Historical dataset showing Ethiopia poverty rate by year from 1995 to 2021.

Poverty Headcount Ratio at Societal Poverty Lines: % of Population data was reported at 41.000 % in 2015. This records a decrease from the previous number of 42.800 % for 2010. Poverty Headcount Ratio at Societal Poverty Lines: % of Population data is updated yearly, averaging 44.700 % from Dec 1995 (Median) to 2015, with 5 observations. The data reached an all-time high of 69.200 % in 1995 and a record low of 41.000 % in 2015. Poverty Headcount Ratio at Societal Poverty Lines: % of 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.WDI: Social: Poverty and Inequality. The poverty headcount ratio at societal poverty line is the percentage of a population living in poverty according to the World Bank's Societal Poverty Line. The Societal Poverty Line is expressed in purchasing power adjusted 2017 U.S. dollars and defined as max($2.15, $1.15 + 0.5*Median). This means that when the national median is sufficiently low, the Societal Poverty line is equivalent to the extreme poverty line, $2.15. For countries with a sufficiently high national median, the Societal Poverty Line grows as countries’ median income grows.;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: Poverty, percent of population: The latest value from 2021 is 33.1 percent, an increase from 23.5 percent in 2015. In comparison, the world average is 24.08 percent, based on data from 72 countries. Historically, the average for Ethiopia from 1995 to 2021 is 35.77 percent. The minimum value, 23.5 percent, was reached in 2015 while the maximum of 45.5 percent was recorded in 1995.

Ethiopia ET: Poverty Headcount Ratio at National Poverty Lines: Rural: % of Rural Population data was reported at 30.400 % in 2010. This records a decrease from the previous number of 39.300 % for 2004. Ethiopia ET: Poverty Headcount Ratio at National Poverty Lines: Rural: % of Rural Population data is updated yearly, averaging 42.350 % from Dec 1995 (Median) to 2010, with 4 observations. The data reached an all-time high of 47.500 % in 1995 and a record low of 30.400 % in 2010. Ethiopia ET: Poverty Headcount Ratio at National Poverty Lines: Rural: % of Rural 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.WDI: Poverty. Rural poverty headcount ratio is the percentage of the rural population living below the national poverty lines.; ; World Bank, Global Poverty Working Group. Data are compiled from official government sources or are computed by World Bank staff using national (i.e. country–specific) poverty lines.; ; This series only includes estimates that to the best of our knowledge are reasonably comparable over time for a country. Due to differences in estimation methodologies and poverty lines, estimates should not be compared across countries.

In 2000 Ethiopia had one of the highest poverty rates in the world, with 56 percent of the population living on less than United States (U.S.) $1.25 purchasing power parity (PPP) a day. Ethiopian households experienced a decade of remarkable progress in wellbeing since then and by the start of this decade less than 30 percent of the population was counted as poor. This poverty assessment documents the nature of Ethiopia’s success and examines its drivers. Agricultural growth drove reductions in poverty, bolstered by pro-poor spending on basic services, and effective rural safety nets. However, although there is some evidence of manufacturing growth starting to reduce poverty in urban centers at the end of the decade, structural change has been remarkably absent from Ethiopia’s story of progress. The poverty assessment looks forward asking what will be needed to end extreme poverty in Ethiopia. In addition to the current successful recipe of agricultural growth and pro-poor spending, the role of the non-farm rural sector, migration, urban poverty reduction, and agricultural productivity gains for women are considered.

Ethiopia: Poverty ratio, percent living on less than 1.90 USD a day: The latest value from 2021 is 38.6 percent, an increase from 33 percent in 2015. In comparison, the world average is 8.37 percent, based on data from 78 countries. Historically, the average for Ethiopia from 1995 to 2021 is 48.28 percent. The minimum value, 33 percent, was reached in 2015 while the maximum of 73.5 percent was recorded in 1995.

Multidimensional Poverty Headcount Ratio: UNDP: % of total population data was reported at 68.700 % in 2019. Multidimensional Poverty Headcount Ratio: UNDP: % of total population data is updated yearly, averaging 68.700 % from Dec 2019 (Median) to 2019, with 1 observations. The data reached an all-time high of 68.700 % in 2019 and a record low of 68.700 % in 2019. Multidimensional Poverty Headcount Ratio: UNDP: % of total 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.WDI: Social: Poverty and Inequality. The multidimensional poverty headcount ratio (UNDP) is the percentage of a population living in poverty according to UNDPs multidimensional poverty index. The index includes three dimensions -- health, education, and living standards.;Alkire, S., Mishra, R., Selden, L. and Suppa, N. (2025). ‘The global Multidimensional Poverty Index (MPI) 2025: Country results and methodological note’, OPHI MPI Methodological Note 61, Oxford Poverty and Human Development Initiative (OPHI), University of Oxford.url: https://ophi.org.uk/publications/MN-61;NA;

Ethiopia: Poverty ratio, percent living on less than 5.50 USD a day: The latest value from 2021 is 93.5 percent, an increase from 89.9 percent in 2015. In comparison, the world average is 28.42 percent, based on data from 78 countries. Historically, the average for Ethiopia from 1995 to 2021 is 94.42 percent. The minimum value, 89.9 percent, was reached in 2015 while the maximum of 97.7 percent was recorded in 1999.

ET: Poverty Headcount Ratio at $3.20 a Day: 2011 PPP: % of Population data was reported at 61.400 % in 2015. This records a decrease from the previous number of 73.100 % for 2010. ET: Poverty Headcount Ratio at $3.20 a Day: 2011 PPP: % of Population data is updated yearly, averaging 78.000 % from Dec 1995 (Median) to 2015, with 5 observations. The data reached an all-time high of 88.300 % in 1999 and a record low of 61.400 % in 2015. ET: Poverty Headcount Ratio at $3.20 a Day: 2011 PPP: % of 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: Poverty. Poverty headcount ratio at $3.20 a day is the percentage of the population living on less than $3.20 a day at 2011 international prices. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. The aggregated numbers for low- and middle-income countries correspond to the totals of 6 regions in PovcalNet, which include low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia). See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

Gathered for the GAFSP Open Data Services activity. This file contains summary statistics of poverty by region 2015 - 2016. Data produced by the National Planning Commission and published in "Ethiopia’s Progress Towards Eradicating Poverty: An Interim Report on 2015/16 Poverty Analysis Study". | This dataset contains important information and resources. For comprehensive details, documentation, and inquiries, please contact data@worldbank.org. Additional metadata and related resources are available on this page.

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.

As of May 2023, **** million people in Ethiopia lacked sufficient food for consumption. The number of inhabitants in the food insecurity situation remained stable compared to the previous month. Furthermore, the prevalence of food insecurity in Ethiopia was measured at ***** percent of the population in May 2023. Overall, the number of people with insufficient food consumption in the country fluctuated, peaking at **** percent million individuals in April 2022.

Proportion of Population Pushed Below the 60% Median Consumption Poverty Line By Out-of-Pocket Health Expenditure: % data was reported at 0.810 % in 2018. This records an increase from the previous number of 0.550 % for 2015. Proportion of Population Pushed Below the 60% Median Consumption Poverty Line By Out-of-Pocket Health Expenditure: % data is updated yearly, averaging 0.390 % from Dec 1999 (Median) to 2018, with 5 observations. The data reached an all-time high of 0.810 % in 2018 and a record low of 0.330 % in 1999. Proportion of Population Pushed Below the 60% Median Consumption Poverty Line By Out-of-Pocket Health Expenditure: % 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. This indicator shows the fraction of a country’s population experiencing out-of-pocket health impoverishing expenditures, defined as expenditures without which the household they live in would have been above the 60% median consumption but because of the expenditures is below the poverty line. Out-of-pocket health expenditure is defined as any spending incurred by a household when any member uses a health good or service to receive any type of care (preventive, curative, rehabilitative, long-term or palliative care); provided by any type of provider; for any type of disease, illness or health condition; in any type of setting (outpatient, inpatient, at home).;Global Health Observatory, World Health Organization (WHO), uri: https://www.who.int/data/gho/data/themes/topics/financial-protection;Weighted average;

ET: Poverty Gap at $1.90 a Day: 2011 PPP: % data was reported at 7.700 % in 2015. This records a decrease from the previous number of 9.100 % for 2010. ET: Poverty Gap at $1.90 a Day: 2011 PPP: % data is updated yearly, averaging 9.100 % from Dec 1995 (Median) to 2015, with 5 observations. The data reached an all-time high of 26.600 % in 1995 and a record low of 7.700 % in 2015. ET: Poverty Gap at $1.90 a Day: 2011 PPP: % 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: Poverty. Poverty gap at $1.90 a day (2011 PPP) is the mean shortfall in income or consumption from the poverty line $1.90 a day (counting the nonpoor as having zero shortfall), expressed as a percentage of the poverty line. This measure reflects the depth of poverty as well as its incidence. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. The aggregated numbers for low- and middle-income countries correspond to the totals of 6 regions in PovcalNet, which include low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia). See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

This marginality hotspot map of Ethiopia uses the lowest quartile as thresholds for the dimensions of marginality. Again, this map shows how many dimension of marginality - as defined by Gatzweiler et al. (2011) - overlap. Quality/Lineage: Indicator - Input - Cut-off point total expenditure at household level - HICE survey data - Total expenditure is defined as all household consumption expenditures as well as non-consumption expenditures; regional level lowest quartile (1671.92 Birr) Prevalence of stunting among children under five, by lowest available subnational administrative unit, varying years (FGGD) - Global raster data layer with 5 arc-minutes resolution. Data compilation by FAO including the prevalence of stunting, LandScan global population database and the percentage of children under five - Percentage of children below 3 standard deviations of WHO growth standards (18.85%) Travel time to major cities: A global map of Accessibility (by Andrew Nelson) - Infrastructural data (based on data of: populated places, cities, road network, travel speeds, railway network, navigable rivers, major waterbodies, shipping lanes, borders, urban areas, elevation and slope); 30 arc-seconds resolution - More than 12 hours travelling to the next agglomeration with ≥50,000 people. percentage of households having health problem in last 2 months and not going to health institution or traditional healer - WMS survey data; regional level - Lowest quartile (49.11%) Global land area with soil constraints Depth, soil chemical status and natural, fertility, drainage, texture, miscellaneous land; - 5 arc-minutes resolution - Soils that have „very frequent severe“ soil constraints as well as soils “unsuitable for agriculture” according to FAO 2007 (FGGD) definition percent of households getting drinking water from unprotected well or spring - DHS survey data; regional level - Lowest quartile (15.83%) percentage of women saying wife beating is ok if she neglects children - DHS survey data - Lowest quartile (70.75%)

Abstract

The level and distribution of poverty in Ethiopia is extensive. According to the results obtained from the 1995/96 and the 1999/2000 Household Income, Consumption and Expenditure Survey and Welfare Monitoring Survey of the Central Statistical Authority (CSA), about 44 percent of the total populations (45 percent in rural areas and 37 percent in urban areas) are found to be below poverty line. The country together with development partners, as a result, has put poverty reduction strategies high on the agenda and working firmly on the implementation program since the beginning of this decade. With firm dedication to reduce poverty, the government has prepared its poverty reduction program entitled “Sustainable Development and Poverty Reduction Program” in 2002. The strategy has been implemented over the past three years.

In light of the plan to reduce poverty over time, strong system of monitoring and evaluation has been put in place. Consequently, the issue of welfare monitoring in Ethiopia arose as part of the Economic Reform Program (ERP). The ERP specifically and strongly underlies to see the effects of the reform program on poverty and building the analytical capacity of the government to monitor and evaluate such effects. To this end, the government has established a Welfare Monitoring System in 1995 to oversight the following major activities: - establish an information system that provides a continuous picture of the poverty scenario in the country; - indicate the impact of reform programs on the level of household welfare; - establish follow-up procedures on the various programs and activities targeted towards poverty reduction; and - conduct regular statistical surveys to assess, in particular, the efficiency of targeted programs.

The CSA and WMU of Ministry of Finance and Economic Development (MoFED) has been the key actors in the M&E system in place by way of producing, analyzing and disseminating poverty related data and results. The program has been supported by the World Bank IDA Credit and the Norwegian Trust Fund.

In line with strengthening the established M&E system of the government, the CSA and WMU of MoFED had also submitted a financing requirement proposal (entitled: Strengthening Data Collection, Analysis and Dissemination on Poverty Monitoring and the MDGs) to the Development Assistant Group (DAG). Following the signing of the Memorandum of Understanding (MOU) between MoFED, CSA and the donors, various implementation activities have also been carried out.

In order to meet the data needs of the Welfare Monitoring System, the CSA has been conducting the two surveys that provide poverty related data: Household Income, Consumption and Expenditure Survey (HICES) and Welfare Monitoring Survey (WMS) since 1995/96. The HICE and WMS surveys provide crucially useful information for the designing and monitoring and evaluation of the country’s poverty reduction strategy: Sustainable Development and Poverty Reduction Program (SDPRP), the various socioeconomic policies and programs and hence monitor the progress towards meeting the Millennium Development Goals (MDGs). The two surveys are inseparable and provide basic data that reflect the standard of living of households, individuals and the society as a whole.

The WMS focuses on wider range of socioeconomic indicators that reflect the nonincome dimensions of poverty. The 2004 survey have been improved to accommodate users needs as much as possible. New features in the current survey include shocks and coping mechanisms, HIV/AIDS related information, estimates of orphan and foster children, major prevailing diseases, plot size and other additional variables.

The main objectives of the WMS are to provide data that enable understand the nonincome aspects of poverty and has the following objectives: - to assess the level, extent and distribution of non-income poverty; - helps assess the quality of life of households/individuals; - to provide basic data that enables design, monitor and evaluate the impact of socioeconomic policies and programs on households/individuals living standard; - provide basic indicators on households’ and individuals’ living standard with respect to basic needs including: -> Education, Health, Child nutrition and care, Access to and utilization of basic facilities, Housing and housing amenities (drinking water, sanitation, energy, etc.), Household assets, Selected indicators of living standard, Vulnerability (Shocks and coping mechanisms, Food security, etc.), and HIV/AIDS and basic population characteristics.

Geographic coverage

The year 2004 Welfare Monitoring Survey covered all rural and urban area of the country except the non-sedentary areas in Afar and Somali Regional States. Excluded are three zones of Afar Region, six zones of Somali Region and all zones of Gambella Region.

Analysis unit

• Households
• Individuals (including adult women aged 15 and above, children aged 5 and below)

Universe

The survey covered households in the selected samples except residents of collective quarters, homeless persons and foreigners.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Frame The list of all households obtained from the 2001/02 Ethiopian Agricultural Sample Enumeration (EASE) is used as a frame to select the sample EAs in the rural areas of the country. In urban areas, on the other hand, the frame, consisting of households by EA obtained from the 2004 Ethiopian Urban Economic Establishment Census (EUEEC), is used to select sample sites for the 2004 welfare monitoring survey. The frame from which sample households were selected was based on a fresh list of households taken at the beginning of the survey period in each of the selected urban and rural EAs.

Sample Design For the purpose of the survey the country was divided into three broad categories including rural category, major urban centers category and other urban centers category.

Category I - Rural: This category consists of the rural areas of 58 zones and special Weredas, which are considered as zones, in 7 regions of the country. Harari region and Addis Ababa City Counsil and Dire Dawa City council were treated independently. Each zone/special Wereda of a region was considered to be a survey domain (i.e. reporting level) for which the major findings of the survey are reported. Rural Harari, Addis Ababa and Dire Dawa each were considered as separate reporting levels.

Category I totally comprises 61 reporting levels. A stratified two-stage cluster sample design in which the primary sampling units (PSUs) were EAs was used to select samples. Twelve households per sample EA were selected as a second Stage Sampling Unit (SSU) to which survey questionnaire finally were administered to the members of sample households.

Category II - Major urban centers: In this category all regional capitals (except Gambella region) and four other major urban centers that have relatively larger population sizes were included. Each of the 14 urban center in this category is taken us a reporting level. Since there is a high variation in the standards of living of the residents of these urban centers (that may have a significant impact on the final results of the survey), each urban center was further stratified into the following three sub-strata.

Sub-stratum 1: Households having a relatively high standard of living Sub-stratum 2: Households having a relatively medium standard of living Sub-stratum 3: Households having a relatively low standard of living

In this category too, a stratified two-stage cluster sample design was adopted to select the primary sampling units (the EAs) and the Second Stage Unit. Allocation of sample EAs to a reporting level among the above mentioned strata were accomplished in proportion to the number of EAs in each stratum. Sixteen households from each of the primary sampling units (EAs) in each reporting level were then selected as a Second Stage Unit (SSU).

Category III - Other urban centers: Urban centers in the country other than those under category II were grouped under this category. A domain of other urban centers is formed for each region (excluding Gambella region) and seven reporting levels were formed in this category. However, there is no domain in category III for Harari, Addis Ababa and Dire Dawa as they do not have urban centers other than those grouped under category II.

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. Sixteen households from each of the selected EAs were finally selected as a third stage sampling unit.

Sample Size and Selection Scheme Category I: A totally of 2,016 EAs and 24,192 households were selected from this category. Sample EAs of each reporting level were selected using Probability Proportional to Size (PPS) with systematic sampling techniques; size being number of household obtained from the 2001/2 Ethiopian Agricultural Sample Enumeration. Twelve households per EA were systematically selected from the fresh list of households prepared at the beginning of the survey.

Category II: In this category 485 EAs and 7,760 households were selected. Sample EAs from each reporting level in this category were also selected using probability proportional to size systematic sampling; size being number of households obtained from the 2004 EUEEC. Sixteen households in each of the selected EAs were systematically selected from the fresh list of households prepared at the beginning of the survey.

Category III: One hundred twenty-seven urban centers, 275 EAs and 4,400 households were selected in this category. Urban

ET: Income Share Held by Lowest 10% data was reported at 2.600 % in 2015. This records a decrease from the previous number of 3.200 % for 2010. ET: Income Share Held by Lowest 10% data is updated yearly, averaging 3.200 % from Dec 1995 (Median) to 2015, with 5 observations. The data reached an all-time high of 4.100 % in 2004 and a record low of 2.600 % in 2015. ET: Income Share Held by Lowest 10% 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: Poverty. Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles.; ; World Bank, Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments. Data for high-income economies are from the Luxembourg Income Study database. For more information and methodology, please see PovcalNet (http://iresearch.worldbank.org/PovcalNet/index.htm).; ; The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand six hundred household surveys across 164 countries in six regions and 25 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only. See PovcalNet (http://iresearch.worldbank.org/PovcalNet/WhatIsNew.aspx) for definitions of geographical regions and industrialized countries.

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).

A decade and a half of relative peace and political stability, broad economic reforms, and far-reaching political decentralization have brought Ethiopia back from one of its lowest levels of income per capita to one of its highest levels over the past forty years. At the same time, Gross Domestic Product per capita today is still only slightly above the levels reached in the early 1970 underscoring the deep-rooted and complex nature of poverty in Ethiopia. The positive developments at the macro level beg the questions of how well the Ethiopian people themselves fared during this period and what can be done to improve their lives further. These are the two overarching questions this study attempts to address, with a larger emphasis on analyzing the relative importance of the different determinants of people's well-being and their policy implications in light of the upcoming revision of Ethiopia's Sustainable Development and Poverty Reduction Strategy (SDPRP). In particular, the study seeks to identify areas of intervention to improve people's well-being and to provide the behavioral foundations for developing sector specific policies. For a comprehensive treatment of the challenges and opportunities related to the different sectors, the study refers to the World Bank Country Status Reports on Health, Education and Rural Development.

In 2019, approximately * in ** Ethiopians reported there were times they did not have enough money to buy food that they and their family needed in the past twelve months. This figure had increased from about * in ** Ethiopians suffering from food insecurity in 2012.