This statistic shows the biggest cities in Ethiopia in 2022. In 2022, approximately 3.86 million people lived in Adis Abeba, making it the biggest city in Ethiopia.

Population in largest city in Ethiopia was reported at 5703628 in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Ethiopia - Population in largest city - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.

Ethiopia ET: Population in Largest City data was reported at 4,215,965.000 Person in 2017. This records an increase from the previous number of 4,039,927.000 Person for 2016. Ethiopia ET: Population in Largest City data is updated yearly, averaging 1,690,413.500 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 4,215,965.000 Person in 2017 and a record low of 519,177.000 Person in 1960. Ethiopia ET: Population in Largest City 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. Population in largest city is the urban population living in the country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; ;

Geographic Coordinate System: GCS_WGS_1984 Datum: D_WGS_1984 Source: Ethiopian Road Authority (ERA)

Population in the largest city (% of urban population) in Ethiopia was reported at 18.25 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Ethiopia - Population in the largest city - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Ethiopia ET: Population in Largest City: as % of Urban Population data was reported at 15.931 % in 2017. This records a decrease from the previous number of 16.255 % for 2016. Ethiopia ET: Population in Largest City: as % of Urban Population data is updated yearly, averaging 29.736 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 36.434 % in 1960 and a record low of 15.931 % in 2017. Ethiopia ET: Population in Largest City: as % of Urban Population 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: Population and Urbanization Statistics. Population in largest city is the percentage of a country's urban population living in that country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; Weighted Average;

Accessibility to major cities dataset is modelled as raster-based travel time/cost analysis, computed for the largest cities (>50k habitants) in the country. This 1km resolution raster dataset is part of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis (GIS-MCDA) aimed at the identification of value chain infrastructure sites (or optimal location).

Lagos, in Nigeria, ranked as the most populated city in Africa as of 2024, with an estimated population of roughly nine million inhabitants living in the city proper. Kinshasa, in Congo, and Cairo, in Egypt, followed with some 7.8 million and 7.7 million dwellers. Among the 15 largest cities in the continent, another two, Kano, and Ibadan, were located in Nigeria, the most populated country in Africa. Population density trends in Africa As of 2022, Africa exhibited a population density of 48.3 individuals per square kilometer. At the beginning of 2000, the population density across the continent has experienced a consistent annual increment. Projections indicated that the average population residing within each square kilometer would rise to approximately 54 by the year 2027. Moreover, Mauritius stood out as the African nation with the most elevated population density, exceeding 640 individuals per square kilometre. Mauritius possesses one of the most compact territories on the continent, a factor that significantly influences its high population density. Urbanization dynamics in Africa The urbanization rate in Africa was anticipated to reach close to 44 percent in 2021. Urbanization across the continent has consistently risen since 2000, with urban areas accommodating 35 percent of the total population. This trajectory is projected to continue its ascent in the years ahead. Nevertheless, the distribution between rural and urban populations shows remarkable diversity throughout the continent. In 2021, Gabon and Libya stood out as Africa’s most urbanized nations, each surpassing 80 percent urbanization. In 2023, Africa's population was estimated to expand by 2.35 percent compared to the preceding year. Since 2000, the population growth rate across the continent has consistently exceeded 2.45 percent, reaching its pinnacle at 2.59 percent between 2012 and 2013. Although the growth rate has experienced a deceleration, Africa's population will persistently grow significantly in the forthcoming years.

Points represent major cities in Ethiopia

Nigeria has the largest population in Africa. As of 2025, the country counted over 237.5 million individuals, whereas Ethiopia, which ranked second, has around 135.5 million inhabitants. Egypt registered the largest population in North Africa, reaching nearly 118.4 million people. In terms of inhabitants per square kilometer, Nigeria only ranked seventh, while Mauritius had the highest population density on the whole African continent in 2023. The fastest-growing world region Africa is the second most populous continent in the world, after Asia. Nevertheless, Africa records the highest growth rate worldwide, with figures rising by over two percent every year. In some countries, such as Niger, the Democratic Republic of Congo, and Chad, the population increase peaks at over three percent. With so many births, Africa is also the youngest continent in the world. However, this coincides with a low life expectancy. African cities on the rise The last decades have seen high urbanization rates in Asia, mainly in China and India. However, African cities are currently growing at larger rates. Indeed, most of the fastest-growing cities in the world are located in Sub-Saharan Africa. Gwagwalada, in Nigeria, and Kabinda, in the Democratic Republic of the Congo, ranked first worldwide. By 2035, instead, Africa's fastest-growing cities are forecast to be Bujumbura, in Burundi, and Zinder, Nigeria.

The metropolitan area of Lagos in Nigeria counted over 14 million middle-class people as of 2018. This was the highest number in Africa. Addis Ababa in Ethiopia followed with 2.7 million individuals belonging to the middle class. The middle-class population included people who had a disposable income of over 75 percent of their salary, were employed, had a business activity, or were in education, and had at least a secondary school degree.

Accessibility to regional cities dataset is modeled as raster-based travel time/cost analysis, computed for the largest cities surrounding the country. The following cities are included: City - Population Addis Ababa, Ethiopia - 5 153 002 Asmara, Eritrea - 1 258 001 Sohag, Egypt - 979 800 Wau, South Sudan - 328 651 Abeche, Chad - 83 155 This 500m resolution raster dataset is part of FAO’s Hand-in-Hand Initiative, Geographical Information Systems - Multicriteria Decision Analysis (GIS-MCDA) aimed at the identification of value chain infrastructure sites (or optimal location).

As of 2018, more than 60 million people were living in urban areas in East Africa. Ethiopia was the country with the largest urban residents in the region, in terms of absolute numbers, roughly 23 million. In its turn, in Djibouti, 760 thousand people lived in urban areas by the same period. Even though, the country was the most urbanized in East Africa, with a share of 78 percent of urban population, in 2018.

Abstract

The 2019 Ethiopia Mini Demographic and Health Survey (EMDHS) is a nationwide survey with a nationally representative sample of 9,150 selected households. All women age 15-49 who were usual members of the selected households and those who spent the night before the survey in the selected households were eligible to be interviewed in the survey. In the selected households, all children under age 5 were eligible for height and weight measurements. The survey was designed to produce reliable estimates of key indicators at the national level as well as for urban and rural areas and each of the 11 regions in Ethiopia.

The primary objective of the 2019 EMDHS is to provide up-to-date estimates of key demographic and health indicators. Specifically, the main objectives of the survey are: ▪ To collect high-quality data on contraceptive use; maternal and child health; infant, child, and neonatal mortality levels; child nutrition; and other health issues relevant to achievement of the Sustainable Development Goals (SDGs) ▪ To collect information on health-related matters such as breastfeeding, maternal and child care (antenatal, delivery, and postnatal), children’s immunizations, and childhood diseases ▪ To assess the nutritional status of children under age 5 by measuring weight and height

Geographic coverage

National coverage

Analysis unit

• Household
• Individual
• Children age 0-5
• Woman age 15-49
• Health facility

Universe

The survey covered all de jure household members (usual residents), all women aged 15-49 and all children aged 0-5 resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame used for the 2019 EMDHS is a frame of all census enumeration areas (EAs) created for the 2019 Ethiopia Population and Housing Census (EPHC) and conducted by the Central Statistical Agency (CSA). The census frame is a complete list of the 149,093 EAs created for the 2019 EPHC. An EA is a geographic area covering an average of 131 households. The sampling frame contains information about EA location, type of residence (urban or rural), and estimated number of residential households.

Administratively, Ethiopia is divided into nine geographical regions and two administrative cities. The sample for the 2019 EMDHS was designed to provide estimates of key indicators for the country as a whole, for urban and rural areas separately, and for each of the nine regions and the two administrative cities.

The 2019 EMDHS sample was stratified and selected in two stages. Each region was stratified into urban and rural areas, yielding 21 sampling strata. Samples of EAs were selected independently in each stratum in two stages. Implicit stratification and proportional allocation were achieved at each of the lower administrative levels by sorting the sampling frame within each sampling stratum before sample selection, according to administrative units in different levels, and by using a probability proportional to size selection at the first stage of sampling.

To ensure that survey precision was comparable across regions, sample allocation was done through an equal allocation wherein 25 EAs were selected from eight regions. However, 35 EAs were selected from each of the three larger regions: Amhara, Oromia, and the Southern Nations, Nationalities, and Peoples’ Region (SNNPR).

In the first stage, a total of 305 EAs (93 in urban areas and 212 in rural areas) were selected with probability proportional to EA size (based on the 2019 EPHC frame) and with independent selection in each sampling stratum. A household listing operation was carried out in all selected EAs from January through April 2019. The resulting lists of households served as a sampling frame for the selection of households in the second stage. Some of the selected EAs for the 2019 EMDHS were large, with more than 300 households. To minimise the task of household listing, each large EA selected for the 2019 EMDHS was segmented. Only one segment was selected for the survey, with probability proportional to segment size. Household listing was conducted only in the selected segment; that is, a 2019 EMDHS cluster is either an EA or a segment of an EA.

In the second stage of selection, a fixed number of 30 households per cluster were selected with an equal probability systematic selection from the newly created household listing. All women age 15-49 who were either permanent residents of the selected households or visitors who slept in the household the night before the survey were eligible to be interviewed. In all selected households, height and weight measurements were collected from children age 0-59 months, and women age 15-49 were interviewed using the Woman’s Questionnaire.

For further details on sample selection, see Appendix A of the final report.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Five questionnaires were used for the 2019 EMDHS: (1) the Household Questionnaire, (2) the Woman’s Questionnaire, (3) the Anthropometry Questionnaire, (4) the Health Facility Questionnaire, and (5) the Fieldworker’s Questionnaire. These questionnaires, based on The DHS Program’s standard questionnaires, were adapted to reflect the population and health issues relevant to Ethiopia. They were shortened substantially to collect data on indicators of particular relevance to Ethiopia and donors to child health programmes.

Cleaning operations

All electronic data files were transferred via the secure internet file streaming system (IFSS) to the EPHI central office in Addis Ababa, where they were stored on a password-protected computer. The data processing operation included secondary editing, which required resolution of computer-identified inconsistencies and coding of open-ended questions. The data were processed by EPHI staff members and an ICF consultant who took part in the main fieldwork training. They were supervised remotely by staff from The DHS Program. Data editing was accomplished using CSPro System software. During the fieldwork, field-check tables were generated to check various data quality parameters, and specific feedback was given to the teams to improve performance. Secondary editing, double data entry from both the anthropometry and health facility questionnaires, and data processing were initiated in April 2019 and completed in July 2019.

Response rate

A total of 9,150 households were selected for the sample, of which 8,794 were occupied. Of the occupied households, 8,663 were successfully interviewed, yielding a response rate of 99%.

In the interviewed households, 9,012 eligible women were identified for individual interviews; interviews were completed with 8,885 women, yielding a response rate of 99%. Overall, there was little variation in response rates according to residence; however, rates were slightly higher in rural than in urban areas.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: nonsampling errors and sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2019 Ethiopia Mini Demographic and Health Survey (EMDHS) to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2019 EMDHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability among all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

Sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95% of all possible samples of identical size and design.

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2019 EMDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed in SAS, using programs developed by ICF. These programs use the Taylor linearization method to estimate variances for survey estimates that are means, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

Note: A more detailed description of estimates of sampling errors are presented in APPENDIX B of the survey report.

Data appraisal

Data Quality Tables

• Household age distribution

- Age distribution of eligible and interviewed women

Abstract

The Central Statistical Agency (CSA) has been providing labour force and related data at different levels and with varying details in their content. These include the 1976 Addis Ababa Manpower and Housing Sample Survey, the 1978 Survey on Population and Housing Characteristics of Seventeen Major Towns, the 1980/81 and 1987/88 Rural Labour Force Surveys, the 1984 and 1994 Population and Housing Census, and 2003 and 2004 Urban Bi-annual Employment Unemployment Survey. The 1996 and 2002 Surveys of Informal Sector and most of the household surveys undertaken by the Agency also provide limited information on the area. Still pieces of information in relation to that of employment can also be derived from small, large and medium scale establishment surveys. Till the 1999 Labour Force Survey (LFS) there hasn't been a comprehensive national labour force survey representing both urban and rural areas. This 2005 LFS is the second in the series.

The 2005 National Labor Force Survey was designed to provide statistical data on the size and characteristics of the economically active and the non-active population of the country, both in urban and rural areas. The data will be useful for policy makers, planners, researchers, and other institutionsand individuals engaged in the design, implementation and monitoring of human resource development plans, programs and projects. The specific objectives of this survey are to: - generate data on the size of work force that is available to participate in production process; - determine the status and rate of economic participation of different sub-groups of the population; - identify those who are actually contributing to the economic development (i.e., employed) and those out of the sphere; - determine the size and rate of unemployed population; - provide data on the structure of the working population; - obtain information about earnings from paid employment; - identify the distribution of employed population working in the formal/informal enterprises; and - provide time series data and trace changes over time.

Geographic coverage

Like the National Labour Force Survey of 1999, it covered both the urban and rural areas of all regions. Exceptions are Gambella Region, where only the urban parts of the region are covered, Affar Region with only zone one and zone three were covered and Somali Region where only Shinile, Jijiga and Liben zones were covered.

Analysis unit

• HouseHold (HH)
• Household Member

Universe

The survey is mainly aimed at providing information on the economic characteristics of the population aged 10 years and over,

Kind of data

Données échantillonées [ssd]

Sampling procedure

2.1 COVERAGE The 2005 (1997 E.C) Labour Force Sample Survey covered all rural and urban parts of the country except all zones of Gambella Region excluding Gambella town, and the non-sedentary population of three zones of Afar & six zones of Somali regions. In the rural parts of the country it was planned to cover 830 Enumeration Areas (EAs) and 24,900 households. All planned EAs were actually covered by the survey; however, due to various reasons it was not possible to conduct the survey in 39 sample households. Ultimately 100.00 % EAs and 99.84% household were covered by the survey. Regarding urban parts of the country it was initially planned to cover 995 EAs and 29,850 households. Eventually 100% of the EAs and 99.24% of the households were successfully covered by the survey.

2.2 SAMPLING FRAME The list of households obtained from the 2001/2 Ethiopian Agricultural Sample Enumeration (EASE) is used to select EAs from the rural part of the country. For urban sample EAs on the other hand the list consisting of households by EA, which was obtained from the 2004 Ethiopian Urban Economic Establishment Census, (EUEEC) was used as a frame. A fresh list of households from each urban and rural EA was prepared at the beginning of the survey period. The list was then used as a frame for selecting sample households of each EAs.

2.3 SAMPLE DESIGN For the purpose of the survey the country was divided into three broad categories. That is; rural, major urban center and other urban center categories.

Category I: Rural: - This category consists of the rural areas of 8 regions and two city administrations found in the country. Regarding the survey domains, each region or city administration was considered to be a domain (Reporting Level) for which major findings of the survey are reported. This category totally comprises 10 reporting levels. A stratified two-stage cluster sample design was used to select samples in which the primary sampling units (PSUs) were EAs. Households per sample EA were selected as a second Stage Sampling Unit (SSU) and the survey questionnaire finally administered to all members of sample households

Category II:- Major urban centers:- In this category all regional capitals and 15 other major urban centers that had a population size of 40,000 or more in 2004 were included. Each urban center in this category was considered as a reporting level. The category has totally 26 reporting levels. In this category too, in order to select the samples, a stratified two-stage cluster sample design was implemented. The primary sampling units were EAs. Households from each sample EA were then selected as a Second Stage Unit.

Category III: - Other urban centers: Urban centers in the country other than those under category II were grouped into this category. Excluding Gambella a domain of other urban centers is formed for each region. Consequently 7 reporting levels were formed in this category. Harari, Addis Ababa and Dire Dawa do not have urban centers other than that grouped in category II. Hence, no domain was formed for these regions under this category. Unlike the above two categories 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. Households from each EA were finely selected at the third stage and the survey questionnaires administered for all of them.

To have more informations on th sampling view the report (Page 8)

Mode of data collection

Interview face à face [f2f]

Research instrument

The questionnaire was organized in to five sections; Section - 1 Area identification of the selected household: this section dealt with area identification of respondents such as region, zone, wereda, etc.,

Section -2 Socio- demographic characteristics of households: it consisted of the general sociodemographic characteristics of the population such as age, sex, education, status and type of disability, status and types of training, marital status and fertility questions.

Section - 3 Productive activities during the last seven days: this section dealt with a range of questions which helps to see the status and characteristics of employed persons in a current status approach such as hours of work in productive activities, occupation, industry, employment status, and earnings from employment. Also questions included are hours spent on fetching water, collection of firewood, and domestic chores and place of work.

Section - 4 Unemployment and characteristics of unemployed persons: this section focused on the size and characteristics of the unemployed population.

Section - 5 Economic activities during the last twelve months: this section covered the usual economic activity status (refereeing to the long reference period), number of weeks of employment /unemployment/inactive, reasons for inactivity, employment status, whether working in the agricultural sector or not and the proportion of income gainedfrom non-agricultural sector.

The questionnaire used in the field for data collection was prepared in Amharic language. Most questions have pre-coded answers.

Cleaning operations

During the fieldwork, the field supervisors, statisticians 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 urban questionnaires were subjected to complete manual editing, while most of rural questionnaires were partially edited. All the edited questionnaires were again fully verified and checked for consistency before they were submitted to the data entry. This system of data processing was followed on the assumption that, there is less complication of activities in rural areas than urban centers.

After the data was entered, it was again verified using the computer edit specification 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 tabulation results. Computer programs used in data entry, machine editing and tabulation were prepared using the Integrated Microcomputer Processing System (IMPS).

Abstract

The Urban Employment and Unemployment Survey program was designed to provide statistical data on the size and characteristics of the economically active and the inactive population of the country on continuous basis. The variables collected in the survey: socio-demographic characteristics of household members; economic activity during the last seven days and six months; including characteristics of employed persons such as hours of work, occupation, industry, employment status, and earnings from paid employment; unemployment and characteristics of unemployed persons.

The general objective of the 2015 Urban Employment and Unemployment Survey is to provide statistical data on the characteristics and size of the economic activity status i.e. employed, unemployed population of the country at urban levels on annual basis. The specific objectives of the survey are to: • collect statistical data on the potential manpower and those who are available to take part in various socio-economic activities; • update the data and determine the size and distribution of the labour force participation and the status of economic activity for different sub-groups of the population at different levels of the country; and also to study the socioeconomic and demographic characteristics of these groups; • identify the size, distribution and characteristics of employed population i.e. working in the formal or informal employment sector of the economy and earnings from paid employees and its distribution by occupation and Industry...etc; • provide data on the size, characteristics and distribution of unemployed population and rate of unemployment; • provide data that can be used to assess the situation of women’s employment or the participation of women in the labour force; and • generated time series data to trace changes over time;

Geographic coverage

The survey covered all urban parts of the country except three zones of Afar and six zones of Somali, where the residents are pastoralists.

Analysis unit

• Household
• Individual

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2007 Population and Housing Census was used as frame to select 30 households from the sample enumeration areas.

The country was divided into two broad categories. 1) Major urban centers: All regional capitals and five other major urban centers were included in this category. This category had a total of 16 reporting levels. A stratified two-stage cluster sample design was implemented to select the samples. The primary sampling units were EAs, from each EA 30 households were selected as a second stage unit.

2) Other urban centers: In this category, all other urban centers were included. This category had a total of 8 reporting levels. 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. From each EA 30 households were selected at the third stage.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire that was used to collect the data had five sections:

Section - 1: Area identification of the selected household: this section dealt with area identification of the respondents such as region, zone, wereda, etc.

Section - 2: Socio- demographic characteristics of households: it consisted of the general socio-demographic characteristics of the population such as age, sex, education, status and type of migration, disability, literacy status, educational Attainment, types of training and marital status.

Section – 3: Economic activities during the last seven days: this section dealt with a range of questions which helps to see the status and characteristics of employed persons in a current status approach such as hours of work in productive activities, occupation, industry, status in employment, earnings from employment, job mobility, service year for paid employees employment in the formal and informal sector and time related under employment.

Section – 4: Unemployment and characteristics of unemployed persons: this section focused on the size, rate and characteristics of the unemployed population.

Section – 5: Economic activities during the last twelve months: this section consists of the usual economic activity status refereeing to the long reference period i.e. engaged in productive activities during most of the last twelve months, reason for not being active, status in employment, main occupation and industry with two digit codes.

Cleaning operations

The filled-in questionnaires that were retrieved from the field were first subjected to manual editing and coding. During the fieldwork, field supervisors and statisticians of the head and 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 to maintain the quality of the data. Consistency checks and rechecks were also made based on frequency and tabulation results. This was done by senior programmers using CSPro software in collaboration with the senior subject matter experts from Manpower Statistics Team of the CSA.

Response rate

Response rate of the survey was 99.8%

Sampling error estimates

Estimation procedures, estimates, and CV's for selected tables are provided in the Annex II and III of the survey final report.

Socio-demographic characteristics of students of Jimma high school, Jimma town southwest Ethiopia, 2021 (N = 388).

ET：最大城市人口在12-01-2017达4,215,965.000人，相较于12-01-2016的4,039,927.000人有所增长。ET：最大城市人口数据按年更新，12-01-1960至12-01-2017期间平均值为1,690,413.500人，共58份观测结果。该数据的历史最高值出现于12-01-2017，达4,215,965.000人，而历史最低值则出现于12-01-1960，为519,177.000人。CEIC提供的ET：最大城市人口数据处于定期更新的状态，数据来源于World Bank，数据归类于全球数据库的埃塞俄比亚 – Table ET.World Bank.WDI：人口和城市化进程统计。

ET：最大城市人口：占城镇人口百分比在12-01-2017达15.931%，相较于12-01-2016的16.255%有所下降。ET：最大城市人口：占城镇人口百分比数据按年更新，12-01-1960至12-01-2017期间平均值为29.736%，共58份观测结果。该数据的历史最高值出现于12-01-1960，达36.434%，而历史最低值则出现于12-01-2017，为15.931%。CEIC提供的ET：最大城市人口：占城镇人口百分比数据处于定期更新的状态，数据来源于World Bank，数据归类于Global Database的埃塞俄比亚 – 表 ET.世界银行：人口和城市化进程统计。

Abstract

The Ethiopian Socioeconomic Survey (ESS) is a collaborative project between the Central Statistics Agency (CSA) of Ethiopia 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 panel household level data with a special focus on improving agriculture statistics and 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.

The specific objectives of the ESS are:

• Development of an innovative model for collecting agricultural data in conjunction with household data;
• Strengthening the capacity to generate a sustainable system for producing accurate and timely information on agricultural households in Ethiopia;
• Development of a model of inter-institutional collaboration between the CSA and relevant federal and local government agencies as well as national and international research and development partners; and
• Comprehensive analysis of household income, well-being, and socio-economic characteristics of households in rural areas and small towns.

The ESS contains several innovative features:

• Integration of household welfare data with agricultural data;
• Creation of a panel data set that can be used to study welfare dynamics, the role of agriculture in development and the changes over time in health, education and labor activities, inter alia;.
• Collection of information on the network of buyers and sellers of goods with which the household interacts;
• Expanding the use of GPS units for measuring agricultural land areas;
• Involvement of multiple actors in government, academia and the donor community in the development of the survey and its contents as well as its implementation and analysis;
• Creation of publicly available micro data sets for researchers and policy makers;

Geographic coverage

National Coverage.

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

ESS is designed to collect panel data in rural and urban areas on a range of household and community level characteristics linked to agricultural activities. The first wave was implemented in 2011-12 and the second wave is implemented in 2013-14. The first wave, ERSS, covered only rural and small town areas. The second wave, ESS, added samples from large town areas. The second wave is nationally representative. The existing panel data (2011/12-2013/14) is only for rural and small towns. Large towns were added during the second wave and, so far, there is only one round. The planned follow-up ESS surveys will continue to be nationally representative. The ESS sample size provides estimates at the national level for rural and small town households. At the regional level, it provides estimates for five regions including Addis Ababa, Amhara, Oromiya, SNNP, and Tigray.

The sample is a two-stage probability sample. The first stage of sampling entailed selecting primary sampling units, which are a sample of the CSA enumeration areas (EAs). A total of 433 EAs were selected based on probability proportional to size of the total EAs in each region. For the rural sample, 290 EAs were selected from the AgSS EAs. For small town EAs, a total of 43 EAs and for large towns 100 EAs were selected. In order to ensure sufficient sample in the most populous regions (Amhara, Oromiya, SNNP, and Tigray) and Addis Ababa, quotas were set for the number of EAs in each region. The sample is not representative for each of the small regions including Afar, Benshangul Gumuz, Dire Dawa, Gambella, Harari, and Somalie regions. However, estimates can be produced for a combination of all smaller regions as one "other region" category.

During the second wave 100 urban EAs were added. The addition also included one more region to the sample, Addis Ababa. In each EA 15 households were selected. The addition of urban EAs increased the sample size from 333 to 433 EAs or from about 3,969 to 5,469 households.

The second stage of sampling was the selection of households to be interviewed in each EA. For rural EAs, a total of 12 households are sampled in each EA. Of these, 10 households were randomly selected from the sample of 30 AgSS households. The AgSS households are households which are involved in farming or livestock activities. Another 2 households were randomly selected from all other non-agricultural households in the selected rural EA (those not involved in agriculture or livestock). In some EAs, there is only one or no such households, in which case, less than two non-agricultural households were surveyed and more agricultural households were interviewed instead so that the total number of households per EA remains the same.

In the small town EAs, 12 households are selected randomly from the listing of each EA, with no stratification as to whether the household is engaged in agriculture/livestock. The same procedure is followed in the large town EAs. However, 15 households were selected in each large town EA.

Households were not selected using replacement. Thus, the final number of household interviewed was slightly less than the 5,469 as planned in the design. A total of 3,776 panel households and 1,486 new households (total 5,262 households) were interviewed with a response rate of 96.2 percent.

Mode of data collection

Face-to-face paper [f2f]

Cleaning operations

The interviews were carried out using paper and pen interviewing method. However, a concurrent data entry arrangement was introduced in this wave. In this arrangement, the enumerators did not wait until all the interviews were completed. Rather, once the enumerators completed some 3 to 4 questionnaires, the supervisors collected those completed interviews from the enumerators and brought them to the branch offices for data entry, while the enumerators are still conducting interviews with other households. Then questionnaires are keyed at the branch offices as soon as they are completed using CSPro data entry application software. The data from the completed questionnaires are then checked for any interview or data entry errors using a stata program. Data entry errors are checked with the data entry clerks and the interview errors are then sent to back to the field for correction and feedback to the ongoing interviews. Several rounds of this process were undertaken until the final data files are produced. In addition, after the fieldwork was completed the paper questionnaires were sent to the CSA headquarters in Addis Ababa for further checking. Additional cleaning was carried out, as needed, by checking the hard copies.

Response rate

Response rate was 96.2 percent.