However, the expected recession caused by the current COVID-19 pandemic could lead to worse labor market outcomes for women, exacerbating gender inequality in the labor market. Through a lens of occupational classification, this study highlights how the COVID-19 pandemic may disrupt the progress made by women in the South African labor market. In the past, depressions and recessions have inadvertently reduced gender inequality in the labor market.
On the other hand, manufacturing represents 8% of employed women, and the share of women in this sector is around 32%. There is already evidence that the COVID-19 pandemic has increased inequalities both in the labor market and in wider society (Statistics South Africa 2020, Adams-Prassl et al. The narrowing of the wage gap at the bottom of the wage distribution is an interesting example.
At the top of the wage distribution, there are more occupational choices for women than at the bottom of the wage distribution. Furthermore, the occupational distribution gap in the wage distribution is much more pronounced for women than for men.
4 Working during ‘hard’ lockdown
This advantage stems from the fact that women in South Africa are, on average, more likely to complete secondary school and more likely to graduate from university (Van Broekhuizen & Spaull 2017). For example, looking at the 9th and 10th deciles, while women are more likely to be in office, teaching, life science and health professions, men are more likely to be in the management of small businesses and in physical science subject. This is because most of the occupations in the essential services category are male-dominated, including miners, construction workers, drivers and mobile machine operators, agricultural workers and protective services.
In addition, the high proportion of women in professional, technical and clerical occupations means that the gender share in the 'both' category (primary work and work from home) is almost equally divided. A breakdown of these classifications by race5 shows that while the majority of employed South Africans are likely to be classified as 'none', this is particularly the case for Africans. Most Africans (66.5%) and blacks (59.89%) fit neither category, compared to 41% of whites. In addition, there is a higher proportion of African and Colored South Africans in basic services and a higher proportion of Asian and white South Africans in the 'work from home' category.
This is related to the relationship between occupational classification, education, and race discussed in the previous section. Empirical evidence both pre- and during the COVID-19 pandemic shows that women were more likely to cope with the "triple burden" of childcare, housework and office work during the "severe" quarantine period. especially the closure of schools and child development centers. Furthermore, women spend up to 5.8 times more time8 than men on personal grooming (men spend only 5 minutes per day on personal grooming, while women spend 29 minutes per day on personal grooming) (Statistics South Africa 2013).
8 According to Statistics South Africa (2013), the care of persons in the household includes care. Women who are able to work from home (or in the 'both' category) are more likely to live with children than men. In this category, women are about 5 percentage points more likely than men to live with very young children and up to 15 percentage points more likely to live with 7-14 year olds.
Thus, a disproportionately large proportion of children in South Africa live in households with women in the group most vulnerable to job loss during severe lockdown.
5 Risky work in a pandemic: physical proximity and exposure to infectious diseases
Of the categories that allowed individuals to continue working, differences in cohabitation with children between men and women are largest for the 'essential services' category. This suggests that during 'hard times', more women than men in jobs classified as essential service work may have had to stop working because of childcare responsibilities, even though their jobs were classified as essential. Moreover, Table 4.2 shows that the difference between men and women living with children is more pronounced for the 'none' category, the category to which 66% of employed women belong (see Table 4.1).
The period of 'hard lockdown' presented a unique situation which brought inequalities in working environments and society into focus. As explained in the method section, the occupational scores are ultimately continuous variables, as the average of respondents is scored. Our definition of 'nearby' or 'exposed' work then corresponds to scores equal to or to the right of the dashed vertical line.
The occupations that fall to the left of the red line in the adjacent employment figure are mainly agricultural workers, grounds and building managers, and some senior office workers who probably have their own offices. In contrast, the right figure shows that most people are not exposed to infections or diseases in their daily work. Indeed, professions considered exposed are largely related to healthcare or professions where workers regularly come into contact with nature.
The "none" category can to some extent be interpreted as defining the safest occupations in terms of risk for COVID-19. Women are generally more likely to do proximal work than men: 77% of women compared to 70%. However, women are much more likely to be exposed to infection or disease even in this direct work: 23% of women's jobs are both exposed and direct, 16 percentage points more than men.
This is mostly driven by the fact that at the bottom of the wage distribution (see Figure A.1) there is a greater proportion of women working in occupations that are both close and exposed.
6 Gendered occupational sorting and vulnerability
The variables for working from home and essential services are from Kerr & Thornton (2020) and variables for proximity and exposure were created from O*NET data on occupational tasks by the. Two-digit occupational code and description per occupation. sorted by proportion of women) Woman Man Essential work of nearby exposed women. Two of the four main occupations in which women work – domestic work and personal care – represent highly vulnerable work.
Moreover, these women are more often at the bottom of the wage distribution (see Figure A.1 in the appendix). This is because women in this part of the wage distribution work in occupations in which they come into direct contact with other people who may be suffering from an infectious disease. The implications here are, as noted above, that women in this part of the wage distribution are at greater risk of losing their income because they were unable to work at all during the 'hard lockdown', or if they were able to work, either because they were essential workers or as a result of the easing of restrictions on economic activity, they are still at greater risk of coming into contact with the virus.
These ideas are set out in Table 6.2, which divides the working into three mutually exclusive categories: those who could work from home; those who could not but were essential workers; and those who could not work from home and were not classified as essential workers. Those who could work from home were supposedly able to continue their economic activity and protect themselves to some extent from losing their job or income. Those who could not work from home, but who were classified as essential, were presumably in occupations that are critical to the functioning of the 'pandemic economy' in which South Africa has both basic economic needs (such as food production) but also urgent balancing public health needs.
First, more women are in the most vulnerable category of occupations that cannot be carried out from home and were in sectors not classified as essential. Women who cannot work from home and who were not essential workers are more likely to be in close and exposed work, i.e. women who cannot work from home but who were classified as essential workers are 8 percentage points (or 40%) more likely than men in the same category to be exposed to infection.
Similar proportions of men and women can work from home, where both exposure and proximity are low, but as noted above, there is evidence that women take on much more housework and childcare, which hampers their ability to do their jobs.
7 Discussion
As we have seen during this pandemic, female-dominated occupations are just as important and just as risky as male-dominated occupations, and during this pandemic there were just as many women on the front lines as men. Third, researchers have been advocating flexible working hours for some time to protect women from the burden of worry they suffer from a double shift in the labor market and housework. It has become apparent that the relevant issue of childcare needs to be addressed, although one of the effects of the COVID-19 pandemic has been the fast-tracking of work-from-home policies into the labor market.
2020), Essential workers, working from home and vulnerability to job loss in South Africa, Technical report, DataFirst, University of Cape Town. 2020), 'Occupational exposure to contamination and the spread of covid-19 in Europe'. 2020), 'Characteristics of workers in low work-from-home and high personal proximity occupations', Becker Friedman Institute for Economic White Paper. Mosomi J (2019a) 'Distributional changes in the gender wage gap in the post-apartheid South African labor market', WIDER Working Paper 2019/17, Helsinki: UNU-WIDER.
An empirical evaluation of gender discrimination in employment, occupation and wages in South Africa in the late 1990s. Paper presented at the DPRU/FES Workshop on Labor Markets and Poverty in South Africa, Johannesburg. Statistics South Africa (2020), Quarterly Labor Force Survey, Statistical Release P 'The Martha effect': The compound female advantage in South African higher education'.
Appendix
