Bootstrap Tests for Regression Models

Modern personal computers are now so powerful that they can be used to carry out simulation-based statistical investigations without involving long delays or the need to access high levels of equipment. When carrying out econometric analyses, the routine use of computer-based methods offers a valuable alternative to the standard approach in which approximations are based upon what happens as the sample size grows without limit. Applied work has to be based upon a finite number of observations. Computationally intensive techniques and, in particular, bootstrap methods provide ways to improve the finite-sample performance of well-known tests. Bootstrap tests can also be employed when conventional theory does not lead to test statistics that can be compared with critical values from some standard distribution. This book uses the familiar linear regression model as a framework for introducing simulation-based tests to applied workers, students and others who carry out empirical econometric analyses.