Simulation-based Tests for Regression Models with IID Errors: Some Non-standard Cases

Abstract

There are important situations in which applied workers cannot use standard statistical tables to obtain asymptotic critical values when carrying out tests in regression analysis. In such cases, the test that is being applied will be called a non-standard asymptotic test. The purpose of this chapter is to provide discussions of some non-standard asymptotic tests of relevance to empirical econometrics. In the absence of convenient tabulated reference distributions, simulation methods offer the possibility of making asymptotically valid inferences. The form of the error distribution for the regression model is assumed to be unspecified and nonparametric bootstrap methods will be taken as the source of asymptotic tests and, in some cases, asymptotic refinements.