Strengthening Gender Statistics (SGS) Project How to Compute SGS Priority Indicators Contents I. INTRODUCTION A. Importance of Metadata for Indicators B. List of Indicators II. ASSET INDICATORS Know the reporting standards – the definitions, concepts and units of measurements used to collect and compute the data per indicator should adhere to agreed upon international standards for each III. EMPLOYMENT INDICATORS IV. ENTREPRENEURSHIP INDICATORS 2 I. Introduction Introduction This document provides Here, metadata are instructions comprehensive metadata on The list of SGS indicators have about how to measure each SGS the 22 SDG and UNSD gender- been divided among the indicator in a standardized way so related indicators in the following three categories: that regional and global statistics economic domain that are part 1. Asset Indicators can be produced and progress of the Strengthening Gender 2. Employment Indicators compared over time and across Statistics (SGS) project. 3. Entrepreneurship Indicators borders. Metadata presented includes information on the following: Gender-related indicators are essential to inform 1. Definition and Concept strategies, policies and 2. Rationale (why it matters) programs, increase 3. Data Source and Collection awareness and monitor 4. Method of Computation gender-related targets. 5. Limitations or Challenges 4 Importance of Metadata for Indicators For successful measurement of any gender-related indicator, it is important to: Understand the rationale – how the collection and computation of data to measure that indicator can help in advancing the gender and development goals of a country Know the reporting standards – the definitions, concepts and units of measurements used to collect and compute the data per indicator should adhere to agreed upon international standards for each Use appropriate methodology – data collection and computation methods must be used correctly 5 List of Indicators — Asset UNSD Minimum # Indicator Description SDG Indicator Indicator Proportion of adults (15 years and older) with an account at a bank or other 1 8.10.2 I.11 financial institution or with a mobile-money service provider 2 Proportion of individuals who own a mobile telephone, by sex 5.b.1 I.18 a) Proportion of total agricultural population with ownership or secure rights 3 over agricultural land, by sex; and (b) share of women among owners or rights- 5.a.1 I.12 bearers of agricultural land, by type of tenure Proportion of total adult population with secure tenure rights to land, (a) with 4a 1.4.2 legally recognized documentation Proportion of total adult population with secure tenure rights to land (b) who 4b 1.4.2 perceive their rights to land as secure, by sex and type of tenure 6 List of Indicators — Employment UNSD Minimum # Indicator Description SDG Indicator Indicator Average number of hours spent on unpaid domestic and care work, 5 by sex, age and location 5.4.1 I.1 6 Average number of hours spent on total work (total work burden), by sex I.2 7 Labor force participation rate for persons aged 15-24 and 15+, by sex I.3 8 Proportion of employed who are own-account workers, by sex I.4 9 Proportion of employed who are contributing family workers, by sex I.5 Proportion of youth (aged 15-24 years) not in education, employment, or 10 training, by sex and age 8.6.1 I.7 7 List of Indicators — Employment UNSD Minimum # Indicator Description SDG Indicator Indicator Percentage distribution of employed population by sector, each sex (sectors 11 I.8 here refer to Agriculture; Industry; Service 12 Proportion of informal employment in total employment, by sector and sex 8.3.1 I.9 13 Unemployment rate, by sex, age, and persons with disabilities 8.5.2 I.10 Average hourly earnings of female and male employees, by occupation, age, 14 8.5.1 I.13 and persons with disabilities 15 Proportion of employed working part-time, by sex I.14 Prime-age employment-to-population ratio by sex, household type and 16 I.15 presence of children 8 List of Indicators — Employment UNSD Minimum # Indicator Description SDG Indicator Indicator 17 Average income of small-scale food producers, by sex and indigenous status 2.3.2 18 Proportion of women in managerial positions 5.5.2 Proportion and number of children aged 5–17 years engaged in child labor, by 19 8.7.1 sex and age 20a Frequency rates of nonfatal occupational injuries, by sex and migrant status 8.8.1 20b Frequency rates of fatal occupational injuries, by sex and migrant status 8.8.1 9 List of Indicators — Entrepreneurship UNSD Minimum # Indicator Description SDG Indicator Indicator 21 Proportion of employed who are employer, by sex I.6 10 II. Asset Indicators Source: UN SDG Metadata Repository SDG Indicator 8.10.2 / SGS Indicator 1 Proportion of adults (15 years and older) with an account at a bank or other financial institution or with a mobile- money-service provider, by sex Source: UN Statistics Division 12 Definition and Concept • This indicator refers to the percentage of adults • It includes respondents who report receiving wages, (ages 15+) who report having an account (by government transfers, or payments for agricultural themselves or together with someone else) at a products into an account at a financial institution or bank or another type of financial institution or through a mobile phone in the past 12 months; personally using a mobile money service in the past paying utility bills or school fees from an account at 12 months. a financial institution in the past 12 months; or receiving wages or government transfers into a card in the past 12 months. • It includes having an account at a bank or other types of financial institution, such as a credit • Mobile money account includes respondents who union, microfinance institution, cooperative, or the report personally using GSMA Mobile Money for the post office, or having a debit card in their own Unbanked (MMU) services in the past 12 months to name. pay bills or to send or receive money. Proportion of adults (15 years and older) with an account at a SDG 8.10.2/ bank or other financial institution or with a mobile-money-service SGS Indicator 1 provider, by sex Why it matters • Access to formal financial services such as savings, • For women, having access to formal financial insurance, payments, credit and remittances is services can be a step toward financial essential to the ability of people to manage their independence. Therefore, making sex lives, build their futures, and grow their businesses. disaggregation for this data point is crucial in measuring gender equality. • Having access to an account is an important starting point for people to access a range of • Disaggregation by income, age, education level, financial services. urban/rural is also required and provides beneficial information. Proportion of adults (15 years and older) with an account at a SDG 8.10.2/ bank or other financial institution or with a mobile-money-service SGS Indicator 1 provider, by sex Data Source and Collection • The indicator is based on data collected through • Unit of Measure surveys capturing individual-level incomes and • Expressed as a percentage financial details or household surveys. (Example: Family Resources Survey in UK, and Survey of Income in USA) • Previously, this data has been compiled by the World Bank every 3 years since 2011, with the last one in 2017, in the Global Findex report (based on individual-level surveys in various countries). Proportion of adults (15 years and older) with an account at a SDG 8.10.2/ bank or other financial institution or with a mobile-money-service SGS Indicator 1 provider, by sex Method of Computation • The indicator is computed using data generated • If individual-level surveys are using representative through individual-level surveys, measuring samples, appropriate sampling weights have to be individual’s ownership of accounts. used in calculating country-level aggregates. • As financial inclusion is an individual-level concept, this is the appropriate measure. Other surveys that are done at household level may measure the access to finance through another member of the household which may overestimate financial inclusion. Proportion of adults (15 years and older) with an account at a SDG 8.10.2/ bank or other financial institution or with a mobile-money-service SGS Indicator 1 provider, by sex SDG Indicator 5.b.1 / SGS Indicator 2 Proportion of individuals who own a mobile telephone, by sex Source: UN Statistics Division 17 Definition and Concept • This indicator measures the percentage of • Individuals who have only active SIM card(s) and individuals who own a mobile (cellular) telephone, not a mobile phone device are excluded. An active by sex. SIM card is a SIM card that has been used in the last three months. • An individual owns a mobile telephone if he/she has a mobile cellular phone device with at least • Individuals who have a mobile phone for personal one active SIM card for personal use. use that is not registered under his/her name are also included. • Mobile cellular phones supplied by employers that can be used for personal reasons (to make personal calls, access the Internet, etc.) are included. Proportion of individuals who own a mobile telephone, by sex SDG 5.b.1/ SGS Indicator 2 Why it matters • A number of studies have highlighted the link • Monitoring this will help design targeted policies to between mobile phone ownership and overcome the gender divide in this regard. Existing empowerment, and productivity growth. data suggests that less women than men own a mobile phone. • Measuring this indicator is important to track gender equality since mobile phone is a personal device that, if owned and not just shared, provides women with a degree of independence and autonomy, including for professional purposes. Proportion of individuals who own a mobile telephone, by sex SDG 5.b.1/ SGS Indicator 2 Data Source and Collection • The indicator is based on data collected through • Other than sex disaggregation, if data allow individual-level national household surveys. breakdown and disaggregation, the indicator can be (Example: LSMS+ survey in Cambodia) broken down by region (urban/rural), by age group, by educational level (ISCED), by labour force status • ITU (International Telecommunication Union) (ILO), and by occupation (ISCO). ITU collects data collects data for this indicator through an annual for all of these breakdowns from countries. questionnaire that is sent to the heads of national statistical offices (NSOs). • Unit of Measure • Expressed as a percentage Proportion of individuals who own a mobile telephone, by sex SDG 5.b.1/ SGS Indicator 2 Method of Computation This indicator is calculated by dividing the total number of in-scope individuals who own a mobile phone by the total number of in-scope individuals. Calculation for sex-disaggregated data No. of women who own a mobile phone No. of men who own a mobile phone Total female in−scope individuals Total male in−scope individuals Proportion of individuals who own a mobile telephone, by sex SDG 5.b.1/ SGS Indicator 2 Relevant Links ITU Manual for Measuring ICT Access and Use by Households and Individuals 2020: https://www.itu.int/en/ITU-D/Statistics/Pages/publications/manual.aspx Proportion of individuals who own a mobile telephone, by sex SDG 5.b.1/ SGS Indicator 2 SDG Indicator 5.a.1 / SGS Indicator 3 (a) Proportion of total agricultural population with ownership or secure rights over agricultural land, by sex; and (b) share of women among owners or rights-bearers of agricultural land, by type of tenure Source: UN Statistics Division 23 Definition and Concept • This indicator has two sub-parts: • It is important to understand what the different o Sub-indicator (a) measures how prevalent terms in this indicator refer to: ownership / tenure rights over agricultural o Agricultural land land is in the reference population o Adult agricultural population (agricultural households), by sex. o Land ownership o Sub-indicator (b) allows to monitor the share o Land tenure rights of women in agricultural households with ownership or tenure rights over agricultural land over the total individuals with ownership / tenure rights. (a) Proportion of total agricultural population with ownership or secure SDG 5.a.1/ rights over agricultural land, by sex; and (b) share of women among SGS Indicator 3 owners or rights-bearers of agricultural land, by type of tenure Definition and Concept Agricultural Land The 2020 World Census of Agriculture proposed an internationally agreed land use classification, according to which there are nine basic land use classes (LU1-LU9) and agricultural land is a subset (LU1-LU5). (a) Proportion of total agricultural population with ownership or secure SDG 5.a.1/ rights over agricultural land, by sex; and (b) share of women among SGS Indicator 3 owners or rights-bearers of agricultural land, by type of tenure Definition and Concept Adult Agricultural Population The reference population for this indicator is the population whose livelihood is linked to agricultural land – i.e., adult individuals living in agricultural households. A household is considered It has operated land for agricultural purposes or held/tended livestock over the agricultural if: past 12 months, regardless of the final purpose Once a household has been classified as ‘agricultural’, all the adult members are eligible of being asked about their tenure rights over agricultural land. (a) Proportion of total agricultural population with ownership or secure SDG 5.a.1/ rights over agricultural land, by sex; and (b) share of women among SGS Indicator 3 owners or rights-bearers of agricultural land, by type of tenure Definition and Concept Adult Agricultural Population Therefore, an individual is part of the reference population if the following two conditions are met: The individual belongs to a household The individual is an adult that has operated land for agricultural (> 18 years) purposes or held/tended livestock over the past 12 months, regardless of the final purpose (a) Proportion of total agricultural population with ownership or secure SDG 5.a.1/ rights over agricultural land, by sex; and (b) share of women among SGS Indicator 3 owners or rights-bearers of agricultural land, by type of tenure Definition and Concept Land Ownership & Land Tenure Rights It is challenging to define ownership and land tenure rights in a way that provides comparable figures across countries. However, it can be contextualized. • Land ownership is a legally recognized right to acquire, to use and to transfer land. In private property systems, land ownership is akin to a freehold tenure. In these contexts, it is more appropriate to • In systems where land is owned by the State, the term use the broader term land tenure rights. land ownership is commonly used to indicate possession of the rights most akin to ownership in a private property system, such as long term leases, occupancy, tenancy or use rights granted by the State, often for several decades, and that are transferrable. (a) Proportion of total agricultural population with ownership or secure SDG 5.a.1/ rights over agricultural land, by sex; and (b) share of women among SGS Indicator 3 owners or rights-bearers of agricultural land, by type of tenure Definition and Concept Land Ownership & Land Tenure Rights To determine whether an individual is said to have ownership or secure tenure rights to agricultural land three conditions (proxies) are considered. Proxy 1 Proxy 2 Proxy 3 Legal Document Right to Sell Right to Bequeath A legally recognized document The individual has the right to sell The individual has the right to pass on should be on the individual’s name, agricultural land the land to another person(s) after his that testifies their tenure rights or her death, by written will, oral will over agricultural land (if recognized by the country) or intestate succession (a) Proportion of total agricultural population with ownership or secure SDG 5.a.1/ rights over agricultural land, by sex; and (b) share of women among SGS Indicator 3 owners or rights-bearers of agricultural land, by type of tenure Definition and Concept Land Ownership & Land Tenure Rights For a list of documents that may be considered as legally recognized, please see pages 31-32 here: https://unstats.un.org/edge/meetings/Dec2017/docs/S10/SDG%20indicator%205.a.1%20_FAO.pdf It is critical that the list of legally binding documents proposed above is customized in order to consider only documents that are enforceable before the law and that guarantee individual’s tenure rights in the national context. (a) Proportion of total agricultural population with ownership or secure SDG 5.a.1/ rights over agricultural land, by sex; and (b) share of women among SGS Indicator 3 owners or rights-bearers of agricultural land, by type of tenure Definition and Concept Reported ownership cannot be used for this indicator • Reported ownership refers to the person(s) who considers him or herself to be an owner of the asset in question, irrespective of whether his or her name is listed as an owner on an ownership document for the asset. Thus, it measures people’s self-perceptions about their ownership status. • It is a key concept for understanding the empowerment effects of asset ownership from a gender perspective since we expect the benefits and behaviors related to asset ownership to be influenced by people’s perceptions of what they believe themselves to own. • However, it cannot be objectively verified and it is not necessarily linked to objective rights over land. (a) Proportion of total agricultural population with ownership or secure SDG 5.a.1/ rights over agricultural land, by sex; and (b) share of women among SGS Indicator 3 owners or rights-bearers of agricultural land, by type of tenure Why It matters • Agricultural land is a key input in developing • Sex disaggregated data on tenure rights disclose the countries, where poverty reduction and actual situation of women’s legal security in relation development strategies are frequently based on the to agricultural land. agricultural sector. • Women often do not consider themselves as • Gender equality: Women could increase their involved in agriculture, whereas in fact they provide productivity and empowerment if they had more substantive support to the household’s agricultural access to productive resources, particularly land. activities, therefore, it is important to include all Robust empirical evidence is needed to monitor the household adults when asking about individual’s gap and track the progress. land tenure rights. (a) Proportion of total agricultural population with ownership or secure SDG 5.a.1/ rights over agricultural land, by sex; and (b) share of women among SGS Indicator 3 owners or rights-bearers of agricultural land, by type of tenure Data Source and Collection • Recommended data sources are o agricultural surveys and o some types of National Household surveys, such as o Living Standard Measurement Surveys (LSMS), Note: If national household surveys are being o Living Conditions Surveys, used in countries or regions where the o Labour Force Surveys (LFS) and percentage of agricultural households is low, an o Multipurpose Household Surveys. oversample of agricultural households is needed o Demographic and Health Surveys (DHS) and to ensure a good precision of the estimates. Multiple Indicator Cluster Surveys (MICS) can be also used as data collection vehicle, provided that their individual questionnaires are administered to individuals beyond the age classes typically used in these surveys (a) Proportion of total agricultural population with ownership or secure SDG 5.a.1/ rights over agricultural land, by sex; and (b) share of women among SGS Indicator 3 owners or rights-bearers of agricultural land, by type of tenure Data Source and Collection • Once a household has been classified as agricultural household either all individuals or one randomly selected individual should be interviewed about their own status. Respondent Selection • Do not use proxy respondents to collect data for this indicator, i.e., no one household member should be How many individuals should be interviewed to collect information on other or all the interviewed and who should report household members. information? • Each individual should only be interviewed on his/her ownership/tenure rights over agricultural land. This can be applied to either one randomly selected member of the household or all members of the household, depending on time or budget constraints. (a) Proportion of total agricultural population with ownership or secure SDG 5.a.1/ rights over agricultural land, by sex; and (b) share of women among SGS Indicator 3 owners or rights-bearers of agricultural land, by type of tenure Data Source and Collection Minimum Set of Data Needed During Collection 1. Whether or not the household has operated land or raised/tended livestock over the past 12 months 2. Sex of the selected individual 3. Age of the selected individual 4. Whether or not the selected individual owns or holds use rights to any agricultural land 5. Whether or not any of the agricultural land owned or held by the respondent has a legally recognized document that allows protecting ownership/tenure rights over the land 6. Whether or not the selected individual is listed as an owner or holder on any of the formal documents 7. Whether or not the selected individual has the right to sell any of the agricultural land, either alone or jointly with someone else 8. Whether or not the selected individual has the right to bequeath any of the agricultural land, either alone or jointly with someone else (a) Proportion of total agricultural population with ownership or secure SDG 5.a.1/ rights over agricultural land, by sex; and (b) share of women among SGS Indicator 3 owners or rights-bearers of agricultural land, by type of tenure Method of Computation The following data needs to be collected according to the guidelines previously discussed, to calculate both sub-indicators: o total adult agricultural population (= adult members in agricultural households [ag HHs]), by sex o the number of adult individuals with ownership or tenure rights over agricultural land, by sex Calculation for sub-indicator (a) Women Men No. of women with ownership or secure rights No. of men with ownership or secure rights over agricultural land over agricultural land Total female agricultural population (in ag HHs) Total male agricultural population (in ag HHs) (a) Proportion of total agricultural population with ownership or secure SDG 5.a.1/ rights over agricultural land, by sex; and (b) share of women among SGS Indicator 3 owners or rights-bearers of agricultural land, by type of tenure Method of Computation Calculation for sub-indicator (b) No. of women with ownership or secure rights over agricultural land Total people with ownerhsip or secure rights over agricultural land There is a self-paced e-learning course on this indicator to support countries in data collection, analysis and reporting for the indicator: https://www.unsdglearn.org/courses/sdg-indicator-5-a-1-equal-tenure- rights-for-women-on-agricultural-land-2/ (a) Proportion of total agricultural population with ownership or secure SDG 5.a.1/ rights over agricultural land, by sex; and (b) share of women among SGS Indicator 3 owners or rights-bearers of agricultural land, by type of tenure SDG Indicator 1.4.2 / SGS Indicator 4 Proportion of total adult population with secure tenure rights to land, (a) with legally recognized documentation, and (b) who perceive their rights to land as secure, by sex and type of tenure Source: UN Statistics Division 38 Definition and Concept • This indicator aims at measuring secure tenure • It measures the results of policies that aim to rights. Tenure security can either come from legally strengthen tenure security for all, including women recognized documentation or from perceived and other vulnerable groups. security of tenure. • An individual can hold land in his/her own name, • It covers (a) all types of land use (such as jointly with other individuals, as a member of a residential, commercial, agricultural, forestry, household, or collectively as member of group, grazing, wetlands based on standard land-use cooperative or other type of association. classification) in both rural and urban areas; and (b) all land tenure types as recognized at the country level, such as freehold, leasehold, public land, customary land. Proportion of total adult population with secure tenure rights to SDG 1.4.2/ land, (a) with legally recognized documentation, and (b) who SGS Indicator 4 perceive their rights to land as secure, by sex and type of tenure Why it matters • This provides a measure of equity between men • If measured at the individual level, the right to and women for secure land rights. bequeath is another proxy of perception of tenure security. Women’s ability to influence • Secure tenure rights for women require particular intergenerational land transfers is an important attention and could be affected by a number of aspect of female empowerment (and is linked to factors, including intra-household power relations, indicator 5.a.1). community level inequalities, or different tenure regimes, and which can be cross tabulated against other factors of difference to ensure that women are not left behind. Proportion of total adult population with secure tenure rights to SDG 1.4.2/ land, (a) with legally recognized documentation, and (b) who SGS Indicator 4 perceive their rights to land as secure, by sex and type of tenure Data Source and Collection • The data sources used are census, multi-topic • An integrated approach to data collection for both household surveys, and in some cases, indicators 1.4.2 and 5.a.1 has been developed by all administrative data (land registries), if the records custodians, UN Habitat, World Bank, and FAO and maintained are compatible with the type of data UN Women. This has a standardized, consolidated needed for the indicator. and succinct survey instrument with essential questions. • The essential questions for both indicators 1.4.2 as well as 5.a.1 have been included in the World • Unit of Measure Bank’s LSMS approach. • Expressed as a percentage Proportion of total adult population with secure tenure rights to SDG 1.4.2/ land, (a) with legally recognized documentation, and (b) who SGS Indicator 4 perceive their rights to land as secure, by sex and type of tenure Method of Computation Part (a) and part (b) of the indicator provide two complementary data sets on security of tenure rights, needed for measuring the indicator. Calculation indicator Part (a) Part (b) ! (a"#!$) %&$h ! '(!!) * + ',&- " ! (a"#!$) who perceive their " +#. ,$($& , / * !(,d × 100 rights as secure Total adult population × 100 Total adult population Proportion of total adult population with secure tenure rights to SDG 1.4.2/ land, (a) with legally recognized documentation, and (b) who SGS Indicator 4 perceive their rights to land as secure, by sex and type of tenure Relevant Links • Integrated approach to data collection for SDG indicators 1.4.2 and 5.a.1: https://gltn.net/download/measuring-individuals-rights-to-land-anintegrated-approach-to-data- collection-for-sdg-indicators-1-4-2-and-5-a-1- english/?wpdmdl=16316&refresh=5efb342458df61593521188 • Consolidated essential questions land module for 1.4.2 and 5.a.1: http://documents.worldbank.org/curated/en/812621505371556739/Landtenure-module-essential- questions-for-data-collection-for-1-4-2-and-5-a-1 • Expert Group Meetings on methodology development using administrative data http://documents.worldbank.org/curated/en/482991505367111149/pdf/119691-WP-P095390- PUBLICSDGEGMproceedingsuseofadministrativedatalandagencies.pdf Proportion of total adult population with secure tenure rights to SDG 1.4.2/ land, (a) with legally recognized documentation, and (b) who SGS Indicator 4 perceive their rights to land as secure, by sex and type of tenure III. Employment Indicators Source: UN SDG Metadata Repository, UNSD Minimum Set of Gender Indicators SDG Indicator 5.4.1 / SGS Indicator 5 Proportion of time spent on unpaid domestic and care work, by sex, age and location Source: UN Statistics Division 45 Definition and Concept • Defined as the proportion of time spent in a day by • The indicator only considers own-use production men and women on unpaid domestic and work of services, which means it only focuses on the caregiving services for own final use by members of activities related to unpaid domestic and caregiving a household or by family members living in other services undertaken by household and family households. members for their own use. • Unpaid domestic and care work includes activities • Disaggregation by location refers to categorization such as cooking, dishwashing, cleaning and based on urban/rural. upkeep of dwelling, laundry, ironing, gardening, servicing and repair of personal and household goods, shopping, and taking care of the children, • If possible, calculate domestic work and care work the elderly, the pets, the sick or the disabled separately. household and family members, as listed in ICATUS 2016. Proportion of time spent on unpaid domestic SDG 5.4.1/ and care work, by sex, age and location SGS Indicator 5 Why it matters • The purpose of the indicator is to measure the • It provides an assessment of gender equality, by amount of time women and men spend doing highlighting discrepancies between how much time unpaid work, to ensure that all work, whether paid women spend on unpaid work, like cooking, or unpaid, is valued. cleaning or taking care of children, as compared to men. Proportion of time spent on unpaid domestic SDG 5.4.1/ and care work, by sex, age and location SGS Indicator 5 Data Source and Collection • Unit of measure • Data for the indicator collected through dedicated time-use surveys or from time-use modules • Expressed as a proportion of time in a day attached to household surveys containing 24-hour • If it says 10% of the time is spent, it indicates diary following respondents activities through the 2.4 hours (2 hours, 24 minutes) a day. day, or stylized questions added to household • It is the average amount of time as a proportion surveys. of the day. The daily average is obtained from an average taken over a weekly period. So, it • Data are collected by NSOs at the country level, does not mean that this given time is spent and are compiled and validated by UNSD. every single day. Proportion of time spent on unpaid domestic SDG 5.4.1/ and care work, by sex, age and location SGS Indicator 5 Limitations Diary v/s stylized time-use data collection methods • Data collected through the two methods are usually not comparable. • Even within the stylized method, the data collected from different stylized survey instruments may differ due to the differing levels of details of activities in the questions asked. Difference in definition of time-use activities Comparability Regional and national classifications of time-use activities may differ from ICATUS 2016, resulting in data that issues: are not comparable across countries. Conflict in reporting main activity and secondary activity Time-use data presented refer to the “main activity� only. Any “secondary activity� performed simultaneously with the main activity is not reflected in the average times shown. For instance, a woman may be cooking and looking after a child simultaneously. For countries reporting cooking as the main activity, time spent caring for children is not accounted for and reflected in the statistics. This may affect international comparability of data on time spent caring for children; it may also underestimate the time women spend on this activity. Proportion of time spent on unpaid domestic SDG 5.4.1/ and care work, by sex, age and location SGS Indicator 5 Method of Computation • If data on time spent are weekly, data are averaged over 7 days of the week to obtain daily average time. • Proportion of time spent on unpaid domestic and care work is calculated as: where, Disaggregation: (1) By sex: male/female; (2) by age (recommended): 15+, 15-24, 25-44, 45-54, 55-64 and 65+ ; (3) by location: urban/rural (following national definitions given the lack of international definition) Proportion of time spent on unpaid domestic SDG 5.4.1/ and care work, by sex, age and location SGS Indicator 5 UNSD Indicator I.2 / SGS Indicator 6 Average number of hours spent on total work (total work burden), by sex Source: UNSD, UN SDSN 51 Definition and Concept • Unpaid work here refers to both the home • This indicator captures individuals’ work burden, production of goods, like collecting water, and both paid and unpaid, by sex. production of domestic and care services, as well as community or volunteer work. (not within SNA • For this indicator, total work burden refers to time production boundary but inside SNA general spent on paid and unpaid work combined, and production boundary; delineated by ICATUS) goes beyond employment. • Paid work corresponds to the SNA production • Total work is any activity performed by persons in boundary and refers to work related activities in the reference population to produce goods or formal employment or informal employment, provide services for use by others or for own use. production of goods by households for income or for own final use, paid construction activities and construction for own capital formation and provision of services for income. Average number of hours spent on total work UNSD I.2/ (total work burden), by sex SGS Indicator 6 Why it matters • Measuring unpaid work included in the total work • Measuring unpaid work is also essential to ensure burden helps to expose the full range of possible the effectiveness of women’s empowerment economic contributions, including the home programs. The time spent by women and girls to production of goods and services. It also exposes collect water, for example, or on care activities can women’s disproportionate unpaid work burden. be significantly reduced by a gender impact analysis of public service provision and infrastructural • For example, in Nepal and Kenya when unpaid and development, such as electricity, roads, rural paid work are combined, women work 1.4 hours schools, or water. for every hour worked by men. [Source: ActionAid (2013). Making Care Visible: Women’s unpaid care work] Average number of hours spent on total work UNSD I.2/ (total work burden), by sex SGS Indicator 6 Data Source and Collection • Data for the indicator is primarily collected through time-use surveys or time-use modules integrated in multipurpose household surveys. • Unit of measure • Expressed as an average number of hours • For some countries, data are obtained from per day regional data compilations (Eurostat, OECD, UNECE and UNECLAC). UNSD is the data custodian. Average number of hours spent on total work UNSD I.2/ (total work burden), by sex SGS Indicator 6 Method of Computation If data being collected on time spent are weekly, data are averaged over 7 days of the week to obtain daily average time. For example, if a five-day work week averaging seven hours per day would show up as an average of five hours of paid work per day (35 hours divided by 7 days). :;<=> ?@ABCD ;E F;@DG GHC?< BI = K;DL (;D H=D=D =M H;H@>=C) U@ABCD ;E ;K?V=MM;@?< K;DLCDG (A=>C) :;<=> ?@ABCD ;E CAH>;ICW (ECA=>C) × 100 :;<=> ?@ABCD ;E CAH>;ICW (A=>C) × 100 Proportion of employed who are own-account UNSD I.4/ workers, by sex SGS Indicator 8 UNSD Indicator I.5 / SGS Indicator 9 Proportion of employed who are contributing family workers, by sex Source: ILO, UNSD 68 Definition and Concept • This indicator captures individuals’ status in • Contributing family work is a form of labour – employment, with respect to being contributing generally unpaid, although compensation might family workers, by sex. come indirectly in the form of family income – that supports production for the market. Contributing family workers hold “self-employment jobs� as own- • The basic criteria used to define the groups of the account workers in a market-oriented establishment classification by status in employment are the type operated by a related person living in the same of economic risk and the type of authority over household. establishments and other workers which the job incumbents have. • This forms part of ‘vulnerable employment’, which is the sum of the employment status groups of own- account workers and contributing family workers. Proportion of employed who are contributing UNSD I.5/ family workers, by sex SGS Indicator 9 Why it matters • Breaking down employment information by status • The discrepancy of gender in the employment status in employment provides a statistical basis for can reveal the social inequality problem. describing workers’ behaviour and conditions of work, and for defining an individual’s socio- • Contributing family work is particularly common economic group. among women, especially women in households where other members engage in self-employment, • Countries that show falling proportions of either specifically in running a family business or in the share of own-account workers or contributing farming. Where large shares of workers are family workers, and a complementary rise in the contributing family workers, there is likely to be share of employees, accompany the move from a poor development, little job growth, widespread low-income situation with a large informal or rural poverty and often a large rural economy. sector to a higher income situation with high job growth. Proportion of employed who are contributing UNSD I.5/ family workers, by sex SGS Indicator 9 Data Source and Collection • Labour force surveys are typically the preferred source of information for this indicator. • Unit of measure • Other household surveys and population censuses • Expressed as a percentage can also be used, however they may be less reliable as they do not typically allow for detailed probing on the labour market activities of the respondents. Proportion of employed who are contributing UNSD I.5/ family workers, by sex SGS Indicator 9 Limitations • The classification by status in employment does not provide information about finer distinctions in working status (for instance, whether workers have casual or regular contracts and the kind of protection the contracts provide against dismissals). Comparability issues: • Could differ across countries due to differing • Another area with scope for measurement definitions for employment figures, and differences differences has to do with the national treatment of in age coverage in defining bounds for labour force particular groups of workers. The international activity. definition of employment calls for inclusion of all persons who worked for at least one hour during the reference period. Workers could be in paid employment or in self-employment, including in less obvious forms of work (mentioned in 19th ICLS), such as unpaid family work, apprenticeship or non- market production Proportion of employed who are contributing UNSD I.5/ family workers, by sex SGS Indicator 9 Method of Computation Calculation for indicator, by sex Women Men U@ABCD ;E M;?I U@ABCD ;E M;?I K;DLCDG (ECA=>C) K;DLCDG (A=>C) :;<=> ?@ABCD ;E CAH>;ICW (ECA=>C) × 100 :;<=> ?@ABCD ;E CAH>;ICW (A=>C) × 100 Proportion of employed who are contributing UNSD I.5/ family workers, by sex SGS Indicator 9 SDG Indicator 8.6.1 / SGS Indicator 10 Proportion of youth (aged 15-24 years) not in education, employment or training Source: UN Statistics Division 74 Definition and Concept • This indicator is also known as "the youth NEET • For this indicator, persons are considered to be in rate“, conveying the proportion of youth (aged 15- training if they are in a non-academic learning 24 years) not in education, employment or training activity through which they acquire specific skills (NEET). intended for vocational or technical jobs. • For this indicator, persons will be considered in • It is important to bear in mind that it is composed of education if they are in formal or non-formal two different sub-groups (unemployed youth not in education, but excluding informal learning education or training and youth outside the labour (definitions in next slide). force not in education or training). • Employment is defined as all persons of working age who, during a short reference period (one week), were engaged in any activity to produce goods or provide services for pay or profit Proportion of youth (aged 15-24 years) not in SDG 8.6.1/ education, employment or training SGS Indicator 10 Definition and Concept • Formal education is defined as education that is institutionalized, intentional, and planned through public organizations and recognized private bodies, and make up the formal education system of a country. • Non-formal education is institutionalized, intentional and planned by an education provider but is considered an addition, alternative and/or a complement to formal education. It may be short in duration and/or low in intensity and it is typically provided in the form of short courses, workshops or seminars. • For this indicator, persons are considered to be in training if they are in a non-academic learning activity through which they acquire specific skills intended for vocational or technical jobs. • Informal learning is intentional or deliberate, but not institutionalized. It is thus less organized and less structured. It may include learning activities that occur in the family, in the work place, in the local community, and in daily life, on a self-directed, family-directed or socially-directed basis. Proportion of youth (aged 15-24 years) not in SDG 8.6.1/ education, employment or training SGS Indicator 10 Why it matters • It serves as a broader measure of potential youth • Sex disaggregation is important for the indicator to labour market entrants than youth unemployment provide a piece to build a larger picture of the because it captures the youth who are outside of gender inconsistencies in this context. the education system, not in training and not in employment. • It includes discouraged worker youth as well as those who are outside the labour force due to disability or engagement in household chores, among other reasons. Proportion of youth (aged 15-24 years) not in SDG 8.6.1/ education, employment or training SGS Indicator 10 Data Source and Collection • Data for the indicator collected through household- based labour force survey. In its absence, it can be sourced from population census and/or other types of household surveys with employment • Unit of measure modules. • Expressed as a percentage • Data are collected by NSOs (in some cases, labour ministries and other related agencies), and are compiled and validated by ILO. Proportion of youth (aged 15-24 years) not in SDG 8.6.1/ education, employment or training SGS Indicator 10 Method of Computation It is important to note here that youth simultaneously in employment and education or training should not be double counted when subtracted from the total number of youth. The formula can also be expressed as: The prevalence and composition of each subgroup would have policy implications, and thus, should also be considered when analysing the NEET rate. Proportion of youth (aged 15-24 years) not in SDG 8.6.1/ education, employment or training SGS Indicator 10 Relevant Links Decent Work and the Sustainable Development Goals: A Guidebook on SDG Labour Market Indicators, available at https://www.ilo.org/stat/Publications/WCMS_647109/lang--en/index.htm ILO Manual – Decent Work Indicators, Concepts and Definitions – Chapter 1, Employment opportunities http://www.ilo.org/integration/resources/pubs/WCMS_229374/lang-- en/index.htm (second version, pages 38) International Standard Classification of Education 2011 (ISCED2011) http://www.uis.unesco.org/Education/Pages/international-standard-classification-ofeducation.aspx ILOSTAT’s Indicator Descriptions – Youth NEET rate (https://ilostat.ilo.org/resources/methods/description- youth-neet/ ) Proportion of youth (aged 15-24 years) not in SDG 8.6.1/ education, employment or training SGS Indicator 10 UNSD Indicator I.8 / SGS Indicator 11 Percentage distribution of employed population by sector, and by sex Source: ILO, UNSD 81 Definition and Concept • The indicator for employment by sector divides • The classification by economic activity refers to the employment into three broad groupings of main activity of the establishment in which a person economic activity: agriculture, industry and worked during the reference period. services (recorded by ISIC codes). Percentage distribution of employed population UNSD I.8/ by sector, and by sex SGS Indicator 11 Why it matters • Sectoral information is particularly useful in • The breakdown of the indicator by sex allows for identifying broad shifts in employment and stages analysis of gender segregation of employment by of development. sector. In some cases, segregation of women in certain sectors may result from cultural attitudes that prevent them from taking up certain kinds of jobs. For example, women may be drawn into lower paying service activities that allow for more flexible work schedules, thus making it easier to balance family responsibilities with work life. Percentage distribution of employed population UNSD I.8/ by sector, and by sex SGS Indicator 11 Data Source and Collection • Labour force surveys are typically the preferred source of information for this indicator. Other types of household surveys and population censuses that record this information can also be used. • Unit of measure • In the absence of the above-mentioned sources, • Expressed as a percentage establishment surveys or administrative records can provide information on employment by economic activity, but they do not cover the entire employed population, typically excluding the informal economy, small establishments and some specific economic activities such as public administration or even in some cases agriculture. Percentage distribution of employed population UNSD I.8/ by sector, and by sex SGS Indicator 11 SDG Indicator 8.3.1 / SGS Indicator 12 Proportion of informal employment in total employment, by sector and by sex Source: UN Statistics Division 85 Definition and Concept • Presented as the share of employment which is • The indicator considers classification of persons into classified as informal in the total economy, and formal or informal employment only based on their separately in agriculture and in non-agriculture. main job and not secondary jobs. • Employment comprises all persons of working age • The categorization of informal employment and who, during a short reference period (one week), enterprises that belong to the informal sector is were engaged in any activity to produce goods or specified ahead. provide services for pay or profit. UNSD INDICATOR I.9 is a sub-part of SDG INDICATOR 8.3.1, wherein, the former only calculates informal employment in non-agriculture employment, by sex Proportion of informal employment in total SDG 8.3.1/ employment, by sector and by sex SGS Indicator 12 Definition and Concept For this indicator, informal employment comprises persons who in their main job were in one of the following categories: Own-account workers, employers and members of producers’ cooperatives employed in their own informal sector enterprises (the characteristics of the enterprise determine the informal nature of their jobs) Contributing family workers, regardless of whether they work in formal or informal sector enterprises (they usually do not have explicit, written contracts of employment, and are not subject to labour legislation, social security regulations, collective agreements, etc., which determines the informal nature of their jobs) Employees holding informal jobs, whether employed by formal sector enterprises, informal sector enterprises, or as paid domestic workers by households (employees are considered to have informal jobs if their employment relationship is, in law or in practice, not subject to national labour legislation, income taxation, social protection or entitlement to certain employment benefits) Proportion of informal employment in total SDG 8.3.1/ employment, by sector and by sex SGS Indicator 12 Definition and Concept An enterprise belongs to the informal sector if it fulfils the three following conditions: It is an unincorporated enterprise (it is not constituted as a legal entity separate from its owners, and it is owned and controlled by one or more members of one or more households, and it is not a quasi- corporation: it does not have a complete set of accounts, including balance sheets) It is a market enterprise (it sells at least some of the goods or services it produces) The enterprise is not registered or the employees of the enterprise are not registered or the number of persons engaged on a continuous basis is below a threshold determined by the country Proportion of informal employment in total SDG 8.3.1/ employment, by sector and by sex SGS Indicator 12 Why it matters • Statistics on informality are key to assessing the • Sex disaggregation for this indicator is crucial to quality of employment in an economy. providing a status check for gender equality goals in a country, considering that a large proportion of informal employment consists of women and other • When social protection coverage and social genders. security benefits are insufficient or even inexistent, and/or wages and pensions are low, individuals may have to take up informal employment. In these situations, unemployment indicators would provide an incomplete picture of the labor market, overlooking major deficits in the quality of employment. Proportion of informal employment in total SDG 8.3.1/ employment, by sector and by sex SGS Indicator 12 Data Source and Collection • Data for the indicator collected through labour- force surveys, with sufficient questions to determine informal nature of jobs and whether • Unit of measure place of work belongs to the formal or informal sector. • Expressed as a percentage • Data are collected by NSOs at the country level, and are compiled and validated by ILO. Proportion of informal employment in total SDG 8.3.1/ employment, by sector and by sex SGS Indicator 12 Method of Computation Proportion of informal employment in total SDG 8.3.1/ employment, by sector and by sex SGS Indicator 12 Relevant Links ILOSTAT indicator description for informality, available at https://ilostat.ilo.org/resources/methods/description-informality/ ILO Guidebook - Decent Work and the Sustainable Development Goals: A Guidebook on SDG Labour Market Indicators (https://www.ilo.org/stat/Publications/WCMS_647109/lang-- en/index.htm ) ILO manual Measuring informality: A statistical manual on the informal sector and informal employment available at http://www.ilo.org/wcmsp5/groups/public/---dgreports/---dcomm/- -- publ/documents/publication/wcms_222979.pdf Proportion of informal employment in total SDG 8.3.1/ employment, by sector and by sex SGS Indicator 12 SDG Indicator 8.5.2 / SGS Indicator 13 Unemployment rate, by sex, age and persons with disabilities Source: UN Statistics Division 93 Definition and Concept • The unemployment rate conveys the percentage of • Persons in employment are defined as all those of persons in the labour force who are unemployed. working age (usually aged 15 and above) who, during a short reference period such as one week or • The labour force corresponds to the sum of one day, were engaged in any activity to produce persons in employment and in unemployment. goods or provide services for pay or profit. • Unemployed persons are defined as all those of working age (usually aged 15 and above) who were not in employment, carried out activities to seek employment during a specified recent period and were currently available to take up employment given a job opportunity Unemployment rate, by sex, age and persons SDG 8.5.2/ with disabilities SGS Indicator 13 Why it matters • The unemployment rate is a useful measure of the • The disaggregation by various factors provides a underutilization of the labour supply. picture of equity in terms of availability of opportunities. • It is seen as an indicator of the efficiency and effectiveness of an economy to absorb its labour force and of the performance of the labour market. Unemployment rate, by sex, age and persons SDG 8.5.2/ with disabilities SGS Indicator 13 Data Source and Collection • Data for the indicator collected through household- based labour force survey. In its absence, it can be sourced from population census and/or other types of household surveys with employment modules. • Unit of measure • For this indicator, it would be inaccurate to source the data from official unemployment registers, because it • Expressed as a percentage would refer to registered unemployment and not to unemployment as defined by this indicator. • Data are collected by NSOs (in some cases, labour ministries and other related agencies), and are compiled and validated by ILO Unemployment rate, by sex, age and persons SDG 8.5.2/ with disabilities SGS Indicator 13 Method of Computation where, “total labour force� refers to the sum of persons in employment and unemployment Unemployment rate, by sex, age and persons SDG 8.5.2/ with disabilities SGS Indicator 13 Relevant Links Decent Work and the Sustainable Development Goals: A Guidebook on SDG Labour Market Indicators, available at https://www.ilo.org/stat/Publications/WCMS_647109/lang--en/index.htm ILO Manual – Decent Work Indicators, Concepts and Definitions – Chapter 1, Employment opportunities http://www.ilo.org/integration/resources/pubs/WCMS_229374/lang-- en/index.htm (second version, pages 34 and 49) Resolution concerning statistics of work, employment and labour underutilization http://www.ilo.org/global/statistics-and- databases/standards-and-guidelines/resolutions-adoptedby-international-conferences-of- labourstatisticians/WCMS_230304/lang--en/index.htm ILOSTAT Indicator descriptions (https://ilostat.ilo.org/resources/methods/descriptionunemployment-rate/ ) ILOSTAT’s topic page on Unemployment and Labour Underutilization (https://ilostat.ilo.org/topics/unemployment-and- labour-underutilization/ ) Unemployment rate, by sex, age and persons SDG 8.5.2/ with disabilities SGS Indicator 13 SDG Indicator 8.5.1 / SGS Indicator 14 Average hourly earnings of female and male employees, by occupation, age and persons with disabilities Source: UN Statistics Division 99 Definition and Concept • This indicator provides information on the mean • Earnings refer to remuneration in cash or in kind hourly earnings from paid employment of paid to employees, as a rule at regular intervals, for employees by sex, occupation, age and disability time worked or work done, together with status. remuneration for time not worked, such as paid leave. It excludes employers’ contributions in terms • For international comparability purposes, of social security and pension schemes and also the statistics of earnings used for this indicator relate benefits received by employees under these to employees’ gross remuneration schemes. Earnings also exclude severance and termination pay. Average hourly earnings of female and male SDG 8.5.1/ employees, by occupation, age and persons with SGS Indicator 14 disabilities Why it matters • Earnings are a key aspect of quality of employment • It provides an assessment of gender equality by and living conditions. indicating the extent to which pay equality is respected or achieved. Further disaggregation by various classifications such as occupation, age, and disability status provides more detailed insight into pay equality. Average hourly earnings of female and male SDG 8.5.1/ employees, by occupation, age and persons with SGS Indicator 14 disabilities Data Source and Collection • Data for the indicator can be collected through different avenues: o Establishment surveys • Unit of measure o Household surveys (especially labour force • Statistics on average hourly earnings of surveys) female and male employees can be o Administrative records used to calculate the gender pay gap, which is expressed as a percentage. • Data are collected by NSOs at the country level, and are compiled and validated by ILO Average hourly earnings of female and male SDG 8.5.1/ employees, by occupation, age and persons with SGS Indicator 14 disabilities Method of Computation Average hourly earnings of female and male employees can be used to calculate the gender pay gap. [ [NCD=XC F;@D>I C=D?J?XG \]^ V [NCD=XC F;@D>I C=D?J?XG _`a]^ ] Y ," * () Y( = × 100 [NCD=XC F;@D>I C=D?J?XG \]^ Average hourly earnings of female and male SDG 8.5.1/ employees, by occupation, age and persons with SGS Indicator 14 disabilities Relevant Links ILO manual: An integrated system of wages statistics, available at http://www.ilo.org/wcmsp5/groups/public/- --dgreports/--- stat/documents/presentation/wcms_315657.pdf Average hourly earnings of female and male SDG 8.5.1/ employees, by occupation, age and persons with SGS Indicator 14 disabilities UNSD Indicator I.14 / SGS Indicator 15 Proportion of employed working part- time, by sex Source: ILO 105 Definition and Concept • The indicator on part-time workers focuses on • Two measures are calculated for this indicator: total individuals whose working hours total less than part-time employment as a proportion of total “full time�, as a proportion of total employment. employment, sometimes referred to as the “part- time employment rate�; and the percentage of the • Since there is no internationally accepted part-time workforce comprised of women. definition as to the minimum number of hours in a week that constitute full-time work, the dividing line is determined either on a country-by-country basis or through the use of special estimations. Proportion of employed working part-time, by sex UNSD I.14/ SGS Indicator 15 Why it matters • Looking at part-time employment by sex is useful to • Part-time workers may face lower hourly wages, see the extent to which the female labour force is ineligibility for certain social benefits and more more likely to work part time than the male labour restricted career and training prospects. force. • Growth in part-time work has been seen as a positive outcome related to the increase in female labour force participation, and arising from policies attempting to raise labour market flexibility. However, the apparent move towards more flexible working arrangements has the risk that it may be less economically secure and less stable than full- time employment Proportion of employed working part-time, by sex UNSD I.14/ SGS Indicator 15 Data Source and Collection • Labour force surveys are typically the preferred source of information for this indicator. • Unit of measure • These are preferred due to several benefits, arising • Expressed as a percentage from how detailed they are in collecting data on hours worked. Population censuses with fairly extensive questionnaires can also be used if relevant. Proportion of employed working part-time, by sex UNSD I.14/ SGS Indicator 15 Limitations Different national definitions Information on part-time work can be expected to differ markedly across countries, principally because countries use different definitions of full-time work and also because they may have different cultural or workplace norms. Age inclusions for labour force Comparability Any cut-off linked to age will result in some people being missed among the “employed� counts; issues: as part-time work is particularly prevalent among the older and younger cohorts, this will lower the measured incidence of part-time employment Main job v/s all jobs The specification of main job or all jobs may be important. In some countries, the time cut-off is based on hours spent on the main job; in others, on total hours spent on all jobs. Measures may therefore reflect usual or actual hours worked on the main job or usual or actual hours worked on all jobs. Proportion of employed working part-time, by sex UNSD I.14/ SGS Indicator 15 Method of Computation Two measures calculated for the indicator part-time employment rate percentage of the part-time workforce comprised of women Proportion of employed working part-time, by sex UNSD I.14/ SGS Indicator 15 UNSD Indicator I.15 / SGS Indicator 16 Prime-age employment-to-population ratio by sex, household type and presence of children Source: ILO (1), ILO (2), UNSD 111 Definition and Concept • The prime age employment-to-population ratio is • Household types include: one-person households, defined as the proportion of a country’s prime households made up of a couple without children, working-age population (25-54 years) that is households made up of a couple and children, lone- employed. parent households, and households including extended family. • Employment comprises all persons of working age who during a specified brief period, such as one week or one day, were in the following categories: a) paid employment (whether at work or with a job but not at work); or b) self-employment (whether at work or with an enterprise but not at work). Prime-age employment-to-population ratio by UNSD I.15/ sex, household type and presence of children SGS Indicator 16 Why it matters • The disaggregation by sex, household type and • Women are often the primary child caretakers and presence of children specifically informs the responsible for various tasks at home, which can employment pattern of a country’s female prohibit them from seeking paid employment, population with respect to the male population, particularly if they are not supported by socio- with variations in types of household and presence cultural attitudes and/or family-friendly policies and of children. programmes that allow them to balance work and family responsibilities. • Among the prime working age, the female rates are not only found to be lower than the corresponding • However, it should also be emphasized that this male rates, but they also typically exhibit a indicator has a gender bias insofar as there is a somewhat different pattern. During this period of tendency to under-count women who do not their life-cycle, women tend to leave employment consider their work as "employment" or are not to give birth to and raise children, returning – but at perceived by others as "working". a lower rate – to economically active life when the children are older. Prime-age employment-to-population ratio by UNSD I.15/ sex, household type and presence of children SGS Indicator 16 Data Source and Collection • Labour force surveys are typically the preferred source of information for this indicator. • Unit of measure • Household surveys and population censuses can also • Expressed as a percentage be used, however they may be less reliable as they do not typically allow for detailed probing on the labour market activities of the respondents. Prime-age employment-to-population ratio by UNSD I.15/ sex, household type and presence of children SGS Indicator 16 Method of Computation The indicator for prime age employment-to-population ratio (EPR) is computed as follows: g#.4 * 5 *7 ,7 &, *&. (' . ! ) " Prime age EPR % = × 100 *&. % *8&,' (' #!($& , Prime-age employment-to-population ratio by UNSD I.15/ sex, household type and presence of children SGS Indicator 16 SDG Indicator 2.3.2 / SGS Indicator 17 Average income of small-scale food producers, by sex and indigenous status Source: UN Statistics Division 116 Definition and Concept • This indicator measures income from on-farm • For this indicator, small-scale food producers are production activities, which is related to the defined as those falling in the intersection of the production of food and agricultural products. This bottom 40 percent of the cumulative distribution of includes income from crop production, livestock land, livestock and revenues. production, fisheries and aquaculture production, and from forestry production. • Annual income should be computed by deducting from revenues the operating costs and the depreciation of assets. Average income of small-scale food producers, by SDG 2.3.2/ sex and indigenous status SGS Indicator 17 Definition and Concept As defined by FAO, small-scale food producers are producers who: operate an amount of land falling in the first two quintiles (the bottom 40 percent) of the cumulative distribution of land size at national level (measured in hectares); and operate a number of livestock falling in the first two quintiles (the bottom 40 percent) of the cumulative distribution of the number of livestock per production unit at national level (measured in Tropical Livestock Units – TLUs); and obtain an annual economic revenue from agricultural activities falling in the first two quintiles (the bottom 40 percent) of the cumulative distribution of economic revenues from agricultural activities per production unit at national level (measured in Purchasing Power Parity Dollars) not exceeding 34,387 Purchasing Power Parity Dollars Average income of small-scale food producers, by SDG 2.3.2/ sex and indigenous status SGS Indicator 17 Why it matters • The 2030 Sustainable Development Agenda has • Sex disaggregation is important for the indicator to emphasized the importance of enhancing income provide assessment for gender equality. of small-scale food producers, as these producers play an important role in the global production of food. This indicator monitors progress for the same. Their increase in income also relates to poverty reduction. Average income of small-scale food producers, by SDG 2.3.2/ sex and indigenous status SGS Indicator 17 Data Source and Collection • Most appropriate source to collect data for the indicator is agriculture surveys. In its absence, explore • Unit of measure household surveys with agriculture module, • The indicator is computed as annual agriculture censuses, or administrative data. income. • Average income of small-scale food • Data are collected by NSOs (or other national producers in constant PPP 2011 USD agencies involved in agriculture surveys), and are compiled and validated by FAO. Average income of small-scale food producers, by SDG 2.3.2/ sex and indigenous status SGS Indicator 17 Limitations • Given the approved methodology, the computation • Such type of surveys are seldom collected at the of the indicator requires survey microdata national level. For this reason the availability of data collected at the farm level on a wide range of for the indicator is altogether limited. variables – including all element allowing to compute revenues and costs of the enterprise • In some countries, data can be obtained from together with labour input and the availability of household surveys reporting details on agricultural land and livestock – referred to the same production. These data sources have to be production unit. considered as second-best solution, given that their sampling is focused on households and not on food production units. Average income of small-scale food producers, by SDG 2.3.2/ sex and indigenous status SGS Indicator 17 Method of Computation To obtain comparable results, values for annual incomes must necessarily be expressed in International Dollars at Purchasing Power Parity (PPP $), based on the conversion provided by the World Bank International Comparison Project. There is a self-paced e-learning course on this indicator to support countries in data collection, analysis and reporting for the indicator: https://elearning.fao.org/course/view.php?id=483 Relevant Links FAO Methodology Paper: https://www.fao.org/3/ca3043en/ca3043en.pdf Average income of small-scale food producers, by SDG 2.3.2/ sex and indigenous status SGS Indicator 17 SDG Indicator 5.5.2 / SGS Indicator 18 Proportion of women in managerial positions Source: UN Statistics Division 123 Definition and Concept • This indicator refers to the proportion of females in • The joint calculation of these two measures provides the total number of persons employed in information on whether women are more managerial positions. represented in junior management than in senior and middle management, thus pointing to an • It is recommended to use two different measures eventual ceiling for women to access higher-level jointly for this indicator: management positions. • the share of females in (total) management and • Calculating only the share of women in (total) • the share of females in senior and middle management would be misleading, in that it would management (thus excluding junior suggest that women hold positions with more management) decision-making power and responsibilities than they actually do. Proportion of women in managerial positions SDG 5.5.2/ SGS Indicator 18 Why it matters • The purpose of the indicator is to provide insights • It does so by measuring the proportion of women into women’s power in decision-making roles and in who are employed in decision-making and the economy as compared to men’s power in the management roles in government, large enterprises same area. and institutions. Proportion of women in managerial positions SDG 5.5.2/ SGS Indicator 18 Data Source and Collection • Recommended source for the indicator is labour force survey or, if not available, other similar types of household surveys, including a module on employment. • In the absence of any labour-related household • Unit of measure survey, establishment surveys or administrative • Expressed as a percentage records may be used to gather information on the female share of employment by the required International Standard Classification of Occupations (ISCO-08) groups. • Data are collected by NSOs at the country level, and are compiled and validated by ILO. Proportion of women in managerial positions SDG 5.5.2/ SGS Indicator 18 Limitations • This indicator's main limitation is that it does not • Its quality is also heavily dependent on the reliability reflect differences in the levels of responsibility of of the employment statistics by occupation at the women in these high- and middle-level positions ISCO two-digit level. or the characteristics of the enterprises and organizations in which they are employed. Proportion of women in managerial positions SDG 5.5.2/ SGS Indicator 18 Method of Computation Using ISCO-08 which can also be expressed as, and, Proportion of women in managerial positions SDG 5.5.2/ SGS Indicator 18 Relevant Links ILO Guidebook: Decent Work and the Sustainable Development Goals: A Guidebook on SDG Labour Market Indicators, available at https://www.ilo.org/stat/Publications/WCMS_647109/lang--en/index.htm ILO Manual – Decent Work Indicators, Concepts and Definitions – Chapter 8, Equal opportunity and treatment in employment http://www.ilo.org/integration/resources/pubs/WCMS_229374/lang--en/index.htm (second version, page 146) International Standard Classification of Occupations 2008 (ISCO-08) http://www.ilo.org/public/english/bureau/stat/isco/isco08/ ILOSTAT– Indicator Descriptions (Employment by occupation, at: https://ilostat.ilo.org/resources/methods/description-employment-by-occupation/ ) Proportion of women in managerial positions SDG 5.5.2/ SGS Indicator 18 SDG Indicator 8.7.1 / SGS Indicator 19 Proportion and number of children aged 5-17 years engaged in child labour, by sex and age Source: UN Statistics Division 130 Definition and Concept • Production boundary set by SNA: limits the frame • This indicator records the number of children of reference for child labour to economic activity reported to be in child labour during the reference General production boundary: extends it to include period (usually the week prior to the survey). The both economic activity and unpaid household proportion of children in child labour is calculated services as the number of children in child labour divided by the total number of children in the population. • The concept of child labour also includes the worst forms of child labour other than hazardous as well as hazardous work. The worst forms of child labour • For the purposes of this indicator, children include include all forms of slavery or similar practices such all persons aged 5 to 17. as trafficking and the recruitment and use of child soldiers, the use or procurement of children for prostitution or other illicit activities, and other work that is likely to harm children’s health, safety or well- being. As a proxy, work beyond age-specific hourly thresholds is used for reporting on this indicator. Proportion and number of children aged 5-17 SDG 8.7.1/ years engaged in child labour, by sex and age SGS Indicator 19 Definition and Concept Indicator 1: Proportion and number of children aged 5-17 years engaged in economic activities at or above age-specific hourly thresholds (SNA production boundary basis) Child labour for the 5 to 11 age range: children working at least 1 hour per week in economic activity; Child labour for the 12 to 14 age range: children working for at least 14 hours per week in economic activity; Child labour for the 15 to 17 age range: children working for more than 43 hours per week in economic activity. Indicator 2: Proportion and number of children aged 5-17 years engaged in economic activities and household chores at or above age-specific hourly thresholds (general production boundary basis) Child labour for the 5 to 11 age range: children working at least 1 hour per week in economic activity and/or involved in unpaid household services for more than 21 hours per week; Child labour for the 12 to 14 age range: children working for at least 14 hours per week in economic activity and/or involved in unpaid household services for more than 21 hours per week; Child labour for the 15 to 17 age range: children working for more than 43 hours per week in economic activity Proportion and number of children aged 5-17 SDG 8.7.1/ years engaged in child labour, by sex and age SGS Indicator 19 Why it matters • Far too many children in the world remain trapped • Statistical information on child labour, and more in child labour, compromising their individual future broadly on all working children, also provide a basis and our collective futures. According to the latest for increasing public awareness of the situation of ILO global estimates, about 152 million children working children and for the development of worldwide – 64 million girls and 88 million boys - appropriate regulatory frameworks and policies. are child labourers. • Reliable, comprehensive and timely data on the nature and extent of child labour provide a basis for determining priorities for national global action against child labour. Proportion and number of children aged 5-17 SDG 8.7.1/ years engaged in child labour, by sex and age SGS Indicator 19 Data Source and Collection • Sources for generating child labour statistics: Household surveys such as Labour Force Surveys, UNICEF-supported Multiple Indicator Cluster Surveys (MICS), Demographic and Health Surveys (DHS), ILO- • Unit of measure supported Statistical Information and Monitoring • Expressed as a proportion Programme on Child Labour (SIMPOC), and World Bank (number of children engaged Living Standard Measurement surveys (LSMS) in child labour over total child population) • Data are collected by NSOs (for the most part) or ministries, government or international agencies that conduct labour force surveys or related household surveys, and are compiled and validated by UNICEF and ILO. Proportion and number of children aged 5-17 SDG 8.7.1/ years engaged in child labour, by sex and age SGS Indicator 19 Limitations • Child labour estimates based on the statistical • This means that there is no single legal definition of standards set out in the ICLS resolution represent child labour across countries, and thus, no single useful benchmarks for international comparative statistical measure of child labour consistent with purposes but are not necessarily consistent with national legislation across countries. estimates based on national child labour legislation. Proportion and number of children aged 5-17 SDG 8.7.1/ years engaged in child labour, by sex and age SGS Indicator 19 Method of Computation Children aged 5-17: Number of children aged 5-17 reported in child labour during the week prior to the survey divided by the total number of children aged 5-17 in the population, multiplied by 100. Children aged 5-14: Number of children aged 5-14 reported in child labour during the week prior to the survey divided by the total number of children aged 5-14 in the population, multiplied by 100. Children aged 15-17: Number of children aged 15-17 reported child labour during the week prior to the survey divided by the total number of children aged 15-17 in the population, multiplied by 100. Proportion and number of children aged 5-17 SDG 8.7.1/ years engaged in child labour, by sex and age SGS Indicator 19 Relevant Links ILO: Model questionnaires on child labour https://www.ilo.org/ipec/ChildlabourstatisticsSIMPOC/model-questionnaires/lang--en/index.htm ILO: Country reports and surveys https://www.ilo.org/ipec/ChildlabourstatisticsSIMPOC/Questionnairessurveysandreports/lang-- en/index.htm UCW: http://www.ucw-project.org/ Proportion and number of children aged 5-17 SDG 8.7.1/ years engaged in child labour, by sex and age SGS Indicator 19 SDG Indicator 8.8.1 / SGS Indicator 20 Fatal and non-fatal occupational injuries per 100,000 workers, by sex and migrant status Source: UN Statistics Division 138 Definition and Concept • This indicator provides information on the number • “Workers in the reference group� refer to the of fatal and non-fatal occupational injuries per average number of workers in the particular group 100,000 workers in the reference group during the under consideration and who are covered by the reference period. It is also known as the incidence source of the data on occupational injuries (for rate of occupational injuries when reported in this example, those of a specific sex or in a specific format. economic activity, occupation, age group, or any combination of these, or those covered by a • Cases of occupational disease and cases of injury particular insurance scheme, accident notification due to commuting accidents should be excluded systems, or household survey). from the statistics, as recommended. Fatal and non-fatal occupational injuries per SDG 8.8.1/ 100,000 workers, by sex and migrant status SGS Indicator 20 Definition and Concept Occupational injury: any personal injury, disease or death resulting from an occupational accident. An occupational injury is different from an occupational disease, which comes as a result of an exposure over a period of time to risk factors linked to the work activity. Diseases are included only in cases where the disease arose as a direct result of an occupational accident. An occupational injury can be fatal or non-fatal (and non-fatal injuries could entail the loss of work days). Occupational accident: an unexpected and unplanned occurrence, including acts of violence, arising out of or in connection with work which results in one or more workers incurring a personal injury, disease or death. Occupational accidents are to be considered travel, transport or road traffic accidents in which workers are injured and which arise out of or in the course of work. Fatal occupational injury: an occupational injury leading to death within one year of the day of the occupational accident Case of occupational injury: the case of one worker incurring one or more occupational injuries as a result of one occupational accident. Fatal and non-fatal occupational injuries per SDG 8.8.1/ 100,000 workers, by sex and migrant status SGS Indicator 20 Why it matters • Mainly, the purpose of the indicator is to provide • Therefore, it is important to have accurate sex information for prevention of occupational injuries, disaggregated data as well as disaggregation by diseases and deaths, as well as a basis for migrant status to highlight how women, men, and policymaking. migrants may be differently affected due to the nature of their occupational involvement. • It could also be used to monitor programmes for the same, estimate consequences of occupational injuries, reveal new risks and particular areas of increasing risk such as a particular occupation, industry or location. Fatal and non-fatal occupational injuries per SDG 8.8.1/ 100,000 workers, by sex and migrant status SGS Indicator 20 Data Source and Collection • Administrative records (sources/agencies for fatal and non-fatal injuries would differ), such as o Labour inspection records o Annual reports o Insurance and compensation records • Unit of measure o Death registers • The fatal and the non-fatal incidence rates are expressed • Household surveys and/or establishment surveys separately as a ratio of cases (especially to cover informal sector and the self- per 100,000 workers. employed) • Data are collected by labour ministries, national insurance, and/or NSOs, and are compiled and validated by ILO Fatal and non-fatal occupational injuries per SDG 8.8.1/ 100,000 workers, by sex and migrant status SGS Indicator 20 Method of Computation Statistics for fatal and non-fatal injuries are recorded separately, so their sum does not translate into total occupational accidents. Therefore, the incidence rates for the two are calculated separately. For the calculation of rates, the numerator and the denominator should have the same coverage. For example, if self-employed persons are not covered by the source of statistics on fatal occupational injuries, they should also be taken out of the denominator. Fatal and non-fatal occupational injuries per SDG 8.8.1/ 100,000 workers, by sex and migrant status SGS Indicator 20 Relevant Links ILO Guidebook - Decent Work and the Sustainable Development Goals: A Guidebook on SDG Labour Market Indicators (https://www.ilo.org/stat/Publications/WCMS_647109/lang-- en/index.htm) ILO Manual – Decent Work Indicators, Concepts and Definitions – Chapter 8, Safe work environment http://www.ilo.org/integration/resources/pubs/WCMS_229374/lang-- en/index.htm (second version, page 156) Resolution concerning statistics of occupational injuries (resulting from occupational accidents) http://www.ilo.org/global/statistics-and-databases/standards-andguidelines/resolutionsadopted-by-international- conferences-of-labourstatisticians/WCMS_087528/lang--en/index.htm Global database on occupational safety and health legislation – LEGOSH http://www.ilo.org/safework/info/publications/WCMS_217849/lang-- en/index.htm Occupational injuries statistics from household surveys and establishment surveys http://www.ilo.org/stat/Publications/WCMS_173153/lang--en/index.htm ILOSTAT Metadata – Indicator descriptions (https://ilostat.ilo.org/resources/methods/description-occupational-injuries/ ) Fatal and non-fatal occupational injuries per SDG 8.8.1/ 100,000 workers, by sex and migrant status SGS Indicator 20 IV. Entrepreneurship Indicators Source: UN SDG Metadata Repository, UNSD Minimum Set of Gender Indicators, EDGE Report UNSD Indicator I.6 / SGS Indicator 21 Proportion of employed who are employers, by sex Source: ILO, UNSD 146 Definition and Concept • This indicator captures individuals’ status in • Employers are those workers who, working on their employment, with respect to being contributing own account or with one or a few partners, hold the family workers, by sex. type of jobs defined as a “self- employment jobs� (i.e. jobs where the remuneration is directly dependent upon the profits derived from the goods and services • The basic criteria used to define the groups of the produced), and, in this capacity, have engaged, on a classification by status in employment are the type continuous basis, one or more persons to work for of economic risk and the type of authority over them as employee(s). establishments and other workers which the job incumbents have. • This forms part of ‘non-vulnerable employment’. Proportion of employed who are employers, by sex UNSD I.6/ SGS Indicator 21 Why it matters • Breaking down employment information by status • Wage and salaried workers together with employers in employment provides a statistical basis for constitute ‘non-vulnerable employment’. Thus, describing workers’ behaviour and conditions of providing an analysis of type of employment and work, and for defining an individual’s socio- relative economic security for an individual, and economic group. their type of authority over establishments and other workers they have. • The discrepancy of gender in the employment status can reveal the social inequality problem. Proportion of employed who are employers, by sex UNSD I.6/ SGS Indicator 21 Data Source and Collection • Labour force surveys are typically the preferred source of information for this indicator. • Unit of measure • Other household surveys and population censuses • Expressed as a percentage can also be used, however they may be less reliable as they do not typically allow for detailed probing on the labour market activities of the respondents. Proportion of employed who are employers, by sex UNSD I.6/ SGS Indicator 21 Limitations • The classification by status in employment does not provide information about finer distinctions in working status (for instance, whether workers have casual or regular contracts and the kind of protection the contracts provide against dismissals). Comparability issues: • Could differ across countries due to differing • Another area with scope for measurement definitions for employment figures, and differences differences has to do with the national treatment of in age coverage in defining bounds for labour force particular groups of workers. The international activity. definition of employment calls for inclusion of all persons who worked for at least one hour during the reference period. Workers could be in paid employment or in self-employment, including in less obvious forms of work (mentioned in 19th ICLS), such as unpaid family work, apprenticeship or non- market production Proportion of employed who are employers, by sex UNSD I.6/ SGS Indicator 21 Method of Computation Calculation for indicator, by sex Women Men U@ABCD ;E GC>EVCAH>;ICW U@ABCD ;E GC>EVCAH>;ICW KF; F=NC CAH>;ICCG (ECA=>C) KF; F=NC CAH>;ICCG (A=>C) :;<=> ?@ABCD ;E CAH>;ICW (ECA=>C) × 100 :;<=> ?@ABCD ;E CAH>;ICW (A=>C) × 100 Proportion of employed who are employers, by sex UNSD I.6/ SGS Indicator 21 Thank you