Ethiopia ET: Population with Access to Improved Drinking Water Sources: % of Total Population data was reported at 13.240 % in 2022. This records an increase from the previous number of 12.880 % for 2021. Ethiopia ET: Population with Access to Improved Drinking Water Sources: % of Total Population data is updated yearly, averaging 8.130 % from Dec 2000 (Median) to 2022, with 23 observations. The data reached an all-time high of 13.240 % in 2022 and a record low of 5.040 % in 2000. Ethiopia ET: Population with Access to Improved Drinking Water Sources: % of Total Population data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Ethiopia – Table ET.OECD.GGI: Social: Access to Services: Non OECD Member: Annual.

Abstract

The 2005 Ethiopia Demographic and Health Survey (2005 EDHS) is part of the worldwide MEASURE DHS project which is funded by the United States Agency for International Development (USAID).

The principal objective of the 2005 Ethiopia Demographic and Health Survey (DHS) is to provide current and reliable data on fertility and family planning behaviour, child mortality, adult and maternal mortality, children’s nutritional status, the utilization of maternal and child health services, knowledge of HIV/AIDS and prevalence of HIV/AIDS and anaemia.

The specific objectives are to: - collect data at the national level which will allow the calculation of key demographic rates; - analyze the direct and indirect factors which determine the level and trends of fertility; - measure the level of contraceptive knowledge and practice of women and men by method, urban-rural residence, and region; - collect high quality data on family health including immunization coverage among children, prevalence and treatment of diarrhoea and other diseases among children under five, and maternity care indicators including antenatal visits and assistance at delivery; - collect data on infant and child mortality and maternal and adult mortality; - obtain data on child feeding practices including breastfeeding and collect anthropometric measures to use in assessing the nutritional status of women and children; - collect data on knowledge and attitudes of women and men about sexually transmitted diseases and HIV/AIDS and evaluate patterns of recent behaviour regarding condom use; - conduct haemoglobin testing on women age 15-49 and children under age five years in a subsample of the households selected for the survey to provide information on the prevalence of anaemia among women in the reproductive ages and young children; - collect samples for anonymous HIV testing from women and men in the reproductive ages to provide information on the prevalence of HIV among the adult population.

This information is essential for informed policy decisions, planning, monitoring, and evaluation of programs on health in general and reproductive health in particular at both the national and regional levels. A long-term objective of the survey is to strengthen the technical capacity of the Central Statistical Agency to plan, conduct, process, and analyse data from complex national population and health surveys. Moreover, the 2005 Ethiopia DHS provides national and regional estimates on population and health that are comparable to data collected in similar surveys in other developing countries. The first ever Demographic and Health Survey (DHS) in Ethiopia was conducted in the year 2000 as part of the worldwide DHS programme. Data from the 2005 Ethiopia DHS survey, the second such survey, add to the vast and growing international database on demographic and health variables.

Wherever possible, the 2005 EDHS data is compared with data from the 2000 EDHS. In addition, where applicable, the 2005 EDHS is compared with the 1990 NFFS, which also sampled women age 15-49. Husbands of currently married women were also covered in this survey. However, for security and other reasons, the NFFS excluded from its coverage Eritrea, Tigray, Asseb, and Ogaden autonomous regions. In addition, fieldwork could not be carried out for Northern Gondar, Southern Gondar, Northern Wello, and Southern Wello due to security reasons. Thus, any comparison between the EDHS and the NFFS has to be interpreted with caution.

Geographic coverage

National

Analysis unit

• Household
• Children under five years
• Women age 15-49
• Men age 15-59

Kind of data

Sample survey data

Sampling procedure

The 2005 EDHS sample was designed to provide estimates for the health and demographic variables of interest for the following domains: Ethiopia as a whole; urban and rural areas of Ethiopia (each as a separate domain); and 11 geographic areas (9 regions and 2 city administrations), namely: Tigray; Affar; Amhara; Oromiya; Somali; Benishangul-Gumuz; Southern Nations, Nationalities and Peoples (SNNP); Gambela; Harari; Addis Ababa and Dire Dawa. In general, a DHS sample is stratified, clustered and selected in two stages. In the 2005 EDHS a representative sample of approximately 14,500 households from 540 clusters was selected. The sample was selected in two stages. In the first stage, 540 clusters (145 urban and 395 rural) were selected from the list of enumeration areas (EA) from the 1994 Population and Housing Census sample frame.

In the census frame, each of the 11 administrative areas is subdivided into zones and each zone into weredas. In addition to these administrative units, each wereda was subdivided into convenient areas called census EAs. Each EA was either totally urban or rural and the EAs were grouped by administrative wereda. Demarcated cartographic maps as well as census household and population data were also available for each census EA. The 1994 Census provided an adequate frame for drawing the sample for the 2005 EDHS. As in the 2000 EDHS, the 2005 EDHS sampled three of seven zones in the Somali Region (namely, Jijiga, Shinile and Liben). In the Affar Region the incomplete frame used in 2000 was improved adding a list of villages not previously included, to improve the region's representativeness in the survey. However, despite efforts to cover the settled population, there may be some bias in the representativeness of the regional estimates for both the Somali and Affar regions, primarily because the census frame excluded some areas in these regions that had a predominantly nomadic population.

The 540 EAs selected for the EDHS are not distributed by region proportionally to the census population. Thus, the sample for the 2005 EDHS must be weighted to produce national estimates. As part of the second stage, a complete household listing was carried out in each selected cluster. The listing operation lasted for three months from November 2004 to January 2005. Between 24 and 32 households from each cluster were then systematically selected for participation in the survey.

Because of the way the sample was designed, the number of cases in some regions appear small since they are weighted to make the regional distribution nationally representative. Throughout this report, numbers in the tables reflect weighted numbers. To ensure statistical reliability, percentages based on 25 to 49 unweighted cases are shown in parentheses and percentages based on fewer than 25 unweighted cases are suppressed.

Note: See detailed sample implementation table in APPENDIX A of the survey report.

Mode of data collection

Face-to-face [f2f]

Research instrument

In order to adapt the standard DHS core questionnaires to the specific socio-cultural settings and needs in Ethiopia, its contents were revised through a technical committee composed of senior and experienced demographers of PHCCO. After the draft questionnaires were prepared in English, copies of the household, women’s and men’s questionnaires were distributed to relevant institutions and individual researchers for comments. A one-day workshop was organized on November 22, 2004 at the Ghion Hotel in Addis Ababa to discuss the contents of the questionnaire. Over 50 participants attended the national workshop and their comments and suggestions collected. Based on these comments, further revisions were made on the contents of the questionnaires. Some additional questions were included at the request of MOH, the Fistula Hospital, and USAID. The questionnaires were finalized in English and translated into the three main local languages: Amharic, Oromiffa and Tigrigna. In addition, the DHS core interviewer’s manual for the Women’s and Men’s Questionnaires, the supervisor’s and editor’s manual, and the HIV and anaemia field manual were modified and translated into Amharic.

The Household Questionnaire was used to list all the usual members and visitors in the selected households. Some basic information was collected on the characteristics of each person listed, including age, sex, education, and relationship to the head of the household. The main purpose of the Household Questionnaire was to identify women and men who were eligible for the individual interview. The Household Questionnaire also collected information on characteristics of the household’s dwelling unit, such as the source of water, type of toilet facilities, materials used for the floor and roof of the house, ownership of various durable goods, and ownership and use of mosquito nets. In addition, this questionnaire was used to record height and weight measurements of women age 15-49 and children under the age of five, households eligible for collection of blood samples, and the respondents’ consent to voluntarily give blood samples.

The Women’s Questionnaire was used to collect information from all women age 15-49 years and covered the following topics. - Household and respondent characteristics - Fertility levels and preferences - Knowledge and use of family planning - Childhood mortality - Maternity care - Childhood illness, treatment, and preventative actions - Anaemia levels among women and children - Breastfeeding practices - Nutritional status of women and young children - Malaria prevention and treatment - Marriage and sexual activity - Awareness and behaviour regarding AIDS and STIs - Harmful traditional practices - Maternal mortality

The Men’s Questionnaire was administered to all men age 15-59 years living in every second household in the sample. The Men’s Questionnaire collected similar information contained in the Women’s Questionnaire, but was shorter because it did not contain questions on reproductive

Population ages 15-64, male (% of male population) in Ethiopia was reported at 57.15 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Ethiopia - Population ages 15-64, male (% of total) - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.

Ethiopia ET: Population: Growth data was reported at 2.464 % in 2017. This records a decrease from the previous number of 2.502 % for 2016. Ethiopia ET: Population: Growth data is updated yearly, averaging 2.702 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 3.601 % in 1992 and a record low of 1.318 % in 1978. Ethiopia ET: Population: Growth data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Ethiopia – Table ET.World Bank.WDI: Population and Urbanization Statistics. Annual population growth rate for year t is the exponential rate of growth of midyear population from year t-1 to t, expressed as a percentage . Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.; ; Derived from total population. Population source: (1) United Nations Population Division. World Population Prospects: 2017 Revision, (2) Census reports and other statistical publications from national statistical offices, (3) Eurostat: Demographic Statistics, (4) United Nations Statistical Division. Population and Vital Statistics Reprot (various years), (5) U.S. Census Bureau: International Database, and (6) Secretariat of the Pacific Community: Statistics and Demography Programme.; Weighted average;

From the AfriPop website..."High resolution, contemporary data on human population distributions are a prerequisite for the accurate measurement of the impacts of population growth, for monitoring changes and for planning interventions. The AfriPop project was initiated in July 2009 with an aim of producing detailed and freely-available population distribution maps for the whole of Africa. Based on the approaches outlined in detail here and here, and summarized on the methods page, fine resolution satellite imagery-derived settlement maps are combined with land cover maps to reallocate contemporary census-based spatial population count data. Assessments have shown that the resultant maps are more accurate than existing population map products, as well as the simple gridding of census data. Moreover, the 100m spatial resolution represents a finer mapping detail than has ever before been produced at national extents. The approaches used in AfriPop dataset production are designed with operational application in mind, using simple and semi-automated methods to produce easily updatable maps. Given the speed with which population growth and urbanisation are occurring across much of Africa, and the impacts these are having on the economies, environments and health of nations, such features are a necessity for both research and operational applications."Data Source: AfriPop.org

Rural population (% of total population) in Ethiopia was reported at 76.34 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Ethiopia - Rural population - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Household

Universe

All housing units and households; all individuals who passed the night of the census date in the dwelling

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: Central Statistical Agency

SAMPLE DESIGN: Systematic sample of every 10th household with a random start, drawn by the country. NOTE: The sample includes data from both the short and the long questionnaire. Only one-fifth of household received the long questionnaire, thus only 20% of the population have responses for most variables.

SAMPLE UNIT: household

SAMPLE FRACTION: 10%

SAMPLE SIZE (person records): 7,434,086

Mode of data collection

Face-to-face [f2f]

Research instrument

Two census questionnaires, a short form and a long form, collected information in five sections: 1) Area identification, 2) Type of residence and housing identification, 3) Details of persons in the household, 4) Deaths in the household during the last 12 month, and 5) Information on housing unit. The long questionnaire was administerd to 1 in 5 households in each enumeration area. The short questionnaire with a subset of the long questionnaire items corresponding to basic demographic and social characteristics (population size, sex, age, religion, mother tongue, ethnic group, disability and orphanage) was administered to the remaining (non-sample) households.

Urban population (% of total population) in Ethiopia was reported at 23.66 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Ethiopia - Urban population (% of total) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Population ages 0-14 (% of total population) in Ethiopia was reported at 39.06 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Ethiopia - Population ages 0-14 (% of total) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Population ages 15-64, total in Ethiopia was reported at 76211823 Persons in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Ethiopia - Population ages 15-64, total - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Abstract

The Ethiopia Socioeconomic Survey (ESS) is a collaborative project between the Central Statistics Agency of Ethiopia (CSA) and the World Bank Living Standards Measurement Study-Integrated Surveys on Agriculture (LSMS-ISA) team. The objective of the LSMS-ISA is to collect multi-topic, household-level panel data with a special focus on improving agriculture statistics and generating a clearer understanding of the link between agriculture and other sectors of the economy. The project also aims to build capacity, share knowledge across countries, and improve survey methodologies and technology.

ESS is a long-term project to collect panel data. The project responds to the data needs of the country, given the dependence of a high percentage of households in agriculture activities in the country. The ESS collects information on household agricultural activities along with other information on the households like human capital, other economic activities, access to services and resources. The ability to follow the same households over time makes the ESS a new and powerful tool for studying and understanding the role of agriculture in household welfare over time as it allows analyses of how households add to their human and physical capital, how education affects earnings, and the role of government policies and programs on poverty, inter alia. The ESS is the first panel survey to be carried out by the CSA that links a multi-topic household questionnaire with detailed data on agriculture.

Geographic coverage

National Regional Urban and Rural

Analysis unit

• Household
• Individual
• Community

Universe

The survey covered all de jure households excluding prisons, hospitals, military barracks, and school dormitories.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame for the new ESS4 is based on the updated 2018 pre-census cartographic database of enumeration areas by CSA. The ESS4 sample is a two-stage stratified probability sample. The ESS4 EAs in rural areas are the subsample of the AgSS EA sample. That means, the first stage of sampling in the rural areas entailed selecting enumeration areas (i.e. the primary sampling units) using simple random sampling (SRS) from the sample of the 2018 AgSS enumeration areas (EAs). The first stage of sampling for urban areas is selecting EAs directly from the urban frame of EAs within each region using systematically with PPS. This is designed in way that automatically results in a proportional allocation of the urban sample by zone within each region. Following the selection of sample EAs, they are allocated by urban rural strata using power allocation which is happened to be closer to proportional allocation.

The second stage of sampling for the ESS4 is the selection of households to be surveyed in each sampled EA using systematic random sampling. From the rural EAs, 10 agricultural households are selected as a subsample of the households selected for the AgSS and 2 non-agricultural households are selected from the non-agriculture households list in that specific EA. The non-agriculture household selection follows the same sampling method i.e. systematic random sampling. One important issue to note in ESS4 sampling is that the total number of agriculture households per EA remains 10 even though there are less than 2 or no non-agriculture households are listed and sampled in that EA.

For urban areas, a total of 15 households are selected per EA regardless of the households’ economic activity. The households are selected using systematic random sampling from the total households listed in that specific EA. Table 3.2 presents the distribution of sample households for ESS4 by region, urban and rural stratum. A total of 7527 households are sampled for ESS4 based on the above sampling strategy.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The survey consisted of five questionnaires, similar with the questionnaires used during the previous rounds with revisions based on the results of the previous rounds as well as on identified areas of need for new data.

The household questionnaire was administered to all households in the sample; multiple modules in the household questionnaire were administered per eligible household members in the sample.

The community questionnaire was administered to a group of community members to collect information on the socio-economic indicators of the enumeration areas where the sample households reside.

The three agriculture questionnaires consisting of a post-planting agriculture questionnaire, post-harvest agriculture questionnaire and livestock questionnaire were administered to all household members (agriculture holders) who are engaged in agriculture activities. A holder is a person who exercises management control over the operations of the agricultural holdings and makes the major decisions regarding the utilization of the available resources. S/he has technical and economic responsibility for the holding. S/he may operate the holding directly as an owner or as a manager. Hence it is possible to have more than one holder in single sampled households. As a result we have administered more than one agriculture questionnaire in a single sampled household if the household has more than one holder.

Household questionnaire: The household questionnaire provides information on education; health (including anthropometric measurement for children); labor and time use; financial inclusion; assets ownership and user right; food and non-food expenditure; household nonfarm activities and entrepreneurship; food security and shocks; safety nets; housing conditions; physical and financial assets; credit; tax and transfer; and other sources of household income. Household location is geo-referenced in order to be able to later link the ESS data to other available geographic data sets (See Appendix 1 for discussion of the geo-data provided with the ESS).

Community questionnaire: The community questionnaire solicits information on infrastructure; community organizations; resource management; changes in the community; key events; community needs, actions and achievements; and local retail price information.

Agriculture questionnaire: The post-planting and post-harvest agriculture questionnaires focus on crop farming activities and solicit information on land ownership and use; land use and agriculture income tax; farm labor; inputs use; GPS land area measurement and coordinates of household fields; agriculture capital; irrigation; and crop harvest and utilization. The livestock questionnaire collects information on animal holdings and costs; and production, cost and sales of livestock by products.

Cleaning operations

Final data cleaning was carried out on all data files. Only errors that could be clearly and confidently fixed by the team were corrected; errors that had no clear fix were left in the datasets. Cleaning methods for these errors are left up to the data user.

Response rate

ESS4 planned to interview 7,527 households from 565 enumeration areas (EAs) (Rural 316 EAs and Urban 249 EAs). A total of 6770 households from 535 EAs were interviewed for both the agriculture and household modules. The household module was not implemented in 30 EAs due to security reasons (See the Basic Information Document for additional information on survey implementation).

Abstract

The fourth edition of the Global Findex offers a lens into how people accessed and used financial services during the COVID-19 pandemic, when mobility restrictions and health policies drove increased demand for digital services of all kinds.

The Global Findex is the world’s most comprehensive database on financial inclusion. It is also the only global demand-side data source allowing for global and regional cross-country analysis to provide a rigorous and multidimensional picture of how adults save, borrow, make payments, and manage financial risks. Global Findex 2021 data were collected from national representative surveys of almost 145,000 people in 139 economies, representing 97 percent of the world’s population. The latest edition follows the 2011, 2014, and 2017 editions, and it includes a number of new series measuring financial health and resilience and contains more granular data on digital payment adoption, including merchant and government payments.

The Global Findex is an indispensable resource for financial service practitioners, policy makers, researchers, and development professionals.

Geographic coverage

Due to ongoing conflict and security issues, Tigray, Gambella, Harari regions were excluded. The excluded areas represent approximately 7% of the total population of Ethiopia.

Kind of data

Observation data/ratings [obs]

Sampling procedure

In most developing economies, Global Findex data have traditionally been collected through face-to-face interviews. Surveys are conducted face-to-face in economies where telephone coverage represents less than 80 percent of the population or where in-person surveying is the customary methodology. However, because of ongoing COVID-19–related mobility restrictions, face-to-face interviewing was not possible in some of these economies in 2021. Phone-based surveys were therefore conducted in 67 economies that had been surveyed face-to-face in 2017. These 67 economies were selected for inclusion based on population size, phone penetration rate, COVID-19 infection rates, and the feasibility of executing phone-based methods where Gallup would otherwise conduct face-to-face data collection, while complying with all government-issued guidance throughout the interviewing process. Gallup takes both mobile phone and landline ownership into consideration. According to Gallup World Poll 2019 data, when face-to-face surveys were last carried out in these economies, at least 80 percent of adults in almost all of them reported mobile phone ownership. All samples are probability-based and nationally representative of the resident adult population. Additionally, phone surveys were not a viable option in 16 economies in 2021, which were then surveyed in 2022.

In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households. Each eligible household member is listed, and the hand-held survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer's gender.

In traditionally phone-based economies, respondent selection follows the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies where mobile phone and landline penetration is high, a dual sampling frame is used.

The same respondent selection procedure is applied to the new phone-based economies. Dual frame (landline and mobile phone) random digital dialing is used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digital dialing is used in economies with limited to no landline presence (less than 20 percent).

For landline respondents in economies where mobile phone or landline penetration is 80 percent or higher, random selection of respondents is achieved by using either the latest birthday or household enumeration method. For mobile phone respondents in these economies or in economies where mobile phone or landline penetration is less than 80 percent, no further selection is performed. At least three attempts are made to reach a person in each household, spread over different days and times of day.

Sample size for Ethiopia is 1000.

Mode of data collection

Face-to-face [f2f]

Research instrument

Questionnaires are available on the website.

Sampling error estimates

Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar. 2022. The Global Findex Database 2021: Financial Inclusion, Digital Payments, and Resilience in the Age of COVID-19. Washington, DC: World Bank.

Population ages 0-14, female (% of female population) in Ethiopia was reported at 38.39 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Ethiopia - Population ages 0-14, female (% of total) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Population, total in Ethiopia was reported at 132059767 in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Ethiopia - Population, total - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

The raster dataset consists of a 1km score grid for dairy processing industry facilities siting, produced under the scope of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis for value chain infrastructure location.

The analysis is based on cattle dairy production intensification potential, defined using crop production, livestock production systems and cattle distribution.

The score is achieved by processing sub-model outputs that characterize logistical factors: 1. Supply - Feed, livestock production systems, dairy distribution. 2. Demand - Human population density, large cities, urban areas. 3. Infrastructure - Transportation network (accessibility)

It consists of an arithmetic weighted sum of normalized grids (0 to 100): (”dairyIntensification” * 0.4) + ("Crop Production" * 0.3) + ("Cost to dry ports" * 0.2) + (“Major Cities Accessibility” * 0.1)

Data publication: 2021-10-18

Contact points:

Metadata Contact: FAO-Data

Resource Contact: Maribel Elias

Data lineage:

Major data sources, FAO GIS platform Hand-in-Hand and OpenStreetMap (open data) including the following datasets: 1. Human Population Density 2020 – WorldPop2020 - Estimated total number of people per grid-cell 1km. 2. Mapspam Production – IFPRI's Spatial Production Allocation Model (SPAM) estimates of crop distribution within disaggregated units. 3. GLW Gridded Livestock of the World - Gridded Livestock of the World (GLW 3 and GLW 2) 4. Global Livestock Production Systems v.5 2011. 5. OpenStreetMap.

Resource constraints:

Creative Commons Attribution-NonCommercial-ShareAlike 3.0 IGO (CC BY-NC- SA 3.0 IGO)

Online resources:

Dairy Processing Location Score: Cattle (Ethiopia - ~ 1Km)

Abstract

Statistical information on all aspects of the population is vital for the design, implementation, monitoring and evaluation of economic and social development plan and policy issues. Labor force survey is one of the most important sources of data for assessing the role of the population of the country in the economic and social development process. It is useful to indicate the extent of available and unutilized human resources that must be absorbed by the national economy to ensure full employment and economic wellbeing of the population. Statistics on the labor force further present the economic activity status and its relationship to other social and economic characteristics of the population. Seasonal and other variations as well as changes over time in the size, distribution, and characteristics of employed and unemployed population can be monitored using up-to-date information from labor force surveys. It serves as an input for assessing the achievements of the Millennium Development Goals (MDGs). Furthermore, labor force data is also useful as a springboard for monitoring and evaluation of the five years growth and transformation plan of the country.

Geographic coverage

The 2012 Urban Employment and Unemployment Survey (UEUS) covered all urban parts of the country except three zones of Afar, Six zones of Somali, where the residents are pastoralists.

Analysis unit

• Households
• Individuals

Universe

This survey follows household approach and covers households residing in conventional households and thus, population residing in the collective quarters such as universities/colleges, hotel/hostel, monasteries, and homeless population etc., were not covered by this survey.

Kind of data

Sample survey data [ssd]

Sampling procedure

The list of households obtained from the 2007 population and housing census was used to select EAs. A fresh list of households from each EA was prepared at the beginning of the survey period. The list was then used as a frame to select 30 households from sample EAs.

The country was divided into two broad categories - major urban centers and other urban center categories.

Category I: In this category all regional capitals and five other major urban centers that have a high population size as compared to others were included. Each urban center in this category was considered as a reporting level. This category has a total of 16 reporting levels. To select the sample, a stratified two-stage cluster sample design was implemented. The primary sampling units were EAs of each reporting level.

Category II: Urban centers other than those under category I were grouped into this category. A stratified three stage cluster sample design was adopted to select samples from this category. The primary sampling units were urban centers and the second stage sampling units were EAs.

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey questionnaire was organized into seven sections. Section 1 - Area identification of the selected household Section 2 - Particulars of household members Section 3 - Economic activity status during the last seven days Section 4 - Unemployment rate and characteristics of unemployed persons Section 5 - Economic activity status the population during the last six months Section 6 - Employment in the informal sector of Employment Section 7 - Economic activity of children aged 5-17 years

A structured questionnaire was used to solicit the required data in the survey. The draft questionnaire was tested by undertaking a pretest in selected kebeles (lower administrative unit) in Addis Ababa. Based on the pretest, the content, logical flow, layout and presentation of the questionnaire was amended. The questionnaire used in the field for data collection was prepared in Amharic language. Most questions have pre coded answers and column numbers were assigned for each question.

Cleaning operations

The filled-in questionnaires that were retrieved from the field were first subjected to manual editing and coding. During the fieldwork the field supervisors and the heads of branch statistical offices have checked the filled-in questionnaires and carried out some editing. However, the major editing and coding operation was carried out at the head office. All the edited questionnaires were again fully verified and checked for consistency before they were submitted to the data entry by the subject matter experts.

Using the computer edit specifications prepared earlier for this purpose, the entered data were checked for consistencies and then computer editing, or data cleaning was made by referring back to the filled-in questionnaire. This is an important part of data processing operation in attaining the required level of data quality. Consistency checks and re-checks were also made based on frequency and tabulation results. This was done by senior programmers using CSPro software in collaboration with the senior subject experts from Manpower Statistics Team of the CSA.

Response rate

Response rate was 99.68%.

Population ages 65 and above, female (% of female population) in Ethiopia was reported at 3.5921 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Ethiopia - Population ages 65 and above, female (% of total) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Ethiopia electricity access for 2023 was 55.40%, a 0% increase from 2022.

<ul style='margin-top:20px;'>

<li>Ethiopia electricity access for 2022 was <strong>55.40%</strong>, a <strong>1.2% increase</strong> from 2021.</li>
<li>Ethiopia electricity access for 2021 was <strong>54.20%</strong>, a <strong>3.1% increase</strong> from 2020.</li>
<li>Ethiopia electricity access for 2020 was <strong>51.10%</strong>, a <strong>3.1% increase</strong> from 2019.</li>
</ul>Access to electricity is the percentage of population with access to electricity. Electrification data are collected from industry, national surveys and international sources.

Abstract

Statistical information on all aspects of the population is vital for the design, implementation and evaluation of economic and social development plan and policy issues. Labour force surveys are one of the important sources of data for assessing the role of the population of a country in the economic and social development process. These surveys provide data on the main characteristics of the work force engaged or available to be engaged in productive activities during a given period and also its distribution in the various sectors of the economy. They are also useful to indicate the extent of available and unutilized human resource that must be absorbed by the national economy to ensure full employment and economic well being of the population. Furthermore, the information obtained from such surveys is useful for the purpose of macro-economic monitoring and human resource development planning. The other broad objective of statistics on the labour force is for the measurement of the relationship between employment, income and other social and economic characteristics of the economically active population for the purpose of formulating and monitoring employment policies and programs, income-generating and maintenance schemes, vocational training and other similar programs. Seasonal and other variations in the size and characteristics of the labour force can also be monitored using up-to-date information from labour force surveys.

In order to further fill the gap in data requirement for the socio-economic development planning, monitoring and evaluation, the Central Statistical Authority (CSA) has conducted Rural Labour Force Survey (RLFS) as a part of the National Integrated Household Survey Program (NIHSP) at the end of 1980. To maintain the continuity and to update the Rural Labour Force Survey of 1981/82 results, another Rural Labour Force Survey was conducted in 1987/88. Also the CSA has conducted the 1976 Addis Ababa Manpower and Housing Sample Survey and the 1978 Manpower and Housing survey in Seventeen Major Towns. Moreover, some data on the labour force were also collected as a part of other surveys such as the 1990 Family and Fertility Survey, 1996 Urban Informal Sector Sample Survey and in the country wide deccennial Population and Housing Censuses of Ethiopia conducted in 1984 and 1994.

The labour force surveys that were conducted earlier were limited in areal coverage and content of the questionnaires. In this respect, both the 1981/82 and 1987/88 surveys covered only the rural part of the country. Till the current survey was conducted, there hasn't been a comprehensive national labour force survey representing both the urban and the rural areas of the country. Moreover, the information that should have been provided through labour force surveys could be said relatively out-dated, as the sector is dynamic and sensitive to economic and social changes. To fill this data gap, a series of current and comprehensive labour force surveys need to be undertaken.

Recognizing this fact, the Central Statistical Authority (CSA) has conducted a national labour force survey in March 1999. The survey is the first of its kind in that it covers the rural and the urban areas and it contains detailed information on the subject. The results of this survey have been already released to users in a publication entitled "Statistical Report on the 1999 National Labour Force Survey (NLFS)" and this presented the data in a former of detailed statistical tables including the concepts and definitions on the major technical terms used in the survey. The CSA hopes that users have benefited a lot from this publication. To increase the utility of the result of the survey, the CSA taught that it necessary to make further analysis on the data. The analytical presentation of this report will be based on the tables that have been presented in the statistical report (Report on Statistical Tables of the 1999 Labour Force Survey, CSA, 1999) and some additional tables produced and included in this report. This chapter presents an overview to the survey background. The 1999 National Labour Force survey was designed to provide statistical data on the size and characteristics of the employed, unemployed, underemployed and the non-active population of the country. In general, the data obtained from the survey is useful for policy makers, planners, researchers and other institutions and individuals engaged in the design and implementation of human resource development projects and programs.

The specific objectives of the 1999 National Labour Force Survey are to :- - collect statistical data on the potential manpower who are available to take part in various socio-economic activities - determine the size and distribution of the labour force; and the status and rates of economic activity and also to study the socio-economic and demographic characteristics of these groups - identify those who contributed to economic development and those who are partially employed, without work and economically inactive - to estimate and assess the levels and characteristics of the unemployed population - generate data on the status and type of professional and vocational training - assess the size and characteristics of children aged between 5 - 14 years that were engaged in economic activities - assess the situation of women's employment or the participation of women in the labour force

Geographic coverage

The survey covered both urban and rural parts of the country, except six zones in Somali Region and two zones in Affar Region

Analysis unit

• Household
• Household member
• Household members aged 10 years and over

Universe

The survey covered all households in selected sample areas except residents of collective quarters, homeless persons and foreigners.

Kind of data

Sample survey data [ssd]

Sampling procedure

The 1999 National Labor Force Survey covered both urban and rural parts of the country, except six zones in Somali Region and two zones in Affar Region. In addition the residents of collective quarters, homeless persons and foreigners were not covered in the survey. For the purpose of the survey, the survey population in the country was divided into urban and rural categories.

Category I: Urban parts of 26 zones, that is 4 zones in Tigray, 10 zones in Amhara, and 12 zones in Oromiya regions; and 9 zones and 5 special weredas in SNNP Region; and urban parts of Affar, Somali, Benishangul-Gumuz, Gambela and Harari regions and Addis Ababa and Dire Dawa Administration were grouped in this category. Each of the above mentioned urban parts of the zones, except the 5 special weredas in SNNP Region were the survey domains (reporting levels). All in all 47 basic urban domains (Reporting levels) including total urban (regional and country level) were defined for the survey.

Category II: Rural parts of 26 Zones that is 4 zones in Tigray, 10 zones in Amhara, 12 zones in Oromiya regions and 9 zones and 5 special weredas in SNNP regions; and rural parts of Affar, Somali, Benishangul-Gumuz, Gambela and Harari regions, Addis Ababa and Dire Dawa Administration were grouped in this category. Each of the above mentioned rural parts of zones and special weredas, except Addis Ababa rural, were the survey domains (reporting levels). All in all 51 basic rural domains (reporting levels) including total rural (regional and country level) were defined for the survey. In addition to the above urban and rural domains, survey results can be reported at regional and country levels by aggregating the survey results for the corresponding urban and rural areas. Definition of the survey domains was based on both technical and resource considerations. More specifically, sample sizes for the domains were determined to enable provision of major indicators with reasonable precision subject to the resources that were available for the survey.

Selection Scheme and Sample Size: In both categories stratified two-stage sample design was used to select the sample in which the Primary Sampling Units (PSUs) were enumeration areas (EAs). Sample EAs from each domain were selected using systematic probability proportional to size; size being number of households obtained from the 1994 Population and Housing Census. From category I, a total of 913 EAs and from category II, a total of 1428 EAs were selected. Within each sample EA, fresh list of households was prepared at the beginning of the survey's fieldwork for urban sites and at the beginning of the 1991 E.C. Agricultural Sample Survey's fieldwork for rural sites. The survey questionnaire was administered to 35 systematically selected households within each of the sampled EAs.

Note: Distributions of sample units by domain (reporting levels) and category are presented in Table 2.1 and Table 2.2 of the 1999 National Labour Force Survey report which is provided in this documentation.

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey has used a structured questionnaire to solicit the required data. Before taking its final shape, the draft questionnaire was tested by undertaking a Pilot Study. Based on the result of the pilot study the content, layout and presentation of the questionnaire was amended. The content of the questionnaire has been further revised on the basis of the discussion made on the user - producer forum organized by the CSA. The questionnaire used in the field was prepared in Amharic language and most questions have pre-coded answers and column numbers were assigned for each question.

The questionnaire is organized into six sections: Section-1 Area identification of the selected household: this section has

Population ages 0-14, total in Ethiopia was reported at 51582434 Persons in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Ethiopia - Population, ages 0-14, total - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.