Simple techniques for the graphical display of simulation evidence concerning the size and power of hypothesis tests are developed and illustrated. Three types of figures — called P value plots, P… (More)

We provide a theoretical framework in which to study the accuracy of bootstrap P values, which may be based on a parametric or nonparametric bootstrap. In the parametric case, the accuracy of a… (More)

This paper employs response surface regressions based on simulation experiments to calculate asymptotic distribution functions for the Johansen-type likelihood ratio tests for cointegration. These… (More)

In practice, bootstrap tests must use a finite number of bootstrap samples. This means that the outcome of the test will depend on the sequence of random numbers used to generate the bootstrap… (More)

Although it is common to refer to “the bootstrap,” there are actually a great many different bootstrap methods that can be used in econometrics. We emphasize the use of bootstrap methods for… (More)

This paper discusses methods for reducing the bias of consistent estimators that are biased in nite samples. These methods are available whenever the bias function, which relates the bias of the… (More)

This paper provides densities and finite sample critical values for the singleequation error correction statistic for testing cointegration. Graphs and response surfaces summarize extensive Monte… (More)

Bootstrap testing of nonlinear models normally requires at least one nonlinear estimation for every bootstrap sample. We show how to reduce computational costs by performing only a fixed, small… (More)

Two procedures are proposed for estimating the rejection probabilities of bootstrap tests in Monte Carlo experiments without actually computing a bootstrap test for each replication. These procedures… (More)

The astonishing increase in computer performance over the past two decades has made it possible for economists to base many statistical inferences on simulated, or bootstrap, distributions rather… (More)