normality. Bootstrap inference can be expected to be more reliable, and appropriate bootstrap procedures are proposed. As an … enough for asymptotic and bootstrap inference to be almost identical, but that, in the twenty-first century, the bootstrap …

In an attempt to free bootstrap theory from the shackles of asymptotic considerations, this paper studies the … possibility of justifying, or validating, the bootstrap, not by letting the sample size tend to infinity, but by considering the … sequence of bootstrap P values obtained by iterating the bootstrap. The main idea of the paper is that, if this sequence …

In an attempt to free bootstrap theory from the shackles of asymptotic considerations, this paper studies the … possibility of justifying, or validating, the bootstrap, not by letting the sample size tend to infinity, but by considering the … sequence of bootstrap P values obtained by iterating the bootstrap. The main idea of the paper is that, if this sequence …

normality. Bootstrap inference can be expected to be more reliable, and appropriate bootstrap procedures are proposed. As an … enough for asymptotic and bootstrap inference to be almost identical, but that, in the twenty-first century, the bootstrap …

The bootstrap is a statistical technique used more and more widely in econometrics. While it is capable of yielding …, if observed, help to obtain the best the bootstrap can offer. Bootstrapping always involves setting up a bootstrap data …-generating process (DGP). The main types of bootstrap DGP in current use are discussed, with examples of their use in econometrics. The …

Despite much recent work on the finite-sample properties of estimators and tests for linear regression models with a … regression coefficient, are functions of only six quadratic forms in the two endogenous variables of the model. They are closely … impossible to perform reliable inference near the point at which the limit is ill-defined. Several bootstrap procedures are …

We first propose procedures for estimating the rejection probabilities for bootstrap tests in Monte Carlo experiments … without actually computing a bootstrap test for each replication. These procedures are only about twice as expensive as … estimating rejection probabilities for asymptotic tersts. We then propose procedures for computing modified bootstrap P values …

We introduce the concept of the bootstrap discrepancy, which measures the difference in rejection probabilities between … a bootstrap test based on a given test statistic and that of a (usually infeasible) test based on the true distribution … of the statistic. We show that the bootstrap discrepancy is of the same order of magnitude under the null hypothesis and …