Direct and Indirect Effects of Lockdown Policies on Poverty and Inequality in Latin America
We estimate the possible effects on poverty and income distribution of the crisis unleashed by Covid-19 on a group of Latin America and Caribbean countries, representing 80% of the total population in the region: Argentina, Brasil, Chile, Colombia, Ecuador, Honduras, Mexico, Paraguay, Peru, and Urug...
- Autores:
-
Álvarez, Andrés
Becerra, Oscar
Bernal, Catalina
Daly, Julio
Quigua, Juliana
Cruz Aguayo, Yyannu
- Tipo de recurso:
- Work document
- Fecha de publicación:
- 2021
- Institución:
- Universidad de los Andes
- Repositorio:
- Séneca: repositorio Uniandes
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.uniandes.edu.co:1992/49801
- Acceso en línea:
- http://hdl.handle.net/1992/49801
- Palabra clave:
- COVID-19
Poverty
Inequality
Latin America
Lockdown policies
Simulations
N36, I38, I14, D57
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/4.0/
| Summary: | We estimate the possible effects on poverty and income distribution of the crisis unleashed by Covid-19 on a group of Latin America and Caribbean countries, representing 80% of the total population in the region: Argentina, Brasil, Chile, Colombia, Ecuador, Honduras, Mexico, Paraguay, Peru, and Uruguay. We use household survey data from pre-crisis national household surveys and, based on prospective scenarios of vulnerability to the shock, we compute the impact that income losses may have on a country's poverty levels and inequality. Our vulnerability scenarios are based on the national policies used to prevent the rapid expansion of the Coronavirus. Additionally, for a sub-sample of 6 countries (Brazil, Chile, Colombia, Ecuador, Mexico and Peru) we use Input-Output linkages to estimate direct and indirect shocks to consider how the differences of the productive structures, economic linkages, and labor market characteristics of each country could result in different effects on poverty and inequality. We find a significant increase on poverty headcount ranging from 25% to 33% percent in our different estimations. The results show heterogeneity on the exposure to the shocks. Two main factors explain differences across countries: their level of specialization in activities labeled as essential (e.g., agriculture, public sector, food retail) and their level of employment protection and stability (i.e., type of contract and employment in larger firms). We find a higher vulnerability to the propagation of the shocks in countries with a bigger agricultural sector, and less vulnerability in countries with bigger firms, and lower informality. |
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