In 2020, 60 percent of children in labor in Sub-Saharan Africa were aged between five and eleven years. The share of working 15 to 17 year olds in the same region was at 16.4 percent. Worldwide, 55.8 percent of working children were aged five to 11 years old.

In 2023, the number of child workers in Indonesia amounted to around 1.01 million people. This indicated a decrease of approximately 40 thousand people compared to 2021. Child labor in Indonesia is still an ongoing issue due to poverty and a lack of access to education in some parts of the country. The pandemic notably affected the problem, as the number of child workers increased in 2020. Although the numbers have decreased since then, they remain higher than the pre-pandemic level. The challenges of child labor in Indonesia The persisting issue of child labor in Indonesia stems from different factors such as economics, social norms, and education. Poverty acts as a crucial driving factor in the case of child labor practices. Many children are pushed to stop attending school and get to work to help the family’s income, as over nine percent of the Indonesian population still lives below the poverty line. The islands in the eastern part of the archipelago, such as Maluku and Papua, had the highest poverty rates of over 20 percent in 2022. It was also found that Papua had the highest share of students who had to attend school and work simultaneously. Moreover, in certain areas of the archipelago, cultural beliefs are linked to entering the labor force at an early age, with some believing this to help shape children to have better life opportunities in the future. The lack of awareness about the effects of child labor and some companies not complying with the laws against child labor further exacerbate the issue. Child labor in the Indonesian agricultural sector Child labor in Indonesia is more prevalent in rural areas. As of 2022, there has been an increase in the child labor rate in Indonesia’s rural areas in the agricultural sector, which most commonly offers informal employment with minimal employment protections. Child workers in this sector face higher risks of being exposed to harmful chemicals used in pesticides and fertilizers, causing raised concerns about their safety. Despite the efforts to overcome this issue, such as child protection laws, government allocations for infrastructure, and government allocations for education to improve living conditions and educational access, the need for strategic initiatives to combat child labor in Indonesia remains.

Africa has the highest incidence of child labor in the world. As of 2021, 26 percent of children aged 5-17 years in Sub-Saharan Africa were involved in child labor, according to estimates. Compared to 2012 and 2016, the rate has increased, peaking in 2021.

The number of children involved in child labor across the Asia-Pacific region decreased continuously between 2008 and 2020. In 2020, approximately 48.7 million children aged five to 17 years were involved in child labor in APAC, equivalent to a 5.6 percent share of children in the age group. This marked a decrease from around 113.6 million in 2008. Projected to decrease further over the next decade, the number is set to reach about 22.7 million in 2030.

Abstract

Bangladesh Bureau of Statistics (BBS) has conducted the National Child Labour Survey (NCLS) in 2002-03. NCLS 2002-2003 covered the entire country and was undertaken to provide reliable estimates of economically active children aged 5-17 years and child labour at national, urban and rural levels, as well as of children engaged in non-economic activities. The sample size and the coverage of the survey as such that it could furnish reliable key estimates by some administrative units such as divisions and regions/former districts. The survey has been designed to obtain estimates on a number of variables or parameters, particularly in relation to economic and non-economic activities of the children in age group 5-14 under usual circumstances and 15-17 in the case of worst forms of child labour (WFCL).

Objectives of the survey The main objective of the survey is to collect comprehensive data on working children aged 5 to 17 years. To achieve the objective, the survey instrument (questionnaire) has been designed as such to identify all activities of the children, economic or non-economic and these are broadly classified as – · attending school only (no other activity); · attending school and also engaged in economic activity; · attending school and also engaged in non-economic activity; · engaged in economic activity only; · engaged in non-economic activity only; · engaged both in economic and non-economic activities; · other children (sick, disabled or reported as idle); · not attending school and · not attending school and also not engaged in any economic and/or noneconomic activities.

The specific objectives of the survey are the following: i) to estimate the number (national, rural, urban etc) of working children and child labour by age, gender, education and residence, etc; ii) to estimate the number of working children by occupation, industry, status in employment etc. at 1- 4 digit Bangladesh Standard Occupation Classification (BSOC) and Bangladesh Standard Industrial Classification (BSIC) level respectively,in the line of the International Standard Industrial Classification of all economic activities (ISIC-Rev 3) and the International Standard Classification of Occupations (ISCO, 1988); iii) to assess the demographic and socio-economic characteristics of the families of working children; iv) to assess the social characteristics and working environment etc. of children; v) to assess average earnings/wages, remuneration, hours of work etc; vi) to assess occupational risk and health hazards, injuries, diseases and extent of disability etc. vii) to assess the extent of exploitation of working children in terms of hours of work and wages earned

Geographic coverage

National

Analysis unit

• Household
• Individual
• Children age 5 to 17

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Design

The NCLS was undertaken using Integrated Multipurpose Sample (IMPS) design The IMPS design is constructed on the basis of the Bangladesh population census 2001. It consists of 1,000 primary sampling units (PSUs) or enumeration blocks (EBs). Out of the total sample PSUs/EBs, 642 PSUs are selected from rural areas, 80 PSUs from statistical metropolitan areas (SMAs) and 278 PSUs from other urban areas or municipalities. In the rural areas, the PSU/EB is defined as a mouza, or the PSU/EB is a part of a mouza, or the combination of neighbouring mouzas; while in the urban areas, the PSu/EB is a mahalla, or a part a part of a mahalla, with an average number of 200 households per PSU. An enumeration block or PSU is constructed on the basis of contiguous census EAs (Enumeration Area) such that each EB/PSU is comprised of 180-220 households. There are 2 stages of stratification. At first 6 administrative divisions (The administrative setup of Bangladesh according to hierachy are as follows:- Division, district/zila, Thana/Upazila or Subdistrict, Union/ward and Village/mahalla. Division comprises of number of district/zila, district/zila consists of number of thana/upazila and Union consists of number of Villages. Mouza is a lowest unit for land revenue purpose. Bangladesh is now comprises of 6 divisions. In rural areas, the lowest unit is called village and in a urban areas it is called as mahalla) are treated as super strata and within these super strata there is a second stage of stratification comprising (i) rural areas, (ii) statistical metropolitan areas (SMAs) and municipalities. The SMAs and municipalities constitute urban area or urban stratum. The IMPS design consist of 16 strata which are : i) six rural strata for 6 divisions; ii) six urban strata for 6 divisions; and iii) four SMA strata for 4 metropolitan cities.

Sampling Scheme

The sampling scheme is PPS with proportional allocation within 16 strata at three stages with one unit selected at each stage. Three different stages are considered to select PSUs/EBs for each strata. Out of these three stages, two stages are dummy stages such that the selection of PSUs are essentially drawn by a single stage cluster sampling procedure. These stages are : i) Thanas are selected at first stage, (ii) Unions/Wards are selected at second stage and (iii) mouza/mahalla are selected at third stage. Then PSU/EBs are determined from the selected mouza by dividing the mouza or by combining a neighboring mouza with the selected mouza so as to make the size of the PSU/EB of around 200 households.

Note: See detailed sampling design in survey report which is presented in this documentation

Mode of data collection

Face-to-face [f2f]

Cleaning operations

Preliminary checking of entries in the filled-in questionnaires were done by the supervisors and enumerators at field level. Thorough manual editing was carried out by the trained editors under the strict supervision of the officers in Dhaka headquarter. Coding of occupation and industry was done as per Bangladesh Standard Occupation Classification (BSOC) and Bangladesh Standard Industrial Classification (BSIC) at 3 and 4 digit level respectively. Other items, such as, geo-codes and open-ended answers, were also coded in accordance with their respective code lists.

The edited and coded questionnaires were sent to Computer Wing, BBS for data processing. Computer edit was done to check internal consistency, omissions and errors. The statistical tables were produced in micro computer environment of the BBS. Each individual record was tallied and expanded using sample weights to obtain national estimate. The weights were calculated on the basis of the estimated population as on January 1, 2003.

Sampling error estimates

Estimate of standard errors and confidence interval information is available in Table 3 of the final report which is presented in this documentation.

Abstract

The Labour Force and Child Labour Force Survey 2013 was conducted by the Bangladesh Bureau of Statistics to provide reliable estimates on the labor force participation in the country at the national and sub-national levels. In 2013, this survey had two components: labor force and child labor.

The labor force component covered population age 15 or older living in the sampled households to obtain estimates on their economic and non-economic activities.

The child labor component was included to estimate the employment of population age 5 to 17, their conditions at the work place, and to probe and diagnose the circumstances leading to the existence of child labor in the country.

The survey covered the randomly selected sample of 36,242 households from 1,512 PSUs/sample enumeration areas distributed across all 64 districts.

Geographic coverage

National coverage

Analysis unit

• Household members 5 years old and older.

Institutional dwellings (hotels, hospitals, prisons, welfare homes, etc.) were excluded from the survey.

Universe

Population age 5 and above

Kind of data

Sample survey data [ssd]

Sampling procedure

The frame used for the selection of the sample for the survey was based on the Population and Housing Census 2011.

The sampling frame was made of Enumeration Areas (EAs), contiguous geographical areas of land with identifiable boundaries. On average, each EA has between 80 and 120 households. The sample has 1,512 PSUs/EAs spread all over the country, and covering all socio-economic classes, thus representative of the population. The survey was distributed into 21 domains rural, urban, and city corporations of seven divisions. From each selected PSU/EA, an equal number of 24 households were selected systematically, with a random start. A two-stage stratified cluster sampling design was adopted. The units for the first stare sample selection were the EAs and the households at the second stage.

Mode of data collection

Face-to-face [f2f]

Vietnam VN: Children in Employment: % of Children Aged 7-14 data was reported at 10.900 % in 2012. This records a decrease from the previous number of 13.000 % for 2011. Vietnam VN: Children in Employment: % of Children Aged 7-14 data is updated yearly, averaging 13.000 % from Dec 2006 (Median) to 2012, with 3 observations. The data reached an all-time high of 21.300 % in 2006 and a record low of 10.900 % in 2012. Vietnam VN: Children in Employment: % of Children Aged 7-14 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Vietnam – Table VN.World Bank.WDI: Labour Force. Children in employment refer to children involved in economic activity for at least one hour in the reference week of the survey.; ; Understanding Children's Work project based on data from ILO, UNICEF and the World Bank.; ;

Abstract

The main objectives of the CLF-CLS 2011-2012 are to collect detailed information on the country's labour force of persons 15 years old and above and children 5 to 17 years old disaggregated by age, gender, region, sector and social category. The survey provides information on the national labour market that can then be used to develop, manage and evaluate labour market policies and programmes. Also, the survey provides detailed information on child workers and hazards at work.

It is intended to promote a gender mainstreamed analysis of the labour market and compile national and provincial statistics relating to informal employment, working poor and vulnerable employment. These statistics will be especially useful to government as it attempts to identify the problems that Cambodians face in the area of employment. With this information available, planners and policy makers will then be better placed to develop policies and programmes to improve the welfare of the people and some information on working people and child labour.

Geographic coverage

National coverage

Analysis unit

• Individuals
• Households

Universe

1. Geographic part: All members from households in Cambodia
2. Education and labour force parts: All members aged 5 and over from households in Cambodia

Kind of data

Sample survey data [ssd]

Sampling procedure

The Cambodia Labour Force and Child Labour Survey 2011-12 covered 24 Capital/provinces in the country and involved 600 Enumeration Areas (EA) randomly selected as primary sampling units, or PSUs, and 9,600 households randomly selected as secondary sampling units, or SSUs. Each EA was randomly selected 16 sample household. Totally, there were 9,600 households to be interviewed.

The sampling frame was based on the village population data files from the 2008 general population census, conducted by the NIS. The CLF-CLS 2011-12 was undertaken in two stages with EAs as the primary sampling units and households as secondary sampling units. It consists of 600 primary sampling units (PSUs) or EAs. Out of the total sample EAs, 54 EAs were allocated for urban areas and the remainder 546 EAs for rural areas.

For details please refer to the document entitled "Report on Selection of Sampled Households from the Sampling Frame for Cambodia Labour Force and Child Labour Survey 2011-2012".

Mode of data collection

Face-to-face [f2f]

Research instrument

The following are the LFS-CLS forms used during the field enumeration and a brief outline of the fieldwork procedures:

Listing Sheet This is a sheet containing a list of the buildings, housing units and households within an enumeration area (EA). Other information pertaining to population of households were also recorded.

Listing sheet was used to record all households in the village or part thereof selected for household enumeration. The current list of households was necessary for sampling households and also as an input to derive household weights

Questionnaire
The Cambodia Labour Force and Child Labour questionnaire consists of a cover page, which contains general information on the household, followed by the 12 sections: A. Household composition and characteristics of household members B. Literacy and Education
C. Training within the last 12 months (outside of the general education system) D. Current activities E. Characteristics of the main job/activity in the last 7 days F. Characteristics of the secondary job/activity in the last 7 days G. Hours of work H. Underemployment I. Job search J. Occupational injuries within the last 12 months K. Participation in production of goods for use by own household L. Other activities

Cleaning operations

All completed questionnaires were brought to NIS for processing. Although completed questionnaires were checked and edited by supervisors in the field, specially because of the length of questionnaires and the complexity of the topics covered the need for manual editing and coding by trained staff was accepted as an essential priority activity to produce a cleaned data file without delay. In all 4 staff comprising 3 processing staff and 1 supervisor were trained for two days by the project staff. An instruction manual for manual editing and coding was prepared and translated into Khmer for the guidance of processing staff.

In order to produce an unedited data file, keying in the data as recorded by field enumerators and supervisors, (without subjecting data to manual edit as required by the Analysis Component Project staff), it was necessary to structure manual editing as a two-phase operation. Thus in the first phase, the processing staff coded the questions such as those industry, and occupation which required coding. Editing was restricted to selected structural edits and some error corrections. These edits were restricted to checking the completeness and consistency of responses, legibility, and totaling of selected questions. Error corrections were made without canceling or obliterating the original entry made by the enumerator, by inserting the correction close to the original entry.

Much of the manual editing was carried out in the second phase, after key entry and one hundred percent verification and extraction of error print outs. A wide range of errors had to be corrected which was expected in view of the complexity of the survey and the skill background of the enumeration and processing staff. The manual edits involved the correction of errors arising from incorrect key entry, in-correct/ failure to include identification, miss-coding of answers, failure to follow skip patterns, misinterpretation of measures, range errors, and other consistency errors.

Response rate

Despite the length of the questionnaire, the respondents cooperated with the survey staff and provided answers to both questionnaires and it was possible to achieve a 100% response rate. At this stage it is not possible to comment on item non-response, and completeness of information provided by the respondents, and the respondent's fatigue arising from the length of the interviews which may have had a bearing on these issues.

Abstract

The Uganda Government is faced with the challenge of elimination of child Labour in the Country. Child Labour contributes to a violation of the rights of Children to education and protection and it is putting at risk the country's progress by limiting the potential of its workforce. The Child Labour Baseline Survey exercise was carried out in three districts of Rakai, Mbale, and Wakiso districts. Lessons learnt will help to re-design Child Labour intervention programmes for the rest of the districts. In Uganda, a child is defined as someone below the age of 18 years. Generally speaking the term child Labour refers to involvement of children in the kind of work that is not allowed for them. When measuring Statistics on Child Labour two issues are considered, i.e;

(i) Age of the child;

(ii) The productive activities in which the child is involved, the nature and conditions in which activities are performed including the time spent in the activity.

The main objective of the 2009 child labour baseline Survey was to facilitate the measurement of the levels and nature of child labour in the focus districts. More than half of the population of surveyed districts is below 15 years of age. The proportion of child headship is low in all the districts. The proportion of paid employees and self employed is highest in Wakiso and lowest in Rakai district. Agriculture is the most dominant sector in which people are engaged followed by the trade sector. The purpose of the 2009 child labour Baseline Survey was to facilitate the measurement of the levels and nature of child labour in the focus districts of Rakai, Mbale and Wakiso. The specific objectives were:

(i) To collect information on the main characteristics of working children and those of the households they live in ( i.e. their demographic composition and details by age/ sex/ ethnicity/ marital status/disability status/orphan hood/ literacy and educational status/ classification by industry occupation and status in employment/ earnings and weekly hours of work/ location of work place/ reasons for not attending school/ reasons for working/ types of unpaid household services done and weekly hours performed/ etc);

(ii) To obtain information to support the analysis of the causes and consequences of children engaged in work, including household earnings and debt, perceptions of parents/ guardians/ children, and the hazards and abuses faced by children at their work;

(iii) To obtain (through FGDs and KIIs) information on

(a) the various forms of child labour prevailing in the districts, particularly on WFCL such as CSEC, street children, children engaged for illicit activities, and forced work by children (b) the underlying forces leading to the persistence of child labour especially the impact of HIV/AIDS, poverty, adult unemployment, OVC issue, and lack of proper schooling facilities; (c) Child trafficking (v) To provide policy makers, researchers and other stakeholders with a comprehensive information and a set of indicators on child labour to guide interventions;

(vi) To act as a basis for the creation of a long -term database on child labour in Uganda.

Geographic coverage

The Child Labour Baseline Survey (2009) was carried out in the districts of Rakai, Wakiso and Mbale.

Analysis unit

The Child Labour Baseline Survey 2009 had the following units of analysis: individuals, and households.

Universe

The survey covered all de jure household members aged 5 years and above resident in the household, and all children aged 5 - 17 years resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

In order to achieve the objectives of the Child Labour Baseline Survey, the study targeted all households with children and communities in the focus districts. The Enumeration Areas (EAs) from the 2002 Population and Housing Census household counts were used as the sampling frame for each of the districts. Each EA was accurately and uniquely identified together with the number of households in it. Independent representative samples were selected from each of the districts using Population proportional to Size (PPS) with the number of households in the EA with children taken as a measure of size. A representative sample was selected from each of these focus districts. In order to ensure that reliable estimates are got for each district, EAs were distributed among the districts according to the measures of size. Allocation of EAs and households per district was as indicated below:

Mode of data collection

Face-to-face [f2f]

Cleaning operations

Due to the need to have the child labour baseline survey records processed fast enough, this exercise started shortly after the commencement of fieldwork. The office editing/coding and data capture process for the survey took approximately 2 weeks. It involved double data entry which ensured that the accuracy of the captured data was checked in the second data capture routine hence increasing on its accuracy. After the data capture machine editing involving structural and consistency edits was carried out before data analysis. The data capture screen was developed using the CSPro (Census and Survey Processing) software.

Response rate

A total of 1,617 households were selected for the Child Labour Baseline Survey (CLBS) Sample. Out of these, 1,585 households were successfully interviewed, yielding a household response rate of 98 percent. A total of 4,431 children aged 5-17 years were listed from the selected households in the household schedule, of which 4,306 children successfully responded to questions about activity status. This gave a children response rate of 97.2 percent

Sampling error estimates

The CLBS 2009 was a sample survey and hence likely to be affected by sampling and non-sampling errors. The following was carrying out to minimize on errors at different stages of implementation: Using a standard child labour questionnaire adjusted to national requirements; Ensuring effective supervision during data collection and use of experienced interviewers; Supervising experienced staff used in the data capture process in addition to carrying out double data entry; Drawing the sample from complete frame of EAs with their corresponding number of households ( as distributed by district); Carrying on edits on the captured data before data analysis.

Annex 3 of the final report presents the standard errors, CVs and confidence intervals for selected indicators.

The skeptics of globalization argue that increased trade openness and foreign direct investment induce developing countries to keep labor costs low, for example, by letting children work. This article argues that there are good theoretical reasons why globalization might actually have the opposite effect.We test this with various measures of childlabor and providethe first anal- ysis of foreign investment in addition to trade. We present evidence that countries that are more open to trade and/or have a higher stock of foreign direct investment also have a lower incidence of child labor. This holds for the labor force participation rate of 10–14-year old children, the sec- ondary school nonattendance rate and a count measure of economic sectors with child labor inci- dence as the dependent variables. Globalization is associated with less, not more, child labor

Percentage of children aged 5-14 years engaged in child labour (by sex, place of residence and household wealth quintile), including country breakdown

Definition: Percentage of children 5–17 years old involved in child labour at the moment of the survey. A child is considered to be involved in child labour under the following conditions: (a) children 5–11 years old who, during the reference week, did at least one hour of economic activity or at least 28 hours of household chores, (b) children 12–14 years old who, during the reference week, did at least 14 hours of economic activity or at least 28 hours of household chores, (c) children 15–17 years old who, during the reference week, did at least 43 hours of economic activity or household chores, and (d) children aged 5–17 years old in hazardous working conditions.

Contains data from the World Bank's data portal. There is also a consolidated country dataset on HDX.

Data here cover child labor, gender issues, refugees, and asylum seekers. Children in many countries work long hours, often combining studying with work for pay. The data on their paid work are from household surveys conducted by the International Labour Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. Gender disparities are measured using a compilation of data on key topics such as education, health, labor force participation, and political participation. Data on refugees are from the United Nations High Commissioner for Refugees complemented by statistics on Palestinian refugees under the mandate of the United Nations Relief and Works Agency.

Goal 8Promote sustained, inclusive and sustainable economic growth, full and productive employment and decent work for allTarget 8.1: Sustain per capita economic growth in accordance with national circumstances and, in particular, at least 7 per cent gross domestic product growth per annum in the least developed countriesIndicator 8.1.1: Annual growth rate of real GDP per capitaNY_GDP_PCAP: Annual growth rate of real GDP per capita (%)Target 8.2: Achieve higher levels of economic productivity through diversification, technological upgrading and innovation, including through a focus on high-value added and labour-intensive sectorsIndicator 8.2.1: Annual growth rate of real GDP per employed personSL_EMP_PCAP: Annual growth rate of real GDP per employed person (%)Target 8.3: Promote development-oriented policies that support productive activities, decent job creation, entrepreneurship, creativity and innovation, and encourage the formalization and growth of micro-, small- and medium-sized enterprises, including through access to financial servicesIndicator 8.3.1: Proportion of informal employment in total employment, by sector and sexSL_ISV_IFEM: Proportion of informal employment, by sector and sex (ILO harmonized estimates) (%)Target 8.4: Improve progressively, through 2030, global resource efficiency in consumption and production and endeavour to decouple economic growth from environmental degradation, in accordance with the 10-Year Framework of Programmes on Sustainable Consumption and Production, with developed countries taking the leadIndicator 8.4.1: Material footprint, material footprint per capita, and material footprint per GDPEN_MAT_FTPRPG: Material footprint per unit of GDP, by type of raw material (kilograms per constant 2010 United States dollar)EN_MAT_FTPRPC: Material footprint per capita, by type of raw material (tonnes)EN_MAT_FTPRTN: Material footprint, by type of raw material (tonnes)Indicator 8.4.2: Domestic material consumption, domestic material consumption per capita, and domestic material consumption per GDPEN_MAT_DOMCMPT: Domestic material consumption, by type of raw material (tonnes)EN_MAT_DOMCMPG: Domestic material consumption per unit of GDP, by type of raw material (kilograms per constant 2010 United States dollars)EN_MAT_DOMCMPC: Domestic material consumption per capita, by type of raw material (tonnes)Target 8.5: By 2030, achieve full and productive employment and decent work for all women and men, including for young people and persons with disabilities, and equal pay for work of equal valueIndicator 8.5.1: Average hourly earnings of employees, by sex, age, occupation and persons with disabilitiesSL_EMP_EARN: Average hourly earnings of employees by sex and occupation (local currency)Indicator 8.5.2: Unemployment rate, by sex, age and persons with disabilitiesSL_TLF_UEM: Unemployment rate, by sex and age (%)SL_TLF_UEMDIS: Unemployment rate, by sex and disability (%)Target 8.6: By 2020, substantially reduce the proportion of youth not in employment, education or trainingIndicator 8.6.1: Proportion of youth (aged 15–24 years) not in education, employment or trainingSL_TLF_NEET: Proportion of youth not in education, employment or training, by sex and age (%)Target 8.7: Take immediate and effective measures to eradicate forced labour, end modern slavery and human trafficking and secure the prohibition and elimination of the worst forms of child labour, including recruitment and use of child soldiers, and by 2025 end child labour in all its formsIndicator 8.7.1: Proportion and number of children aged 5–17 years engaged in child labour, by sex and ageSL_TLF_CHLDEC: Proportion of children engaged in economic activity and household chores, by sex and age (%)SL_TLF_CHLDEA: Proportion of children engaged in economic activity, by sex and age (%)Target 8.8: Protect labour rights and promote safe and secure working environments for all workers, including migrant workers, in particular women migrants, and those in precarious employmentIndicator 8.8.1: Fatal and non-fatal occupational injuries per 100,000 workers, by sex and migrant statusSL_EMP_FTLINJUR: Fatal occupational injuries among employees, by sex and migrant status (per 100,000 employees)SL_EMP_INJUR: Non-fatal occupational injuries among employees, by sex and migrant status (per 100,000 employees)Indicator 8.8.2: Level of national compliance with labour rights (freedom of association and collective bargaining) based on International Labour Organization (ILO) textual sources and national legislation, by sex and migrant statusSL_LBR_NTLCPL: Level of national compliance with labour rights (freedom of association and collective bargaining) based on International Labour Organization (ILO) textual sources and national legislationTarget 8.9: By 2030, devise and implement policies to promote sustainable tourism that creates jobs and promotes local culture and productsIndicator 8.9.1: Tourism direct GDP as a proportion of total GDP and in growth rateST_GDP_ZS: Tourism direct GDP as a proportion of total GDP (%)Target 8.10: Strengthen the capacity of domestic financial institutions to encourage and expand access to banking, insurance and financial services for allIndicator 8.10.1: (a) Number of commercial bank branches per 100,000 adults and (b) number of automated teller machines (ATMs) per 100,000 adultsFB_ATM_TOTL: Number of automated teller machines (ATMs) per 100,000 adultsFB_CBK_BRCH: Number of commercial bank branches per 100,000 adultsIndicator 8.10.2: Proportion of adults (15 years and older) with an account at a bank or other financial institution or with a mobile-money-service providerFB_BNK_ACCSS: Proportion of adults (15 years and older) with an account at a financial institution or mobile-money-service provider, by sex (% of adults aged 15 years and older)Target 8.a: Increase Aid for Trade support for developing countries, in particular least developed countries, including through the Enhanced Integrated Framework for Trade-related Technical Assistance to Least Developed CountriesIndicator 8.a.1: Aid for Trade commitments and disbursementsDC_TOF_TRDCMDL: Total official flows (commitments) for Aid for Trade, by donor countries (millions of constant 2018 United States dollars)DC_TOF_TRDDBMDL: Total official flows (disbursement) for Aid for Trade, by donor countries (millions of constant 2018 United States dollars)DC_TOF_TRDDBML: Total official flows (disbursement) for Aid for Trade, by recipient countries (millions of constant 2018 United States dollars)DC_TOF_TRDCML: Total official flows (commitments) for Aid for Trade, by recipient countries (millions of constant 2018 United States dollars)Target 8.b: By 2020, develop and operationalize a global strategy for youth employment and implement the Global Jobs Pact of the International Labour OrganizationIndicator 8.b.1: Existence of a developed and operationalized national strategy for youth employment, as a distinct strategy or as part of a national employment strategySL_CPA_YEMP: Existence of a developed and operationalized national strategy for youth employment, as a distinct strategy or as part of a national employment strategy

This map shows the average number of children born to a woman during her lifetime. Data from Population Reference Bureau's 2017 World Population Data Sheet. The world's total fertility rate reported in 2017 was 2.5 as a whole. Replacement-Level fertility is widely recognized as 2.0 children per woman, so as to "replace" each parent in the next generation. Countries depicted in pink have a total fertility rate below replacement level whereas countries depicted in teal have a total fertility rate above replacement level. In countries with very high child mortality rates, a replacement level of 2.1 could be used, since not every child will survive into their reproductive years. Determinants of Total Fertility Rate include: women's education levels and opportunities, marriage rates among women of childbearing age (generally defined as 15-49), contraceptive usage and method mix/effectiveness, infant & child mortality rates, share of population living in urban areas, the importance of children as part of the labor force (or cost/penalty to women's labor force options that having children poses), and religious and cultural norms, among many other factors. This map was made using the Global Population and Maternal Health Indicators layer.

In 2020, 9.3 percent of children aged 12 to 14 years worldwide were in child labor. Eleven percent of children in this age group were boys and 7.5 percent girls. Boys were prevalent in every age group of working children in 2020.

Goal 8Promote sustained, inclusive and sustainable economic growth, full and productive employment and decent work for allTarget 8.1: Sustain per capita economic growth in accordance with national circumstances and, in particular, at least 7 per cent gross domestic product growth per annum in the least developed countriesIndicator 8.1.1: Annual growth rate of real GDP per capitaNY_GDP_PCAP: Annual growth rate of real GDP per capita (%)Target 8.2: Achieve higher levels of economic productivity through diversification, technological upgrading and innovation, including through a focus on high-value added and labour-intensive sectorsIndicator 8.2.1: Annual growth rate of real GDP per employed personSL_EMP_PCAP: Annual growth rate of real GDP per employed person (%)Target 8.3: Promote development-oriented policies that support productive activities, decent job creation, entrepreneurship, creativity and innovation, and encourage the formalization and growth of micro-, small- and medium-sized enterprises, including through access to financial servicesIndicator 8.3.1: Proportion of informal employment in total employment, by sector and sexSL_ISV_IFEM: Proportion of informal employment, by sector and sex (ILO harmonized estimates) (%)Target 8.4: Improve progressively, through 2030, global resource efficiency in consumption and production and endeavour to decouple economic growth from environmental degradation, in accordance with the 10-Year Framework of Programmes on Sustainable Consumption and Production, with developed countries taking the leadIndicator 8.4.1: Material footprint, material footprint per capita, and material footprint per GDPEN_MAT_FTPRPG: Material footprint per unit of GDP, by type of raw material (kilograms per constant 2010 United States dollar)EN_MAT_FTPRPC: Material footprint per capita, by type of raw material (tonnes)EN_MAT_FTPRTN: Material footprint, by type of raw material (tonnes)Indicator 8.4.2: Domestic material consumption, domestic material consumption per capita, and domestic material consumption per GDPEN_MAT_DOMCMPT: Domestic material consumption, by type of raw material (tonnes)EN_MAT_DOMCMPG: Domestic material consumption per unit of GDP, by type of raw material (kilograms per constant 2010 United States dollars)EN_MAT_DOMCMPC: Domestic material consumption per capita, by type of raw material (tonnes)Target 8.5: By 2030, achieve full and productive employment and decent work for all women and men, including for young people and persons with disabilities, and equal pay for work of equal valueIndicator 8.5.1: Average hourly earnings of employees, by sex, age, occupation and persons with disabilitiesSL_EMP_EARN: Average hourly earnings of employees by sex and occupation (local currency)Indicator 8.5.2: Unemployment rate, by sex, age and persons with disabilitiesSL_TLF_UEM: Unemployment rate, by sex and age (%)SL_TLF_UEMDIS: Unemployment rate, by sex and disability (%)Target 8.6: By 2020, substantially reduce the proportion of youth not in employment, education or trainingIndicator 8.6.1: Proportion of youth (aged 15–24 years) not in education, employment or trainingSL_TLF_NEET: Proportion of youth not in education, employment or training, by sex and age (%)Target 8.7: Take immediate and effective measures to eradicate forced labour, end modern slavery and human trafficking and secure the prohibition and elimination of the worst forms of child labour, including recruitment and use of child soldiers, and by 2025 end child labour in all its formsIndicator 8.7.1: Proportion and number of children aged 5–17 years engaged in child labour, by sex and ageSL_TLF_CHLDEC: Proportion of children engaged in economic activity and household chores, by sex and age (%)SL_TLF_CHLDEA: Proportion of children engaged in economic activity, by sex and age (%)Target 8.8: Protect labour rights and promote safe and secure working environments for all workers, including migrant workers, in particular women migrants, and those in precarious employmentIndicator 8.8.1: Fatal and non-fatal occupational injuries per 100,000 workers, by sex and migrant statusSL_EMP_FTLINJUR: Fatal occupational injuries among employees, by sex and migrant status (per 100,000 employees)SL_EMP_INJUR: Non-fatal occupational injuries among employees, by sex and migrant status (per 100,000 employees)Indicator 8.8.2: Level of national compliance with labour rights (freedom of association and collective bargaining) based on International Labour Organization (ILO) textual sources and national legislation, by sex and migrant statusSL_LBR_NTLCPL: Level of national compliance with labour rights (freedom of association and collective bargaining) based on International Labour Organization (ILO) textual sources and national legislationTarget 8.9: By 2030, devise and implement policies to promote sustainable tourism that creates jobs and promotes local culture and productsIndicator 8.9.1: Tourism direct GDP as a proportion of total GDP and in growth rateST_GDP_ZS: Tourism direct GDP as a proportion of total GDP (%)Target 8.10: Strengthen the capacity of domestic financial institutions to encourage and expand access to banking, insurance and financial services for allIndicator 8.10.1: (a) Number of commercial bank branches per 100,000 adults and (b) number of automated teller machines (ATMs) per 100,000 adultsFB_ATM_TOTL: Number of automated teller machines (ATMs) per 100,000 adultsFB_CBK_BRCH: Number of commercial bank branches per 100,000 adultsIndicator 8.10.2: Proportion of adults (15 years and older) with an account at a bank or other financial institution or with a mobile-money-service providerFB_BNK_ACCSS: Proportion of adults (15 years and older) with an account at a financial institution or mobile-money-service provider, by sex (% of adults aged 15 years and older)Target 8.a: Increase Aid for Trade support for developing countries, in particular least developed countries, including through the Enhanced Integrated Framework for Trade-related Technical Assistance to Least Developed CountriesIndicator 8.a.1: Aid for Trade commitments and disbursementsDC_TOF_TRDCMDL: Total official flows (commitments) for Aid for Trade, by donor countries (millions of constant 2018 United States dollars)DC_TOF_TRDDBMDL: Total official flows (disbursement) for Aid for Trade, by donor countries (millions of constant 2018 United States dollars)DC_TOF_TRDDBML: Total official flows (disbursement) for Aid for Trade, by recipient countries (millions of constant 2018 United States dollars)DC_TOF_TRDCML: Total official flows (commitments) for Aid for Trade, by recipient countries (millions of constant 2018 United States dollars)Target 8.b: By 2020, develop and operationalize a global strategy for youth employment and implement the Global Jobs Pact of the International Labour OrganizationIndicator 8.b.1: Existence of a developed and operationalized national strategy for youth employment, as a distinct strategy or as part of a national employment strategySL_CPA_YEMP: Existence of a developed and operationalized national strategy for youth employment, as a distinct strategy or as part of a national employment strategy

A computerized data set of demographic, economic and social data for 227 countries of the world. Information presented includes population, health, nutrition, mortality, fertility, family planning and contraceptive use, literacy, housing, and economic activity data. Tabular data are broken down by such variables as age, sex, and urban/rural residence. Data are organized as a series of statistical tables identified by country and table number. Each record consists of the data values associated with a single row of a given table. There are 105 tables with data for 208 countries. The second file is a note file, containing text of notes associated with various tables. These notes provide information such as definitions of categories (i.e. urban/rural) and how various values were calculated. The IDB was created in the U.S. Census Bureau''s International Programs Center (IPC) to help IPC staff meet the needs of organizations that sponsor IPC research. The IDB provides quick access to specialized information, with emphasis on demographic measures, for individual countries or groups of countries. The IDB combines data from country sources (typically censuses and surveys) with IPC estimates and projections to provide information dating back as far as 1950 and as far ahead as 2050. Because the IDB is maintained as a research tool for IPC sponsor requirements, the amount of information available may vary by country. As funding and research activity permit, the IPC updates and expands the data base content. Types of data include: * Population by age and sex * Vital rates, infant mortality, and life tables * Fertility and child survivorship * Migration * Marital status * Family planning Data characteristics: * Temporal: Selected years, 1950present, projected demographic data to 2050. * Spatial: 227 countries and areas. * Resolution: National population, selected data by urban/rural * residence, selected data by age and sex. Sources of data include: * U.S. Census Bureau * International projects (e.g., the Demographic and Health Survey) * United Nations agencies Links: * ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/08490

UNICEF's country profile for Democratic People’s Republic of Korea, including under-five mortality rates, child health, education and sanitation data.

Abstract

The objectives of the 2001 Ethiopia Stand-alone Child Lobour Survey was to provide Statistical data on children's activities focusing on the status of schooling non-economic and economic activities. Specifically, the Survey was aimed at to provide statistical data that will help to: (a) establish the demographic and socio-economic characteristics of children: age, sex, status and levels of education and training occupations, skill-levels, hours of work, earnings and other working and living conditions; (b) assess the working situation of children and the influence on their education, health physical and mental development; (c) examine the characteristics of the sectors that employ most children; (d) identify where and how long the children have been working and the factors that lead children to work or families to put children to work and; (e) assess the health and welfare status of working children.

The survey collected information for all members of selected households as well as for children aged 5-17 years. Data collected for all members of the household include particulars of household members, like age, sex, religion, ethnicity, school attendance and training and marital status; economic activity status of the population aged 5 years and over during the last seven days, if non-working (economically and active) reason for not working, number of hours worked, ... etc.; economic activities of population aged 10 years and over during the last twelve months; housing conditions, housing facilities and household income and expenditure were collected.

For children aged 5-17 years, information on movement of children between households; school attendance and reason for dropouts; domestic activities and idleness; health and welfare situations of children who have been working at any time in the past; conditions of employment of children who are working for a non-relative person for pay; perception of parents of those children that are engaged in economic activity about the children’s working conditions were collected from their parents or guardians. Similar information about children aged 10-17 years were also collected from children themselves.

Geographic coverage

National coverage

Analysis unit

• Households
• Individuals
• Children aged 5-17 years

Universe

The survey is not covered non-sedentary areas of two zones of the Affar Region and six zones of the Somali Region. Residents of collective quarters, homeless and foreigners were not covered in the survey.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Frame: The Enumeration Area (EA) delineated for the 1994 Population and Housing Census of Ethiopia was used as a sampling frame for the selection of Primary Sampling Units (PSU). The sampling frame used for the selection f ultimate sampling units (households) as a fresh list of households, which was prepared b y the enumerator in the sampled E A at the time of the survey.

Sample Design: The 2001 Stand-alone National Child Labour Survey of Ethiopia covered both rural and urban parts of the country. However, it has not covered non-sedentary areas of two zones of the Affar Region and six zones of the Somali Region. Residents of collective quarters, homeless and foreigners were not covered in the survey. For the purpose of the survey, the population of the country was divided into three major categories namely, rural, major urban centers and other urban centers.

Category I: Rural parts of each regional state were grouped in this category. Each of the regions was a reporting level: thus, there are 11 reporting levels in this category.

Category II: Major urban centers were grouped under this category. The list of urban centers included in this category (domain of study). Each of them were used as the survey domains for which the survey results were reported, hence, the reporting levels under this category are totally 11 major urban centers, namely, Mekele, Gonder, Dessie, Bahir Dar, Nazreth, Debre Zeit, Jimma, Awassa, Harar, Addis Ababa and DireDawa.

Category III: Other urban centers, which were not included in category II, were included in this category. Except for Harari Region, Addis Ababa and Dire Dawa administrations, each region was serving as a reporting level independently by their respective regional states. As we can see from Table 2.3 this category has 8 reporting levels.

In addition to the above domains of study, the survey results were also reported at regional and country levels by aggregating the survey results from the corresponding domains. All in all 48 basic survey domains (reporting levels) including urban part of each regional state, total (urban + rural) part of each region, country level urban, country level rural and country level total were defined for the survey.

Sample Size Selection Schema: A sample size of 1,257 EAs was fixed based upon the required precision level and available resource for the survey. The 1999 National Labor Force Survey result was used to determine the required number of sample households per PSU/EA. For this survey, it was found that about 35 households per EA would give fair and reasonable estimates at a required reporting level for the variables under study.

In category II, and I stratified two-stage cluster sampling was used for the selection of ultimate sampling units. The Primary Sampling Units (PSUs) are EAs and secondary sampling units are households. In category III stratified three-stages cluster sampling was used for the selection of ultimate sampling units. In this category the PSUs are towns, the Secondary Sampling Units (SSUs) are EAs and the tertiary sampling units are households t he probability proportional to size (PPS) systematic sampling, size being total number of households obtained from the 1994 population and housing census was used for selection of towns and E As.

From category I a total of 723 EAs, from category II a total of 305 EAs and from category III a total of 229 EAs were selected after generating afresh listing of households within each sample EA at the beginning of the field work the survey questionnaire was administered to 35 systematically selected households for rural and both categories of the urban domains. Based on the results of the survey coverage rate of sample EAs was 100 percent and response rate of sampled household was 99.1percent.

Mode of data collection

Face-to-face [f2f]

Research instrument

At the inception of the survey design, the ILO has provided the Central Statistical Authority (CSA) a draft module questionnaire that was tested and applied in other African countries to be used as a base and to decide on the content and format of the Ethiopia Stand-alone Child Labour Survey. The ILO's module questionnaire was then redesigned to reflect the existing conditions of the country, in close consultation with Ministry of Labour and Social Affairs (MOLSA) and the ILO in order to satisfy the data requirements of the country as well as the feasibility in the data collection operations. Accordingly, the survey questionnaire modified into three forms, where Form-I of the questionnaire that refers to demographic and socio-economic condition of household members was administered to each member of the selected households. Form-II of the survey questionnaire refers to children aged 5-17 years and the information was collected by interviewed from the parents or guardians of the children, while Form-III was addressed to children aged 10-17 years and the children themselves give the responses to the questions.

In the process of designing the survey questionnaire, a pilot survey was conducted where the questionnaires and other survey instruments were tested in the field and amended accordingly. Furthermore, a half day user-producer forum was prepared that involved the Ministry of Labour and Social Affairs, other concerned government agencies, the ILO Area Office in Addis Ababa and NGO's that are involved in child issues. Comments and inputs on the draft content of the survey questionnaire from the users aspect were obtained and are used as inputs in finalizing the questionnaire.

Briefly the major variables included in the three Forms of the questionnaire are presented below.

Form - I: Area Identification of the Selected Household and Socio-demographic Characteristics of Household Members Section 1: Area identification of the selected household. Section 2: Particulars of respondents and household members, that is, socio-demographic characteristics of the population like age, sex, religion, ethnicity, schooling and training and marital status.
Section 3: Economic activities of the population aged 5 years and over during the last seven days; this section identifies working and non-working population and reason for not working, number of hours worked, amount and source of earnings of children as well as other members of household.
Section 4: Economic activities of population aged 10 years and over during the last twelve months. Section 5: Household section of the questionnaire that deals with housing conditions, housing facilities and household income and expenditure.

Form - II: Economic Activity Status of Children Aged 5-17 Years - to be addressed to Parents, Guardians or Heads of Households Section 6: Movement of children between households; Section 7: Schooling and reason for dropouts; Section 8: Domestic activities without payment and idleness; Section 9: Health and welfare situations of children who have been working at any time in the past; Section 10: Conditions of employment of children who are working for a non-relative person for pay; Section 11: Perception of parents of those children that

Abstract

The Ghana Child Labour Survey is the first nationwide survey in the country specifically designed to collect information on the various aspects of working children, within the framework of the International Programme on the Elimination of Child Labour (IPEC). It is a two-in-one survey, which canvassed children in households as well as children on the street, using two different sample designs. The fieldwork was conducted in February 2001, with technical assistance from the International Labour Organization (ILO). It is expected that the results of the survey will generate more awareness of child labour issues, promote the campaign against its practice, and serve as the basis for the formulation of appropriate intervention programmes.

Geographic coverage

National

Analysis unit

Individual person (household head and children)

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2001 Ghana Child Labour Survey comprised both a nationwide probability sample survey of all households in Ghana and a supplementary non-probability survey of street children.

The sampling frame for the household-based sample survey was the list of all 26,555 Enumeration Areas (EAs) from the 2000 Population and Housing Census of Ghana with corresponding data on number of households. The household sample survey was based on a two-stage stratified cluster design. The frame was stratified into urban and rural localities of residence and by the 10 administrative regions in the country.

At the first stage, 500 Enumeration Areas (EAs) were systematically selected, with probability proportional to size, the measure of size being the number of census households. At the second stage, 20 households were selected from each of the 500 EAs to produce an overall sample size of 10,000 households. The design ensured that every household in the country had the same chance to be selected; in other words, the sample was self-weighting (see Appendix II for a detailed explanation of the sample design). The sampling process yielded the allocation of households to each stratum (urban/rural and region) shown in Table 2.1. The sample also yielded an average weight of 370.12 for each child. This means that each child in the survey represents about 370 children.

Mode of data collection

Face-to-face [f2f]

Cleaning operations

Data entry was centralized at the head office. The main data entry software was the IMPS (Integrated Microcomputer Processing System). The two questionnaires, street children and the household questionnaires, were entered separately. Edit programs in CONCOR were used to edit the data, after which error listings were printed and corrected on EA level.

After editing, the ASCII data were put together and cleaned further, using SPSS and SAS. This was done by running consistency checks on every variable and the database was generated thereby. The analysis and tabulation were executed in SAS and SPSS. Estimates, standard errors, confidence intervals and design effects were generated using the CENVAR module in IMPS.

Response rate

Out of the 10,000 selected households, 9,889 were successfully interviewed, indicating a household response rate of 98.9 percent. A similar response rate was achieved in all regions and in rural/urban areas.