Authors: Erika Martínez Fernández, Lina Tafur Marín, Laura Silva Aguilar, Susana Martinez-Restrepo
Employment loss brought by the COVID-19 crisis mainly shifted towards inactivity rather than unemployment. It is estimated that from the 114 million lost jobs in 2020 globally, 33 million translated into unemployment and 81 million into inactivity, [1] being women the most affected, particularly women in the Global South. Prior to the onset of COVID-19, women in the Global South were already underrepresented in the labor force with Inactivity Rates that almost doubled men’s, females reaching on average 57% and males 28%. [2]
The adverse effects of the economic crisis triggered by COVID-19 have equally hit hard women holding vulnerable employment in urban areas and women in agriculture in rural areas whose work has been traditionally unrecognized by National Accounts Statistics. The lack of recognition is explained by the fact that workers, especially women, underreport their employment status, [3] which leads to gaps and biases in recording occupations accurately within labor statistics. [4]
This brief explores the linkages between women’s inactivity and their high share in rural unrecognized and/or unpaid occupations, especially in agriculture, amid COVID-19. The analysis is conducted using 2019, 2020, and 2021 annual indicators by ILOSTAT and the 2021 World Bank Women, Business and the Law data. These resources combined enable a deep understanding of why women were hit the hardest by the economic effects of the COVID-19 crisis. “Women’s inactivity and their participation in agriculture jobs during COVID-19” is the third brief of the series Gender and COVID by Corewoman and Cepei.
One of the challenges to carry out this analysis is the limitations of the variable “contributing family workers” from ILO to make inferences regarding women’s status of employment in rural areas. Although it serves as a proxy, it is worth mentioning that not all jobs performed under this category are unpaid agricultural jobs. In this context, this brief introduces the concept of unrecognized and/or unpaid agricultural jobs, referring to those performed by some women in rural areas but that remain undocumented or overlooked by official databases. In addition, recent datasets about employment in agriculture for Global South regions are pre-COVID-19 (from 2019), limiting modeling calculations to compare and break down by sex pre and post-COVID-19 differences in employment status for women holding jobs in the sector.
INACTIVITY: CULTURAL NORMS, LACK OF REGULATIONS, AND THE COVID-19 CARE CRISIS
Even before the pandemic, women were more likely than men to be out of the labor market or remain inactive. [5] Inactivity is understood as the percentage of working age people who are jobless and are not looking for a job, meaning they are outside of the labor force. [6] During COVID-19, female labor force participation continued to decline since many women actively looking for a job stopped their search. Two factors shed light on the increased inactivity among women. First, women, especially working mothers, have disproportionately undertaken the caregiving burden amid mobility restrictions to stop the spread of COVID-19, resulting in schools and childcare facilities closures and more women quitting their jobs. Second, employment loss affected feminized sectors the most. Globally, the average share of women’s employment was higher in three of the four most affected sectors: accommodations and food services, retail and wholesale trade, and other services. [7]
Inactivity has costly implications for women. Once women become inactive for a long time, they may struggle to go back to the labor force, [8] as has occurred during COVID-19. This situation leaves them with low possibilities of having stable employment with decent work conditions or getting a pension, threatening their economic freedom opportunities in the short and long term.
Figure 1 shows inactivity data in the Global South before and after COVID-19 (2019-202). Figure 1A suggests that before COVID-19, female Inactivity Rates in the Arab States and Southern Asia were already exceptionally high, with a gap ranging between 60 and 54 percentage points compared to men. Conversely, women in Sub-Saharan Africa experienced the smallest Inactivity Rate gap relative to other subregions of the Global South. Similarly, Figure 1B exhibits the changes in the Inactivity Rate by sex and regions for 2019-2020 and indicates a slight increase in Eastern Asia by 1.6 percentage points but modest stability in Central and Western Asia, Southeastern Asia, Latin America and the Caribbean. However, women in Sub-Saharan Africa, who before COVID-19 had the smallest gap in Inactivity Rates in the Global South, experienced the highest variation, which could be associated with the adverse effects of COVID-19.
By 2021, the share of inactive women and men by region was less nuanced than changes in the Inactivity Rate for the 2019-2020 period, as Figure 2 indicates. Inactivity is higher in subregions where culture can be a restrictive factor for women’s participation. For example, [9] in the Arab States, [10] 82% of women have been inactive by 2021, mainly because they face legal restrictions on their capacity and ability to get a job and need permission from their family or husbands to be employed. [11] Likewise, Southern Asia (77.3%), which also exceeds the average inactivity in the Global South (56%), could reflect the effects of weak or non-existant mechanisms to prohibit discrimination in employment based on gender. Despite restrictions on women’s legal capacities to get a job in Sub-Saharan Africa, the prevalence of vulnerable employment over formal employment, even for men, is likely to promote women’s participation in the labor force, primarily in occupations of the agricultural and service sectors, sometimes both, but frequently holding vulnerable employment.
RURAL WOMEN IN AGRICULTURE AMIDST COVID-19: MOSTLY UNRECOGNIZED AND UNPAID
Women contribute 25.3% of the agricultural labor force worldwide. [12] According to the most recent comparable data across countries, women in the Global South constitute 43% of the agricultural workforce. Drilling down at the Global South subregional level, the female share of the labor force in the sector is 26% in Latin America. However, relative to other Global South subregions, a more significant proportion of women in Sub-Saharan Africa and South Asia —53% and 57%, [13] respectively— rely more on the jobs provided by the agricultural sector to participate in the workforce and generate income.
Rural women are often involved in activities that overlap between productive and caregiving activities. Some of them include growing crops and harvesting, feeding animals, collecting water, processing and preparing food, or caring for other household members. The problem with such overlap is that despite the evident contribution of women to rural economic activities, they are very often disregarded as “economically active employment” in national accounts statistics which, as a result, limits the accurate identification of the impact COVID-19 is having on women in agriculture. [14]
In the Global South, a small proportion of the population is in wage labor, with women being less likely than men to work for wages. [15] Moreover, although women are by and large the principal caregivers of households globally, the burden is even heavier for women who work in agriculture in the Global South. Unpaid care work, including cleaning, cooking, collecting water and firewood, and taking care of children and the elderly, puts excessive pressure on rural women and drives their education attainment levels down. [16] This context favors female labor participation in low-productivity employment in smallholder agriculture or vulnerable employment severely affected by COVID-19.
Rural women in agriculture usually engage their work in the sector as own-account workers in their farms, as unpaid workers on family farms, and as paid or unpaid employees on other farms and agricultural enterprises. When women in rural areas work as paid employees, they are more likely than men to hold seasonal jobs, part-time, and low-wage jobs; However, they are often more prone to work as unpaid workers on family farms.
As noted in previous sections, this brief uses the variable “contributing family workers” as a proxy to analyze the status of employment of women in rural jobs, although acknowledging its limitations. As seen in Figure 2, the share of women as contributing family workers and own-account is higher among rural women than urban women, which hints at a higher vulnerability of employment in rural areas. This insight reveals that a significant share of contributing family workers and own-account workers interchange between agriculture and service occupations that are within agricultural value chains. The largest gap between rural and urban women in self-employment is Eastern Asia (27.9 pp) and Latin America and the Caribbean (25.2 pp), pointing to a lack of formal employment in rural areas compared to urban areas, which leads women to become self-employed. However, the subregions with the highest proportion of contributing family workers are South Asia (39.6%) and Sub-Saharan Africa, suggesting that a significant number of rural women work as agricultural workers.
It is estimated that when women work in commercial farms as contributing family workers or as paid or unpaid employees in other farms, they participate as informal workers in value chains [17] severely affected by mobility restrictions and new sanitary requirements due to COVID-19. [18] Although the impact of these measures on value chains reaches all rural workers, rural women are less likely to own land and productive assets than men, which makes them particularly vulnerable to economic shocks and accessing loans to mitigate its effects. [19]
Evidence suggests a current wave of feminization of agriculture linked to men leaving rural areas to work in urban centers. [20] Nevertheless, it is worth mentioning that such dynamics in the sector do not necessarily translate into more land-ownership and income for women, which usually limits their productivity and full inclusion into the agricultural economy. [21] Emerging evidence during COVID-19 indicates that as women had less access to formal loans to buffer the income loss and spent more time caring for other family members, they invested less time on income-generating activities [22] affecting their household income. [23]
CONSIDERATIONS FOR POLICY ACTION
During the onset of the COVID-19, women in the Global South have been struggling with vulnerable unemployment and high informality and Inactivity Rates. Despite the disproportionate effects of the pandemic on women, they have not been at the core of the economic recovery plans set out by governments, as most initiatives continue to lack gender dimensions and benefit mainly male labor-intensive sectors. Some of the big steps to break such a path in policymaking are the following:
Promote Tax Incentives for Women’s Re-Engagement in the Labor Markets
Tax incentives can create new opportunities for women to access traditionally male-dominated sectors and promote women to re-enter the workforce. [24] In 2013, the Malaysian government placed a tax incentive program giving income tax exemptions for up to 12 months to encourage women to re-enter the labor force after motherhood. This type of incentive could lessen the impacts of COVID-19 and promote women’s comeback to the workforce. Also, public and private organizations must consider women’s constraints to prevent women from leaving their jobs, which would stop female unemployment and inactivity from increasing.
Collect Reliable National-Level Data on Women’s Labor Market Contributions, Especially in Agriculture
There is a need to fill data gaps on women’s inactivity, but especially on their role in agriculture, to shed light on the individuals and communities affected by gender inequality and the magnitude of the impact caused by COVID-19. Data from agricultural census around the globe should be sex-disaggregated to understand women’s insertion in agricultural value chains and their role and opportunities in the sector. Applying other data forms, such as Big Data, could be instrumental in filling data gaps. [25] In the same line, standardized methodologies could measure women’s inclusion in agriculture and make it comparable globally. The Women’s Empowerment Agriculture Index (WEAI), for instance, measures women’s empowerment within their households and communities and can account for inequality levels between men and women to address the challenges in their empowerment process within the agricultural sector. [26]
Tackle Legal Barriers That Hinder Rural Women’s Access to Credit and Property
Access to land, productive assets, and equal rights to control property are essential to promote women’s sustainable work in agriculture, especially when agriculture is increasingly becoming feminized and the primary source of income for women living in rural areas. Moreover, legal discrimination or the lack of legal protection affects women’s likelihood for applying and accessing financial services and thus their ability to save, borrow and get insurance, which is critical to bounce back from the COVID-19 economic shock. Therefore, regulations to protect rural women against discrimination from accessing productive assets and credits should be a priority for governments of the Global South in recovery policies amid COVID-19. Such mechanisms will allow women to engage more in waged labor rather than unpaid work. It will also enable them to generate income and, in the long term, the possibility of innovating and formalizing their small self-subsistence farms into business initiatives that could lead to a more inclusive recovery for women in rural areas.
[1] The Inactivity Rate is the number of persons of working age outside the labour force (that is, not employed or unemployed) expressed as a percentage of the working-age population. International Labour Organization. (2021). ILO Monitor: COVID-19 and the world of work. Seventh edition Updated estimates and analysis. https://www.ilo.org/wcmsp5/groups/public/@dgreports/@dcomm/documents/briefingnote/wcms_767028.pdf
[2] International Labour Organization. “ILO Data Explorer”. International Labor Organization, 2020. https://www.ilo.org/shinyapps/bulkexplorer1/?lang=en&segment=indicator&id=EAP_2WAP_SEX_AGE_RT_A.
The Inactivity Rate for the global South is the result of the average inactivity of all the regions of the global South included in the document
[3] ILO 1993 International Classification of Status in Employment (ICSE-93) classifies jobs into five main categories, which can be grouped under two main types of jobs: paid employment jobs (employees) and self-employment jobs (employers, own-account workers, contributing family workers and members of producers’ cooperatives).
Durr, Jochen. “Women in Agricultural Value Chains: Unrecognized Work and Contributions to the Guatemalan Economy.” AgEcon 3, no. 2 (2018): 20–35. https://doi.org/10.22004/ag.econ.293597.
[4] Data collection instruments usually overlap occupations in agriculture with unpaid caregiving activities, which hinders accurate measurement of national labor statistics across countries in the Global South (FAO, 2010).
[5] Karkee, Vipasana, and Marie-Claire Sodergren. “How Women Are Being Left behind in the Quest for Decent Work for All.” ILOSTAT. International Labour Organization, March 29, 2021. https://ilostat.ilo.org/how-women-are-being-left-behind-in-the-quest-for-decent-work-for-all/
[6] ILOStat. Persons outside the labour force: How inactive are they really? Spotlight on work statistics. International Labour Organization.
[7] Madgavkar, Anu, Olivia White, Mekala Krishnan, Deepa Mahajan, and Xavier Azcue. Covid-19 and Gender Equality: Countering the Regressive Effects. Mckinsey Global Institute. Mckinsey, July 15, 2020. https://www.mckinsey.com/featured-insights/future-of-work/covid-19-and-gender-equality-countering-the-regressive-effects.
[8] International Labour Organization. ILO Monitor: COVID-19 and The World of Work. Seventh Edition. International Labour Organization.
[9] World Bank Group. Women, Business and the Law. World Bank Group, 2021. https://wbl.worldbank.org/en/wbl.
[10] Referred to as the Middle East and North Africa in the 2021 World Bank’s Women, Business and the Law
[11] Ibid.
[12] International Labour Organization. ILOSTAT database, Employment in agriculture (% female employment), 2021. Data are from 2019 but the last update are from 2021.
[13] International Labour Organization, ILOSTAT database, 2021. Employment in agriculture (% female employment), 2021. Data are from 2019 but the last update are from 2021.
[14] FAO. (2011). Women in Agriculture: Closing the Gender Gap for Development. http://www.fao.org/3/i2050e/i2050e.pdf
[15] The World Bank. (2007). Agriculture for Development. https://openknowledge.worldbank.org/handle/10986/5990
[16] Actionaid. Rep. Incorporation of Women’s Economic Empowerment and Unpaid Care Work into Regional Polices: Africa. ActionAid, 2017. https://actionaid.org/publications/2017/policy-brief-incorporation-womens-economic-empowerment-and-unpaid-care-work
[17] Deere, Carmen Diana. Rep. The Feminization of Agriculture? Economic Restructuring in Rural Latin America. Geneva: United Nations Institute for Social Development, 2005.
[18] OECD. COVID-19 and the food and agriculture sector: Issues and policy responses, 2021
[19] FAO. Gendered Impacts of COVID-19 and equitable policy responses in agriculture, food security and nutrition, 2020. http://www.fao.org/policy-support/tools-and-publications/resources-details/es/c/1276740/
[20] Slavchevska, Vanya, Susan Kaaria, and Sanna Liisa Taivalmaa. “The Feminization of Agriculture.” The Oxford Handbook of Food, Water and Society, 2019, 267–84. https://doi.org/10.1093/oxfordhb/9780190669799.013.55.
[21] African Development Bank. Rep. Economic Empowerment of African Women through Equitable Participation in Agricultural Value Chains. Abidjan: African Development Bank , 2015.
[22] Feed the Future. Assessing the Impact of Covid-19 on Rural Women and Men in Northern Ghana. The US Government’s Global Hunger & Food Security Initiative.
[23] Meeme, Verenardo. “African Women in Agriculture Suffer Disproportionately in COVID-19 Pandemic.” Alliance for Science. Cornell, February 23, 2021. https://allianceforscience.cornell.edu/blog/2021/02/african-women-in-agriculture-suffer-disproportionately-in-covid-19-pandemic/.
[24] Ibid.
[25] Brennan, Elliott. “Leveraging Big Data for Gender Equality in Agriculture.” Food Tank, April 30, 2018. https://foodtank.com/news/2018/03/cgiar-platform-big-data-agriculture-international-womens-day-pressforprogress/.
[26] http://ebrary.ifpri.org/utils/getfile/collection/p15738coll2/id/126937/filename/127148.pdf