We examine the use of noncompete agreements (NCAs) and their relationship with wage bargaining and wage outcomes using new data from the National Longitudinal Survey of Youth 1997. NCAs cover 18 percent of the workers in our sample, and adoption patterns are broadly consistent with prior research. The NCA–wage correlation is positive and highly sensitive to controls for demographics and job characteristics, suggesting selection into NCAs causes positive bias in the estimates. While it is not obvious what the baseline level of the NCA–wage differential is, some heterogeneous effects are more stable: the NCA–wage differential is lower for workers who do not bargain over wages, have less education, have lower ability, or live in a state that enforces NCAs. Notably, wage bargaining—which is only marginally more likely with NCAs in our most saturated model—does not explain the heterogeneous effects across subgroups. We discuss these findings in light of competing theories of the social value of NCAs.
{"title":"Noncompete agreements, bargaining, and wages: evidence from the National Longitudinal Survey of Youth 1997","authors":"D. Rothstein, Evan Starr","doi":"10.21916/mlr.2022.18","DOIUrl":"https://doi.org/10.21916/mlr.2022.18","url":null,"abstract":"We examine the use of noncompete agreements (NCAs) and their relationship with wage bargaining and wage outcomes using new data from the National Longitudinal Survey of Youth 1997. NCAs cover 18 percent of the workers in our sample, and adoption patterns are broadly consistent with prior research. The NCA–wage correlation is positive and highly sensitive to controls for demographics and job characteristics, suggesting selection into NCAs causes positive bias in the estimates. While it is not obvious what the baseline level of the NCA–wage differential is, some heterogeneous effects are more stable: the NCA–wage differential is lower for workers who do not bargain over wages, have less education, have lower ability, or live in a state that enforces NCAs. Notably, wage bargaining—which is only marginally more likely with NCAs in our most saturated model—does not explain the heterogeneous effects across subgroups. We discuss these findings in light of competing theories of the social value of NCAs.","PeriodicalId":47215,"journal":{"name":"Monthly Labor Review","volume":" ","pages":""},"PeriodicalIF":2.6,"publicationDate":"2022-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48703753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Estimates from the Job Openings and Labor Turnover Survey (JOLTS) highlighted large increases in job openings and quits throughout 2021. Job openings reached a series high in December 2021 of 11.4 million, and quits reached a series high in November of 4.5 million. By contrast, layoffs and discharges trended lower throughout 2021, reaching a series low of 1.3 million in December. The series lows followed the large increase in layoffs and discharges that occurred at the onset of the COVID-19 pandemic, when this measure reached a series high of 13.0 million in March 2020. The movement in these JOLTS estimates signaled a stronger demand for labor in 2021, following the February–April 2020 pandemic-induced recession.
{"title":"Job openings and quits reach record highs in 2021, layoffs and discharges fall to record lows","authors":"Rick Penn, Eric Nezamis","doi":"10.21916/mlr.2022.17","DOIUrl":"https://doi.org/10.21916/mlr.2022.17","url":null,"abstract":"Estimates from the Job Openings and Labor Turnover Survey (JOLTS) highlighted large increases in job openings and quits throughout 2021. Job openings reached a series high in December 2021 of 11.4 million, and quits reached a series high in November of 4.5 million. By contrast, layoffs and discharges trended lower throughout 2021, reaching a series low of 1.3 million in December. The series lows followed the large increase in layoffs and discharges that occurred at the onset of the COVID-19 pandemic, when this measure reached a series high of 13.0 million in March 2020. The movement in these JOLTS estimates signaled a stronger demand for labor in 2021, following the February–April 2020 pandemic-induced recession.","PeriodicalId":47215,"journal":{"name":"Monthly Labor Review","volume":" ","pages":""},"PeriodicalIF":2.6,"publicationDate":"2022-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47767055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Roxanna Edwards, Lawrence S. Essien, Michael Daniel Levinstein
In summary, major employment and unemployment measures from the CPS continued to show improvement in 2021. The national unemployment rate trended down in each quarter of 2021, reaching 4.2 percent by the end of the year. The jobless rate decreased for men and women, as well as for all major race and ethnicity groups. The unemployment rate decreased among all occupations, with the sharpest decline in service occupations. The employment-population ratio increased by 1.8 percentage points, to 59.2 percent in the fourth quarter of 2021, while the labor force participation rate improved at a much slower pace, rising by 0.3 percentage point to reach 61.8 percent by the end of the year. The level of self-employment in nonagricultural industries increased throughout 2021. The percentage of people who teleworked because of the COVID-19 pandemic declined throughout 2021 and ended the year at 11.1 percent.
{"title":"U.S. labor market shows improvement in 2021, but the COVID-19 pandemic continues to weigh on the economy","authors":"Roxanna Edwards, Lawrence S. Essien, Michael Daniel Levinstein","doi":"10.21916/mlr.2022.16","DOIUrl":"https://doi.org/10.21916/mlr.2022.16","url":null,"abstract":"In summary, major employment and unemployment measures from the CPS continued to show improvement in 2021. The national unemployment rate trended down in each quarter of 2021, reaching 4.2 percent by the end of the year. The jobless rate decreased for men and women, as well as for all major race and ethnicity groups. The unemployment rate decreased among all occupations, with the sharpest decline in service occupations. The employment-population ratio increased by 1.8 percentage points, to 59.2 percent in the fourth quarter of 2021, while the labor force participation rate improved at a much slower pace, rising by 0.3 percentage point to reach 61.8 percent by the end of the year. The level of self-employment in nonagricultural industries increased throughout 2021. The percentage of people who teleworked because of the COVID-19 pandemic declined throughout 2021 and ended the year at 11.1 percent.","PeriodicalId":47215,"journal":{"name":"Monthly Labor Review","volume":" ","pages":""},"PeriodicalIF":2.6,"publicationDate":"2022-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49400960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Total nonfarm employment in the United States continued to recover in 2021, with some industries fully recovering and subsequently expanding amid the coronavirus disease 2019 pandemic. The leisure and hospitality industry and the professional and business services industry led the widespread employment gains over the year.
{"title":"Employment recovery continues in 2021, with some industries reaching or exceeding their prepandemic employment levels","authors":"M. Ramos","doi":"10.21916/mlr.2022.15","DOIUrl":"https://doi.org/10.21916/mlr.2022.15","url":null,"abstract":"Total nonfarm employment in the United States continued to recover in 2021, with some industries fully recovering and subsequently expanding amid the coronavirus disease 2019 pandemic. The leisure and hospitality industry and the professional and business services industry led the widespread employment gains over the year.","PeriodicalId":47215,"journal":{"name":"Monthly Labor Review","volume":" ","pages":""},"PeriodicalIF":2.6,"publicationDate":"2022-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45392925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
For its seasonally adjusted data, the Bureau of Labor Statistics (BLS) seeks to remove all fluctuations that are caused by the yearly cycle of seasons. The coronavirus 2019 pandemic posed a challenge to this task, because its effect was strong, across the entire economy, and lasted for at least several months. To ensure that the effects of the pandemic were not being incorporated into the seasonal adjustment factors, the Current Employment Statistics program took additional actions such as splitting the seasonal adjustment into two runs (prepandemic and postpandemic) and incorporating additional types of outliers into its models.
{"title":"The challenges of seasonal adjustment for the Current Employment Statistics survey during the COVID-19 pandemic","authors":"Nicole Hudson, Jeannine Jeannine, J. Kropf","doi":"10.21916/mlr.2022.14","DOIUrl":"https://doi.org/10.21916/mlr.2022.14","url":null,"abstract":"For its seasonally adjusted data, the Bureau of Labor Statistics (BLS) seeks to remove all fluctuations that are caused by the yearly cycle of seasons. The coronavirus 2019 pandemic posed a challenge to this task, because its effect was strong, across the entire economy, and lasted for at least several months. To ensure that the effects of the pandemic were not being incorporated into the seasonal adjustment factors, the Current Employment Statistics program took additional actions such as splitting the seasonal adjustment into two runs (prepandemic and postpandemic) and incorporating additional types of outliers into its models.","PeriodicalId":47215,"journal":{"name":"Monthly Labor Review","volume":" ","pages":""},"PeriodicalIF":2.6,"publicationDate":"2022-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47316588","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Blake Hoarty, Steven M. Muri, Daniel J. Pallotta, Marie Rogers, Jonathan C. Weinhagen, Jeffrey S. Wilson
The U.S. Bureau of Labor Statistics publishes seasonally adjusted Consumer Price Index (CPI) and Producer Price Index (PPI) data monthly. Seasonal adjustment removes within-year seasonal patterns from data. To seasonally adjust data and estimate seasonal patterns of time series, the CPI and PPI use a filter-based approach that employs moving averages of historical data. In 2020, many PPIs and CPIs experienced extreme movements because of the coronavirus disease 2019 (COVID-19) pandemic. For example, the PPI and CPI for gasoline decreased 53.0 percent and 16.5 percent in April 2020, respectively. Because the CPI and PPI use historical data to estimate seasonal patterns, the extreme price movements in 2020 could have adversely affected the capability of the two price programs to accurately estimate seasonally adjusted data. This article explains how the CPI and PPI mitigated the effects of the COVID-19 pandemic on their seasonally adjusted price indexes. Mitigation steps included identifying price indexes whose movements were affected by the pandemic, estimating time series models to quantify these effects, and removing pandemic-related price movements from the data before estimating seasonal patterns.
{"title":"PPI and CPI seasonal adjustment during the COVID-19 pandemic","authors":"Blake Hoarty, Steven M. Muri, Daniel J. Pallotta, Marie Rogers, Jonathan C. Weinhagen, Jeffrey S. Wilson","doi":"10.21916/mlr.2022.13","DOIUrl":"https://doi.org/10.21916/mlr.2022.13","url":null,"abstract":"The U.S. Bureau of Labor Statistics publishes seasonally adjusted Consumer Price Index (CPI) and Producer Price Index (PPI) data monthly. Seasonal adjustment removes within-year seasonal patterns from data. To seasonally adjust data and estimate seasonal patterns of time series, the CPI and PPI use a filter-based approach that employs moving averages of historical data. In 2020, many PPIs and CPIs experienced extreme movements because of the coronavirus disease 2019 (COVID-19) pandemic. For example, the PPI and CPI for gasoline decreased 53.0 percent and 16.5 percent in April 2020, respectively. Because the CPI and PPI use historical data to estimate seasonal patterns, the extreme price movements in 2020 could have adversely affected the capability of the two price programs to accurately estimate seasonally adjusted data. This article explains how the CPI and PPI mitigated the effects of the COVID-19 pandemic on their seasonally adjusted price indexes. Mitigation steps included identifying price indexes whose movements were affected by the pandemic, estimating time series models to quantify these effects, and removing pandemic-related price movements from the data before estimating seasonal patterns.","PeriodicalId":47215,"journal":{"name":"Monthly Labor Review","volume":" ","pages":""},"PeriodicalIF":2.6,"publicationDate":"2022-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42346761","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"CPI outlet samples from the CE: a new life for the Point-of-Purchase Survey","authors":"Barbieri Greg, A. Stockburger","doi":"10.21916/mlr.2022.11","DOIUrl":"https://doi.org/10.21916/mlr.2022.11","url":null,"abstract":"","PeriodicalId":47215,"journal":{"name":"Monthly Labor Review","volume":" ","pages":""},"PeriodicalIF":2.6,"publicationDate":"2022-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44043205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kendra Asher, J. Glaser, P. Meyer, Jay Stewart, J. Varghese
{"title":"Revisions to BLS quarterly labor productivity estimates: How large are they?","authors":"Kendra Asher, J. Glaser, P. Meyer, Jay Stewart, J. Varghese","doi":"10.21916/mlr.2022.10","DOIUrl":"https://doi.org/10.21916/mlr.2022.10","url":null,"abstract":"","PeriodicalId":47215,"journal":{"name":"Monthly Labor Review","volume":" ","pages":""},"PeriodicalIF":2.6,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49134227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The U.S. Bureau of Labor Statistics publishes eight diffusion index series that measure the dispersion of employment change across either all 50 states and the District of Columbia or 389 metropolitan statistical areas. These data provide a tool for analysis of employment changes and additional information about the labor market. This article explains how the diffusion indexes are calculated, examines the differences between the indexes, and describes how the data are interpreted and how the data respond during economic turning points and the coronavirus disease 2019 pandemic.
美国劳工统计局(Bureau of Labor Statistics)发布了8个扩散指数系列，衡量全美50个州、哥伦比亚特区或389个大都市统计区就业变化的分散程度。这些数据为分析就业变化提供了工具，并提供了有关劳动力市场的额外信息。本文解释了扩散指数的计算方法，分析了指数之间的差异，并描述了如何解释数据以及数据在经济拐点和2019年冠状病毒病大流行期间的反应。
{"title":"Diffusion indexes of state and metropolitan area employment changes","authors":"TJ Lepoutre","doi":"10.21916/mlr.2022.9","DOIUrl":"https://doi.org/10.21916/mlr.2022.9","url":null,"abstract":"The U.S. Bureau of Labor Statistics publishes eight diffusion index series that measure the dispersion of employment change across either all 50 states and the District of Columbia or 389 metropolitan statistical areas. These data provide a tool for analysis of employment changes and additional information about the labor market. This article explains how the diffusion indexes are calculated, examines the differences between the indexes, and describes how the data are interpreted and how the data respond during economic turning points and the coronavirus disease 2019 pandemic.","PeriodicalId":47215,"journal":{"name":"Monthly Labor Review","volume":" ","pages":""},"PeriodicalIF":2.6,"publicationDate":"2022-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47969404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Using new data from the 2021 Business Response Survey, a large, nationally representative survey of U.S. private sector businesses, this article presents unique estimates of telework patterns observed during the coronavirus disease 2019 (COVID-19) pandemic. We find that, between July and September 2021, 13 percent of all U.S. private sector jobs involved teleworking full time and 9 percent involved teleworking some of the time. Telework was less common in establishments that increased base wages during the pandemic. The share of establishments that increased telework was larger among establishments that started offering flexible work hours or compressed work schedules after the pandemic hit. Telework was also associated with reductions in workplace square footage and relocation. Within each industry sector, low-paying establishments had a smaller share of jobs that involved telework.
{"title":"Telework during the COVID-19 pandemic: estimates using the 2021 Business Response Survey","authors":"Michaela Dalton, J. Groen","doi":"10.21916/mlr.2022.8","DOIUrl":"https://doi.org/10.21916/mlr.2022.8","url":null,"abstract":"Using new data from the 2021 Business Response Survey, a large, nationally representative survey of U.S. private sector businesses, this article presents unique estimates of telework patterns observed during the coronavirus disease 2019 (COVID-19) pandemic. We find that, between July and September 2021, 13 percent of all U.S. private sector jobs involved teleworking full time and 9 percent involved teleworking some of the time. Telework was less common in establishments that increased base wages during the pandemic. The share of establishments that increased telework was larger among establishments that started offering flexible work hours or compressed work schedules after the pandemic hit. Telework was also associated with reductions in workplace square footage and relocation. Within each industry sector, low-paying establishments had a smaller share of jobs that involved telework.","PeriodicalId":47215,"journal":{"name":"Monthly Labor Review","volume":" ","pages":""},"PeriodicalIF":2.6,"publicationDate":"2022-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46380358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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