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  • Search: subject:"Wild cluster bootstrap"
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Year of publication
Subject
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wild cluster bootstrap 44 CRVE 39 clustered data 33 grouped data 28 Bootstrap approach 27 Bootstrap-Verfahren 27 Cluster analysis 26 Clusteranalyse 26 Regional cluster 26 Regionales Cluster 26 cluster-robust variance estimator 22 Estimation theory 18 Schätztheorie 18 robust inference 18 Induktive Statistik 15 Statistical inference 15 difference-in-differences 13 wild bootstrap 13 panel data 12 Clustered data 10 Wild cluster bootstrap 8 DiD 7 Panel 6 Panel study 6 Theorie 6 Theory 6 randomization inference 6 inference 5 Difference-in-differences 4 Edgeworth expansion 4 G8 education reform 4 Instruction time 4 Monte Carlo simulation 4 Monte-Carlo-Simulation 4 placebo laws 4 treatment model 4 Bildungsniveau 3 Bildungsreform 3 Causality analysis 3 Cluster-robust variance estimator 3
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Online availability
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Free 47 Undetermined 6
Type of publication
All
Book / Working Paper 46 Article 8
Type of publication (narrower categories)
All
Working Paper 40 Graue Literatur 23 Non-commercial literature 23 Arbeitspapier 21 Article in journal 7 Aufsatz in Zeitschrift 7 Article 1
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Language
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English 52 Undetermined 2
Author
All
MacKinnon, James G. 46 Webb, Matthew 28 Nielsen, Morten Ørregaard 25 Webb, Matthew D. 6 Djogbenou, Antoine A. 4 Huebener, Mathias 4 Marcus, Jan 4 Behncke, Stefanie 3 Djogbenou, Antoine 2 Roodman, David Malin 2 Nielsen, Morten Ørregard 1
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Institution
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Economics Department, Queen's University 2 Institute for the Study of Labor (IZA) 1 School of Economics and Political Science, Universität St. Gallen 1
Published in...
All
Queen's Economics Department working paper 18 Queen's Economics Department Working Paper 9 Queen’s Economics Department Working Paper 9 Journal of econometrics 4 CREATES research paper 3 IZA Discussion Papers 2 Working Papers / Economics Department, Queen's University 2 Economics of Education Review 1 Economics of education review 1 Journal of applied econometrics 1 Journal of business & economic statistics : JBES ; a publication of the American Statistical Association 1 University of St. Gallen Department of Economics working paper series 2009 1
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Source
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ECONIS (ZBW) 30 EconStor 20 RePEc 4
Showing 41 - 50 of 54
Cover Image
Difference-in-differences inference with few treated clusters
MacKinnon, James G.; Webb, Matthew D. - 2016
variants of the wild cluster bootstrap can over-reject or under-reject severely, and that procedures based on randomization …
Persistent link: https://www.econbiz.de/10011583198
Saved in:
Cover Image
The subcluster wild bootstrap for few (treated) clusters
MacKinnon, James G.; Webb, Matthew D. - 2016
cluster bootstrap fails dramatically when the number of treated clusters is very small. We propose a family of new procedures …Inference based on cluster-robust standard errors is known to fail when the number of clusters is small, and the wild …
Persistent link: https://www.econbiz.de/10011583207
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Cover Image
Inference with large clustered datasets
MacKinnon, James G. - 2016
Inference using large datasets is not nearly as straightforward as conventional econometric theory suggests when the disturbances are clustered, even with very small intra-cluster correlations. The information contained in such a dataset grows much more slowly with the sample size than it would...
Persistent link: https://www.econbiz.de/10011583208
Saved in:
Cover Image
Difference-in-differences inference with few treated clusters
MacKinnon, James G.; Webb, Matthew - 2016
variants of the wild cluster bootstrap can over-reject or under-reject severely, and that procedures based on randomization …
Persistent link: https://www.econbiz.de/10011428007
Saved in:
Cover Image
The subcluster wild bootstrap for few (treated) clusters
MacKinnon, James G.; Webb, Matthew - 2016
cluster bootstrap fails dramatically when the number of treated clusters is very small. We propose a family of new procedures …Inference based on cluster-robust standard errors is known to fail when the number of clusters is small, and the wild …
Persistent link: https://www.econbiz.de/10011528395
Saved in:
Cover Image
Inference with large clustered datasets
MacKinnon, James G. - 2016
Inference using large datasets is not nearly as straightforward as conventional econometric theory suggests when the disturbances are clustered, even with very small intra-cluster correlations. The information contained in such a dataset grows much more slowly with the sample size than it would...
Persistent link: https://www.econbiz.de/10011528432
Saved in:
Cover Image
Randomization inference for difference-in-differences with few treated clusters
MacKinnon, James G.; Webb, Matthew - In: Journal of econometrics 218 (2020) 2, pp. 435-450
Persistent link: https://www.econbiz.de/10012483166
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Cover Image
Wild Bootstrap Inference for Wildly Different Cluster Sizes
MacKinnon, James G.; Webb, Matthew D. - Economics Department, Queen's University - 2015
critical values based on the wild cluster bootstrap performs much better. However, this procedure fails when a small number of …
Persistent link: https://www.econbiz.de/10011185158
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Asymptotic theory and wild bootstrap inference with clustered errors
Djogbenou, Antoine A.; MacKinnon, James G.; Nielsen, … - In: Journal of econometrics 212 (2019) 2, pp. 393-412
Persistent link: https://www.econbiz.de/10012304028
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Cover Image
Reworking Wild Bootstrap Based Inference for Clustered Errors
Webb, Matthew D. - Economics Department, Queen's University - 2014
few clusters, the wild cluster bootstrap results in p-values that are not point identified. I suggest two alternative wild …
Persistent link: https://www.econbiz.de/10010961655
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