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WILD BOOTSTRAP INFERENCE FOR WILDLY DIFFERENT CLUSTER SIZES

Journal of applied econometrics (Chichester, England), 2017-03, Vol.32 (2), p.233-254

2017

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The wild bootstrap for few (treated) clusters

The econometrics journal, 2018-06, Vol.21 (2), p.114-135

2018

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How cluster-robust inference is changing applied econometrics

The Canadian journal of economics, 2019-08, Vol.52 (3), p.851-881

MacKinnon, James G.

2019

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Using large samples in econometrics

Journal of econometrics, 2023-08, Vol.235 (2), p.922-926

MacKinnon, James G.

2023

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Cluster-robust inference: A guide to empirical practice

Journal of econometrics, 2023-02, Vol.232 (2), p.272-299

2023

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Randomization inference for difference-in-differences with few treated clusters

Journal of econometrics, 2020-10, Vol.218 (2), p.435-450

2020

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Bootstrap Methods in Econometrics

The Economic record, 2006-09, Vol.82 (s1), p.S2-S18

MacKINNON, JAMES G.

2006

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Fast and wild: Bootstrap inference in Stata using boottest

The Stata journal, 2019-03, Vol.19 (1), p.4-60

2019

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Numerical distribution functions for unit root and cointegration tests

Journal of applied econometrics (Chichester, England), 1996-11, Vol.11 (6), p.601-618

MacKinnon, James G.

1996

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Asymptotic theory and wild bootstrap inference with clustered errors

Journal of econometrics, 2019-10, Vol.212 (2), p.393-412

2019

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Numerical distribution functions of likelihood ratio tests for cointegration

Journal of applied econometrics (Chichester, England), 1999-09, Vol.14 (5), p.563-577

1999

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Wild Bootstrap and Asymptotic Inference With Multiway Clustering

Journal of business & economic statistics, 2021-03, Vol.39 (2), p.505-519

2021

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Testing for the appropriate level of clustering in linear regression models

Journal of econometrics, 2023-08, Vol.235 (2), p.2027-2056

2023

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Featured Cover

Journal of applied econometrics (Chichester, England), 2023-08, Vol.38 (5), p.n/a

2023

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Fast and reliable jackknife and bootstrap methods for cluster‐robust inference

Journal of applied econometrics (Chichester, England), 2023-08, Vol.38 (5), p.671-694

2023

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Bootstrap tests for overidentification in linear regression models

Econometrics, 2015-12, Vol.3 (4), p.825-863

2015

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Wild Bootstrap Tests for IV Regression

Journal of business & economic statistics, 2010-01, Vol.28 (1), p.128-144

2010

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WILD CLUSTER BOOTSTRAP CONFIDENCE INTERVALS

Actualité économique, 2020-12, Vol.96 (4), p.721-743

MacKinnon, James G.

2020

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The case against JIVE

Journal of applied econometrics (Chichester, England), 2006-09, Vol.21 (6), p.827-833

2006

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NUMERICAL DISTRIBUTION FUNCTIONS OF FRACTIONAL UNIT ROOT AND COINTEGRATION TESTS

Journal of applied econometrics (Chichester, England), 2014-01, Vol.29 (1), p.161-171

2014

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The power of bootstrap and asymptotic tests

Journal of econometrics, 2006-08, Vol.133 (2), p.421-441

2006

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Approximate bias correction in econometrics

Journal of econometrics, 1998-08, Vol.85 (2), p.205-230

1998

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Bootstrap inference in a linear equation estimated by instrumental variables

The econometrics journal, 2008-01, Vol.11 (3), p.443-477

2008

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Wild Cluster Bootstrap Confidence Intervals

Actualité économique, 2015-03, Vol.91 (1-2), p.11-33

MacKinnon, James G.

2015

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Inference with Large Clustered Datasets

Actualité économique, 2016-12, Vol.92 (4), p.649-665

MacKinnon, James G.

2016

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WILD BOOTSTRAP INFERENCE FOR WILDLY DIFFERENT CLUSTER SIZES

The wild bootstrap for few (treated) clusters

How cluster-robust inference is changing applied econometrics

Using large samples in econometrics

Cluster-robust inference: A guide to empirical practice

Randomization inference for difference-in-differences with few treated clusters

Bootstrap Methods in Econometrics

Fast and wild: Bootstrap inference in Stata using boottest

Numerical distribution functions for unit root and cointegration tests

Asymptotic theory and wild bootstrap inference with clustered errors

Numerical distribution functions of likelihood ratio tests for cointegration

Wild Bootstrap and Asymptotic Inference With Multiway Clustering

Testing for the appropriate level of clustering in linear regression models

Featured Cover

Fast and reliable jackknife and bootstrap methods for cluster‐robust inference

Bootstrap tests for overidentification in linear regression models

Wild Bootstrap Tests for IV Regression

WILD CLUSTER BOOTSTRAP CONFIDENCE INTERVALS

The case against JIVE

NUMERICAL DISTRIBUTION FUNCTIONS OF FRACTIONAL UNIT ROOT AND COINTEGRATION TESTS

The power of bootstrap and asymptotic tests

Approximate bias correction in econometrics

Bootstrap inference in a linear equation estimated by instrumental variables

Wild Cluster Bootstrap Confidence Intervals

Inference with Large Clustered Datasets

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