The paper investigates the usefulness of bootstrap methods for small s
ample inference in cointegrating regression models. It discusses the s
tandard bootstrap, the recursive bootstrap, the moving block bootstrap
and the stationary bootstrap methods. Some guidelines for bootstrap d
ata generation and test statistics to consider are provided and some s
imulation evidence presented suggests that the bootstrap methods, when
properly implemented, can provide significant improvement over asympt
otic inference. (C) 1997 Elsevier Science S.A.