| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/t0327 |
| 来源ID | Technical Working Paper 0327 |
| Robust Inference with Multi-way Clustering | |
| A. Colin Cameron; Jonah B. Gelbach; Douglas L. Miller | |
| 发表日期 | 2006-09-29 |
| 出版年 | 2006 |
| 语种 | 英语 |
| 摘要 | In this paper we propose a new variance estimator for OLS as well as for nonlinear estimators such as logit, probit and GMM, that provcides cluster-robust inference when there is two-way or multi-way clustering that is non-nested. The variance estimator extends the standard cluster-robust variance estimator or sandwich estimator for one-way clustering (e.g. Liang and Zeger (1986), Arellano (1987)) and relies on similar relatively weak distributional assumptions. Our method is easily implemented in statistical packages, such as Stata and SAS, that already offer cluster-robust standard errors when there is one-way clustering. The method is demonstrated by a Monte Carlo analysis for a two-way random effects model; a Monte Carlo analysis of a placebo law that extends the state-year effects example of Bertrand et al. (2004) to two dimensions; and by application to two studies in the empirical public/labor literature where two-way clustering is present. |
| 主题 | Econometrics ; Estimation Methods |
| URL | https://www.nber.org/papers/t0327 |
| 来源智库 | National Bureau of Economic Research (United States) |
| 引用统计 | |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/570203 |
| 推荐引用方式 GB/T 7714 | A. Colin Cameron,Jonah B. Gelbach,Douglas L. Miller. Robust Inference with Multi-way Clustering. 2006. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
| t0327.pdf（364KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。
