2024 年 5 月 31 日 CRETA Seminar - Standard Errors for Two-Way Clustering with Serially Correlated Time Effects

訊息標題：

2024 年 5 月 31 日 CRETA Seminar - Standard Errors for Two-Way Clustering with Serially Correlated Time Effects

簡介摘要：

國立臺灣大學計量理論與應用研究中心 (CRETA) 及臺灣經濟計量學會 (TES) 將於 2024 年 5 月 31 日舉辦 CRETA Seminar。相關資訊如下：

 

【 5 月 31 日 CRETA Seminar】

日期：2024 年 5 月 31 日 (週五) 下午 2:00~3:30

地點：國立臺灣大學管理學院二號館 103 教室

講者：

Prof. Yuya Sasaki (Brian and Charlotte Grove Chair & Professor of Economics Department of Economics, Vanderbilt University)

https://sites.google.com/site/yuyasasaki/

 

演講主題：Standard Errors for Two-Way Clustering with Serially Correlated Time Effects

 

講題摘要：We propose improved standard errors and an asymptotic distribution theory for two-way clustered panels. Our proposed estimator and theory allow for arbitrary serial dependence in the common time effects, which is excluded by existing two-way methods, including the popular two-way cluster standard errors of Cameron, Gelbach, and Miller (2011) and the cluster bootstrap of Menzel (2021). Our asymptotic distribution theory is the first which allows for this level of interdependence among the observations. Under weak regularity conditions, we demonstrate that the least squares estimator is asymptotically normal, our proposed variance estimator is consistent, and t-ratios are asymptotically standard normal, permitting conventional inference. The main results extend to two-way fixed-effect models; we argue that two-way clustering is still necessary even if two-way fixed effects are included in estimation. We present simulation evidence that confidence intervals constructed with our proposed standard errors obtain superior coverage performance relative to existing methods. We illustrate the relevance of the proposed method in an empirical application to a standard Fama-French three-factor regression.

 

備註事項：

欲參加CRETA Seminar的朋友們，煩請事先報名。  

報名期限：2024/5/30 (四)  中午 12:00

報名網址：https://docs.google.com/forms/d/1tYyhtXc3iX1JR_DKNStI1zYhSff4i94bs9l0VtDsHhQ/edit

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