The effect of shocks to GDP on employment in SADC member states during COVID‐19 using a Bayesian hierarchical model

Ilan Strauss, Gilad Isaacs and Josh Rosenberg

African Development Review, 2021, vol. 33, issue S1, S221-S237

Abstract: Using a simple Bayesian ‘mixed effects’ hierarchical model we provide econometric estimates of annual 2020 employment losses in the context of the COVID‐19 pandemic for 15 SADC member states on the basis of historical GDP data between 2000 and 2019 and 2020 forecasts. Our mixed effects model consists of country‐varying coefficients, as well as ‘fixed’ (pooled) coefficients. This allows us to fully explore variation between countries. The model provides estimates for losses in total employment and women's employment, from which we infer income losses. We find that roughly half of estimated SADC countries have total employment losses below or approaching 25% of all jobs, while the other half have total losses exceeding 25%. Around one‐third of all jobs for women risk being lost during 2020 for Madagascar, Comoros, Angola, Botswana, Namibia, and South Africa. Our model implies that most SADC countries will experience an equivalent loss of wage income in excess of 10% of GDP (whether through pure job losses and/or reductions in wages and working hours). Policy implications are briefly discussed.

Date: 2021
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