Simple Formulas for Standard Errors that Cluster by Both Firm and Time

S. B. Thompson
{"title":"Simple Formulas for Standard Errors that Cluster by Both Firm and Time","authors":"S. B. Thompson","doi":"10.2139/ssrn.914002","DOIUrl":null,"url":null,"abstract":"When estimating finance panel regressions, it is common practice to adjust standard errors for correlation either across firms or across time. These procedures are valid only if the residuals are correlated either across time or across firms, but not across both. This paper shows that it is very easy to calculate standard errors that are robust to simultaneous correlation along two dimensions, such as firms and time. The covariance estimator is equal to the estimator that clusters by firm, plus the estimator that clusters by time, minus the usual heteroskedasticity-robust ordinary least squares (OLS) covariance matrix. Any statistical package with a clustering command can be used to easily calculate these standard errors.","PeriodicalId":437258,"journal":{"name":"Corporate Finance: Capital Structure & Payout Policies","volume":"59 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1420","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Corporate Finance: Capital Structure & Payout Policies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.914002","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1420

Abstract

When estimating finance panel regressions, it is common practice to adjust standard errors for correlation either across firms or across time. These procedures are valid only if the residuals are correlated either across time or across firms, but not across both. This paper shows that it is very easy to calculate standard errors that are robust to simultaneous correlation along two dimensions, such as firms and time. The covariance estimator is equal to the estimator that clusters by firm, plus the estimator that clusters by time, minus the usual heteroskedasticity-robust ordinary least squares (OLS) covariance matrix. Any statistical package with a clustering command can be used to easily calculate these standard errors.
按公司和时间聚集的标准误差的简单公式
在估计财务面板回归时,通常的做法是调整跨公司或跨时间的相关性的标准误差。这些程序只有当残差在时间或公司之间相关时才有效,但在两者之间不相关。本文表明,很容易计算出对企业和时间等两个维度同时相关具有鲁棒性的标准误差。协方差估计量等于按公司聚类的估计量加上按时间聚类的估计量,减去通常的异方差-鲁棒普通最小二乘(OLS)协方差矩阵。任何带有集群命令的统计包都可以用来轻松地计算这些标准误差。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信