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Poverty and Its Correlates among Kenyan Refugees during the COVID-19 Pandemic: A Random Effects Probit Regression Model

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  • Abayomi Samuel Oyekale

    (Department of Agricultural Economics and Extension, North-West University Mafikeng Campus, Mmabatho 2735, South Africa)

Abstract

Poverty remains a major problem among refugees, and the COVID-19 pandemic seems to have exacerbated its incidences. In Kenya, although refugees ordinarily face serious economic conditions, COVID-19 worsened their economic status. The objective of this paper was to analyze the determinants of poverty dynamics among Kenyan refugees during the COVID-19 pandemic. The data were the COVID-19 rapid response panel data that were collected between May 2020 and June 2021 by the Kenyan National Bureau of Statistics (KNBS), the United Nations High Commissioner for Refugees (UNHCR) and the University of California, Berkeley with technical assistance from the World Bank. The random effects probit regression model was used for data analysis using the absolute and relative poverty lines. The results showed that, using the Kenya’s national poverty lines, 73.03% of the respondents were poor across time, while there was a steady decline in poverty incidences from 76.55 in July–September 2020 to 68.44% in March–June 2021. The results further showed the presence of significant heterogeneity, thereby justifying the panel estimation approach. Poverty significantly declined ( p < 0.05) with receipt of food assistance, remittances, gifts, amount of loan, amount realized from sale of assets and agricultural enterprises, while it increased with education, household size, non-farm enterprises, residence in urban areas, and at the Kakuma, Kalobeyei and Shona camps. It was concluded that welfare deprivation among refugees during COVID-19 is pathetic, and post-COVID-19 recovery should, among other things, take cognizance of place and camp of residence, and access to some form of socioeconomic support.

Suggested Citation

  • Abayomi Samuel Oyekale, 2022. "Poverty and Its Correlates among Kenyan Refugees during the COVID-19 Pandemic: A Random Effects Probit Regression Model," Sustainability, MDPI, vol. 14(16), pages 1-12, August.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:16:p:10270-:d:891525
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    References listed on IDEAS

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    1. Dang, Hai-Anh H. & Verme, Paolo, 2019. "Estimating Poverty for Refugee Populations: Can Cross-Survey Imputation Methods Substitute for Data Scarcity?," GLO Discussion Paper Series 429, Global Labor Organization (GLO).
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    4. Verme, Paolo & Gigliarano, Chiara, 2019. "Optimal targeting under budget constraints in a humanitarian context," World Development, Elsevier, vol. 119(C), pages 224-233.
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