Abstract
This study examines to what extent international migrants were affected by the Covid-19 pandemic, focusing on the formal labor market in Brazil. The investigation is framed by a quantitative methodological framework based on Brazilian administrative data to identify hirings and dismissals of migrant workers. In dialogue with the literature on migration and crisis, the hypothesis of the study was that migrant populations would lose more jobs due to the pandemic and would be more affected than nationals. In contrast, the data show that the sectoral and occupational allocation of migrants newly settled in Brazil resulted in them having a positive employment balance, even compared to native workers. In addition, we found that the impact of the pandemic was uneven across different groups of migrants, and it depends on economic activity sectors and occupations. This research demystifies the idea that migrants are the first affected by the economic crises. The article brings theoretical contributions from the perspective of south-south migrations.
Keywords:
Covid-19 pandemic; Labor market; Migration; Brazil
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* The relative excess plotted in this figure is obtained by first calculating the relative net balance (hirings minus dismissals divided by hirings) for each month-year and then calculating the difference between 2019 and 2020.Source: Data from the Ministry of Economy, RAIS-CTPS-CAGED harmonized database.
* The figure shows occupational groups (1-digit CBO - Classificação Brasileira de Ocupações). We removed the armed forces occupational group because only three hirings and dismissals were registered in 2020 (none in 2019).Source: Data from the Ministry of Economy, RAIS-CTPS-CAGED harmonized database.
* Wages are deflated by the main Brazilian Consumer Price Index (IPCA), considering prices fixed in December 2020. Because the number of hours worked is unavailable, but only in groups (e.g., 41-44 hours worked in the week), hourly wages were calculated by dividing each wage by the higher number of hours worked in each group (44 in this case) and then by four weeks in a month. Only hirings were considered, and we excluded values lower than 0.3 and higher than 150 minimum salaries since they were likely to be imputation errors. Furthermore, we did not consider intermittent workers. The kernel density was calculated using default options from the R package ggplot2, including the Silverman rule of thumb bandwidth selector (nrd0) and a Gaussian kernel.Source: Data from the Ministry of Economy, RAIS-CTPS-CAGED harmonized database.
Source: Data from the Ministry of Economy, RAIS-CTPS-CAGED harmonized database.