Abstract

The Ethiopia Socioeconomic Panel Survey (ESPS) is a collaborative project between the Ethiopian Statistical Service (ESS) 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. ESPS 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 on agriculture activities in the country. The ESPS collects information on household agricultural activities along with other information on the households like human capital, other economic activities, and access to services and resources. The ability to follow the same households over time makes the ESPS 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 ESPS is the first-panel survey to be carried out by the Ethiopian Statistical Service 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 second phase ESPS panel survey is based on the updated 2018 pre-census cartographic database of enumeration areas by the Ethiopian Statistical Service (ESS). The sample is a two-stage stratified probability sample. The ESPS 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 systematic PPS. This is designed to automatically result 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 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 ESPS sampling is that the total number of agriculture households per EA remains at 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.

The ESPS-5 kept all the ESPS-4 samples except for those in the Tigray region and a few other places. A more detailed description of the sample design is provided in Section 3 of the Basic Information Document provided under the Related Materials tab.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The ESPS-5 survey consisted of four questionnaires (household, community, post-planting, and post-harvest questionnaires), similar to those used in previous waves but revised based on the results of those waves and on the need for new data they revealed. The following new topics are included in ESPS-5:

a. Dietary Quality: This module collected information on the household’s consumption of specified food items.

b. Food Insecurity Experience Scale (FIES): In this round the survey has implemented FIES. The scale is based on the eight food insecurity experience questions on the Food Insecurity Experience Scale | Voices of the Hungry | Food and Agriculture Organization of the United Nations (fao.org).

c. Basic Agriculture Information: This module is designed to collect minimal agriculture information from households. It is primarily for urban households. However, it was also used for a few rural households where it was not possible to implement the full agriculture module due to security reasons and administered for urban households. It asked whether they had undertaken any agricultural activity, such as crop farming and tending livestock) in the last 12 months. For crop farming, the questions were on land tenure, crop type, input use, and production. For livestock there were also questions on their size and type, livestock products, and income from sales of livestock or livestock products.

d. Climate Risk Perception: This module was intended to elicit both rural and urban households perceptions, beliefs, and attitudes about different climate-related risks. It also asked where and how households were obtaining information on climate and weather-related events.

e. Agriculture Mechanization and Video-Based Agricultural Extension: The rural area community questionnaire covered these areas rural areas. On mechanization the questions related to the penetration, availability and accessibility of agricultural machinery. Communities were also asked if they had received video-based extension services.

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

ESPS-5 planned to interview 7,527 households from 565 enumeration areas (EAs) (Rural 316 EAs and Urban 249 EAs). However, due to the security situation in northern Ethiopia and to a lesser extent in the western part of the country, only a total of 4999 households from 438 EAs were interviewed for both the agriculture and household modules. The security situation in northern parts of Ethiopia meant that, in Tigray, ESPS-5 did not cover any of the EAs and households previously sampled. In Afar, while 275 households in 44 EAs had been covered by both the ESPS-4 agriculture and household modules, in ESPS-5 only 252 households in 22 EAs were covered by both modules. During the fifth wave, security was also a problem in both the Amhara and Oromia regions, so there was a comparable reduction in the number of households and EAs covered there.

More detailed information is available in the BID.

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 Ethiopia 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, 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 Coverage.

Analysis unit

Households

Universe

ESS uses a nationally representative sample of over 5,000 households living in rural and urban areas. The urban areas include both small and large towns.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample is a two-stage probability sample. The first stage of sampling entailed selecting primary sampling units, or 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. A total of 43 and 100 EAs were selected for small town and urban areas, respectively. In order to ensure sufficient sample size 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. A more detailed description of the sample design is provided in Section 3 of the Basic Information Document provided under the Related Materials tab.

Mode of data collection

Mixed data collection mode

Cleaning operations

The interviews were carried out using pen-and-paper (PAPI) as well as computer-assisted personal interviewing (CAPI) method. A concurrent data entry arrangement was implemented for PAPI. In this arrangement, the enumerators did not wait until all the interviews were completed. Rather, once the enumerators completed approximately 3-4 questionnaires, supervisors collected these interviews from enumerators and brought them to the branch offices for data entry. This process took place as enumerators continued administering interviews with other households. Then questionnaires were keyed at the branch offices as soon as they were completed using the CSPro data entry application software. The data from the completed questionnaires were then checked for any interview or data entry errors using a STATA program. Data entry errors were flagged for the data entry clerks and the interview errors were 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 were produced. Additional cleaning was carried out, as needed, by checking the hard copies. In ESS3, CAPI (with a Survey Solutions platform) was used to collect the community data in large town areas.

Response rate

During wave 3, 1255 households were re-interviewed yielding a response rate of 85 percent. Attrition in urban areas is 15% due to consent refusal and inability to trace the whereabouts of sample households.

The Ethiopian 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 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

This contribution consists of three datasets, and three survey questionnaires used to gather these data (English version). The datasets include information about Ethiopian urban and rural consumers, sampled in one city and one food hub (i.e., local production regions) in Ethiopia. Back to back with the survey activities done with urban consumers, lab experiments were run. The experimental protocols have been submitted separately. The datasets are provided as Excel Workbooks, while the questionnaires are provided in PDF format.

Abstract

Ethiopia hosts over 900,000 refugees, making it the sixth-largest refugee population in the world and the second-largest in Sub-Saharan Africa. Most refugees are from South Sudan, Eritrea, Somalia, and Sudan, which have experienced some combination of long-running domestic conflict, border disputes with Ethiopia, recurrent drought, and other climate shocks. The national household survey of Ethiopia – Household Welfare Statistics Survey (HoWStat) – currently excludes displaced populations from its sample of households. We have little information on their socioeconomic outcomes and poverty levels compared to Ethiopians. The Socio-Economic Survey of Refugees (SESRE) aims at solving two existing problems: (i) gaps in data on the socioeconomic dimensions of refugees and (ii) gaps in analytical studies presenting the socioeconomic outcomes of refugees and hosts. Moreover, the SESRE serves as a feasibility study to include refugees in HoWStat’s data collection effort, including sampling, data collection, and analysis.

Geographic coverage

The SESRE covers all current major refugee camps: Eritreans, South Sudanese, and Somalis, as well as the out-of-camp refugees in Addis Ababa. In addition, the survey covers the respective host communities around the camps, including the host communities of Addis Ababa. Due to the conflict in the Tigray region of Ethiopia between 2020 and 2022, Eritrean refugees living in camps in Tigray could not be included in this survey.

Analysis unit

Household and individual

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for this survey was 3,456 households from eight domains, with data was collected from 3,452 households. There are three domains for the three largest in-camp refugee groups—Eritreans, Somalis, and South Sudanese—three for host communities of these major refugee groups, and one for refugees and one for host communities in Addis Ababa. In all categories, a stratified, two-stage cluster sample design technique was used to select EAs and 12 households per EA, whereby the EAs were considered a Primary Sampling Unit and the households as the Secondary Sampling Unit. The SESRE is designed to estimate demographic, socioeconomic, welfare, and refugee-specific indicators of the eight domains.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire contains modules on: Sociodemographic, Jobs and Livelihood, Welfare and Equity, Aspirations, Social Cohesion, and Markets and Opportunities. The questionnaire is available for download.

This contribution consists of four datasets, and two survey questionnaires used to gather these data (English version). The datasets include information about Ethiopian small crop and peri-urban farmers, sampled in the two local Food Hubs (i.e., local production regions) in Ethiopia. In both locations lab-in-the-field experiments were run with farmers. The experimental protocols have been submitted separately. The datasets are provided as Excel Workbooks, while the questionnaires are provided in PDF format.

Ethiopia ET: Proportion of People Living Below 50 Percent Of Median Income: % data was reported at 12.400 % in 2015. This records an increase from the previous number of 9.400 % for 2010. Ethiopia ET: Proportion of People Living Below 50 Percent Of Median Income: % data is updated yearly, averaging 9.400 % from Dec 1995 (Median) to 2015, with 5 observations. The data reached an all-time high of 12.400 % in 2015 and a record low of 5.200 % in 2004. Ethiopia ET: Proportion of People Living Below 50 Percent Of Median Income: % 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: Social: Poverty and Inequality. The percentage of people in the population who live in households whose per capita income or consumption is below half of the median income or consumption per capita. The median is measured at 2017 Purchasing Power Parity (PPP) using the Poverty and Inequality Platform (http://www.pip.worldbank.org). For some countries, medians are not reported due to grouped and/or confidential data. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported.;World Bank, Poverty and Inequality Platform. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are mostly from the Luxembourg Income Study database. For more information and methodology, please see http://pip.worldbank.org.;;The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than 2000 household surveys across 169 countries. See the Poverty and Inequality Platform (PIP) for details (www.pip.worldbank.org).

Ethiopia ET: Population: per 1 000 Inhabitants data was reported at 120,283.010 Person in 2021. This records an increase from the previous number of 117,190.880 Person for 2020. Ethiopia ET: Population: per 1 000 Inhabitants data is updated yearly, averaging 78,580.505 Person from Dec 1990 (Median) to 2021, with 32 observations. The data reached an all-time high of 120,283.010 Person in 2021 and a record low of 47,878.070 Person in 1990. Ethiopia ET: Population: per 1 000 Inhabitants 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: Demography: Non OECD Member: Annual.

This data set is collected by centeral statistic agency of Ethiopia with reference to 2013 and 2015 poverty and inequality indicating variables.The onlly modification made here is new variables are created systematically on the basis of old variables with STATA gen command.This done because poverty and inequality analysis needs further process and creating suitable welfare indicator.

Degree of socio-economic marginality in areas with capabilitiy gaps Socio-economic marginality: Socio-economic marginality in Ethiopia was defined by the following economic, health and educational conditional indicators: 1. Economy: 1.1 Regional poverty headcount indices (% of population whose income/consumption is below the poverty line = 3781 birr) 1.2 Food poverty headcount indices (% of population whose income/consumption for food is below the cost of 2.200 kcal/day per adult food consumption) 1.3 Wealth index (% of population being part of the lowest/2.lowest wealth quintile) 2. Health: 2.1 Child mortality rate (no. of deaths out of 1000 live births <5 years) 2.2 Nutritional status of children (% of children <5 years being stunted) 2.3 Nutritional status of adults (% of men/women age 15-49 with BMI <18.5 = acute under nutrition) 3. Education: 3.1 Illiteracy rate (% of population not being able to read/write in their native language) 3.2 Net enrolment ratio primary school 3.3 Net enrolement ratio high school Data source: 1.1/1.2: Ministry of Finance and Economy Development (2012): Ethiopia‘s Progress Towards Eradicating Poverty: An Interim Report on Poverty Analysis Study (2010/11). Addis Ababa, Ethiopia 1.3/2.1/2.2/2.3: Central Statistical Agency(CSA), ICF International (2012): Ethiopia Demographic and Health Survey 2011. Addis Ababa, Ethiopia; Calverton, USA Capability gap: Areas with good agro-ecological suitability, but limited socio-economic capabilities of farmers to make use of this suitability. Agro-ecological suitability in Ethiopia was defined from the raster data set of agro-ecological suitability for rainfed crops (Fischer et al. 2002) Data source: Fischer et al. (2002): Global Agro-ecological Assessment for Agriculture in the 21st Century: Methodology and Results. International Institute for Applied Systems Analysis, Laxenburg, Austria The socio-economic capabilities of farmers were defined by the following indicators: 1. Access to technology (% of holders applying inorganic fertilizer to any crop during Meher season) 2. Access to credit (% of holders utilizing credit services) 3. Access to knowledge (% of holders utilizing advisory services) Data source: Central Statistical Agency (CSA) (2002): Ethiopian Agricultural Sample Enumeration. Addis Ababa, Ethiopia

LIVES is an initiative designed by the International Livestock Research Institute (ILRI), the International Water Management Institute (IWMI) and their national partners to build upon the success of the Canadian International Development Agency-funded project, Improving Productivity and Market Success of Smallholders in Ethiopia (IPMS). This dataset contains the household baseline Socio-economic survey.

Ethiopia ET: Population: Ages 15-64: % of Total Population data was reported at 58.210 % in 2021. This records an increase from the previous number of 57.880 % for 2020. Ethiopia ET: Population: Ages 15-64: % of Total Population data is updated yearly, averaging 52.160 % from Dec 1990 (Median) to 2021, with 32 observations. The data reached an all-time high of 58.210 % in 2021 and a record low of 51.090 % in 2000. Ethiopia ET: Population: Ages 15-64: % 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: Demography: Non OECD Member: Annual.

Supporting information file (two tables informing variables included in Principal Component Analysis (PCA). Table S1. Variables included in Principal Component Analysis (PCA) for wealth index creation. Table S2. Background descriptions of the variables included in the PCA analysis. (DOCX)

BackgroundTuberculosis (TB) is a disease of public health concern, with a varying distribution across settings depending on socio-economic status, HIV burden, availability and performance of the health system. Ethiopia is a country with a high burden of TB, with regional variations in TB case notification rates (CNRs). However, TB program reports are often compiled and reported at higher administrative units that do not show the burden at lower units, so there is limited information about the spatial distribution of the disease. We therefore aim to assess the spatial distribution and presence of the spatio-temporal clustering of the disease in different geographic settings over 10 years in the Sidama Zone in southern Ethiopia.MethodsA retrospective space–time and spatial analysis were carried out at the kebele level (the lowest administrative unit within a district) to identify spatial and space-time clusters of smear-positive pulmonary TB (PTB). Scan statistics, Global Moran’s I, and Getis and Ordi (Gi*) statistics were all used to help analyze the spatial distribution and clusters of the disease across settings.ResultsA total of 22,545 smear-positive PTB cases notified over 10 years were used for spatial analysis. In a purely spatial analysis, we identified the most likely cluster of smear-positive PTB in 192 kebeles in eight districts (RR= 2, p

Comprehensive socio-economic dataset for Ethiopia including population demographics, economic indicators, geographic data, and social statistics. This dataset covers key metrics such as GDP, population density, area, capital city, and regional classifications.

The GAR15 global exposure database is based on a top-down approach where statistical information including socio-economic, building type, and capital stock at a national level are transposed onto the grids of 5x5 or 1x1 using geographic distribution of population data and gross domestic product (GDP) as proxies.

Ethiopia ET: Percentage of Population Exposed to More Than 10 Micrograms per Cub m data was reported at 100.000 % in 2019. This stayed constant from the previous number of 100.000 % for 2018. Ethiopia ET: Percentage of Population Exposed to More Than 10 Micrograms per Cub m data is updated yearly, averaging 100.000 % from Dec 1990 (Median) to 2019, with 14 observations. The data reached an all-time high of 100.000 % in 2019 and a record low of 100.000 % in 2019. Ethiopia ET: Percentage of Population Exposed to More Than 10 Micrograms per Cub m 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: Air Quality and Health: Non OECD Member: Annual.

The poverty headcount in Ethiopia is falling. The share of the population below the national poverty line decreased from 30 percent in 2011 to 24 percent in 2016. This decrease was achieved in spite of the fact that the 2015-16 survey was conducted during the severe El-Nino drought. The observed reduction in poverty is robust to the use of alternative deflators. The fall in the poverty headcount was driven mainly by Ethiopia’s strong economic growth over that period. This poverty assessment focuses on the evolution of poverty and other social indicators in Ethiopia between 2011 and 2016. It uses data from a variety of sources, mainly the Household Consumption and Expenditure Survey (HCES), the Welfare Monitoring Surveys (WMS), the Ethiopia Socioeconomic Survey (ESS) and the Demographic and Health Surveys (DHS), to observe trends in monetary and non-monetary dimensions of living standards and to examine the drivers of these trends, with a special focus on government programs. The aim of the poverty assessment is to provide policymakers and development partners with information and analysis that can be used to improve the effectiveness of their poverty reduction and social programs.

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.