CONSISTENT SIGNIFICANCE TESTING FOR NONPARAMETRIC REGRESSION

This article presents a framework for individual and joint tests of si gnificance employing nonparametric estimation procedures. The proposed test is based on nonparametric estimates of partial derivatives, is r obust to functional misspecification for general classes of models, an d employs nested pivotal bootstrapping procedures. Two simulations and one application are considered to examine size and power relative to misspecified parametric models, and to test for the linear unpredictab ility of exchange-rate movements for G7 currencies.