The J test for nonnested regression models often works badly as an asypmtotic test, but it generally works very well when bootstrapped. We provide a theroretical analysis of the J test which explains both of these phenomena. We also propose a modified version of the test which works even better...

Bootstrap tests are tests for which the significance level is calculated by some sort of bootstrap procedure, which may be parametric or nonparametric. We provide a theoretical framework in which to study the size distorsions of bootstrap P values. We show that, in many circumstances, the size...

Most confidence intervals, whether based on asymptotic theory or the bootstrap, are implicitly based on inverting a Wald test. Since Wald test statistics are not invariant under nonlinear reparametrizations of the restrictions they test, confidence intervals based on them are not invariant...

Le test J applique aux modeles de regression non emboites a souvent des performances qui sont mauvaises pour la version asymptotique du test, mais tres bonnes pour la forme bootstrap. On donne une analyse theorique qui explique les deux phenomenes. On propose une version modifiee du test qui,...