Russell Davidson 的有关 Bootstrap方法的理论与应用（10个pdf）

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Notes on the Bootstrap
byRussell Davidson

GREQAM
Centre de la Vieille Charite
2 rue de la Charite
13002 Marseille, France
Department of Economics
Queen's University
Kingston, Ontario, Canada
K7L 3N6

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Russell Davidson 的有关 Bootstrap方法的理论与应用（10个pdf）
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关键词：Bootstrap方法 Bootstrap Bootstra Davidson Russell PDF 理论 Davidson Russell Bootstrap

BOOTSTRAP TESTS: HOW MANY BOOTSTRAPS?
Russell Davidson James G. MacKinnon

ABSTRACT
In practice, bootstrap tests must use a nite 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 samples, and it necessarily
results in some loss of power. We examine the extent of this power loss and
propose a simple pretest procedure for choosing the number of bootstrap
samples so as to minimize experimental randomness. Simulation experiments
suggest that this procedure will work very well in practice.

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Russell Davidson 的有关 Bootstrap方法的理论与应用（10个pdf）
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Russell Davidson 的有关 Bootstrap方法的理论与应用（10个pdf）
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Improving the Reliability of Bootstrap Tests
by
Russell Davidson

Abstract
We rst propose a procedure for estimating the rejection probabilities for bootstrap
tests in Monte Carlo experiments without actually computing a bootstrap
test for each replication. This procedure is only about twice as expensive (per
replication) as estimating rejection probabilities for asymptotic tests. We then
propose a procedure for computing modi ed bootstrap P values that will often be
more accurate than ordinary ones. This procedure is closely related to the double
bootstrap, but it is far less computationally demanding. Simulations show that
both procedures often work very well.

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Russell Davidson 的有关 Bootstrap方法的理论与应用（10个pdf）
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Bootstrap Methods in Econometrics
by
Russell Davidson

Abstract
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 inference, particularly hypothesis testing, and we also
discuss bootstrap confidence intervals. There are important cases in which bootstrap
inference tends to be more accurate than asymptotic inference. However, it is not
always easy to generate bootstrap samples in a way that makes bootstrap inference
even asymptotically valid.

Bootstrap Inference in a Linear Equation
Estimated by Instrumental Variables
Russell Davidson

Abstract
We study several tests for the coefficient of the single right-hand-side endogenous variable
in a linear equation estimated by instrumental variables. We show that all the
test statistics—Student’s t, Anderson-Rubin, Kleibergen’s K, and likelihood ratio
(LR)—can be written as functions of six random quantities. This leads to a number
of interesting results about the properties of the tests under weak-instrument asymptotics.
We then propose several new procedures for bootstrapping the three non-exact
test statistics and a conditional version of the LR test. These use more efficient estimates
of the parameters of the reduced-form equation than existing procedures.
When the best of these new procedures is used, K and conditional LR have excellent
performance under the null, and LR also performs very well. However, power considerations
suggest that the conditional LR test, bootstrapped using this new procedure
when the sample size is not large, is probably the method of choice.

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Russell Davidson 的有关 Bootstrap方法的理论与应用（10个pdf）
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Russell Davidson 的有关 Bootstrap方法的理论与应用（10个pdf）
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上一贴的内容

Chapter1、Random Number Generators

Chapter 2、Random Numbers from Various Distributions

1.The Exponential, Logistic, and Geometric Distributions

2. The Cauchy Distribution

3. The Gamma Distribution

4. The Poisson Distribution

5. The Chi-squared, Beta, t, and Fisher Distributions

6. The Header File

7. The Makefile for the Full Random Library

这是一本书的前两章，有程序代码

Simulating the Bootstrap Rejection Probability

1. The Bootstrap Discrepancy

2. Basic Setup for Simulation

3. Bootstrap Samples

4. Approximate Estimation of the Bootstrap Discrepancy

5. A Better Approximation

6. The Best Approximatio

141130.pdf (138.37 KB)

2007-7-26 00:16:00 上传

Russell Davidson 的有关 Bootstrap方法的理论与应用（10个pdf）

Master Analyse Economique et Econom´etrie
Simulation and the Bootstrap

法语的

141131.pdf (263.34 KB)

2007-7-26 00:17:00 上传

Russell Davidson 的有关 Bootstrap方法的理论与应用（10个pdf）

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2007-7-26 00:18:00 上传

Russell Davidson 的有关 Bootstrap方法的理论与应用（10个pdf）
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The Power of Bootstrap and Asymptotic Tests
by
Russell Davidson

Abstract
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 under non-null processes described by a Pitman drift. However, complications arise
in the measurement of power. If the test statistic is not an exact pivot, critical values
depend on which data-generating process (DGP) is used to determine the distribution
under the null hypothesis. We propose as the proper choice the DGP which minimizes
the bootstrap discrepancy. We also show that, under an asymptotic independence
condition, the power of both bootstrap and asymptotic tests can be estimated cheaply by
simulation. The theory of the paper and the proposed simulation method are illustrated
by Monte Carlo experiments using the logit model.