Cluster-robust jackknife and bootstrap inference for binary response models
Year of publication: |
2024
|
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Authors: | MacKinnon, James G. ; Nielsen, Morten Ørregaard ; Webb, Matthew |
Publisher: |
Kingston (Ontario) : Queen's University, Department of Economics |
Subject: | logit model | logistic regression | clustered data | grouped data | cluster-robust variance estimator | CRVE | cluster jackknife | robust inference | wild cluster boot-strap | linearization |
Series: | |
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Type of publication: | Book / Working Paper |
Type of publication (narrower categories): | Working Paper |
Language: | English |
Other identifiers: | 1899407871 [GVK] |
Classification: | C12 - Hypothesis Testing ; C15 - Statistical Simulation Methods; Monte Carlo Methods ; C21 - Cross-Sectional Models; Spatial Models ; C23 - Models with Panel Data |
Source: |
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Cluster-robust jackknife and bootstrap inference for binary response models
MacKinnon, James G., (2024)
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Testing for the appropriate level of clustering in linear regression models
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Cluster-robust inference: A guide to empirical practice
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Fast and reliable jackknife and bootstrap methods for cluster-robust inference
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Cluster-robust inference : a guide to empirical practice
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Fast and wild : bootstrap inference in stata using bottest
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