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Gu, Ariel 
ORCID: https://orcid.org/0000-0002-3993-8165 and Yoo, Hong Il
(2019)
Vcemway: A one-stop solution for robust inference with multiway clustering.
Stata Journal, 19 (4).
pp. 900-912.
ISSN 1536-867X
Abstract
Most Stata commands allow cluster(varname) or vce(cluster clustvar) as an option, popularizing the use of standard errors that are robust to oneway clustering. For adjusting standard errors for multiway clustering, there is no solution that is as widely applicable. While several community-contributed packages support multiway clustering, each package is compatible only with a subset of models that Stata’s ever-expanding library of commands allows the researcher to fit. We introduce a command, vcemway, that provides a one-stop solution for multiway clustering. vcemway works with any estimation command that allows cluster(varname) as an option, and it adjusts standard errors, individual significance statistics, and confidence intervals in output tables for multiway clustering in specified dimensions. The covariance matrix used in making this adjustment is stored in e(V), meaning that any subsequent call to postestimation commands that use e(V) as input (for example, test and margins) will also produce results that are robust to multiway clustering.
| Item Type: | Article |
|---|---|
| Additional Information: | Publisher Copyright: © 2019 StataCorp LLC. |
| Uncontrolled Keywords: | boottest,cmgreg,ivreg2,multiway clustering,reghdfe,st0582,two-way clustering,vcemway,mathematics (miscellaneous) ,/dk/atira/pure/subjectarea/asjc/2600/2601 |
| Faculty \ School: | Faculty of Social Sciences > School of Economics |
| UEA Research Groups: | Faculty of Social Sciences > Research Groups > Applied Econometrics And Finance Faculty of Social Sciences > Research Centres > Centre for Competition Policy |
| Related URLs: | |
| Depositing User: | LivePure Connector |
| Date Deposited: | 10 Nov 2022 13:30 |
| Last Modified: | 09 Jan 2024 01:36 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/89760 |
| DOI: | 10.1177/1536867X19893637 |
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