferred use of panel-block resampling in both dimensions when confronted with data properties typically found in empirical panel VAR applications.
