Nigeria NG: Exports: Low- and Middle-Income Economies: % of Total Goods Exports: Middle East & North Africa data was reported at 0.484 % in 2016. This records an increase from the previous number of 0.341 % for 2015. Nigeria NG: Exports: Low- and Middle-Income Economies: % of Total Goods Exports: Middle East & North Africa data is updated yearly, averaging 0.065 % from Dec 1962 (Median) to 2016, with 54 observations. The data reached an all-time high of 1.316 % in 1962 and a record low of 0.001 % in 1977. Nigeria NG: Exports: Low- and Middle-Income Economies: % of Total Goods Exports: Middle East & North Africa data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Nigeria – Table NG.World Bank.WDI: Exports. Merchandise exports to low- and middle-income economies in Middle East and North Africa are the sum of merchandise exports from the reporting economy to low- and middle-income economies in the Middle East and North Africa region according to World Bank classification of economies. Data are as a percentage of total merchandise exports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.; ; World Bank staff estimates based data from International Monetary Fund's Direction of Trade database.; Weighted average;

Nigeria NG: Income Share Held by Lowest 20% data was reported at 5.400 % in 2009. This records a decrease from the previous number of 5.700 % for 2003. Nigeria NG: Income Share Held by Lowest 20% data is updated yearly, averaging 5.400 % from Dec 1985 (Median) to 2009, with 5 observations. The data reached an all-time high of 6.000 % in 1985 and a record low of 3.700 % in 1996. Nigeria NG: Income Share Held by Lowest 20% data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Nigeria – Table NG.World Bank.WDI: Poverty. Percentage share of income or consumption is the share that accrues to subgroups of population indicated by deciles or quintiles. Percentage shares by quintile may not sum to 100 because of rounding.; ; 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.

The average for 2023 based on 49 countries was 68.91 years. The highest value was in Sri Lanka: 77.48 years and the lowest value was in Nigeria: 54.46 years. The indicator is available from 1960 to 2023. Below is a chart for all countries where data are available.

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

Nigeria NG: Exports: Low- and Middle-Income Economies: % of Total Goods Exports: Sub-Saharan Africa data was reported at 12.239 % in 2016. This records a decrease from the previous number of 12.485 % for 2015. Nigeria NG: Exports: Low- and Middle-Income Economies: % of Total Goods Exports: Sub-Saharan Africa data is updated yearly, averaging 6.409 % from Dec 1960 (Median) to 2016, with 56 observations. The data reached an all-time high of 12.485 % in 2015 and a record low of 0.693 % in 1960. Nigeria NG: Exports: Low- and Middle-Income Economies: % of Total Goods Exports: Sub-Saharan Africa data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Nigeria – Table NG.World Bank: Exports. Merchandise exports to low- and middle-income economies in Sub-Saharan Africa are the sum of merchandise exports from the reporting economy to low- and middle-income economies in the Sub-Saharan Africa region according to World Bank classification of economies. Data are as a percentage of total merchandise exports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.; ; World Bank staff estimates based data from International Monetary Fund's Direction of Trade database.; Weighted average;

Merchandise imports from low- and middle-income economies in Sub-Saharan Africa (% of total merchandise imports) in Nigeria was reported at 1.8818 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Nigeria - Merchandise imports from developing economies in Sub-Saharan Africa (% of total merchandise imports) - actual values, historical data, forecasts and projections were sourced from the World Bank on October of 2025.

Caffeine Citrate data across five low- and middle-income countries

https://doi.org/10.5061/dryad.ksn02v7c4

This dataset is responses from stakeholders and providers describing the demand, policies, and supply factors affecting the availability and clinical use of Caffeine Citrate (CC) across Nigeria, Ethiopia, South Africa, Kenya and five States in India (where permission was given to share with the public). The dataset covers responses on the presence or absence of caffeine citrate in the Essential Medicines List (EML) and treatment guidelines, apnea of prematurity treatment protocols and practices, different brands of drugs registered in countries, procurement information and barriers limiting access. The data gives insights into status of caffeine, the treatment practices and barriers to access in each country. Apnea of prematurity (AOP) is a common complication among preterm infants (< 37 weeks' gestation), globally. However, access to ...

Nigeria NG: Imports: Low- and Middle-Income Economies: % of Total Goods Imports: Middle East & North Africa data was reported at 0.600 % in 2016. This records an increase from the previous number of 0.471 % for 2015. Nigeria NG: Imports: Low- and Middle-Income Economies: % of Total Goods Imports: Middle East & North Africa data is updated yearly, averaging 0.324 % from Dec 1962 (Median) to 2016, with 54 observations. The data reached an all-time high of 1.740 % in 1969 and a record low of 0.169 % in 1983. Nigeria NG: Imports: Low- and Middle-Income Economies: % of Total Goods Imports: Middle East & North Africa data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Nigeria – Table NG.World Bank: Imports. Merchandise imports from low- and middle-income economies in Middle East and North Africa are the sum of merchandise imports by the reporting economy from low- and middle-income economies in the Middle East and North Africa region according to the World Bank classification of economies. Data are expressed as a percentage of total merchandise imports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.; ; World Bank staff estimates based data from International Monetary Fund's Direction of Trade database.; Weighted average;

The average for 2021 based on 44 countries was 4.56 percent. The highest value was in Kiribati: 14.2 percent and the lowest value was in Nigeria: 0.38 percent. The indicator is available from 1970 to 2023. Below is a chart for all countries where data are available.

Actual value and historical data chart for Nigeria Merchandise Imports From Developing Economies In Middle East North Africa Percent Of Total Merchandise Imports

Merchandise imports from low- and middle-income economies in Latin America & the Caribbean (% of total merchandise imports) in Nigeria was reported at 2.5848 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Nigeria - Merchandise imports from developing economies in Latin America & the Caribbean (% of total merchandise imports) - actual values, historical data, forecasts and projections were sourced from the World Bank on November of 2025.

As of April 2025, South Africa's GDP was estimated at over 410 billion U.S. dollars, the highest in Africa. Egypt followed, with a GDP worth around 347 billion U.S. dollars, and ranked as the second-highest on the continent. Algeria ranked third, with nearly 269 billion U.S. dollars. These African economies are among some of the fastest-growing economies worldwide. Dependency on oil For some African countries, the oil industry represents an enormous source of income. In Nigeria, oil generates over five percent of the country’s GDP in the third quarter of 2023. However, economies such as the Libyan, Algerian, or Angolan are even much more dependent on the oil sector. In Libya, for instance, oil rents account for over 40 percent of the GDP. Indeed, Libya is one of the economies most dependent on oil worldwide. Similarly, oil represents for some of Africa’s largest economies a substantial source of export value. The giants do not make the ranking Most of Africa’s largest economies do not appear in the leading ten African countries for GDP per capita. The GDP per capita is calculated by dividing a country’s GDP by its population. Therefore, a populated country with a low total GDP will have a low GDP per capita, while a small rich nation has a high GDP per capita. For instance, South Africa has Africa’s highest GDP, but also counts the sixth-largest population, so wealth has to be divided into its big population. The GDP per capita also indicates how a country’s wealth reaches each of its citizens. In Africa, Seychelles has the greatest GDP per capita.

Nigeria NG: Exports: Low- and Middle-Income Economies: % of Total Goods Exports: Latin America & The Caribbean data was reported at 4.444 % in 2016. This records a decrease from the previous number of 9.196 % for 2015. Nigeria NG: Exports: Low- and Middle-Income Economies: % of Total Goods Exports: Latin America & The Caribbean data is updated yearly, averaging 2.278 % from Dec 1962 (Median) to 2016, with 54 observations. The data reached an all-time high of 11.515 % in 2004 and a record low of 0.001 % in 1974. Nigeria NG: Exports: Low- and Middle-Income Economies: % of Total Goods Exports: Latin America & The Caribbean data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Nigeria – Table NG.World Bank.WDI: Exports. Merchandise exports to low- and middle-income economies in Latin America and the Caribbean are the sum of merchandise exports from the reporting economy to low- and middle-income economies in the Latin America and the Caribbean region according to World Bank classification of economies. Data are as a percentage of total merchandise exports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.; ; World Bank staff estimates based data from International Monetary Fund's Direction of Trade database.; Weighted average;

Actual value and historical data chart for Nigeria Merchandise Imports From Developing Economies In South Asia Percent Of Total Merchandise Imports

Actual value and historical data chart for Nigeria Merchandise Imports From Developing Economies Within Region Percent Of Total Merchandise Imports

This dataset contains national-level data on financial, human, and institutional resources for agricultural research and development (R&D). Accurate, reliable, and internationally comparable quantitative information on investments, human capacity, and the institutional structure of agricultural R&D is fundamental to understanding the contribution of research to agricultural growth in low- and middle-income countries. Providing such data is the mission of IFPRI’s Agricultural Science and Technology Indicators (ASTI) program. Through its large network of national, regional, and international partners, ASTI collects and analyzes data from government, higher education, nonprofit, and (where possible) private-sector agencies involved in agricultural R&D. The program conducts ongoing analysis of these datasets; disseminates the results of this analysis to promote advocacy and support policymaking; and builds national and regional capacity for data collection and analysis.This data was collected in 2014 and made it to Dataverse in 2015. Data File: http://www.asti.cgiar.org/nigeria

Abstract

The Global Findex 2025 reveals how mobile technology is equipping more adults around the world to own and use financial accounts to save formally, access credit, make and receive digital payments, and pursue opportunities. Including the inaugural Global Findex Digital Connectivity Tracker, this fifth edition of Global Findex presents new insights on the interactions among mobile phone ownership, internet use, and financial inclusion.

The Global Findex is the world’s most comprehensive database on digital and financial inclusion. It is also the only global source of comparable demand-side data, allowing cross-country analysis of how adults access and use mobile phones, the internet, and financial accounts to reach digital information and resources, save, borrow, make payments, and manage their financial health. Data for the Global Findex 2025 were collected from nationally representative surveys of about 145,000 adults in 141 economies. The latest edition follows the 2011, 2014, 2017, and 2021 editions and includes new series measuring mobile phone ownership and internet use, digital safety, and frequency of transactions using financial services.

The Global Findex 2025 is an indispensable resource for policy makers in the fields of digital connectivity and financial inclusion, as well as for practitioners, researchers, and development professionals.

Geographic coverage

National Coverage

Analysis unit

Individual

Kind of data

Observation data/ratings [obs]

Sampling procedure

In most low- and middle-income economies, Global Findex data were collected through face-to-face interviews. In these economies, an area frame design was used for interviewing. In most high-income economies, telephone surveys were used. In 2024, face-to-face interviews were again conducted in 22 economies after phone-based surveys had been employed in 2021 as a result of mobility restrictions related to COVID-19. In addition, an abridged form of the questionnaire was administered by phone to survey participants in Algeria, China, the Islamic Republic of Iran, Libya, Mauritius, and Ukraine because of economy-specific restrictions. In just one economy, Singapore, did the interviewing mode change from face to face in 2021 to phone based in 2024.

In economies in which face-to-face surveys were conducted, the first stage of sampling was the identification of primary sampling units. These units were then stratified by population size, geography, or both and clustered through one or more stages of sampling. Where population information was available, sample selection was based on probabilities proportional to population size; otherwise, simple random sampling was used. Random route procedures were used to select sampled households. Unless an outright refusal occurred, interviewers made up to three attempts to survey each sampled household. To increase the probability of contact and completion, attempts were made at different times of the day and, where possible, on different days. If an interview could not be completed at a household that was initially part of the sample, a simple substitution method was used to select a replacement household for inclusion.

Respondents were randomly selected within sampled households. Each eligible household member (that is, all those ages 15 or older) was listed, and a handheld survey device randomly selected the household member to be interviewed. For paper surveys, the Kish grid method was used to select the respondent. In economies in which cultural restrictions dictated gender matching, respondents were randomly selected from among all eligible adults of the interviewer’s gender.

In economies in which Global Findex surveys have traditionally been phone based, respondent selection followed the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies in which mobile phone and landline penetration is high, a dual sampling frame was used.

The same procedure for respondent selection was applied to economies in which phone-based interviews were being conducted for the first time. Dual-frame (landline and mobile phone) random digit dialing was used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digit dialing was used in economies with limited or no landline presence (less than 20 percent). For landline respondents in economies in which mobile phone or landline penetration is 80 percent or higher, respondents were selected randomly by using either the next-birthday method or the household enumeration method, which involves listing all eligible household members and randomly selecting one to participate. For mobile phone respondents in these economies or in economies in which mobile phone or landline penetration is less than 80 percent, no further selection was performed. At least three attempts were made to reach the randomly selected person in each household, spread over different days and times of day.

Research instrument

The English version of the questionnaire is provided for download.

Sampling error estimates

Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in: Klapper, Leora, Dorothe Singer, Laura Starita, and Alexandra Norris. 2025. The Global Findex Database 2025: Connectivity and Financial Inclusion in the Digital Economy. Washington, DC: World Bank. https://doi.org/10.1596/978-1-4648-2204-9.

This dataset measures food availability and access for 76 low- and middle-income countries. The dataset includes annual country-level data on area, yield, production, nonfood use, trade, and consumption for grains and root and tuber crops (combined as R&T in the documentation tables), food aid, total value of imports and exports, gross domestic product, and population compiled from a variety of sources. This dataset is the basis for the International Food Security Assessment 2015-2025 released in June 2015. This annual ERS report projects food availability and access for 76 low- and middle-income countries over a 10-year period. Countries (Spatial Description, continued): Democratic Republic of the Congo, Ecuador, Egypt, El Salvador, Eritrea, Ethiopia, Gambia, Georgia, Ghana, Guatemala, Guinea, Guinea-Bissau, Haiti, Honduras, India, Indonesia, Jamaica, Kenya, Kyrgyzstan, Laos, Lesotho, Liberia, Madagascar, Malawi, Mali, Mauritania, Moldova, Mongolia, Morocco, Mozambique, Namibia, Nepal, Nicaragua, Niger, Nigeria, North Korea, Pakistan, Peru, Philippines, Rwanda, Senegal, Sierra Leone, Somalia, Sri Lanka, Sudan, Swaziland, Tajikistan, Tanzania, Togo, Tunisia, Turkmenistan, Uganda, Uzbekistan, Vietnam, Yemen, Zambia, and Zimbabwe. Resources in this dataset:Resource Title: CSV File for all years and all countries. File Name: gfa25.csvResource Title: International Food Security country data. File Name: GrainDemandProduction.xlsxResource Description: Excel files of individual country data. Please note that these files provide the data in a different layout from the CSV file. This version of the data files was updated 9-2-2021

More up-to-date files may be found at: https://www.ers.usda.gov/data-products/international-food-security.aspx

Nigeria NG: Exports: Low- and Middle-Income Economies: % of Total Goods Exports: Outside Region data was reported at 47.404 % in 2016. This records a decrease from the previous number of 48.782 % for 2015. Nigeria NG: Exports: Low- and Middle-Income Economies: % of Total Goods Exports: Outside Region data is updated yearly, averaging 3.783 % from Dec 1960 (Median) to 2016, with 56 observations. The data reached an all-time high of 48.782 % in 2015 and a record low of 0.078 % in 1974. Nigeria NG: Exports: Low- and Middle-Income Economies: % of Total Goods Exports: Outside Region data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Nigeria – Table NG.World Bank.WDI: Exports. Merchandise exports to low- and middle-income economies outside region are the sum of merchandise exports from the reporting economy to other low- and middle-income economies in other World Bank regions according to the World Bank classification of economies. Data are expressed as a percentage of total merchandise exports by the economy. Data are computed only if at least half of the economies in the partner country group had non-missing data.; ; World Bank staff estimates based data from International Monetary Fund's Direction of Trade database.; Weighted average;

IntroductionThe use of tobacco among adolescents in low- and middle-income countries is a public health issue of concern. The tobacco industry’s aggressive marketing tactics target young people in African countries, leading to early initiation of tobacco use. While existing evidence focuses on 13-15-year-olds, data from Sub-Saharan Africa indicates that smoking initiation ranges from as young as 7 years old to around 16 years old. The lack of data on adolescent tobacco use in African countries limits policymakers’ ability to implement evidence-based tobacco control policies. This study aims to address the critical lack of quality and timely primary data on adolescent tobacco use, thereby enhancing the country’s capacity to target interventions effectively, engage local governments, and attract global attention and funding for adolescent health initiatives.MethodsWe will conduct a cross-sectional nationwide survey among adolescents aged 10–17 years in urban and rural areas of the Democratic Republic of Congo (DRC), Kenya and Nigeria. This household-based survey will utilize a multi-stage stratified sample design to ensure representation across diverse geographic and demographic characteristics. The sample size calculations resulted in nationally representative samples of 6,701 adolescents in Kenya, 4,803 adolescents in the DRC, and 7,948 adolescents in Nigeria.DiscussionThrough this initiative, we aim to catalyze action at national and international levels to combat the tobacco epidemic among adolescents in Sub Saharan Africa. The findings from the study will empower stakeholders to advocate effective tobacco control measures, promote adolescent health, and safeguard future generations from the harmful effects of tobacco use.