{"title":"Estimating Earnings Losses of Migrant Workers Due to COVID-19.","authors":"Manolo I Abella, S K Sasikumar","doi":"10.1007/s41027-020-00281-y","DOIUrl":null,"url":null,"abstract":"<p><p>While the wide-ranging impact of COVID-19 on incomes and livelihoods of people around the world will take some time to become known and understood, it is already clear that those who are in manual, mostly low-wage, occupations are among the worst-hit workers. This paper uses data from a sample survey of migrant workers to come up with useful parameters for estimating the potential losses from possible retrenchment of migrant workers due to the pandemic. The paper employs a simple estimation model using parameters derived from data collected from a KNOMAD-ILO survey of low-skilled migrant workers in the India-Saudi Arabia migration corridor, conducted during 2016-2017. An important finding is that the aggregate losses that low-skilled Indian workers in Saudi Arabia are likely to incur due to COVID-19-related retrenchment may be as high as 21% of their expected earnings. Adding recruitment costs can push up their losses to 36% of expected or potential earnings, while the aggregate remittances to their families could drop by USD 2 billion.</p>","PeriodicalId":34915,"journal":{"name":"Indian Journal of Labour Economics","volume":null,"pages":null},"PeriodicalIF":1.0000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s41027-020-00281-y","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Indian Journal of Labour Economics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s41027-020-00281-y","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2020/10/21 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 7
Abstract
While the wide-ranging impact of COVID-19 on incomes and livelihoods of people around the world will take some time to become known and understood, it is already clear that those who are in manual, mostly low-wage, occupations are among the worst-hit workers. This paper uses data from a sample survey of migrant workers to come up with useful parameters for estimating the potential losses from possible retrenchment of migrant workers due to the pandemic. The paper employs a simple estimation model using parameters derived from data collected from a KNOMAD-ILO survey of low-skilled migrant workers in the India-Saudi Arabia migration corridor, conducted during 2016-2017. An important finding is that the aggregate losses that low-skilled Indian workers in Saudi Arabia are likely to incur due to COVID-19-related retrenchment may be as high as 21% of their expected earnings. Adding recruitment costs can push up their losses to 36% of expected or potential earnings, while the aggregate remittances to their families could drop by USD 2 billion.
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.
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