Abstract :
Weintroduce block bootstrap techniques that are (first order) valid in recursive
estimation frameworks. Thereafter, we present two examples where predictive
accuracy tests are made operational using our new bootstrap procedures. In one
application, we outline a consistent test for out-of-sample nonlinear Granger
causality, and in the other we outline a test for selecting among multiple alternative
forecasting models, all of which are possibly misspecified. In a Monte
Carlo investigation, we compare the finite sample properties of our block bootstrap
procedures with the parametric bootstrap due to Kilian (Journal of Applied
Econometrics 14 (1999), 491–510), within the context of encompassing and predictive
accuracy tests. In the empirical illustration, it is found that unemployment
has nonlinear marginal predictive content for inflation.
