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: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: 2017 PPP per day data was reported at 1.820 Intl $/Day in 2015. This records an increase from the previous number of 1.750 Intl $/Day for 2010. Ethiopia ET: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: 2017 PPP per day data is updated yearly, averaging 1.785 Intl $/Day from Dec 2010 (Median) to 2015, with 2 observations. The data reached an all-time high of 1.820 Intl $/Day in 2015 and a record low of 1.750 Intl $/Day in 2010. Ethiopia ET: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: 2017 PPP per day 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. Mean consumption or income per capita (2017 PPP $ per day) of the bottom 40%, used in calculating the growth rate in the welfare aggregate of the bottom 40% of the population in the income distribution in a country.;World Bank, Global Database of Shared Prosperity (GDSP) (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity).;;The choice of consumption or income for a country is made according to which welfare aggregate is used to estimate extreme poverty in the Poverty and Inequality Platform (PIP). The practice adopted by the World Bank for estimating global and regional poverty is, in principle, to use per capita consumption expenditure as the welfare measure wherever available; and to use income as the welfare measure for countries for which consumption is unavailable. However, in some cases data on consumption may be available but are outdated or not shared with the World Bank for recent survey years. In these cases, if data on income are available, income is used. Whether data are for consumption or income per capita is noted in the footnotes. Because household surveys are infrequent in most countries and are not aligned across countries, comparisons across countries or over time should be made with a high degree of caution.

Ethiopia ET: Income Share Held by Highest 10% data was reported at 31.400 % in 2015. This records an increase from the previous number of 27.400 % for 2010. Ethiopia ET: Income Share Held by Highest 10% data is updated yearly, averaging 27.400 % from Dec 1995 (Median) to 2015, with 5 observations. The data reached an all-time high of 38.000 % in 1995 and a record low of 25.500 % in 1999. Ethiopia ET: Income Share Held by Highest 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 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.

Homegarden avocado cultivation offers a viable option for smallholder farmers to diversify their sources of income and food. This study examined the contribution of avocado cultivars to household income diversification and food security in the Jewe and Upper Gana kebeles of Central Ethiopia. Data were collected from 164 households using a semi-structured questionnaire and supplemented with focus group discussions. The results of this study indicated that Nabal, Hass, and Ettinger were the most commonly cultivated avocado cultivars. On average, the households owned four improved avocado trees. This study revealed that households had highly diversified income sources, with an average SID value of 0.63. The average fruit yields for the Nabal, Hass, and Ettinger cultivars ranged from 45 to 60 kg per household. These cultivars contributed approximately 14% and 10% of the household income sources and food consumption scores, respectively. This study found that, on average, households consumed 40 kg of Hass and 25 kg of Ettinger fruits, and sold 55 kg of Nabal and 25 kg of Ettinger fruits per harvest season. Improved avocado cultivation was positively associated with household income and food consumption. Local governments should encourage cultivation of these cultivars to enhance income and food security for farmers. The cultivation of improved avocado cultivars has sparked significant interest among Ethiopian smallholder farmers owing to the potential benefits offered by the different cultivars. This study examines how avocado cultivars contribute to household income diversification and food consumption among smallholder farmers in Central Ethiopia. The findings indicated that Nabal, Hass, and Ettinger were the most commonly grown avocado cultivars, which significantly contributed to household income sources and food consumption. Furthermore, 64% of the total avocado harvest was used to generate household income, while 36% was used for food consumption. Expanding these three avocado cultivars has the potential to maximise economic profits, enhance food and nutrition security, and support demand-driven avocado farming practices, both within the country and beyond. Consequently, these findings provide valuable information to local government agricultural extension experts, fruit tree development partners, avocado seedling production enterprises, and smallholder avocado farmers. The results can also guide policymakers in developing local-specific enabling policy frameworks that encourage the cultivation of these avocado cultivars on a wider scale, thereby enhancing food security and household income generation.

Average family income of the respondents with satisfaction (N = 546).

While the market for sustainably certified products grows, the debate on whether smallholder farmers benefit from this certification movement is far from over. We present empirical findings across three continents. Identical household surveys were conducted among 738 smallholder coffee farmers organized in primary cooperatives in Ethiopia, India and Nicaragua. The comparative analysis which is based on the propensity score matching approach shows that the impacts of Fairtrade certification on coffee yields and income vary across countries. In Ethiopia, the coffee farmers from Fairtrade certified cooperatives fare worse than their non-certified counterparts both in coffee yield and income. In the Indian case study, the Fairtrade cooperative members have yield and price advantages over the non-certified farmers. This has in turn led to higher net revenue from coffee for certified farmers. In Nicaragua, coffee farmers from Fairtrade and double (Fairtrade-Organic) certified cooperatives also benefit in terms of net revenue but there is no statistically significant effect on yield and household income. A comparison of the Fairtrade minimum floor price and the weight-equivalent Fairtrade cooperative price in the three countries shows that Nicaraguan Fairtrade certified farmers have obtained a higher average price than the Fairtrade mandated minimum price, whereas in Ethiopia the certified farmers received a much lower price. In India, the certified average price was closer to the minimum floor price. We conclude that coffee cooperatives and the motivation and capability of their staff play a central role in training their member farmers about each aspect of coffee growing and certification.

Socio-demographic characteristics of study patients and household assets (n = 96).

Duration of illness, number of caregivers, lost workdays, loss of income and indirect costs per VL episode in US$ (1US$ = 28.91 ET Birr in 2019).

Ethiopia ET: Female Headed Households data was reported at 25.400 % in 2016. This records a decrease from the previous number of 26.100 % for 2011. Ethiopia ET: Female Headed Households data is updated yearly, averaging 24.500 % from Dec 2000 (Median) to 2016, with 4 observations. The data reached an all-time high of 26.100 % in 2011 and a record low of 22.800 % in 2005. Ethiopia ET: Female Headed Households 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. Female headed households shows the percentage of households with a female head.; ; Demographic and Health Surveys.; ; The composition of a household plays a role in the determining other characteristics of a household, such as how many children are sent to school and the distribution of family income.

Ethiopia ET: BoP: Current Account: Secondary Income: Financial Corporations, Non Financial Corporations, Households & NPISHs: Personal Transfers: Debit data was reported at 29.870 USD mn in 2016. This records an increase from the previous number of 14.438 USD mn for 2015. Ethiopia ET: BoP: Current Account: Secondary Income: Financial Corporations, Non Financial Corporations, Households & NPISHs: Personal Transfers: Debit data is updated yearly, averaging 3.449 USD mn from Dec 1977 (Median) to 2016, with 39 observations. The data reached an all-time high of 64.414 USD mn in 2010 and a record low of 0.000 USD mn in 1994. Ethiopia ET: BoP: Current Account: Secondary Income: Financial Corporations, Non Financial Corporations, Households & NPISHs: Personal Transfers: Debit data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s Ethiopia – Table ET.IMF.BOP: BPM6: Balance of Payments: Detailed Presentation: Annual.

Ethiopia ET: Mobile Account: Income: Poorest 40%: % Aged 15+ data was reported at 0.000 % in 2014. Ethiopia ET: Mobile Account: Income: Poorest 40%: % Aged 15+ data is updated yearly, averaging 0.000 % from Dec 2014 (Median) to 2014, with 1 observations. Ethiopia ET: Mobile Account: Income: Poorest 40%: % Aged 15+ 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: Banking Indicators. Mobile account denotes the percentage of respondents who report personally using a mobile phone to pay bills or to send or receive money through a GSM Association (GSMA) Mobile Money for the Unbanked (MMU) service in the past 12 months; or receiving wages, government transfers, or payments for agricultural products through a mobile phone in the past 12 months.; ; Demirguc-Kunt et al., 2015, Global Financial Inclusion Database, World Bank.; Weighted average;

Ethiopia ET: BoP: Current Account: Secondary Income: Financial Corporations, Non Financial Corporations, Households & NPISHs: Credit data was reported at 5.331 USD bn in 2016. This records an increase from the previous number of 5.299 USD bn for 2015. Ethiopia ET: BoP: Current Account: Secondary Income: Financial Corporations, Non Financial Corporations, Households & NPISHs: Credit data is updated yearly, averaging 318.536 USD mn from Dec 1977 (Median) to 2016, with 40 observations. The data reached an all-time high of 5.331 USD bn in 2016 and a record low of 18.357 USD mn in 1977. Ethiopia ET: BoP: Current Account: Secondary Income: Financial Corporations, Non Financial Corporations, Households & NPISHs: Credit data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s Ethiopia – Table ET.IMF.BOP: BPM6: Balance of Payments: Detailed Presentation: Annual.

Ethiopia ET: Mobile Account: Income: Richest 60%: % Aged 15+ data was reported at 0.046 % in 2014. Ethiopia ET: Mobile Account: Income: Richest 60%: % Aged 15+ data is updated yearly, averaging 0.046 % from Dec 2014 (Median) to 2014, with 1 observations. Ethiopia ET: Mobile Account: Income: Richest 60%: % Aged 15+ 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: Banking Indicators. Mobile account denotes the percentage of respondents who report personally using a mobile phone to pay bills or to send or receive money through a GSM Association (GSMA) Mobile Money for the Unbanked (MMU) service in the past 12 months; or receiving wages, government transfers, or payments for agricultural products through a mobile phone in the past 12 months.; ; Demirguc-Kunt et al., 2015, Global Financial Inclusion Database, World Bank.; Weighted average;

Ethiopia ET: BoP: Current Account: Secondary Income: Financial Corporations, Non Financial Corporations, Households & NPISHs: Personal Transfers: ow Workers Remittances data was reported at 742.366 USD mn in 2016. This records a decrease from the previous number of 1.072 USD bn for 2015. Ethiopia ET: BoP: Current Account: Secondary Income: Financial Corporations, Non Financial Corporations, Households & NPISHs: Personal Transfers: ow Workers Remittances data is updated yearly, averaging 4.290 USD mn from Dec 1977 (Median) to 2016, with 39 observations. The data reached an all-time high of 1.782 USD bn in 2014 and a record low of -0.435 USD mn in 1985. Ethiopia ET: BoP: Current Account: Secondary Income: Financial Corporations, Non Financial Corporations, Households & NPISHs: Personal Transfers: ow Workers Remittances data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s Ethiopia – Table ET.IMF.BOP: BPM6: Balance of Payments: Detailed Presentation: Annual.

Ethiopia ET: BoP: Current Account: Secondary Income: Financial Corporations, Non Financial Corporations, Households & NPISHs: Personal Transfers data was reported at 380.278 USD mn in 2017. This records a decrease from the previous number of 742.366 USD mn for 2016. Ethiopia ET: BoP: Current Account: Secondary Income: Financial Corporations, Non Financial Corporations, Households & NPISHs: Personal Transfers data is updated yearly, averaging 6.736 USD mn from Dec 1977 (Median) to 2017, with 40 observations. The data reached an all-time high of 1.782 USD bn in 2014 and a record low of -0.435 USD mn in 1985. Ethiopia ET: BoP: Current Account: Secondary Income: Financial Corporations, Non Financial Corporations, Households & NPISHs: Personal Transfers data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s Ethiopia – Table ET.IMF.BOP: BPM6: Balance of Payments: Detailed Presentation: Annual.

Ethiopia ET: BoP: Current Account: Secondary Income: Financial Corporations, Non Financial Corporations, Households & NPISHs: Debit data was reported at 42.866 USD mn in 2016. This records an increase from the previous number of 16.156 USD mn for 2015. Ethiopia ET: BoP: Current Account: Secondary Income: Financial Corporations, Non Financial Corporations, Households & NPISHs: Debit data is updated yearly, averaging 4.106 USD mn from Dec 1977 (Median) to 2016, with 40 observations. The data reached an all-time high of 70.255 USD mn in 2012 and a record low of 0.202 USD mn in 1994. Ethiopia ET: BoP: Current Account: Secondary Income: Financial Corporations, Non Financial Corporations, Households & NPISHs: Debit data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s Ethiopia – Table ET.IMF.BOP: BPM6: Balance of Payments: Detailed Presentation: Annual.

Ethiopia ET: BoP: Current Account: Secondary Income: Financial Corporations, Non Financial Corporations, Households & NPISHs: Other Current Transfers: Credit data was reported at 4.559 USD bn in 2016. This records an increase from the previous number of 4.212 USD bn for 2015. Ethiopia ET: BoP: Current Account: Secondary Income: Financial Corporations, Non Financial Corporations, Households & NPISHs: Other Current Transfers: Credit data is updated yearly, averaging 301.627 USD mn from Dec 1977 (Median) to 2016, with 40 observations. The data reached an all-time high of 4.559 USD bn in 2016 and a record low of 18.357 USD mn in 1977. Ethiopia ET: BoP: Current Account: Secondary Income: Financial Corporations, Non Financial Corporations, Households & NPISHs: Other Current Transfers: Credit data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s Ethiopia – Table ET.IMF.BOP: BPM6: Balance of Payments: Detailed Presentation: Annual.

Ethiopia ET: Account at a Financial Institution: Income: Richest 60%: % Aged 15+ data was reported at 25.700 % in 2014. Ethiopia ET: Account at a Financial Institution: Income: Richest 60%: % Aged 15+ data is updated yearly, averaging 25.700 % from Dec 2014 (Median) to 2014, with 1 observations. Ethiopia ET: Account at a Financial Institution: Income: Richest 60%: % Aged 15+ 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: Banking Indicators. Account at a financial institution denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution.; ; Demirguc-Kunt et al., 2015, Global Financial Inclusion Database, World Bank.; Weighted average;

Ethiopia ET: BoP: Current Account: Secondary Income: Financial Corporations, Non Financial Corporations, Households & NPISHs: Personal Transfers: ow Workers Remittances: Credit data was reported at 772.236 USD mn in 2016. This records a decrease from the previous number of 1.087 USD bn for 2015. Ethiopia ET: BoP: Current Account: Secondary Income: Financial Corporations, Non Financial Corporations, Households & NPISHs: Personal Transfers: ow Workers Remittances: Credit data is updated yearly, averaging 10.062 USD mn from Dec 1977 (Median) to 2016, with 39 observations. The data reached an all-time high of 1.796 USD bn in 2014 and a record low of 0.000 USD mn in 1994. Ethiopia ET: BoP: Current Account: Secondary Income: Financial Corporations, Non Financial Corporations, Households & NPISHs: Personal Transfers: ow Workers Remittances: Credit data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s Ethiopia – Table ET.IMF.BOP: BPM6: Balance of Payments: Detailed Presentation: Annual.