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Title: Extensions to IVX methods of inference for return-predictability Authors:  Robert Taylor - University of Essex (United Kingdom) [presenting]
Matei Demetrescu - University of Kiel (Germany)
Paulo Rodrigues - Universidade Nova de Lisboa (Portugal)
Iliyan Georgiev - University of Bologna (Italy)
Abstract: IVX methods have proved particularly valuable in predictive regressions as they allow for possibly strongly persistent and endogenous regressors. We make three contributions. First, we demonstrate that, provided either a suitable bootstrap implementation is employed or heteroscedasticity-consistent standard errors are used, previous IVX-based predictability tests retain asymptotically pivotal inference, regardless of the degree of persistence or endogeneity of the (putative) predictor, under considerably weaker assumptions on the innovations than were required formerly. Second, we develop asymptotically valid bootstrap implementations of the IVX tests under these conditions. Monte Carlo simulations show that the bootstrap methods we propose can deliver considerably more accurate finite-sample inference than the asymptotic implementation of these tests used previously under certain problematic parameter constellations, most notably for their implementation against one-sided alternatives, and where multiplepredictors are included. Third, under the same conditions as we consider for the full sample tests, we show how sub-sample implementations of the IVX approach, coupled with a suitable bootstrap, can be used to develop asymptotically valid one-sided and two-sided tests for the presence of temporary windows of predictability.