Open AccessSocio-economic status, resilience, and vulnerability of households under COVID-19: Case of village-level data in Sichuan province
Author(s) -
Imran Ur Rahman,
Jing Deng,
Junrong Liu,
Mohsin Shafi
Publication year - 2021
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0249270
Subject(s) - vulnerability (computing) , poverty , psychological resilience , household income , snowball sampling , socioeconomics , survey data collection , covid-19 , shock (circulatory) , government (linguistics) , demographic economics , economics , transfer payment , business , geography , economic growth , welfare , philosophy , computer security , mathematics , psychotherapist , linguistics , archaeology , pathology , computer science , psychology , medicine , statistics , disease , infectious disease (medical specialty) , market economy
This paper investigates economic impacts of COVID-19 on households based on differences in the socio-economic status (SES). We determine the household-level effects of the COVID-19 shock using income sources, types of industries, communities’ resilience, household susceptibility, and relevant policy measures. For this purpose, we used primary data of 555 households collected through snowball sampling technique using an online survey questionnaire from different villages mostly located in Sichuan Province, China. Using step-wise binary logistic regression analysis, we estimated and validated the model. Results suggest the use of SES as a better measure for understanding the impacts of COVID-19 on different households. We find that households with low SES tend to depend more on farmland income and transfer payments from the government. Contrarily, high SES households focus more on business and local employment as sources of income generation. Poor households were less resilient and more likely to fall back into poverty due to COVID-19, while the opposite stands true for non-poor households with high SES. Based on the estimations, policies encouraging employment and businesses complemented with loans on lower interest rates are recommended, which may increase the SES, thus minimizing vulnerability and enhancing the households’ resilience towards poverty alleviation and economic shocks.