Ethiopia ET: International Development Association: Resource Allocation Index: 1=Low To 6=High data was reported at 3.425 NA in 2017. This records a decrease from the previous number of 3.467 NA for 2016. Ethiopia ET: International Development Association: Resource Allocation Index: 1=Low To 6=High data is updated yearly, averaging 3.425 NA from Jul 2005 (Median) to 2017, with 13 observations. The data reached an all-time high of 3.492 NA in 2015 and a record low of 3.383 NA in 2005. Ethiopia ET: International Development Association: Resource Allocation Index: 1=Low To 6=High 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: Defense and Official Development Assistance. IDA Resource Allocation Index is obtained by calculating the average score for each cluster and then by averaging those scores. For each of 16 criteria countries are rated on a scale of 1 (low) to 6 (high).; ; World Bank Group, CPIA database (http://www.worldbank.org/ida).; Unweighted average;

Ethiopia ET: GDP: Growth: Gross Value Added: Agriculture data was reported at 6.713 % in 2017. This records an increase from the previous number of 2.590 % for 2016. Ethiopia ET: GDP: Growth: Gross Value Added: Agriculture data is updated yearly, averaging 5.278 % from Jul 1982 (Median) to 2017, with 36 observations. The data reached an all-time high of 17.381 % in 1987 and a record low of -20.528 % in 1985. Ethiopia ET: GDP: Growth: Gross Value Added: Agriculture 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: Gross Domestic Product: Annual Growth Rate. Annual growth rate for agricultural value added based on constant local currency. Aggregates are based on constant 2010 U.S. dollars. Agriculture corresponds to ISIC divisions 1-5 and includes forestry, hunting, and fishing, as well as cultivation of crops and livestock production. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 3 or 4.; ; World Bank national accounts data, and OECD National Accounts data files.; Weighted average; Note: Data for OECD countries are based on ISIC, revision 4.

Graph and download economic data for Life Expectancy at Birth, Total for Ethiopia (SPDYNLE00INETH) from 1960 to 2023 about life expectancy, Ethiopia, life, and birth.

Ethiopia ET: Export Volume Index data was reported at 302.020 2000=100 in 2016. This records a decrease from the previous number of 310.384 2000=100 for 2015. Ethiopia ET: Export Volume Index data is updated yearly, averaging 86.142 2000=100 from Dec 1981 (Median) to 2016, with 36 observations. The data reached an all-time high of 310.384 2000=100 in 2015 and a record low of 28.980 2000=100 in 1992. Ethiopia ET: Export Volume Index 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: Trade Index. Export volume indexes are derived from UNCTAD's volume index series and are the ratio of the export value indexes to the corresponding unit value indexes. Unit value indexes are based on data reported by countries that demonstrate consistency under UNCTAD quality controls, supplemented by UNCTAD’s estimates using the previous year’s trade values at the Standard International Trade Classification three-digit level as weights. To improve data coverage, especially for the latest periods, UNCTAD constructs a set of average prices indexes at the three-digit product classification of the Standard International Trade Classification revision 3 using UNCTAD’s Commodity Price Statistics, international and national sources, and UNCTAD secretariat estimates and calculates unit value indexes at the country level using the current year’s trade values as weights. For economies for which UNCTAD does not publish data, the export volume indexes (lines 72) in the IMF's International Financial Statistics are used.; ; United Nations Conference on Trade and Development, Handbook of Statistics and data files, and International Monetary Fund, International Financial Statistics.; ;

This poverty assessment focuses on the evolution of poverty and other social indicators in Ethiopia between 2010-11 and 2015-2016 (henceforth referred to as 2011 and 2016). Using data from a variety of sources, mainly the twinned household living standards surveys (HCES and WMS), the Ethiopia Socioeconomic Survey (ESS) and the Demographic and Health Surveys (DHS), the poverty assessment documents trends in monetary and non-monetary dimensions of living standards and examines the drivers of observed trends, with a special focus on government programs. The aim of the poverty assessment is to provide policy makers and development partners with information and analysis that can be used to improve the effectiveness of their poverty reduction and social programs.

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.

Ethiopia ET: Net Official Development Assistance Received per Capita: Current Price data was reported at 39.779 USD in 2016. This records an increase from the previous number of 32.378 USD for 2015. Ethiopia ET: Net Official Development Assistance Received per Capita: Current Price data is updated yearly, averaging 10.514 USD from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 44.766 USD in 2009 and a record low of 0.655 USD in 1964. Ethiopia ET: Net Official Development Assistance Received per Capita: Current Price 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: Defense and Official Development Assistance. Net official development assistance (ODA) per capita consists of disbursements of loans made on concessional terms (net of repayments of principal) and grants by official agencies of the members of the Development Assistance Committee (DAC), by multilateral institutions, and by non-DAC countries to promote economic development and welfare in countries and territories in the DAC list of ODA recipients; and is calculated by dividing net ODA received by the midyear population estimate. It includes loans with a grant element of at least 25 percent (calculated at a rate of discount of 10 percent).; ; Development Assistance Committee of the Organisation for Economic Co-operation and Development, Geographical Distribution of Financial Flows to Developing Countries, Development Co-operation Report, and International Development Statistics database. Data are available online at: www.oecd.org/dac/stats/idsonline. World Bank population estimates are used for the denominator.; Weighted average;

Abstract

The survey was conducted in Ethiopia between June 2015 and February 2016 as part of Enterprise Surveys project, an initiative of the World Bank. The objective of the survey is to obtain feedback from enterprises on the state of the private sector as well as to help in building a panel of enterprise data that will make it possible to track changes in the business environment over time, thus allowing, for example, impact assessments of reforms. Through interviews with firms in the manufacturing and services sectors, the survey assesses the constraints to private sector growth and creates statistically significant business environment indicators that are comparable across countries.

In Ethiopia, data from 848 establishments was analyzed. Stratified random sampling was used to select the surveyed businesses. The data was collected using CAPI mode.

The standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs and labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures. Over 90 percent of the questions objectively ascertain characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance.

Geographic coverage

National

Analysis unit

The primary sampling unit of the study is an establishment. The establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must make its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.

Universe

The whole population, or the universe, covered in the Enterprise Surveys is the non-agricultural private economy. It comprises: all manufacturing sectors according to the ISIC Revision 3.1 group classification (group D), construction sector (group F), services sector (groups G and H), and transport, storage, and communications sector (group I). Note that this population definition excludes the following sectors: financial intermediation (group J), real estate and renting activities (group K, except sub-sector 72, IT, which was added to the population under study), and all public or utilities sectors. Companies with 100% government ownership are not eligible to participate in the Enterprise Surveys.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample was selected using stratified random sampling. Three levels of stratification were used in this country: industry, establishment size, and region.

Industry stratification was designed in the way that follows: the universe was stratified into four manufacturing industries (Food and Beverages (ISIC Rev. 3.1 code 15), Textile and Garments including leather (ISIC codes 17-19), Non-metallic mineral products (ISIC code 26), and other manufacturing (ISIC Codes 16, 20-25, 27-37)) and three services sectors (Transportation (ISIC codes 60-62, 64), Retail (ISIC code 52) and Other Services (ISIC codes 45, 50, 51,55 and 72)).

Size stratification was defined as follows: small (5 to 19 employees), medium (20 to 99 employees), and large (more than 99 employees).

Regional stratification for the 2015 Ethiopia ES was done across six geographic regions: Addis Ababa and Dire Dawa city administrations, and Amhara, Oromia, SNNPR and Tigray regional states.

The sample frame consisted of listings of firms from two sources. First, for panel firms, the list of 644 firms covered in the 2011 Ethiopia Enterprise Survey (i.e. "panel" firms) is used. Secondly, for fresh firms (i.e., firms that were not covered in the 2011 survey), business registry data collected from the Trade and Industry Bureaus of the six administrative regions and cities, and additional list of business registry data from the Federal Ministry of Trade and Industry were used.

The enumerated establishments with 5 employees or more (fresh and panel) were then used as the sample frame for the Ethiopia Enterprise Survey with the aim of obtaining interviews of 900 establishments.

Given the impact that non-eligible units included in the sample universe may have on the results, adjustments may be needed when computing the appropriate weights for individual observations. The percentage of confirmed non-eligible units as a proportion of the total number of sampled establishments contacted for the survey was 33% (1056 out of 3447 establishments), reflecting the fact that the fresh sample frame is based on a business registry data4. In fact, most of the non-eligibility issue is the result of firms turning out to be micro (which is not part of our sampling universe) up on screening.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The following survey instruments are available: - Manufacturing Module Questionnaire - Services Module Questionnaire

Questionnaires have common questions (core module) and respectfully additional manufacturing and services specific questions.

The eligible manufacturing industries have been surveyed using the Manufacturing questionnaire (includes the core module, plus manufacturing specific questions). Retail firms have been interviewed using the Services questionnaire (includes the core module plus retail specific questions) and the residual eligible services have been covered using the Services questionnaire (includes the core module). Each variation of the questionnaire is identified by the index variable, a0.

The survey is fielded via manufacturing or services questionnaires in order not to ask questions that are irrelevant to specific types of firms, e.g. a question that relates to production and nonproduction workers should not be asked of a retail firm. In addition to questions that are asked across countries, all surveys are customized and contain country-specific questions. An example of customization would be including tourism-related questions that are asked in certain countries when tourism is an existing or potential sector of economic growth.

Cleaning operations

Data entry and quality controls are implemented by the contractor and data is delivered to the World Bank in batches (typically 10%, 50% and 100%). These data deliveries are checked for logical consistency, out of range values, skip patterns, and duplicate entries. Problems are flagged by the World Bank and corrected by the implementing contractor through data checks, callbacks, and revisiting establishments.

Response rate

Survey non-response must be differentiated from item non-response. The former refers to refusals to participate in the survey altogether whereas the latter refers to the refusals to answer some specific questions. Enterprise Surveys suffer from both problems and different strategies were used to address these issues.

Item non-response was addressed by two strategies: a- For sensitive questions that may generate negative reactions from the respondent, such as corruption or tax evasion, enumerators were instructed to collect "Refusal to respond" (-8) as a different option from "Don't know" (-9). b- Establishments with incomplete information were re-contacted in order to complete this information, whenever necessary.

Survey non-response was addressed by maximizing efforts to contact establishments that were initially selected for interview. Attempts were made to contact the establishment for interview at different times/days of the week before a replacement establishment (with similar strata characteristics) was suggested for interview. Survey non-response did occur but substitutions were made in order to potentially achieve strata-specific goals.

The number of interviews per contacted establishments was 0.25. This number is the result of two factors: explicit refusals to participate in the survey, as reflected by the rate of rejection (which includes rejections of the screener and the main survey) and the quality of the sample frame, as represented by the presence of ineligible units. The number of rejections per contact was 0.04.

Government expenditure on education, total (% of GDP) in Ethiopia was reported at 3.7365 % in 2022, according to the World Bank collection of development indicators, compiled from officially recognized sources. Ethiopia - Public spending on education, total (% of GDP) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Graph and download economic data for Consumer Price Index for Ethiopia (DDOE02ETA086NWDB) from 1965 to 2017 about Ethiopia, CPI, price index, indexes, and price.

Abstract

Sustainable Development Goal (SDG) target 2.1 commits countries to end hunger, ensure access by all people to safe, nutritious and sufficient food all year around. Indicator 2.1.2, “Prevalence of moderate or severe food insecurity based on the Food Insecurity Experience Scale (FIES)”, provides internationally-comparable estimates of the proportion of the population facing difficulties in accessing food. More detailed background information is available at http://www.fao.org/in-action/voices-of-the-hungry/fies/en/ .

The FIES-based indicators are compiled using the FIES survey module, containing 8 questions. Two indicators can be computed: 1. The proportion of the population experiencing moderate or severe food insecurity (SDG indicator 2.1.2), 2. The proportion of the population experiencing severe food insecurity.

These data were collected by FAO through the Gallup World Poll. General information on the methodology can be found here: https://www.gallup.com/178667/gallup-world-poll-work.aspx. National institutions can also collect FIES data by including the FIES survey module in nationally representative surveys.

Microdata can be used to calculate the indicator 2.1.2 at national level. Instructions for computing this indicator are described in the methodological document available under the "DOCUMENTATION" tab above. Disaggregating results at sub-national level is not encouraged because estimates will suffer from substantial sampling and measurement error.

Geographic coverage

National coverage

Analysis unit

Individuals

Universe

Individuals of 15 years or older.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample was drawn proportional to the population and the country was stratified by region and by population size strata. Exclusions: None Design effect: 1.4

Mode of data collection

Face-to-face [f2f]

Cleaning operations

Statistical validation assesses the quality of the FIES data collected by testing their consistency with the assumptions of the Rasch model. This analysis involves the interpretation of several statistics that reveal 1) items that do not perform well in a given context, 2) cases with highly erratic response patterns, 3) pairs of items that may be redundant, and 4) the proportion of total variance in the population that is accounted for by the measurement model.

Sampling error estimates

The margin of error is estimated as 3.7 .This is calculated around a proportion at the 95% confidence level. The maximum margin of error was calculated assuming a reported percentage of 50% and takes into account the design effect.

Ethiopia ET: External Debt: COM: Commitments: International Development Association (IDA) data was reported at 1.422 USD bn in 2016. This records an increase from the previous number of 1.051 USD bn for 2015. Ethiopia ET: External Debt: COM: Commitments: International Development Association (IDA) data is updated yearly, averaging 115.370 USD mn from Dec 1970 (Median) to 2016, with 47 observations. The data reached an all-time high of 2.030 USD bn in 2014 and a record low of 0.000 USD mn in 1999. Ethiopia ET: External Debt: COM: Commitments: International Development Association (IDA) 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: External Debt: Commitments and Currency Composition. Commitments (IDA) are the sum of new commitments on public and publicly guaranteed loans from the International Development Association (IDA). Data are in current U.S. dollars.; ; World Bank, International Debt Statistics.; Sum;

Ethiopia ET: External Debt: NFL: Net Financial Flows: International Development Association (IDA) data was reported at 932.771 USD mn in 2017. This records a decrease from the previous number of 1.177 USD bn for 2016. Ethiopia ET: External Debt: NFL: Net Financial Flows: International Development Association (IDA) data is updated yearly, averaging 76.951 USD mn from Dec 1970 (Median) to 2017, with 48 observations. The data reached an all-time high of 1.177 USD bn in 2016 and a record low of 2.821 USD mn in 1970. Ethiopia ET: External Debt: NFL: Net Financial Flows: International Development Association (IDA) 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: External Debt: Net Flows and Net Transfers. Net financial flows received by the borrower during the year are disbursements of loans and credits less repayments of principal. IDA is the International Development Association, the concessional loan window of the World Bank Group. Data are in current U.S. dollars.; ; World Bank, International Debt Statistics.; Sum;

Employment to population ratio, 15+, total (%) (modeled ILO estimate) in Ethiopia was reported at 65.38 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Ethiopia - Employment to population ratio, 15+, total - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

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

Abstract

Young Lives: An International Study of Childhood Poverty is a collaborative project investigating the changing nature of childhood poverty in selected developing countries. The UK’s Department for International Development (DFID) is funding the first three-year phase of the project.

Young Lives involves collaboration between Non Governmental Organisations (NGOs) and the academic sector. In the UK, the project is being run by Save the Children-UK together with an academic consortium that comprises the University of Reading, London School of Hygiene and Tropical Medicine, South Bank University, the Institute of Development Studies at Sussex University and the South African Medical Research Council.

The study is being conducted in Ethiopia, India (in Andhra Pradesh), Peru and Vietnam. These countries were selected because they reflect a range of cultural, geographical and social contexts and experience differing issues facing the developing world; high debt burden, emergence from conflict, and vulnerability to environmental conditions such as drought and flood.

Objectives of the study The Young Lives study has three broad objectives: • producing good quality panel data about the changing nature of the lives of children in poverty. • trace linkages between key policy changes and child poverty • informing and responding to the needs of policy makers, planners and other stakeholders There will also be a strong education and media element, both in the countries where the project takes place, and in the UK.

The study takes a broad approach to child poverty, exploring not only household economic indicators such as assets and wealth, but also child centred poverty measures such as the child’s physical and mental health, growth, development and education. These child centred measures are age specific so the information collected by the study will change as the children get older.

Further information about the survey, including publications, can be downloaded from the Young Lives website.

Geographic coverage

Young Lives is an international study of childhood poverty, involving 12,000 children in 4 countries. - Ethiopia (20 communities in Addis Ababa, Amhara, Oromia, and Southern National, Nationalities and People's Regions) - India (20 sites across Andhra Pradesh and Telangana) - Peru (74 communities across Peru) - Vietnam (20 communities in the communes of Lao Cai in the north-west, Hung Yen province in the Red River Delta, the city of Danang on the coast, Phu Yen province from the South Central Coast and Ben Tre province on the Mekong River Delta)

Analysis unit

Individuals; Families/households

Universe

Location of Units of Observation: Cross-national; Subnational Population: Children aged approximately 1 year old and their households, and children aged 8 years old and their households, in Ethiopia, India (Andhra Pradesh), Peru and Vietnam, in 2002. See documentation for details of the exact regions covered in each country.

Kind of data

Sample survey data [ssd]

Sampling procedure

Purposive selection/case studies

A key need for the study's objectives was to obtain data at different levels - the children, their households, the community in which they resided, as well as at regional and national levels. This need thus determined that children should be selected in geographic clusters rather than randomly selected across the country. There was, however, a much more important reason for recruiting children in clusters - the sites are also intended to provide suitable settings for a range of complementary thematic studies. For example, one or a few sites may be used for a qualitative study designed to achieve a deeper level of understanding of some social issues, either because they are important in that particular place, or because the sites are appropriate locales to investigate a more general concern. The quantitative panel study is seen as the foundation upon which a coherent and interesting range of linked studies can be set up.

Thus the design was decided, in each country, comprising 20 geographic clusters with 100 children sampled in each cluster.

For details on sample design, see the methodological document which is available in the documentation.

Sampling deviation

Ethiopia: 1,999 (1-year-olds), 1,000 (8-year-olds); India: 2,011 (1-year-olds), 1,008 (8-year-olds); Peru: 2,052 (1-year-olds), 714 (8-year-olds); Vietnam: 2,000 (1-year-olds), 1,000 (8-year-olds).

Mode of data collection

Face-to-face interview

Research instrument

Every questionnaire used in the study consists of a 'core' element and a country-specific element, which focuses on issues important for that country.

The core element of the questionnaires consists of the following sections: Core 6-17.9 month old household questionnaire • Section 1: Locating information • Section 2: Household composition • Section 3: Pregnancy, delivery and breastfeeding • Section 4: Child care • Section 5: Child health • Section 6: Caregiver background • Section 7: Livelihoods and time allocation • Section 8: Economic changes • Section 9: Socio-economic status • Section 10: Caregiver psychosocial well-being • Section 11: Social capital • Section 12: Tracking details • Section 13: Anthropometry

Core 7.5-8.5 year old household questionnaire • Section 1: Locating information • Section 2: Household composition • Section 3: Births and deaths • Section 4: Child school • Section 5: Child health • Section 6: Caregiver background • Section 7: Livelihoods and time allocation • Section 8: Economic changes • Section 9: Socio-economic status • Section 10: Child mental health • Section 11: Social capital • Section 12: Tracking details • Section 13: Anthropometry

The communnity questionnaire consists of the following sections: • Section 1: Physical environment • Section 2: Social environment • Section 3: Infrastructure and access • Section 4: Economy • Section 5: Health and education

Ethiopia ET: International Development Association: Grants data was reported at 156.219 USD mn in 2017. This records an increase from the previous number of 0.000 USD mn for 2016. Ethiopia ET: International Development Association: Grants data is updated yearly, averaging 0.000 USD mn from Dec 1970 (Median) to 2017, with 48 observations. The data reached an all-time high of 488.368 USD mn in 2009 and a record low of 0.000 USD mn in 2016. Ethiopia ET: International Development Association: Grants 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: Defense and Official Development Assistance. IDA grants are net disbursements of grants from the International Development Association (IDA). Data are in current U.S. dollars. Regional allocations are included in aggregate data.; ; World Bank, International Debt Statistics.; Sum;

Ethiopia ET: Net Official Development Assistance and Official Aid Received: Current Price data was reported at 4.074 USD bn in 2016. This records an increase from the previous number of 3.234 USD bn for 2015. Ethiopia ET: Net Official Development Assistance and Official Aid Received: Current Price data is updated yearly, averaging 643.290 USD mn from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 4.074 USD bn in 2016 and a record low of 15.350 USD mn in 1960. Ethiopia ET: Net Official Development Assistance and Official Aid Received: Current Price 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: Defense and Official Development Assistance. Net official development assistance (ODA) consists of disbursements of loans made on concessional terms (net of repayments of principal) and grants by official agencies of the members of the Development Assistance Committee (DAC), by multilateral institutions, and by non-DAC countries to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. It includes loans with a grant element of at least 25 percent (calculated at a rate of discount of 10 percent). Net official aid refers to aid flows (net of repayments) from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. Data are in current U.S. dollars.; ; Development Assistance Committee of the Organisation for Economic Co-operation and Development, Geographical Distribution of Financial Flows to Developing Countries, Development Co-operation Report, and International Development Statistics database. Data are available online at: www.oecd.org/dac/stats/idsonline.; Sum;

Ethiopia ET: External Debt: Present Value: % of Exports of Goods, Services and Primary Income data was reported at 292.088 % in 2016. Ethiopia ET: External Debt: Present Value: % of Exports of Goods, Services and Primary Income data is updated yearly, averaging 292.088 % from Dec 2016 (Median) to 2016, with 1 observations. Ethiopia ET: External Debt: Present Value: % of Exports of Goods, Services and Primary 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: External Debt: Debt Outstanding, Debt Ratio and Debt Service. Present value of debt is the sum of short-term external debt plus the discounted sum of total debt service payments due on public, publicly guaranteed, and private nonguaranteed long-term external debt over the life of existing loans. The exports denominator is a three-year average.; ; World Bank, Global Development Finance.; ;

Ethiopia ET: GNI: PPP data was reported at 198,104.479 Intl $ mn in 2017. This records an increase from the previous number of 177,024.389 Intl $ mn for 2016. Ethiopia ET: GNI: PPP data is updated yearly, averaging 40,025.985 Intl $ mn from Dec 1990 (Median) to 2017, with 28 observations. The data reached an all-time high of 198,104.479 Intl $ mn in 2017 and a record low of 18,050.926 Intl $ mn in 1992. Ethiopia ET: GNI: 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.WDI: Gross Domestic Product: Purchasing Power Parity. PPP GNI (formerly PPP GNP) is gross national income (GNI) converted to international dollars using purchasing power parity rates. An international dollar has the same purchasing power over GNI as a U.S. dollar has in the United States. Gross national income is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. Data are in current international dollars. For most economies PPP figures are extrapolated from the 2011 International Comparison Program (ICP) benchmark estimates or imputed using a statistical model based on the 2011 ICP. For 47 high- and upper middle-income economies conversion factors are provided by Eurostat and the Organisation for Economic Co-operation and Development (OECD).; ; World Bank, International Comparison Program database.; Gap-filled total;