Unpaid Work An Obstacle to Gender Equality and Economic Empowerment including Women s Labour Force Participation Indira Hirway Centre For Development Alternatives, India Expert Trigger Presentation Sex-disaggregated data for the SDG Indicators in Asia and the Pacific Bangkok, May 25-27 2016 This presentation discusses What is unpaid work and why we are concerned about it Meaning of recognition of unpaid work in statistics, and how we can give visibility to unpaid work What is the state of data collection to track unpaid work in ESCAP region? Impact of unequal distribution of unpaid (and paid) work on labour market performance of women? Which are the groups of unpaid workers that need special attention so that they are not left behind? How adequate is the indicator 5.4.1 for measuring women s unpaid work? 1
Concept of Unpaid Work Unpaid work is essentially that work which does not receive any direct remuneration Unpaid non-sna work: household upkeep, care and voluntary services Unpaid SNA work: unpaid family help, subsistence production and collection of free goods No/low visibility, poor recognition and excluded from national policies Why are we concerned about unpaid work - 1 The demarcation line between paid and unpaid work is a line of patriarchy that excludes women from the economy Some built-in weaknesses of unpaid work Unpaid is highly unequally distributed between men and women; paid work is also unequally distributed, and in most cases women carry, on an average, larger burden of total work than what men carry Unequal distribution of unpaid work could be violation of human rights of unpaid workers 2
Continued The distribution of unpaid work is not a matter of free choice. It is imposed on women as a social construct It is a life time tax on women that pushes them into invisibility/marginexclusion from mainstream economics That is why it is included as an important goal in SDG Giving visibility to Unpaid Work in data through time use surveys Role of time survey is giving visibility to unpaid work of men and women In-depth picture of participation and the average time spent by men and women on different SNA, non-sna and personal activities Information on the overall burdens of work on men and women, time spent on drudgery by men and women, time stress experienced by men and women Determinations of gender inequalities in the patterns of time use (area based, household based and individual characteristics) Impact of the unequal distribution of time by men and women on women s opportunities in life (compared to men s), i.e. impact on labour market, human capital formation and social capital formation 3
Table 1 Status of TUS in the Selected Countries Status Countries Developed countries where TUS is mainstreamed Australia, Japan, Korea (ROK), New Zealand No TUS conducted Afghanistan, Brunei Darussalam, Maldives Marshall Islands, Myanmar, Palau, Singapore Small TUS only Indonesia, Fiji, Kiribati, Papua New Guinea, Samoa, Solomon Islands, Sri Lanka, Tuvalu and Vanuatu Official Pilot TUS only Only Rural / urban TUS National modular TUS Philippines Iran (Islamic Republic) only urban TUS Cambodia, Lao PDR, Nepal, Timor Leste, Malaysia, Vietnam, Cook Islands National / Large TUS using time diary Bangladesh, China, India, Mongolia, Pakistan, Thailand Countries with only small scale time use surveys Objectives Small sample, small period, snapshot of a day Data collection methods Classifications used Pilot surveys 4
Why countries have not conducted National time use surveys? Costs are high Low level of literacy Poor some of time for some people Technical expertise to collect and analyze the data Poor appreciation of national time use data National modular time use surveys LSMS and modular time use surveys LFS and modular time use surveys Other national surveys and modular time use surveys 5
Problems with modular time use surveys Apparent advantages Limited scope for data collection Use of stylized questions and their limitations When 24-time diary is a module National time use surveys using 24-hour time diary Objectives Background questionnaire Sampling of households and members Time sampling 6
Continued Data collection methods Simultaneous activities Classification of time use activities Context variables Major Weakness of time use surveys Background questionnaire Sampling- household/members and time sampling Data collection methods Simultaneous activities Classification of time use activities Issues related to terminology 7
Some observations Positives developments Long way to go mainstreaming time use surveys in national statistical systems Main constraints in mainstreaming time use surveys Need to use 24-hour time diary based national time use surveys -one in 3-5 years Inferences for the future Standardization and harmonization Capacity building of stakeholders Mainstreaming time use surveys Recent resolution on statistics on work 8
Unpaid work and performance of women in the labour market Unpaid work, backed by social norms, restrict performance of women in the labour market in multiple ways UW restricts women s participation in the labour market UW and social norms tend to affect human capital formation among women adversely Managing UW responsibility along with labour market work restricts women s choice of work Continued.. Women overcrowded in low productivity, low wage activities and enjoy relatively low diversification Low mobility of women restricts upward and horizontal mobility of women in the labour market Women get overall low wages due to segregation as well as discrimination in the labour market Women experience higher incidence of unemployment due to their multiple limitations 9
Our analysis of micro time use data in two countries UW, the most important factor that keeps women away from the labour market (71% women reported that they are not in the labour market due to their unpaid work responsibilities) Of those women in the labour market, 38.4% are unpaid family helpers (8% of men), 23% women workers are piece-rated workers (7.5% men worker), 17% women workers regular workers (29% men workers) 22% men workers in the formal sector, against 10% of women workers, 70% men workers are own account self-employed against 74% of women workers, and the rest are in other categories of enterprises 72% of women workers receive monthly income up to Rs 2000 as against 42% of men workers, and 15% of men workers earn more than Rs 9000 as against 3% of women workers Groups likely to be left behind if data not collected Interest of all women is compromised if unpaid work is neglected policies based on a partial view of the economy will be faulty Women who are poor and in the labour market Women who are time poor Women in agriculture Women in remote/lagging areas women in care of chronically sick including HIV/AIDS care 10
Unpaid work and SDGs Inequalities in the time use, and particularly the inequalities in the time spent on unpaid work by men and women have significant impact on gender equalities and women s empowerment Unpaid work or inequalities in the time use of men and women impact on almost all SDGs somehow not recognized implicitly under the SDGs Need to make all SDGs gender sensitive in the context of one major constraint of women, namely, unequal distribution of unpaid work between men and women Inclusion of unpaid work in SDG framework SDG 5.4: Recognize and value unpaid are and domestic work through the provision of public services, infrastructure and social protection policies, and the promotion of shared responsibility within the household and the family as nationally appropriate SDG 5.5: Ensure women s full and effective participation and equal opportunities for leadership at all levels of decision making in political, economic and public life SDG indicator 5.4.1 Proportion of time spent on unpaid domestic and care work, by sex, age and location 11
Indicator 5.4.1: Proportion of time spent on unpaid domestic and care work, by sex, age and location Very valid indicator, as it has significant impact on gender equality and women s empowerment Need to put a time line for achieving this goal (no time line has been given to the goals and targets on gender equality) By 2020, each country should mainstream time use surveys in their natural statistical systems In order to highlight women s double burden on additional indicator can be added: Ratio of total work(sna + non-sna) by men and women Time spent by men and women on leisure, rest and relaxation 12