Michael D. Giandrea, R. Kornfeld, P. Meyer, Susan G. Powers
The U.S. Bureau of Economic Analysis (BEA) and the U.S. Bureau of Labor Statistics (BLS) use estimates of depreciation rates for structures and equipment to construct estimates of capital stock from data on capital investments. The depreciation rates are based on research by Frank C. Wykoff and Charles R. Hulten from the 1980s. More recent studies by Statistics Canada, from 2007 and 2015, use Canadian data on used asset transactions from Canada’s Annual Capital and Repair Expenditures Survey of establishments. They found faster depreciation rates, especially for structures. Sheharyar Bokhari and David Geltner’s 2019 study of U.S. used asset prices also found faster depreciation rates for structures. To illustrate the potential effects of implementing these estimates from newer studies, we created a concordance to match Canadian to U.S. asset categories. We reestimated BEA capital stock measures and the BLS capital and total factor productivity (TFP) measures using depreciation rates based on the Canadian Annual Capital and Repair Expenditures Survey. Using these faster depreciation rates results in substantially lower estimates of net capital stocks and higher estimates of depreciation in BEA accounts but has minimal effects on growth rates of TFP in the BLS accounts.
{"title":"Alternative capital asset depreciation rates for U.S. capital and total factor productivity measures","authors":"Michael D. Giandrea, R. Kornfeld, P. Meyer, Susan G. Powers","doi":"10.21916/mlr.2022.24","DOIUrl":"https://doi.org/10.21916/mlr.2022.24","url":null,"abstract":"The U.S. Bureau of Economic Analysis (BEA) and the U.S. Bureau of Labor Statistics (BLS) use estimates of depreciation rates for structures and equipment to construct estimates of capital stock from data on capital investments. The depreciation rates are based on research by Frank C. Wykoff and Charles R. Hulten from the 1980s. More recent studies by Statistics Canada, from 2007 and 2015, use Canadian data on used asset transactions from Canada’s Annual Capital and Repair Expenditures Survey of establishments. They found faster depreciation rates, especially for structures. Sheharyar Bokhari and David Geltner’s 2019 study of U.S. used asset prices also found faster depreciation rates for structures. To illustrate the potential effects of implementing these estimates from newer studies, we created a concordance to match Canadian to U.S. asset categories. We reestimated BEA capital stock measures and the BLS capital and total factor productivity (TFP) measures using depreciation rates based on the Canadian Annual Capital and Repair Expenditures Survey. Using these faster depreciation rates results in substantially lower estimates of net capital stocks and higher estimates of depreciation in BEA accounts but has minimal effects on growth rates of TFP in the BLS accounts.","PeriodicalId":47215,"journal":{"name":"Monthly Labor Review","volume":" ","pages":""},"PeriodicalIF":2.6,"publicationDate":"2022-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46136637","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}
Lucy P. Eldridge, Sabrina Wulff Pabilonia, Drake Palmer, Jay Stewart, J. Varghese
{"title":"Improving estimates of hours worked for U.S. productivity measurement","authors":"Lucy P. Eldridge, Sabrina Wulff Pabilonia, Drake Palmer, Jay Stewart, J. Varghese","doi":"10.21916/mlr.2022.27","DOIUrl":"https://doi.org/10.21916/mlr.2022.27","url":null,"abstract":"","PeriodicalId":47215,"journal":{"name":"Monthly Labor Review","volume":" ","pages":""},"PeriodicalIF":2.6,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41537723","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}
Shredding Paper by Michael G. Hillard is an interesting chronicle of the economic and technological history of Maine’s paper industry. It highlights the plight of factory workers with the rise of U.S
Michael G.Hillard的《碎纸》是一部有趣的缅因州造纸工业经济和技术史编年史。它突显了随着美国的崛起，工厂工人的困境
{"title":"Automotive dealerships 2007–19: profit-margin compression and product innovation","authors":"Kevin M. Camp, Michael Havlin, Sara Stanley","doi":"10.21916/mlr.2022.26","DOIUrl":"https://doi.org/10.21916/mlr.2022.26","url":null,"abstract":"Shredding Paper by Michael G. Hillard is an interesting chronicle of the economic and technological history of Maine’s paper industry. It highlights the plight of factory workers with the rise of U.S","PeriodicalId":47215,"journal":{"name":"Monthly Labor Review","volume":" ","pages":""},"PeriodicalIF":2.6,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42108326","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}
Alaska experienced a local recession from March 2015 to April 2018. Falling oil prices combined with the state government’s dependence on oil revenue contributed to job losses throughout the economy. Unemployment did not increase mainly because Alaska’s population is aging rapidly and leaving the labor force through retirement.
{"title":"Oil, budgets, migration, and retirees: Alaska’s 2015–18 recession","authors":"Brent Buxton","doi":"10.21916/mlr.2022.25","DOIUrl":"https://doi.org/10.21916/mlr.2022.25","url":null,"abstract":"Alaska experienced a local recession from March 2015 to April 2018. Falling oil prices combined with the state government’s dependence on oil revenue contributed to job losses throughout the economy. Unemployment did not increase mainly because Alaska’s population is aging rapidly and leaving the labor force through retirement.","PeriodicalId":47215,"journal":{"name":"Monthly Labor Review","volume":" ","pages":""},"PeriodicalIF":2.6,"publicationDate":"2022-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46893009","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 Modeled Wage Estimates (MWE) provide annual estimates of average hourly wages for occupations by job characteristics and within a given geographical location. These estimates are produced by borrowing from the strength and breadth of the Occupational Employment and Wage Statistics (OEWS) and National Compensation Survey (NCS) programs to provide more details on occupational wages than either program provides individually. Job characteristics refer to the attributes of workers within an occupation and include worker bargaining status (union and nonunion), work status (part-time and full-time), basis of pay (incentive-based or time-based), and work level (levels 1–15). In this article, we present experimental estimates calculated by grouping work-level data. Grouped level estimates may help researchers, human resources professionals, jobseekers, and other data users to get a better understanding of how pay varies for entry, intermediate, and experienced work levels.
{"title":"Introducing Modeled Wage Estimates by grouped work levels","authors":"Joana Allamani, M. Hudak, Adam Issan","doi":"10.21916/mlr.2022.23","DOIUrl":"https://doi.org/10.21916/mlr.2022.23","url":null,"abstract":"The Modeled Wage Estimates (MWE) provide annual estimates of average hourly wages for occupations by job characteristics and within a given geographical location. These estimates are produced by borrowing from the strength and breadth of the Occupational Employment and Wage Statistics (OEWS) and National Compensation Survey (NCS) programs to provide more details on occupational wages than either program provides individually. Job characteristics refer to the attributes of workers within an occupation and include worker bargaining status (union and nonunion), work status (part-time and full-time), basis of pay (incentive-based or time-based), and work level (levels 1–15). In this article, we present experimental estimates calculated by grouping work-level data. Grouped level estimates may help researchers, human resources professionals, jobseekers, and other data users to get a better understanding of how pay varies for entry, intermediate, and experienced work levels.","PeriodicalId":47215,"journal":{"name":"Monthly Labor Review","volume":" ","pages":""},"PeriodicalIF":2.6,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47978462","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":"Occupational licensing and interstate migration in the United States","authors":"T. Cooke, M. Ellis, Richard Wright","doi":"10.21916/mlr.2022.22","DOIUrl":"https://doi.org/10.21916/mlr.2022.22","url":null,"abstract":"","PeriodicalId":47215,"journal":{"name":"Monthly Labor Review","volume":"1 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2022-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68368583","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}
Breakthroughs in artificial intelligence (AI) and robotics have led to substantial concern that large-scale job losses are imminent. Selected occupations are often cited as illustrations of technological displacement that is or will become a more general problem, but these discussions are often impressionistic. This article compiles a list of specific occupations cited in the automation literature and examines the occupations’ employment trends since 1999 and projected employment to 2029. There is little support in U.S. Bureau of Labor Statistics data or projections for the idea of a general acceleration of job loss or a structural break with trends pre-dating the AI revolution with respect to the occupations cited as examples. Offsetting factors and other limitations of the automation thesis are discussed.
人工智能(AI)和机器人技术的突破引发了人们对大规模失业迫在眉睫的担忧。某些职业经常被引用为技术取代的例证，这是或将成为一个更普遍的问题，但这些讨论往往是印象主义的。本文编制了自动化文献中引用的特定职业列表，并研究了自1999年以来这些职业的就业趋势以及到2029年的预计就业情况。美国劳工统计局(Bureau of Labor Statistics)的数据或预测几乎没有支持以下观点:失业普遍加速，或与人工智能革命之前的趋势出现结构性突破。讨论了自动化论文的抵消因素和其他限制。
{"title":"Growth trends for selected occupations considered at risk from automation","authors":"M. Handel","doi":"10.21916/mlr.2022.21","DOIUrl":"https://doi.org/10.21916/mlr.2022.21","url":null,"abstract":"Breakthroughs in artificial intelligence (AI) and robotics have led to substantial concern that large-scale job losses are imminent. Selected occupations are often cited as illustrations of technological displacement that is or will become a more general problem, but these discussions are often impressionistic. This article compiles a list of specific occupations cited in the automation literature and examines the occupations’ employment trends since 1999 and projected employment to 2029. There is little support in U.S. Bureau of Labor Statistics data or projections for the idea of a general acceleration of job loss or a structural break with trends pre-dating the AI revolution with respect to the occupations cited as examples. Offsetting factors and other limitations of the automation thesis are discussed.","PeriodicalId":47215,"journal":{"name":"Monthly Labor Review","volume":"38 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2022-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68368502","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}
Matthew S. Dey, Elizabeth Weber Handwerker, David S. Piccone Jr, J. Voorheis
This article uses multiple surveys and data sourced from administrative records to examine trends in wage inequality from 2003 to 2019. Survey evidence shows that wages were growing more unequal from 2003 to 2013 as wages grew faster among high-wage workers than among low-wage workers. However, from 2013 to 2019, the same surveys show substantial wage gains for workers in the second and third deciles of the wage distribution, particularly among material moving workers and health aides. Administrative tax data also show substantial gains in annual wage and salary earnings income for earners in the lower portion of the earnings distribution in the same years. Wage growth among lower wage workers was large enough to reduce overall wage inequality from 2013 to 2019 in Occupational Employment and Wages Survey data. In tax data, wage growth among lower earning workers was large enough to reduce overall earnings inequality from 2010 to 2018. In data from the Current Population Survey, a plateau was found in overall wage inequality—rather than the clear decline found in the other two data sources—in the later years of the economic expansion.
{"title":"Were wages converging during the 2010s expansion?","authors":"Matthew S. Dey, Elizabeth Weber Handwerker, David S. Piccone Jr, J. Voorheis","doi":"10.21916/mlr.2022.19","DOIUrl":"https://doi.org/10.21916/mlr.2022.19","url":null,"abstract":"This article uses multiple surveys and data sourced from administrative records to examine trends in wage inequality from 2003 to 2019. Survey evidence shows that wages were growing more unequal from 2003 to 2013 as wages grew faster among high-wage workers than among low-wage workers. However, from 2013 to 2019, the same surveys show substantial wage gains for workers in the second and third deciles of the wage distribution, particularly among material moving workers and health aides. Administrative tax data also show substantial gains in annual wage and salary earnings income for earners in the lower portion of the earnings distribution in the same years. Wage growth among lower wage workers was large enough to reduce overall wage inequality from 2013 to 2019 in Occupational Employment and Wages Survey data. In tax data, wage growth among lower earning workers was large enough to reduce overall earnings inequality from 2010 to 2018. In data from the Current Population Survey, a plateau was found in overall wage inequality—rather than the clear decline found in the other two data sources—in the later years of the economic expansion.","PeriodicalId":47215,"journal":{"name":"Monthly Labor Review","volume":" ","pages":""},"PeriodicalIF":2.6,"publicationDate":"2022-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47089424","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}
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}
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