The distributional consequences of social distancing on poverty and labour income inequality in Latin America and the Caribbean

Isaure Delaporte*, Julia Escobar, Werner Pena

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

This paper estimates the potential distributional consequences of the first phase of the COVID-19 lockdowns on poverty and labour income inequality in 20 Latin American and Caribbean (LAC) countries. We estimate the share of individuals that are potentially able to remain active under the lockdown by taking into account individuals’ teleworking capacity but also whether their occupation is affected by legal workplace closures or mobility restrictions. Furthermore, we compare the shares under the formal (de jure) lockdown policies assuming perfect compliance with the shares under de facto lockdowns where there is some degree of non-compliance. We then estimate individuals’ potential labour income losses and examine changes in poverty and labour income inequality. We find an increase in poverty and labour income inequality in most of the LAC countries due to social distancing; however, the observed changes are lower under de facto lockdowns, revealing the potential role of non-compliance as a coping strategy during the lockdowns. Social distancing measures have led to an increase in inequality both between and within countries. Lastly, we show that most of the dispersion in the labour income loss across countries is explained by the sectoral/occupational employment structure of the economies.
Original languageEnglish
Number of pages59
JournalJournal of Population Economics
VolumeFirst Online
DOIs
Publication statusPublished - 28 Jul 2021

Keywords

  • COVID-19
  • Social distancing
  • Compliance
  • Employment
  • Poverty
  • Labour income inequality

Fingerprint

Dive into the research topics of 'The distributional consequences of social distancing on poverty and labour income inequality in Latin America and the Caribbean'. Together they form a unique fingerprint.

Cite this