COVID-19, Labor Market Shocks, and Poverty in Brazil - A Microsimulation Analysis

Jul 19, 2026

Estimates the short-term economic impact of the COVID-19 crisis on Brazilian households relative to labor market shocks using a microsimulation model that integrates subnational shocks from a computable general equilibrium growth framework. Results indicate over 30 million workers could experience sizable labor income declines in 2020, with two-thirds among informal and own-account workers lacking unemployment protection. Income losses would reduce average per capita income by 7.6%, increase inequality by 4%, and—despite unemployment insurance—push 8.4 million into poverty. The Auxilio Emergencial transfer can absorb the shock for the poorest 40% and reduce poverty, while later phases may require fiscally prudent AE extensions considering restricted or less generous designs.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages43

Reading Time1 h 48 min

Section 1. Brazilian’s economic vulnerability to COVID-19

Section 2: Methodology

2.1 Modeling COVID-19 income shocks

2.2 Modeling unemployment protection

2.3 Modeling the Bolsa Familia queue

Section 3: Results

3.1 Impact on household income

3.2 Impact on Poverty and Inequality

3.3 Caveat: Perfect Targeting of AE

3.4 After the Auxilio Emergencial ends

Section 4: Conclusion

Annex

Public Disclosure Authorized Public Disclosure Authorized COVID-19, Labor Market Shocks, and Poverty in Brazil: A Microsimulation Analysis 1 Fabio Cereda, Rafael M. Rubião, and Liliana D. Sousa Poverty and Equity Global Practice, World Bank July 31, 2020 Abstract: In this note we estimate the short-term economic impact of the COVID-19 crisis on Brazilian families visa-vis labor shocks. The analysis, using a microsimulation model which incorporates subnational shocks from a computable general equilibrium growth model, shows that over 30 million workers in Brazil may see significant reductions in their labor income in 2020 due to the COVID-19 pandemic. Two-thirds of these workers are informal workers or own-account workers, groups without access to unemployment protection. These household shocks would reduce average per capita income by 7.6 percent, with the largest impact on the second and third quintiles of the income distribution. These income shocks are inequalityincreasing: without any mitigation measures, inequality would increase by 4 percent. The country’s first line of defense, its existing unemployment insurance system, reduces the income shock to 5.3 percent. Even so, an additional 8.4 million Brazilians could fall into poverty. The policy responses announced by the government, and particularly the Auxilio Emergencial (AE) transfer, have the potential to fully absorb the labor income shock for the poorest 40 percent and reduce poverty. Yet, these results reflect annualized income, obscuring the sharp reduction in monthly income if demand shocks persist after the AE ends. Looking towards the next phase of the response, considering extensions of AE that are either less generous or more restricted provide a fiscally prudent approach for continuing to support Brazil’s most vulnerable. 1 This is a background note for: World Bank. 2020.“COVID 19 in Brazil: Impacts and Policy Responses.” World Bank, Washington, DC. © World Bank. [https://openknowledge.worldbank.org/handle/10986/34223 License: CC BY 3.0 IGO.](https://openknowledge.worldbank.org/handle/10986/34223 License: CC BY 3.0 IGO.) . Acknowledgements The authors recognize the contributions of the broad team who worked on “COVID-19 in Brazil: Impactsand Policy Responses,” in particular Marek Hanusch, Cornelius Fleischhaker, Joaquim Bento de Souza Ferreira Filho, Xavier Ciera, and Antonio Soares Martins Neto, as well as the team who has contributed to BraSim, especially Matteo Morgandi, Katharina Maria Fietz, Alison Rocha De Farias, and Jia Gao. The authors worked under the guidance of Paloma Anos Casero, Ximena Del Carpio, Rafael Munoz Moreno and Pablo Acosta. The authors are grateful for comments received from Gabriela Inchauste and Hernan Winkler. Contents Section 1. Brazilian’s economic vulnerability to COVID-19 ....................................................................... 6 Section 2: Methodology .............................................................................................................................. 10 2.1 Modeling COVID-19 income shocks ............................................................................................... 11 2.2 Modeling unemployment protection ................................................................................................. 13 2.3 Modeling the Bolsa Familia queue ................................................................................................... 15 Section 3: Results........................................................................................................................................ 16 3.1 Impact on household income ............................................................................................................ 17 3.2. Impact on Poverty and Inequality .................................................................................................... 21 3.3 Caveat: Perfect Targeting of AE .....................

FAQs

How does the study measure the impact of COVID-19 on Brazilian households?

It uses a microsimulation model that incorporates subnational shocks derived from a computable general equilibrium growth model, then tracks resulting changes in labor income, poverty, and inequality.

What groups are most affected by labor income reductions in 2020?

Over 30 million workers may see significant labor income reductions, and two-thirds are informal workers or own-account workers who do not have access to unemployment protection.

How do unemployment insurance and Auxilio Emergencial (AE) change the poverty and inequality outcomes?

Unemployment insurance reduces the income shock from 7.6% to 5.3%, yet 8.4 million could still fall into poverty. AE can potentially fully absorb the labor income shock for the poorest 40% and reduce poverty, with later design choices affecting fiscal prudence and targeting.

Jul 19, 2026

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