The impact of COVID-19 on inequality in South Africa

Abstract

The COVID-19 pandemic has raised concerns regarding its possible adverse income distributive consequences, and its different impact according to socioeconomic subgroups (Furceri et al. 2020). This research measures the impact of COVID-19 on inequality in South Africa. To do this the study uses the National Income Dynamic Study (NIDS) wave 5 (2018) and the National Income Dynamic Study Coronavirus Rapid Mobile (NIDS-CRAM) survey waves 1 "“ 5 (2020 - 2021) datasets to study income inequality in South Africa prior to and during the COVID-19 pandemic until mid-2021. The factor method developed by Lerman and Yitzhaki's (1985) is used to identify the overall contribution of the different factor sources to income inequality. Labour income is identified as the largest contributing factor and so labour income inequality is decomposed by income determinants using the regression-based decomposition method proposed by Fields (2003). The analysis reveals that labour income worsened during the periods of strictest COVID lockdown, before returning to pre-pandemic levels of inequality as lockdown was eased. Education is the most important determinant of labour income inequality across all time periods, particularly for White, urban and female participants. Although education remains a driving factor of labour income inequality during the national disaster, its contribution lessens as the economy starts recovering by March 2021. Consequently, the contributions of gender, race, age and region increase during the same period. Identifying whom the inequal impact of pandemic has affected worse offers insight that emphasizes the importance social grant systems to aid bridge the inequality gap associated with COVID-19.