[ad_1]
The current COVID-19 pandemic and the policy measures to combat it have profound effects on the economic and social life of citizens. They threaten jobs and the livelihoods and long-term well-being of millions of people around the world.
South Africa has not been exempted from the socio-economic effects of the pandemic. Its economy has been in decline since entering a strict lockdown as the main public health response to curb the spread of the virus in March 2020. This is reflected in its latest available statistics on gross domestic product (GDP) and employment.
The country’s economy was not in great shape even before the lockdown. It was hit hard by the global financial crisis in 2008, recording an average growth of just over 2% between 2008 and 2012. And now the National Treasury has forecast that the economy will contract 7.8% in 2020 due to COVID-19 measures.
The unemployment rate in South Africa has been consistently high over time, exceeding 20% over the past decade. The official unemployment rate hit a record high of 30.8% in the third quarter of 2020.
Understanding the effects of the global pandemic on employment – at aggregate and sectoral levels – is therefore essential for governments, policy makers, workers and employers. This should help minimize the long-term effects of the pandemic while ensuring the safety of individuals and the sustainability of businesses and jobs.
This article focuses on providing the results of an applied economic analysis on sectoral winners and losers during the pandemic. We also identify those who have been most affected and assess the South African government’s policy response to minimize its effects.
So far, the government’s response to deal with the impact of the pandemic has consisted of two main interventions: a stimulus package launched in April 2020 and in October 2020 a longer term stimulus package. Our article focuses on the short-term stimulus package.
Simulation exercise
Since data on sector GDP, aggregate GDP, and poverty lag behind employment figures, the results of economic modeling such as the one we present here can help provide useful information in the interval.
This article presents the results of our COVID-19 policy response simulations. The models trace a variety of channels through which the pandemic affected the economy.
The simulation exercise showed that the sectors and workers most affected by the COVID-19 pandemic were the mining / minerals sectors, the construction sector, the transport sector and most of the service sectors such as the retail and accommodation.
But the fallout meant that ultimately all sectors were affected. The reduction in economic activities has resulted in a reduction in the demand for labor and capital. This, in turn, has led to a reduction in the income of all agents of the economy. Households were not spared. In particular, households dependent on income from unskilled labor suffered the most because these workers were the most constrained after the lockdown.
Mining and minerals have been affected by the foreclosure as well as falling mineral prices on the world market. Based on the model results, we estimated that 864,000 were affected in a moderate scenario of the COVID-19 crisis. In a harsh expression of the crisis, we estimate that 1.3 million jobs will be affected. This is in line with the results of Statistics South Africa’s quarterly employment statistics. This showed full-time job losses of more than 568,000 (-6.2%) year-over-year between June 2019 and June 2020 (at the height of the COVID-19 lockdown) and losses of more than 525,000 (-5.7%) in full-time employment year on year between September 2019 and September 2020.
Major impact
Overall, the effects of the simulated COVID-19 pandemic have been quite harsh on both the production and demand side of the economy. The decline in GDP growth (-10%) is largely due to the marked slowdown in economic activity coupled with widespread disruptions in both international and national supply chains.
Lower GDP growth and increased unemployment invariably translate into higher unemployment and poverty rates. By extending the analysis to poverty, the modeling results show a slight increase in poverty, increasing by 2.5 percentage points.
In addition, women, especially households headed by the poorest women, have been more affected. Indeed, they derive a greater share of their income from low-skilled type of work.
As the country tries to bring the pandemic under control, our findings underscore the importance of interventions in at least three areas: protection of vulnerable populations, support of vulnerable sectors and diversification of foreign trade.
It is important to note that, given the lack of information on the current pandemic, the results of this situation and any modeling exercise will be surrounded by uncertainties. Therefore, the directions and intensity of the changes should be emphasized.
Implications for policy
The most interesting aspect of our results from a policy intervention perspective is that the decline in employment and poverty is not uniform across skill levels and gender. As is often the case in economic crises, there are winners and losers, and in this case, it is the less skilled workers and poor women who suffer the most.
This suggests that, when developing a reconstruction strategy, the government should promote investments in the service sectors, help these different sectors to put in place protective barriers to allow the different activities to restart and especially to recover. recover some of the lost jobs.
A set of supportive measures to increase the purchasing power of consumers and reduce the operating costs of these businesses and industries would also be effective interventions.
As the country intervenes to cushion the poor, economic growth stimulus must be put in place at the same time. Policy options could include increasing public investment, accelerating the implementation of existing policies, and diversifying the export and import basket. This could include increasing high value-added commodities in total exports and increasing the share of primary products in total imports.
The authors do not work, consult, own stock, or receive funding from any company or organization that would benefit from this article, and have not disclosed any relevant affiliation beyond their academic appointment.
By Jessika Bohlmann, PhD (Economics), University of Pretoria and
Helene Maisonnave, Professor of Economics, Le Havre Normandie And University
Margaret Chitiga-Mabugu, Director and Director, School of Public Management and Administration, University of Pretoria and
Martin Henseler, Researcher, EDEHN – Le Havre Normandie Economics Team, Le Havre Normandie University And
Ramos Emmanuel Mabugu, professor, Sol Pic University
Source link
