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《工人调整和再培训通知法案》（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。我们汇集了美国各地的WARN数据，对于许多大型州，我们的数据始于20世纪90年代。我们将这些数据汇总为州级WARN通知受影响工人数量的非平衡月度面板数据，并每月更新两次该面板。我们还使用动态因子模型（dynamic factor model）将该面板汇总为国家级失业指标（即‘WARN因子’）。<br> <b><br>数据收集</b><br>我们通过从各州网站收集WARN通知，每月更新两次数据。对于许多州，我们通过使用互联网数字档案和联系州政府官员来扩展历史数据。<br> <br><b>引用</b><br>如需了解更多关于数据和动态因子模型的信息，请参阅：Krolikowski, Pawel M. 与 Kurt G. Lunsford. 2022. 《提前裁员通知与总失业》. 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<b>.<br><br></b><b>文件描述</b><br>主目录中名为WARNFiles_YYYYMMDD.zip的文件包含我们最新的数据。此压缩文件中的所有数据均截至文件名中列出的日期收集。我们数据的往期版本存放在‘Archived_Vintages’文件夹中，采用相同的命名规范。<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文件包含各州每月受WARN通知影响的工人数量。这些数据未经季节性调整，是动态因子模型的输入数据。3. WARNFactors_YYYYMMDD.csv 该.csv文件包含动态因子模型的输出结果。输出结果标注如下：WARN Factor：动态因子模型得出的因子估计值；MSE：WARN因子的估计均方误差；WARN_hat：由WARN因子推导的受WARN通知影响的工人数量；WARN_sum：自2006年1月起构成平衡面板的若干州受WARN通知影响的工人数量之和，这些州可能在每次更新时发生变化。<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。