Labour Incomes in India: A Comparison of Two National Household Surveys.

IF 1 Q3 ECONOMICS Indian Journal of Labour Economics Pub Date : 2023-01-01 Epub Date: 2023-02-25 DOI:10.1007/s41027-023-00427-8
Mrinalini Jha, Amit Basole
{"title":"Labour Incomes in India: A Comparison of Two National Household Surveys.","authors":"Mrinalini Jha, Amit Basole","doi":"10.1007/s41027-023-00427-8","DOIUrl":null,"url":null,"abstract":"<p><p>The COVID-19 pandemic created a need for high-frequency employment and income data. Policy-makers and researchers of developing countries typically have not had access to such data. In India, a new private high-frequency panel dataset has recently emerged as the dataset of choice for analysis of the economic impact of COVID-19. This is the Consumer Pyramids Household Survey (CPHS) conducted by the Centre for Monitoring the Indian Economy (CMIE). But the CPHS has also been criticised for being inadequately representative nationally by missing poor and vulnerable households in its sample. We examine the comparability of monthly labour income estimates for the pre-pandemic year (2018-19) for CPHS and the official Periodic Labour Force Survey (PLFS). Across different methods and assumptions, as well as rural/urban locations, CPHS mean monthly labour earnings are anywhere between 5 percent and 50 percent higher than corresponding PLFS estimates. In addition to the sampling concerns raised in the literature, we point to differences in the way employment and income are captured in the two surveys as possible causes of these differences. While CPHS estimates are always higher, it should also be emphasised that the two surveys agree on some stylised facts regarding the Indian workforce. An individual earning ₹50,000 per month lies in the top 5 percent of the income distribution in India as per both surveys. Second, both PLFS and CPHS show that half the Indian workforce earns below the recommended National Minimum Wage.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s41027-023-00427-8.</p>","PeriodicalId":34915,"journal":{"name":"Indian Journal of Labour Economics","volume":null,"pages":null},"PeriodicalIF":1.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9961298/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Indian Journal of Labour Economics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s41027-023-00427-8","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/2/25 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0

Abstract

The COVID-19 pandemic created a need for high-frequency employment and income data. Policy-makers and researchers of developing countries typically have not had access to such data. In India, a new private high-frequency panel dataset has recently emerged as the dataset of choice for analysis of the economic impact of COVID-19. This is the Consumer Pyramids Household Survey (CPHS) conducted by the Centre for Monitoring the Indian Economy (CMIE). But the CPHS has also been criticised for being inadequately representative nationally by missing poor and vulnerable households in its sample. We examine the comparability of monthly labour income estimates for the pre-pandemic year (2018-19) for CPHS and the official Periodic Labour Force Survey (PLFS). Across different methods and assumptions, as well as rural/urban locations, CPHS mean monthly labour earnings are anywhere between 5 percent and 50 percent higher than corresponding PLFS estimates. In addition to the sampling concerns raised in the literature, we point to differences in the way employment and income are captured in the two surveys as possible causes of these differences. While CPHS estimates are always higher, it should also be emphasised that the two surveys agree on some stylised facts regarding the Indian workforce. An individual earning ₹50,000 per month lies in the top 5 percent of the income distribution in India as per both surveys. Second, both PLFS and CPHS show that half the Indian workforce earns below the recommended National Minimum Wage.

Supplementary information: The online version contains supplementary material available at 10.1007/s41027-023-00427-8.

Abstract Image

Abstract Image

Abstract Image

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
印度的劳动收入:印度的劳动收入:两项全国住户调查的比较》。
COVID-19 大流行需要高频率的就业和收入数据。发展中国家的政策制定者和研究人员通常无法获得此类数据。在印度,最近出现了一个新的私人高频面板数据集,成为分析 COVID-19 经济影响的首选数据集。这就是印度经济监测中心 (CMIE) 开展的消费者金字塔家庭调查 (CPHS)。但 CPHS 也因其样本中缺少贫困和弱势家庭而被批评为缺乏全国代表性。我们研究了 CPHS 和官方定期劳动力调查(PLFS)对大流行前一年(2018-19 年)的月度劳动收入估算的可比性。在不同的方法和假设以及农村/城市地区,CPHS 的平均月劳动收入比相应的 PLFS 估计值高出 5% 到 50%。除了文献中提出的抽样问题外,我们还指出这两项调查在获取就业和收入方式上的差异可能是造成这些差异的原因。虽然 CPHS 的估计值总是较高,但还应强调的是,这两项调查在有关印度劳动力的一些典型事实上是一致的。根据这两项调查,月收入为 50,000 ₹ 的个人属于印度收入分布的前 5%。其次,PLFS 和 CPHS 都显示,一半印度劳动力的收入低于建议的全国最低工资标准:在线版本包含补充材料,可查阅 10.1007/s41027-023-00427-8。
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
Indian Journal of Labour Economics
Indian Journal of Labour Economics Economics, Econometrics and Finance-Economics and Econometrics
CiteScore
3.20
自引率
6.70%
发文量
48
期刊介绍: Indian Journal of Labour Economics (IJLE) is one of the few prominent Journals of its kind from South Asia. It provides eminent economists and academicians an exclusive forum for an analysis and understanding of issues pertaining to labour economics, industrial relations including supply and demand of labour services, personnel economics, distribution of income, unions and collective bargaining, applied and policy issues in labour economics, and labour markets and demographics. The journal includes peer reviewed articles, research notes, sections on promising new theoretical developments, comparative labour market policies or subjects that have the attention of labour economists and labour market students in general, particularly in the context of India and other developing countries.
期刊最新文献
Can Female Political Representation Impact Female Labour Force Participation Rate? A Study across Indian States using Fixed Effect Panel Data Model Archana Aggarwal: Labouring Lives: Industry and Informality in New India Discerning the Long-Term Pace and Patterns of Employment in India Enterprise Informality in India: The Blind Spots in Public Policy Exploring the Informal Sector in Nepal: Performance Trend, Dualism, and Rural-Urban Dynamics
×
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