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Inference with Few Heterogeneous Clusters

Author(s): Ibragimov, Rustam; Mueller, Ulrich K

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dc.contributor.authorIbragimov, Rustam-
dc.contributor.authorMueller, Ulrich K-
dc.date.accessioned2019-12-04T19:07:56Z-
dc.date.available2019-12-04T19:07:56Z-
dc.date.issued2016-03-04en_US
dc.identifier.citationIbragimov, Rustam, Mueller, Ulrich K. (2016). Inference with Few Heterogeneous Clusters. REVIEW OF ECONOMICS AND STATISTICS, 98 (1), 83 - 96. doi:10.1162/REST_a_00545en_US
dc.identifier.issn0034-6535-
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/pr1kj12-
dc.description.abstractSuppose estimating a model on each of a small number of potentially heterogeneous clusters yields approximately independent, unbiased, and Gaussian parameter estimators. We make two contributions in this setup. First, we show how to compare a scalar parameter of interest between treatment and control units using a two-sample t-statistic, extending previous results for the one-sample t-statistic. Second, we develop a test for the appropriate level of clustering; it tests the null hypothesis that clustered standard errors from a much finer partition are correct. We illustrate the approach by revisiting empirical studies involving clustered, time series, and spatially correlated data.en_US
dc.format.extent83 - 96en_US
dc.language.isoenen_US
dc.relation.ispartofREVIEW OF ECONOMICS AND STATISTICSen_US
dc.rightsFinal published version. Article is made available in OAR by the publisher's permission or policy.en_US
dc.titleInference with Few Heterogeneous Clustersen_US
dc.typeJournal Articleen_US
dc.identifier.doidoi:10.1162/REST_a_00545-
dc.identifier.eissn1530-9142-
pu.type.symplectichttp://www.symplectic.co.uk/publications/atom-terms/1.0/journal-articleen_US

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