COVID-19 Pandemic - A Labour Impact Analysis - An Important Step Towards Solving the Labour Challenge in the Midst of a Covid-19 Storm - IQbusiness

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COVID-19 Pandemic - A Labour Impact Analysis - An Important Step Towards Solving the Labour Challenge in the Midst of a Covid-19 Storm - IQbusiness
COVID-19 Pandemic –
A Labour Impact Analysis
An Important Step Towards Solving the Labour
Challenge in the Midst of a Covid-19 Storm
COVID-19 Pandemic - A Labour Impact Analysis - An Important Step Towards Solving the Labour Challenge in the Midst of a Covid-19 Storm - IQbusiness
Foreword

The COVID-19 pandemic has wreaked havoc             businesses. Employment outcomes depend
in global health systems, global economies          both on economic growth as well as the
and now global financial systems. The impact         absorptive capacity of the economy (Altman,
of the pandemic is being modelled daily and         2003) and economic growth alone can be
forecasts are being revised continuously as         achieved through growth in productivity levels,
more data points become available. As the           without it resulting in employment growth.
Minister of Finance, Tito Mboweni, said in          According to IDC report South African Report: An
his address on COVID-19 and the economy,            Overview of Key Trends Since 1994, the average
“The COVID-19 pandemic is one of the greatest       annual growth rate of GDP between 1994 and
challenges that has ever faced our nation”.         2000 was 2.9%, while employment growth
The COVID-19 outbreak poses a great challenge       over the same period was an average of 0.5%
as its devastating effects will not be limited       per annum; between 2001 and 2007, a period
to the health of millions of people but also the    that was a high growth period for South Africa,
health of the global economy and subsequently,      the average GDP growth rate was recorded at
South Africa’s economic outlook. The South          4.3% while employment growth was a meagre
African Reserve Bank (SARB) revised its estimates   1%. In the period that followed between 2008
for 2020 economic growth from an initially          and 2012, South Africa experienced jobless
revised 0.2% contraction in March, and states       growth, where economic growth averaged 2,2%
that they expect the South African economy          over the period while employment declined
to contract by 6.1% in 2020. Further downward       0.4% per annum over the same period - the
revisions are expected as more statistical          phenomenon of jobless growth has remained
data is collected.                                  a key feature of the South African economy
                                                    since.
In this report we explore the impact that this
will have on labour and employment outcomes         In the same vein, you can have productivity
in the country, sectors, households and             gains than do not result in a commensurate

2
COVID-19 Pandemic - A Labour Impact Analysis - An Important Step Towards Solving the Labour Challenge in the Midst of a Covid-19 Storm - IQbusiness
growth in output; and to illustrate, Tsebe             growth. This labour impact report details
and Biniza in their paper Analysing Total              the pockets of labour vulnerabilities on the
Factor Productivity Growth for South Africa’s          back of the COVID-19 pandemic and offers
Manufacturing Sector Using a DEA-Based                 ideas for a new labour market place that
Malmquist Productivity Index found that between        could inform future skills development programs
1994 and 2013 total factor productivity in             given a more detailed understanding of the
the entire manufacturing sector grew by                labour complexities of the South African
0.5% per annum – while over the same                   economy.
period manufacturing contribution to GDP
shrunk from 20.9% in 1994 to 12.4% in 2012.
(Tsebe & Biniza, 2015 ). In fact, the capital-labour
ratio widened from 176 100 in 1994 to 195
501 in 2012, while output per labour increased
from 68 821 to 92 126 in the same period.

Wolassa Kumo, found that there were three
critical challenges that were holding back
Total Factor Productivity (TFP) growth and
efficiency gains, namely 1) skills shortages 2)          Sifiso Skenjana
infrastructure deficits, and 3) weak domestic           Chief Economist, IQbusiness
competition. Human capital being key to TFP
growth is also supported by Nobel winning
Paul Romer’s endogenous growth theory
which argues that investments in human
capital, knowledge creation and innovation
are key contributors to long term economic

                                                                                                    3
Introduction – The Labour Complex:
A Tale of Many Stories

The labour question is one of the most complex issues that       the learner cohort solve for the businesses current and
has continued to escape policy makers, labour, and               future skills needs – hence a sultry absorption rate of 68%.
business for a good portion of the last two decades. The         The labour data from Stats SA shows that roughly 91% of
relationship between private sector, public sector and wage      those who are unemployed either have a matric attainment
bargaining remains a hostile one as they struggle to find a       or less. In addition, the primary and secondary combined
meeting of minds with respect to issues of perceived rigidity    dropout rate is 50%, meaning that roughly half of the learners
of labour laws, issues pertaining to wage inequality and         who start the learning curriculum (grade 1) don’t make it to
resource prioritisation – the theory of the firm.                 grade 12. Not only does this create a social risk to the economy,
                                                                 but also a looming fiscal problem.
Demand and Supply Skills Mismatch
                                                                 Urbanisation and Brain Drain
The South African economy continues to be characterised
as an economy that … “creates jobs for the labour force it       The large metro’s have growing net positive migration rates
wishes it had and not for the labour force it currently has” …   while the smaller towns. According to the mid-year population
and while it is important to future proof the economy in a       statistics from Stats SA, Gauteng, Western Cape and the
continuously changing global market place, a preceding           North West Province are expected to have net migrants of
step ought to fixate on policy imperatives that will inform       1 048 440, 311 004 and 107 733 respectively. This also
higher current labour absorption. The finance and business        means that the other provinces who will be experiencing
services – a sector that generally attracts and requires a       net immigration will also be losing some of the intellectual
higher skills profile - contributes approximately one fifth of     skills that could be important contributors to the social and
the GDP, with roughly 16% of the labour force, while other       economic development of those towns and cities.
labour intensive sectors like agriculture, tourism, mining,
construction contribute significantly less than what they         Professionalisation of Municipalities: The Northern Cape is
ought to.                                                        home to three of the largest wind energy projects in the
                                                                 country namely Longyuan Mulilo Green Energy, Loeriesfontein
Learning from the German Model: In 2016 almost half of           Wind Farm 2, and Khobab Wind - each with generation
the German labour force had gone through a vocational            capacity of 138.96MW, 138.23MW and 137.74MW respectively.
training qualification, which blended on the job skills           An approach to professionalise these municipalities would
training and an academic component, with an approximate          be to ensure that the national comparative advantage the
1.3 million apprenticeships per annum according to the           municipality enjoys is wind generation and its ability attract
Federal Statistical Office (Destatis). The average absorption      professionals who can ensure that the province remains a
rate of graduate was reported at 68%. What is particularly       lead province for wind energy generation. Housing these
interesting about this model is 1) the learning programmes       skills in the municipality ensures that the public sector is
are administered under the economic affairs department            professionalised with highly technical skills and attracts
(labour and human capital development is an economic             such labour from other provinces, ultimately limiting the
planning issue) and 2) that the curricula were co-authored,      extent of brain drain. This model is how Gauteng became
assessed and examined by both private sector and the             what it is on the back of marketing itself as a mining skills
department of education. What this means is that business        opportunity province, before later establishing itself as the
can design learning outcomes directionally, to ensure that       broader economic centre of the country.

4
Wage Inequality                                                     These findings were echoed by the 2018/2019 Global Wage
                                                                    Report, which found that South Africa had the highest wage
Mind the Gap: The Inequality Trends Report 2019 from                disparities in the world based on gender and race. It becomes
Stats SA in partnership with SALDRU and Agence Francaise            a complex conversation therefore with the unions when
de Dévelopement (AFD) found that wage inequality was the            they demand above inflation increases to close the wage
largest driver of income inequality in South Africa. Specifically,   gap, while also refusing to contextualise the firms’ economic
they argued that:                                                   environment and its ability to sustainably raise wages above
                                                                    inflation over time.

“Throughout the years, income from the labour
                                                                    Labour Laws
market has been the leading source of household
income in South Africa, accounting for over 70% of
                                                                    South Africa’s labour laws are broadly touted to be rigid by
total income. The report found that labour market                   international standards. Some of these rigidities have been
income is the main driver of income inequality in                   directed towards the arbitration process and firm
South Africa, contributing 74% towards overall income               constraints with respect to hiring and firing, restricting their
inequality in the country in 2015. Nevertheless, social             ability to freely optimise their skills compliment according

grants and remittances have played a crucial role in                to their needs. Some of the world’s largest development
                                                                    institutions have dynamic views on the labour law issue in
reducing the income inequality gap between the
                                                                    South Africa. In 2008, the World Bank lamented in the
bottom and top deciles”
                                                                    Doing Business Report that restrictive labours in South
                                                                    Africa would harm workers and not protect them. And 8
They further argued that:
                                                                    years later in their 2016 Doing business report found that
                                                                    “under-regulation in the areas of working time and minimum
“The distribution of earnings depicts the heavily racialised
                                                                    wage protection can have harmful effects on the productivity
inequality present in the South African labour market               and would exacerbate the effects of macroeconomic shocks”.
between 2011 and 2015. In addition to having worse                  Based on their most recent position, loose labour legislation
employment outcomes, black Africans also earn the                   in a COVID-19 environment would have disproportionately
lowest wages when they are employed. Whites, in                     worse labour outcomes.

contrast, earned substantially higher wages than all
                                                                    Rigid or Protective: The jury is certainly still out on whether
other population groups. Their monthly average real
                                                                    labour laws in South Africa are sufficiently protective of the
earnings were more than three times higher than
                                                                    labour force or they are unnecessarily and unsustainably
those of black Africans. Females were less likely to be             rigid and may result in worse off labour and economic
employed and earned approximately 30% less on                       growth outcomes.
averageas compared to males.”

                                                                                                                                 5
Labour Categories – A Commuter
Analogy

A Way Forward                                                   mass layoffs. The typical train rider would be mine workers,
                                                                craft workers, plant operator, permanent farm workers and
However complex the labour question is for South Africa,        construction workers etc. The generalised education attainment
this report aims to charter a path into understanding, in       attributable to this group is 1) secondary schooling not
more granularity the vulnerabilities of the labour force both   completed and 2) secondary school completed and on this
from a COVID-19 perspective as well as a broader structural     measure account for approximately 39.16% of the labour
perspective; whose understanding would better enable the        force. From a generalised occupation perspective, this
response interventions for effective labour reforms.             group accounts for 19.98% of the labour force.
In order to understand South Africa’s labour force and its
vulnerability to the COVID-19 outbreak, we use a commuter       The bus riders
analogy to describe the categories that constitute our
labour market. In using this analogy, the transport ascribed    We define bus riders as semi-skilled employees with
to each grouping is based on the skills level and degree of     relatively more balanced security and limited mobility.
mobility of its members. Two perspectives have been             Analogously they move from bus stop to bus stop, and
adopted using the level of education and occupations of         there is little variation and differentiation in route and
South Africa’s employed labour force obtained from the          routine. These are the workers that would typically be sales
October-December 2019 Quarterly Labour Force Survey.            and services staff, clerks, technicians, retail till operators,
This allows for an analysis of their employment opportunities   call centre staff etc. From a generalised occupation
and risk propensity to any major disruption in the economy.     perspective they account for approximately 35.76% of the
                                                                labour force. The educational attainment perspective
The hitch hikers                                                approximates this group to 27.90% generalized as 1)
                                                                secondary completed and 2) some qualification / certification
We define the hitch hikers as the labour group that is largely   post-secondary schooling
unskilled with an analogous hitch-hike model, where they
take their chances for opportunistic demand gaps in the         The Uber riders
labour force. These are the workers you would generally see
when driving past hardware store, temporary farm workers,       We define Uber riders as skilled employees with a high
piece job takers and domestic workers. The generalised          degree of mobility. Analogously, they have discretion on
education attainment attributable to this group is 1) no        when to move and the mode of transport. Typically, these
schooling, 2) less than primary completed and 3) completed      are labour market participants who are professionals or
primary. By education attainment this group makes up            managers occupationally and account for a generalised
approximately 11.07%. From a generalised occupation             14.48% of the labour force from an occupation point of
perspective, this group is either 1) elementary workers or 2)   view. Broadly these workers would have a tertiary education
domestic workers, accounting for 29.08% of the labour           attainment level and account for a generalised 21.88% of
force by occupation.                                            the labour force through this dimension.

The train riders                                                The labour attribution in each of the commuter clusters
                                                                allows us to have a skills-based (occupation and education)
We define the train riders as the unskilled and semi-skilled     view of the labour force and to model for the labour market
labour in high employment density sectors with high risk of     risk propensity of each of the clusters.

6
FIGURE 1 – MINIMUM AND MAXIMUM SIZE OF COMMUTER CLUSTER
REPRESENTATION IN LABOUR FORCE

                                                                                                                   29.08
                                        11.07
Hitch Hikers

                                                                                                                                                39.16
                                                        19.98
Train Riders

                                                                                    27.90                                      35.76

Bus Stoppers

                                                               21.88
                                             14.48
Uber Riders

       Education Attainment              Occupation Attribution

Hitch Hikers: Range of hitch hikers is between 11.06% and 29.08% of the labour force by occupation and education attainment. Interpreting this range
means that a) at a minimum we have 11.06% of the labour force as hitch hikers. b) at a maximum this number is 29.08%.

Train Riders: Range of train riders is between 19.98% and 39.16% of the labour force by occupation and education attainment.

Bus Riders: Range of bus stoppers is between 27.90% and 35.76% of the labour force by occupation and education attainment

Uber Riders: Range of Uber riders is between 14.48% and 21.88% of the labour force by occupation and education attainment

                                                                                                                                                       7
COVID-19 Risk Assessment of Labour
Measurement
Categories and Sector Implications

Industries that are key contributors to South Africa’s GDP       economic effect than the direct effects from mortality and
such as trade and hospitality are greatly dependent on the       morbidity because if social distancing works only a small
free movement of people and will therefore be heavily            fraction of the population will be infected. As a result of
impacted by the sudden inability to operate as per normal.       Covid-19 we are already seeing demand in the healthcare
The fourth quarter GDP numbers reported that finance and          sector skyrocket, while on the other hand we are seeing a
business services, Government, trade and manufacturing           plummet in demand for sectors such as air transportation
were the industries with the largest contributions to GDP,       and tourism. Concurrently, many sectors are facing issues
accounting for 20%, 18%, 17% and 13% respectively (Stats         on the supply-side as the lock-down has left workers of
SA, 2020).                                                       non-essential businesses confined to their households.

Fortunately, much of the work conducted by finance and            Table 1 and Table 2 indicate the amount of labour
business services, for example, can continue as employees        withdrawn due to social distancing we use and the extent to
work from home. However, not all industries are able to          which workers in given occupations can perform their
leverage off of digital solutions and cannot allow their          requisite tasks at home. All the occupations with a Remote
employees to continue their work remotely. The table             Labour Index (RLI) of 1 indicate that all work activities
below leverages the research from del Rio-Chanona and            associated with the occupation can be performed entirely
Others (2020), Supply and demand shocks in the COVID-19          in the household while a remote Labour Index of 0
pandemic: An industry and occupation perspective.                indicates that none of the occupation’s activates could be
                                                                 performed at home.
This report shows the labour force's risk to the COVID-19
outbreak in terms of an industry's ability to work remotely      Occupations in education and financial specialists are
and whether they are defined as essential. It is argued that      estimated to have almost 100% ability to perform their
a higher propensity to work remotely mitigates the negative      work from home, while occupations in Construction, Farming
impacts of shocks to the economy and necessary measures          and extraction work are estimated to have almost a 0%
such as a total lockdown because delivery can largely continue   ability to perform any of their work from home. Therefore,
as per normal, regardless if an industry is considered           all occupations with an RLI of 0, if deemed as a non-essential
essential or not. However, if an industry has a lower ability    service,have no ability to function during the lockdown
to have its work conducted remotely, it has a higher risk of     period, regardless of demand supply of labour will be
being adversely affected by an event such as the COVID-19         unattainable.
pandemic. This due to having to cease business activity.
Where an industry is unable to conduct its work remotely         In order to gain an understanding of which non-essential
but is considered essential and therefore must still operate,    industries will be able to remain productive (supply labour)
it has an extremely high degree of risk because workers risk     during the lock-down period we use Table 1 to look at how
exposure to the Coronavirus.                                     industries are ranked according to their RLI. Industries with
                                                                 the highest average RLI values relate to information,
As the government mandates non-essential businesses to           finance and insurance, while industries with the lowest
close and social distancing practices to slow down the           average RLI relate to agriculture, forestry and hunting and
spread of Coronavirus, the South African supply market           accommodation and food services (restaurants, takeaway
faces significant uncertainty about the effects social             outlets and catering services).
distancing and lockdown will have on lives and livelihoods.
We expect to see social distancing measures having a greater

8
TABLE 1 - RISK BASED ON INDUSTRY'S ABILITY TO WORK REMOTELY VS ESSENTIALITY
 Industry                               Remote          Essential       Risk by       Health Risk/       Loss of       Labour Force
                                        Labour            Score         Remote          Risk of          Income         Category by
                                         Index           Median         Labour         Exposure            Risk         Commuter
                                        Median                                                                            Analogy

 Agriculture, Forestry, Fishing                                        Extremely        Extremely                       Hitch Hikers,
                                         0.144           0.500                                          Low Risk
 and Hunting                                                           High Risk        High Risk                       Train Riders

                                                                                                        Extremely
 Mining                                  0.278           0.000          High Risk       Low Risk                        Train Riders
                                                                                                        High Risk

                                                                                                                        Hitch Hikers,
 Construction                            0.308           0.659          High Risk       Low Risk        High Risk
                                                                                                                        Train Riders

 Administrative Support, and                                                            Moderate
                                         0.322           0.600          High Risk                       Low Risk        Train Riders
 Waste Management Remediation                                                             Risk

                                                                                        Extremely                       Train Riders,
 Transportation and Warehousing          0.337           1.000          High Risk                       Low Risk
                                                                                        High Risk                        Bus Riders

                                                                                                        Extremely       Train Riders,
 Manufacturing                           0.346           0.250          High Risk       Low Risk
                                                                                                        High Risk        Bus Riders

 Accommodation and Food                                                                                 Extremely
                                         0.356           0.000          High Risk       Low Risk                        Train Riders
 Services                                                                                               High Risk

                                                                                        Extremely                       Bus Riders,
 Healthcare and Social Assistance        0.390           1.000          High Risk                       Low Risk
                                                                                        High Risk                       Uber Riders

                                                                        Moderate        Extremely                       Train Riders,
 Utilities                               0.419           1.000                                          Low Risk
                                                                          Risk          High Risk                        Bus Riders

 Arts, Entertainment and                                                Moderate                        Moderate        Train Riders,
                                         0.427           0.000                          Low Risk
 Recreation                                                               Risk                            Risk           Bus Riders

                                                                        Moderate        Extremely
 Public Administration                   0.437           1.000                                          Low Risk            Bus Riders
                                                                          Risk          High Risk

                                                                        Moderate                        Moderate
 Real Estate Rental and Leasing          0.466           0.000                          Low Risk                        Uber Riders
                                                                          Risk                            Risk

                                                                        Moderate                        Moderate
 Retail Trade                            0.472           0.301                          Low Risk                            Bus Riders
                                                                          Risk                            Risk

                                                                                                        Moderate
 Wholesale Trade                         0.504           0.457          Low Risk        Low Risk                            Bus Riders
                                                                                                          Risk

                                                                                                                        Bus Riders,
 Education Services                      0.597           1.000          Low Risk        Low Risk        Low Risk
                                                                                                                        Uber Riders

 Professional, Scientific and                                                                                            Bus Riders,
                                         0.630           1.000          Low Risk        Low Risk        Low Risk
 Technical Services                                                                                                     Uber Riders

 Management of Companies and
                                         0.659           1.000          Low Risk        Low Risk        Low Risk        Uber Riders
 Enterprises

                                                                                                                        Bus Riders,
 Information                             0.666           1.000          Low Risk        Low Risk        Low Risk
                                                                                                                        Uber Riders

                                                                                                                        Bus Riders,
 Finance and Insurance                   0.726           1.000          Low Risk        Low Risk        Low Risk
                                                                                                                        Uber Riders

0-0.2 = Extremely High Risk | 0.21-0.4 = High Risk | 0.41-0.5 = Moderate Risk | 0.51-0.8 = Low Risk | 0.8+ = Minimal Risk
Source: del Rio-Chanona & Others (2020) and IQbusiness Analysis

                                                                                                                                         9
TABLE 2 - RISK BASED ON OCCUPATION'S ABILITY TO WORK REMOTELY VS ESSENTIALITY
 Industry                               Remote          Essential       Risk by       Health Risk/       Loss of       Labour Force
                                        Labour            Score         Remote          Risk of          Income         Category by
                                         Index           Median         Labour         Exposure            Risk         Commuter
                                        Median                                                                            Analogy

                                                                        Extremely                       Extremely
 Extraction Workers                   0.071428571     0.288858322                       Low Risk                        Train Riders
                                                                        High Risk                       High Risk
                                                                                                                        Hitch Hikers,
                                                                        Extremely       Extremely
 Farming, Fishing and Forestry             0.1        0.916246529                                        Low Risk       Train Riders,
                                                                        High Risk       High Risk
                                                                                                                        (Bus Riders)
                                                                        Extremely                       Extremely       Hitch Hikers,
 Construction                            0.1125       0.375572144                       Low Risk
                                                                        High Risk                       High Risk       Train Riders
 Production / Manufacturing                                             Extremely                       Extremely       Train Riders,
                                      0.133333333     0.362090307                       Low Risk
 Occupations                                                            High Risk                       High Risk        Bus Riders
 Installation, Maintenance and                                          Extremely       Extremely
                                      0.155870446     0.624344384                                        Low Risk       Train Riders
 Repair Workers                                                         High Risk       High Risk
 Building and Grounds Cleaning                                          Extremely       Extremely                       Hitch Hikers,
                                      0.176923077     0.657159621                                        Low Risk
 and Maintenance                                                        High Risk       High Risk                       Train Riders
 Transportation and Material                                            Extremely       Extremely
                                           0.2        0.895438484                                        Low Risk       Train Riders
 Moving Occupations                                                     High Risk       High Risk
                                                                                        Extremely
 Healthcare Support Occupations       0.266666667     0.985501949       High Risk                        Low Risk           Bus Riders
                                                                                        High Risk
                                                                                        Extremely
 Protective Service Occupations       0.266666667     0.998663325       High Risk                        Low Risk           Bus Riders
                                                                                        High Risk
 Personal Care and Service
                                      0.304347826     0.390156919       High Risk       Low Risk        High Risk       Hitch Hikers
 Occupations
 Food Preparation and Serving                                                                                           Hitch Hikers,
                                      0.348484849      0.14082331       High Risk       Low Risk        High Risk
 Occupations                                                                                                            Train Riders
 Healthcare Practioners and                                                             Extremely
                                      0.363636364     0.995056683       High Risk                        Low Risk       Uber Riders
 Technical Occupations                                                                  High Risk
                                                                                        Moderate
 Legal Occupations                    0.535714286     0.986529587       Low Risk                         Low Risk       Uber Riders
                                                                                          Risk
                                                                                        Moderate
 Office and Administrative Support      0.541958042     0.753799992       Low Risk                         Low Risk           Bus Riders
                                                                                          Risk
 Life, Physical and Social Science                                                      Moderate
                                      0.555555556     0.979899497       Low Risk                         Low Risk       Uber Riders
 Occupations                                                                              Risk
 Arts, Design, Entertainment,                                                           Moderate                        Train Riders,
                                      0.571428571     0.565350927       Low Risk                         Low Risk
 Sports and Media                                                                         Risk                           Bus Riders
 Community and Social Services                                                          Moderate
                                      0.576923077     0.994583649       Low Risk                         Low Risk           Bus Riders
 Occupations                                                                              Risk
 Architecture and Engineering                                                           Moderate
                                      0.612244898     0.777434357       Low Risk                         Low Risk       Uber Riders
 Occupations                                                                              Risk
                                                                                        Moderate
 Management Occupation                0.693979933     0.796055082       Low Risk                         Low Risk       Uber Riders
                                                                                          Risk
 Sales Occupations                    0.696153846     0.485205997       Low Risk        Low Risk         Low Risk           Bus Riders
 Business Operations Specialists           0.7        0.813993346       Low Risk        Low Risk         Low Risk       Uber Riders
 Computer and Mathematical
                                      0.764705882     0.803128077       Low Risk        Low Risk         Low Risk       Uber Riders
 Occupations
 Financial Specialists                0.791666667     0.859092012       Low Risk        Low Risk         Low Risk       Uber Riders
 Education, Training and Library
                                      0.804761905           1         Minimal Risk      Low Risk         Low Risk       Uber Riders
 Occupations
0-0.2 = Extremely High Risk | 0.21-0.4 = High Risk | 0.41-0.5 = Moderate Risk | 0.51-0.8 = Low Risk | 0.8+ = Minimal Risk
Source: del Rio-Chanona & Others (2020) and IQbusiness Analysis

10
Health Risk/Risk of Exposure: Occupations that are consid-       has been allowed to continue (remotely or not remotely).
ered essential (>0.5) but have a low ability to work remotely,   Loss of income risk is extremely high where the ability to
are considered to have an extremely high risk to COVID-19        work remotely is extremely low and the occupation is not
exposure. Occupations that are essential but have a high         essential.
ability to work remotely, are likely to only have a moderate
health risk if they conduct most of their work remotely but      From the tables 1 and table 2 we are able ascertain which
may have the possibility of coming across clients or             job profiles and industries are at particular risk to loss of
colleagues. Occupations that are neither essential nor have      income and negative health exposure. The view of which
a higher propensity to work remotely are considered to           commuter cluster is associated with the occupation and
have a low health risk at present as they would be subject       industry at risk is particularly valuable to ensure that any
to lockdown regulations.                                         interventions to support job retention and minimised negative
                                                                 health exposure is targeted and is with the right context.
Loss of Income Risk: Loss of income risk is low where
occupations are defined as essential and so business activity

                                                                                                                          11
Navigating a New Labour
Market Reality

Velocity of Money – A Sector View                                significantly lower than the global average of 1.4%, slightly
(Tactical Approaches)                                            below the 1.5% that South Africa targets.

An opportunity the country missed in the pre-COVID-19            Technological growth has helped many economies experi-
economic context was an opportunity to take advantage of         ence “catch-up” growth. Germany went through this
sectors with a velocity of money. Simply, for certain sectors,   between 1880 and 1910, transitioning from being a largely
one unit of currency spent moves faster into the real economy    rural economy to being in a technology led growth transition
and benefits are realized in the aggregate output numbers         thanks to the establishment of Technical Training Institutes
in a shorter space of time. Take for example tourism, last       and a proliferation of specialised R&D laboratories for
year an exhibition match between Roger Feder and Rafael          manufacturing. Israel, a former drought-stricken country
Nadal was announced mid-year and by the time ticket sales        with now some of the most advanced agricultural and
opened, roughly 51 954 tickets were sold out in minutes,         water desalination technology in 2018 spent 4.9% of the
many selling in excess of R1000 per ticket. The ticket sales     GDP towards GERD. The country is home to the largest
would be followed by flight and accommodation bookings,           reverse-osmosis desalination facility in the world and now
followed by dining and drinks before and after the event.        runs a water surplus. There are plenty more case studies
And before you knew it, the cumulative economy created           available to motivate why South Africa should be targeting
by an event planned over six months could amount to a            a GERD of above 5% for the next 20 years.
minimum of R60 million. Tourism is a sector that is broadly
labour absorptive, with a high velocity of money. This is an     Digitally Intensified Workplaces
economic low hanging fruit that South Africa has to take
advantage of in a post-COVID-19 economic environment.            COVID-19 has ironically become a vitamin B shot for digital
                                                                 transformation and the future way of work. Microsoft has
A human capital and innovation centred                           seen a significant increase in user minutes as lockdowns
long-term aggregate output economy – A                           have been implemented among various countries around
Paul Romer reality                                               the world, as a result of the Covid-19 global pandemic. On
                                                                 the 31st of March Microsoft teams hit a daily record of 2.7
According to Romer’s endogenous growth theory, capital           billion meeting minutes in one day, a 200 percent increase
only accounts for one third on the variation in income per       from 900 million on 16 March 2020. With the advent of the
capita across countries – leaving the other two thirds to        Fourth Industrial Revolution, we have already found
total factor productivity, the product of an investment in       ourselves living in an increasingly digitalised world. Not
human capital, innovation and the knowledge economy.             only are we collaborating through digital platforms
One of the critical things we will need coming of the            internally with colleagues, but communication with custom-
COVID-19 pandemic is a labour investment strategy as well        ers is occurring through digital channels and products are
as a complimentary R&D agenda that will inform the scale         being offered to consumers digitally. Again, delivery can
of long-term economic growth that is required to catapult        and should continue as per normal if the infrastructure to
labour absorption.                                               enable these channels is accessible and functional. The
                                                                 outbreak of COVID-19 and the subsequent enforcement of
The National Advisory Council on Innovation estimated that       social distancing and lockdowns across the world has then
South Africa’s gross expenditure of research and development     forced us to test just how digitalised we are. Companies
(GERD) spend as a proportion of GDP was 0.68% in 2018,           that have committed to digitalising their products and the

12
way they communicate with customers will see the benefits             inequality of opportunity are likely to be exacerbated in a
of this during this time but companies that have also made           time like this. Labour force participants in industries and
an effort to digitalise their entire operating model should           occupations that cannot digitalise or work remotely during
be in a position where they can minimise adverse impacts             a COVID-19-induced lockdown, are likely to be most affected
to business activity.                                                and these happen to also be labour force participants in
                                                                     lower income groups.
It is important to acknowledge that not all businesses are in a
position to digitalise. Either due to scale or the very nature of    Re-shoring Supply Chains
their work, many companies will struggle as a result of the
Coronavirus outbreak. The hospitality industry, for example,         The import-demand ratio (IDR) explains the percentage of
will be particularly affected due to its reliance on people being     imports required to satisfy domestic demand. According to
able to move freely and visit their establishments. Small            the International Trade Administration Commission of South
businesses that were also heavily reliant on the routine foot        Africa (ITAC) mining and manufacturing have been the most
traffic brought about by proximity to central business                 dominant contributors to what has been an increasing IDR
districts and public transport hubs will also suffer from the         from 1996 to date with declines only experienced during
reduced movement of people on a daily basis. Although the            the financial crisis of 2008. Figure 3 below shows that the
lockdown is a very unique response to a very unique                  global economy is particularly susceptible to rising import
challenge, we have not seen a global health pandemic of              intensity in the medical products space given that a
this size for almost a hundred years, this does again draw           minimum of 60% of export volume is attributable to three
attention to problems of inequality around the world but             exporters.
especially countries like South Africa. Income inequality and

FIGURE 2: TOTAL EXPORTS TO WORLD AND SHARES IMPORTED FROM TOP 3 EXPORTERS
OF COVID-19 MEDICAL PRODUCTS
Nitrile and sterile gloves                                             80%                                      60%
Ventilators, oxygen masks and nebulizers                               65%                                      35%
Patient monitors and pulse oxi meters                                  65%                                      35%
Medical Masks                                                          77%                                      23%
Hand Sanitizer                                                         65%                                      23%
Flow-spitter for (oxygen supply)                                       65%                                      35%
Catheters                                                              65%                                      35%
Enzymes                                                                68%                                      32%
Humidifiers                                                             64%                                      36%
Venturi masks                                                          65%                                      35%

    World impact share from Top 3 Exporters %       From rest of the world %

Source: Peterson Institute for International Economics

                                                                                                                            13
COVID-19 has necessitated government and its agencies to            and commitment. Tilapias constituted over 90 percent
explore ways to support the development of local medical            of the total aquaculture harvest. The Government has
product manufacturing to ensure we are able to meet the
                                                                    placed aquaculture as one of the top priorities in the
health needs of the population in a context of rapidly rising
                                                                    country’s    development      agenda     and    substantial
infection rates. In the true spirit of “never letting a good
                                                                    support is being given to fish farmers in various
crisis go to waste” the policy makers have been presented
with an opportunity to take a more permanent view to building       aspects of the industry” FAO (2016)
domestic manufacturing capacity for critical sectors. Maybe
our reindustrialisation strategy should channel resource to         The Ghana case study not only enables us to think about

building domestic manufacturing capacity towards priority           the opportunities of expanding the potential output of our

sectors as well as the sectors where South Africa already           fisheries sector as a labour absorptive, high value goods

enjoys a comparative advantage continentally and globally           sector but also on the policy / legislative balancing act

including but not limited to citrus, macadamia, avocado             required to embark successfully on a sustainable growth path.

farming, medicinal bio diversity, viticulture etc.
                                                                    The Social Compact
Leveraging incentives
                                                                    The uncharted territory global economies find themselves

It is an opportune time to revisit the DTI sector code incentives   necessitate a move away from ideologues and towards a path

to ensure that we are able to sufficiently exploit incentives         of collaboration toward sustainable long-term development

as a crowding in mechanism for inward investment into target        outcomes. When asked about struggle songs and the value

sectors of the economy. When the economy is constrained             thereof, former President Mandela said that “it was the

in its ability to drive fiscal stimulus, then ought to explore way   time and space we couple be united in mission, irrespective

to use our current resources and infrastructure to drive            of our individual backgrounds”. Maybe the COVID-19

investment. Ghana embarked on what would ordinarily be              pandemic is the struggle song South Africa needed in order

deemed as a counterintuitive policy by allowing for tax             to refresh, and rejourney towards a new normal informed

exemptions for fish farming inputs, which on balance                 mutually benefit social compacts between government,

would reduce the cost of farming the high value Talapia             labour, business and civil society.

domestically. So the policy was pro import intensity for the
net benefit they expected in potential output.

“Fish farming has grown rapidly from 1 200 tonnes in
2005 to 38 500 tonnes in 2014, spurred by high prices
of tilapia, the quickly expanding cage farming in the
Volta Basin and the high level of government interest

14
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                                                                                                                                                                   15
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