Advance Layoff Notice Data from the WARN Act

We collect novel and timely data from advance layoff notices filed under the Worker Adjustment and Retraining Notification (WARN) Act. The act requires larger employers to notify affected workers at least 60 days before a potential mass layoff. We assemble WARN data from across the United States, and for many large states our data begin in the 1990s. We aggregate these data into an unbalanced, monthly panel of the state-level number of workers affected by WARN notices, and we update this panel twice a month. We also aggregate this panel to a national-level indicator of job loss (the "WARN factor") using a dynamic factor model.<br> <b><br>Data Collection</b><br>We update the data twice a month by collecting WARN notices from state websites. For many states, we have extended our historical data by using digital archives of the internet and contacting state officials.<br> <br><b>Citation</b><br>To learn more about the data and the dynamic factor model, see:<br>Krolikowski, Pawel M. and Kurt G. Lunsford. 2022. “Advance Layoff Notices and Aggregate Job Loss.” Federal Reserve Bank of Cleveland, Working Paper no. 20-03R. https://doi.org/10.26509/frbc-wp-202003R<b>.<br><br></b><b>File Description</b><br>The file labelled WARNFiles_YYYYMMDD.zip in the main directory contains our most recent data. All data included in this zip file were collected as of the date listed in the file name. Previous vintages of our data appear in the `Archived_Vintages’ folder, with the same naming convention.<br> <br>The zip files contain three files:<br> <br> 1. README.txt <br>2. WARNData_NSA_YYYYMMDD.csv This .csv contains the number of workers affected by WARN notices by state and month. These data are not seasonally adjusted. These data are the input into the dynamic factor model. 3. WARNFactors_YYYYMMDD.csv This .csv contains the output of the dynamic factor model. The output is labeled as follows: WARN Factor: the estimates of the factor from the dynamic factor model. MSE: the estimated mean squared errors of the WARN factor. WARN_hat: the number of workers affected by WARN notices as implied by the WARN factor. WARN_sum: the sum of the number of workers affected by WARN notices from several states that form a balanced panel beginning in January 2006. These states can change every update.<b>Disclaimer</b><br>These data are updated by the authors and are not an official product of the Federal Reserve Bank of Cleveland.<br>

我们从根据《工人调整与再培训通知法案》（Worker Adjustment and Retraining Notification, WARN Act）提交的提前裁员通知中收集新颖且及时的数据。该法案要求大型雇主在潜在大规模裁员前至少60天通知受影响的工人。我们汇总了全美范围内的WARN数据，对于许多大型州而言，数据始于20世纪90年代。我们将这些数据聚合为非平衡月度面板，记录各州层面受WARN通知影响的工人数量，并每月更新该面板两次。同时，我们通过动态因子模型（dynamic factor model）将该面板聚合为国家级失业指标（即“WARN因子”）。<br><b><br>数据收集</b><br>我们通过各州网站收集WARN通知，每月更新数据两次。对于许多州，我们利用互联网数字档案和联系州政府官员扩展历史数据。<br><br><b>引用</b><br>若需了解更多数据及动态因子模型相关信息，请参见：Krolikowski, Pawel M. 与 Kurt G. Lunsford. 2022.《提前裁员通知与总体失业》。克利夫兰联邦储备银行（Federal Reserve Bank of Cleveland）工作论文第20-03R号。https://doi.org/10.26509/frbc-wp-202003R<br><br><b>文件说明</b><br>主目录中名为WARNFiles_YYYYMMDD.zip的文件包含最新数据，所有数据均截至文件名所列日期收集。往期数据版本存于“Archived_Vintages”文件夹，采用相同命名规范。<br><br>压缩文件包含三个文件：<br><br>1. README.txt<br>2. WARNData_NSA_YYYYMMDD.csv：该CSV文件记录各州每月受WARN通知影响的工人数量，未经季节性调整，是动态因子模型的输入数据。<br>3. WARNFactors_YYYYMMDD.csv：该CSV文件包含动态因子模型的输出结果，标签说明如下：<br>WARN因子：动态因子模型的因子估计值；<br>均方误差（Mean Squared Error, MSE）：WARN因子的估计均方误差；<br>WARN_hat：由WARN因子推导的受WARN通知影响的工人数量；<br>WARN_sum：自2006年1月起构成平衡面板的若干州中受WARN通知影响的工人数量总和，这些州可能在每次更新时变化。<br><b>免责声明</b><br>这些数据由作者更新，并非克利夫兰联邦储备银行的官方产品。