Introducing Modeled Wage Estimates by grouped work levels

IF 2.4 4区 经济学 Q2 INDUSTRIAL RELATIONS & LABOR Monthly Labor Review Pub Date : 2022-09-01 DOI:10.21916/mlr.2022.23
Joana Allamani, M. Hudak, Adam Issan
{"title":"Introducing Modeled Wage Estimates by grouped work levels","authors":"Joana Allamani, M. Hudak, Adam Issan","doi":"10.21916/mlr.2022.23","DOIUrl":null,"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":null,"pages":null},"PeriodicalIF":2.4000,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Monthly Labor Review","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.21916/mlr.2022.23","RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"INDUSTRIAL RELATIONS & LABOR","Score":null,"Total":0}
引用次数: 0

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.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
引入按分组工作级别划分的模拟工资估算
模拟工资估计(MWE)提供了按工作特征和给定地理位置的职业的平均小时工资的年度估计。这些估计是通过借鉴职业就业和工资统计(OEWS)和国家薪酬调查(NCS)计划的力量和广度得出的,以提供比任何一个计划单独提供的更多关于职业工资的细节。工作特征是指一个职业中工人的属性,包括工人的谈判地位(工会和非工会)、工作状态(兼职和全职)、工资基础(基于激励或基于时间)和工作水平(1-15级)。在本文中,我们提出了通过分组工作级数据计算的实验估计。分组水平估计可以帮助研究人员、人力资源专业人员、求职者和其他数据用户更好地了解初级、中级和有经验的工作水平的薪酬变化情况。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Monthly Labor Review
Monthly Labor Review INDUSTRIAL RELATIONS & LABOR-
自引率
7.70%
发文量
25
期刊最新文献
ERISA at 50: BLS tracks the evolution of retirement benefits Examining U.S. inflation across households grouped by equivalized income Two hours to the office, two minutes to the kitchen table: trends in local public-transportation expenditures from 2018 to 2021 Introducing Producer Price Index research series based on a geometric-mean formula Unemployment rate inches up during 2023, labor force participation rises
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1