78 datasets found
  1. Nigeria NG: Income Share Held by Highest 20%

    • ceicdata.com
    Updated Apr 18, 2012
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    CEICdata.com (2012). Nigeria NG: Income Share Held by Highest 20% [Dataset]. https://www.ceicdata.com/en/nigeria/poverty/ng-income-share-held-by-highest-20
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    Dataset updated
    Apr 18, 2012
    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 1985 - Dec 1, 2009
    Area covered
    Nigeria
    Description

    Nigeria NG: Income Share Held by Highest 20% data was reported at 49.000 % in 2009. This records an increase from the previous number of 46.000 % for 2003. Nigeria NG: Income Share Held by Highest 20% data is updated yearly, averaging 49.000 % from Dec 1985 (Median) to 2009, with 5 observations. The data reached an all-time high of 56.500 % in 1996 and a record low of 45.000 % in 1985. Nigeria NG: Income Share Held by Highest 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.

  2. Income per capita in Nigeria 2013-2023

    • statista.com
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    Statista, Income per capita in Nigeria 2013-2023 [Dataset]. https://www.statista.com/statistics/1291432/gross-national-income-per-capita-in-nigeria/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Nigeria
    Description

    The national gross income per capita in Nigeria decreased to ***** U.S. dollars compared to the previous year. This marks the lowest national gross income during the observed period. Gross national income (GNI) per capita is the total amount of money received by a country (regardless of whether it originates in the country or abroad) divided by the midyear population. The World Bank uses a conversion system known as the Atlas method, which uses a price adjusted, three year moving average, which smooths out exchange rate fluctuations.Find more statistics on other topics about Nigeria with key insights such as gross national income (GNI), value of personal remittances paid, and personal remittances received.

  3. Nigeria NG: Income Share Held by Lowest 20%

    • ceicdata.com
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    CEICdata.com, Nigeria NG: Income Share Held by Lowest 20% [Dataset]. https://www.ceicdata.com/en/nigeria/poverty/ng-income-share-held-by-lowest-20
    Explore at:
    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 1985 - Dec 1, 2009
    Area covered
    Nigeria
    Description

    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.

  4. T

    Nigeria Disposable Personal Income

    • tradingeconomics.com
    • pt.tradingeconomics.com
    • +12more
    csv, excel, json, xml
    Updated May 15, 2025
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    TRADING ECONOMICS (2025). Nigeria Disposable Personal Income [Dataset]. https://tradingeconomics.com/nigeria/disposable-personal-income
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    xml, excel, csv, jsonAvailable download formats
    Dataset updated
    May 15, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Mar 31, 2007 - Jun 30, 2024
    Area covered
    Nigeria
    Description

    Disposable Personal Income in Nigeria increased to 21437390.24 NGN Million in the second quarter of 2024 from 20532203.99 NGN Million in the first quarter of 2024. This dataset provides - Nigeria Disposable Personal Income - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  5. Middle-class population in African cities 2018

    • statista.com
    Updated Apr 28, 2023
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    Statista (2023). Middle-class population in African cities 2018 [Dataset]. https://www.statista.com/statistics/1254370/number-of-middle-class-people-in-selected-cities-in-africa/
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    Dataset updated
    Apr 28, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2018
    Area covered
    Africa
    Description

    The metropolitan area of Lagos in Nigeria counted over 14 million middle-class people as of 2018. This was the highest number in Africa. Addis Ababa in Ethiopia followed with 2.7 million individuals belonging to the middle class. The middle-class population included people who had a disposable income of over 75 percent of their salary, were employed, had a business activity, or were in education, and had at least a secondary school degree.

  6. Nigeria NG: Income Share Held by Lowest 10%

    • ceicdata.com
    Updated Dec 15, 2020
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    CEICdata.com (2020). Nigeria NG: Income Share Held by Lowest 10% [Dataset]. https://www.ceicdata.com/en/nigeria/poverty/ng-income-share-held-by-lowest-10
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    Dataset updated
    Dec 15, 2020
    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 1985 - Dec 1, 2009
    Area covered
    Nigeria
    Description

    Nigeria NG: Income Share Held by Lowest 10% data was reported at 2.000 % in 2009. This records a decrease from the previous number of 2.100 % for 2003. Nigeria NG: Income Share Held by Lowest 10% data is updated yearly, averaging 2.000 % from Dec 1985 (Median) to 2009, with 5 observations. The data reached an all-time high of 2.500 % in 1985 and a record low of 1.300 % in 1996. Nigeria NG: 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 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.; ; 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.

  7. f

    Living Standards Survey, 2018-2019 - Nigeria

    • microdata.fao.org
    Updated Nov 8, 2022
    + more versions
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    National Bureau of Statistics (NBS) (2022). Living Standards Survey, 2018-2019 - Nigeria [Dataset]. https://microdata.fao.org/index.php/catalog/1761
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    Dataset updated
    Nov 8, 2022
    Dataset provided by
    National Bureau of Statistics, Nigeria
    Authors
    National Bureau of Statistics (NBS)
    Time period covered
    2018 - 2019
    Area covered
    Nigeria
    Description

    Abstract

    The main objectives of the 2018/19 NLSS are: i) to provide critical information for production of a wide range of socio-economic and demographic indicators, including for benchmarking and monitoring of SDGs; ii) to monitor progress in population's welfare; iii) to provide statistical evidence and measure the impact on households of current and anticipated government policies. In addition, the 2018/19 NLSS could be utilized to improve other non-survey statistical information, e.g. to determine and calibrate the contribution of final consumption expenditures of households to GDP; to update the weights and determine the basket for the national Consumer Price Index (CPI); to improve the methodology and dissemination of micro-economic and welfare statistics in Nigeria.

    The 2018/19 NLSS collected a comprehensive and diverse set of socio-economic and demographic data pertaining to the basic needs and conditions under which households live on a day to day basis. The 2018/19 NLSS questionnaire includes wide-ranging modules, covering demographic indicators, education, health, labour, expenditures on food and non-food goods, non-farm enterprises, household assets and durables, access to safety nets, housing conditions, economic shocks, exposure to crime and farm production indicators.

    Geographic coverage

    National coverage

    Analysis unit

    Households

    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

    SAMPLING PROCEDURE The 2018/19 NLSS sample is designed to provide representative estimates for the 36 states and the Federal Capital Territory (FCT), Abuja. By extension. The sample is also representative at the national and zonal levels. Although the sample is not explicitly stratified by urban and rural areas, it is possible to obtain urban and rural estimates from the NLSS data at the national level. At all stages, the relative proportion of urban and rural EAs as has been maintained. Before designing the sample for the 2018/19 NLSS, the results from the 2009/10 HNLSS were analysed to extract the sampling properties (variance, design effect, etc.) and estimate the required sample size to reach a desired precision for poverty estimates in the 2018/19 NLSS.

    EA SELECTION: The sampling frame for the 2018/19 NLSS was based on the national master sample developed by the NBS, referred to as the NISH2 (Nigeria Integrated Survey of Households 2). This master sample was based on the enumeration areas (EAs) defined for the 2006 Nigeria Census Housing and Population conducted by National Population Commission (NPopC). The NISH2 was developed by the NBS to use as a frame for surveys with state-level domains. NISH2 EAs were drawn from another master sample that NBS developed for surveys with LGA-level domains (referred to as the “LGA master sample”). The NISH2 contains 200 EAs per state composed of 20 replicates of 10 sample EAs for each state, selected systematically from the full LGA master sample. Since the 2018/19 NLSS required domains at the state-level, the NISH2 served as the sampling frame for the survey. Since the NISH2 is composed of state-level replicates of 10 sample EAs, a total of 6 replicates were selected from the NISH2 for each state to provide a total sample of 60 EAs per state. The 6 replicates selected for the 2018/19 NLSS in each state were selected using random systematic sampling. This sampling procedure provides a similar distribution of the sample EAs within each state as if one systematic sample of 60 EAs had been selected directly from the census frame of EAs.

    A fresh listing of households was conducted in the EAs selected for the 2018/19 NLSS. Throughout the course of the listing, 139 of the selected EAs (or about 6%) were not able to be listed by the field teams. The primary reason the teams were not able to conduct the listing in these EAs was due to security issues in the country. The fieldwork period of the 2018/19 NLSS saw events related to the insurgency in the north east of the country, clashes between farmers and herdsman, and roving groups of bandits. These events made it impossible for the interviewers to visit the EAs in the villages and areas affected by these conflict events. In addition to security issues, some EAs had been demolished or abandoned since the 2006 census was conducted. In order to not compromise the sample size and thus the statistical power of the estimates, it was decided to replace these 139 EAs. Additional EAs from the same state and sector were randomly selected from the remaining NISH2 EAs to replace each EA that could not be listed by the field teams. This necessary exclusion of conflict affected areas implies that the sample is representative of areas of Nigeria that were accessible during the 2018/19 NLSS fieldwork period. The sample will not reflect conditions in areas that were undergoing conflict at that time. This compromise was necessary to ensure the safety of interviewers.

    HOUSEHOLD SELECTION: Following the listing, the 10 households to be interviewed were selected from the listed households. These households were selected systemically after sorting by the order in which the households were listed. This systematic sampling helped to ensure that the selected households were well dispersed across the EA and thereby limit the potential for clustering of the selected households within an EA. Occasionally, interviewers would encounter selected households that were not able to be interviewed (e.g. due to migration, refusal, etc.). In order to preserve the sample size and statistical power, households that could not be interviewed were replaced with an additional randomly selected household from the EA. Replacement households had to be requested by the field teams on a case-by-case basis and the replacement household was sent by the CAPI managers from NBS headquarters. Interviewers were required to submit a record for each household that was replaced, and justification given for their replacement. These replaced households are included in the disseminated data. However, replacements were relatively rare with only 2% of sampled households not able to be interviewed and replaced.

    Sampling deviation

    Although a sample was initially drawn for Borno state, the ongoing insurgency in the state presented severe challenges in conducting the survey there. The situation in the state made it impossible for the field teams to reach large areas of the state without compromising their safety. Given this limitation it was clear that a representative sample for Borno was not possible. However, it was decided to proceed with conducting the survey in areas that the teams could access in order to collect some information on the parts of the state that were accessible.

    The limited area that field staff could safely operate in in Borno necessitated an alternative sample selection process from the other states. The EA selection occurred in several stages. Initially, an attempt was made to limit the frame to selected LGAs that were considered accessible. However, after selection of the EAs from the identified LGAs, it was reported by the NBS listing teams that a large share of the selected EAs were not safe for them to visit. Therefore, an alternative approach was adopted that would better ensure the safety of the field team but compromise further the representativeness of the sample. First, the list of 788 EAs in the LGA master sample for Borno were reviewed by NBS staff in Borno and the EAs they deemed accessible were identified. The team identified 359 EAs (46%) that were accessible. These 359 EAs served as the frame for the Borno sample and 60 EAs were randomly selected from this frame. However, throughout the course of the NLSS fieldwork, additional insurgency related events occurred which resulted in 7 of the 60 EAs being inaccessible when they were to be visited. Unlike for the main sample, these EAs were not replaced. Therefore, 53 EAs were ultimately covered from the Borno sample. The listing and household selection process that followed was the same as for the rest of the states.

    Mode of data collection

    Computer Assisted Personal Interview [capi]

    Research instrument

    Two sets of questionnaires – household and community – were used to collect information in the NLSS2018/19. The Household Questionnaire was administered to all households in the sample. The Community Questionnaire was administered to the community to collect information on the socio-economic indicators of the enumeration areas where the sample households reside.

    Household Questionnaire: The Household Questionnaire provides information on demographics; education; health; labour; food and non-food expenditure; household nonfarm income-generating activities; food security and shocks; safety nets; housing conditions; assets; information and communication technology; agriculture and land tenure; and other sources of household income.

    Community Questionnaire: The Community Questionnaire solicits information on access to transported and infrastructure; community organizations; resource management; changes in the community; key events; community needs, actions and achievements; and local retail price information.

    Cleaning operations

    CAPI: The 2018/19 NLSS was conducted using the Survey Solutions Computer Assisted Person Interview (CAPI) platform. The Survey Solutions software was developed and maintained by the Development Economics Data Group (DECDG) at the World Bank. Each interviewer and supervisor was given a tablet which they used to

  8. Gini coefficient in Nigeria 2019, by area

    • statista.com
    • ai-chatbox.pro
    Updated Aug 31, 2022
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    Statista (2022). Gini coefficient in Nigeria 2019, by area [Dataset]. https://www.statista.com/statistics/1121404/gini-coefficient-in-nigeria/
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    Dataset updated
    Aug 31, 2022
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2019
    Area covered
    Nigeria
    Description

    According to governmental data from 2020, the Gini coefficient in Nigeria was 35.1 points as of 2019. The Gini index gives information on the distribution of income in a country. In an ideal situation in which incomes are perfectly distributed, the coefficient is equal to zero.

    The first eight countries with the biggest inequality in income distribution in the world are located in Sub-Saharan Africa, with an index over 50 points.

  9. Monthly living wage for individuals and families in Nigeria 2020

    • statista.com
    • ai-chatbox.pro
    Updated May 20, 2020
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    Statista (2020). Monthly living wage for individuals and families in Nigeria 2020 [Dataset]. https://www.statista.com/statistics/1119087/monthly-living-wage-in-nigeria/
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    Dataset updated
    May 20, 2020
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2020
    Area covered
    Nigeria
    Description

    On average, the monthly cost of living for an individual in Nigeria amounted to ****** Nigerian Naira, which equaled roughly *** U.S. dollars. On the other hand, this figure added up to ******* Naira for a family, about *** U.S. dollars. In 2020, the minimum wage in Nigeria reached ****** Naira.

  10. Nigeria NG: Income Share Held by Third 20%

    • ceicdata.com
    Updated Dec 15, 2020
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    CEICdata.com (2020). Nigeria NG: Income Share Held by Third 20% [Dataset]. https://www.ceicdata.com/en/nigeria/poverty/ng-income-share-held-by-third-20
    Explore at:
    Dataset updated
    Dec 15, 2020
    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 1985 - Dec 1, 2009
    Area covered
    Nigeria
    Description

    Nigeria NG: Income Share Held by Third 20% data was reported at 14.400 % in 2009. This records a decrease from the previous number of 15.400 % for 2003. Nigeria NG: Income Share Held by Third 20% data is updated yearly, averaging 14.400 % from Dec 1985 (Median) to 2009, with 5 observations. The data reached an all-time high of 15.500 % in 1985 and a record low of 12.300 % in 1996. Nigeria NG: Income Share Held by Third 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.

  11. u

    Poverty state in Nigeria

    • researchdata.up.ac.za
    xlsx
    Updated Oct 31, 2023
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    Chioma Amaechi; Adrino Mazenda; Stellah Nambalirwa Lubinga (2023). Poverty state in Nigeria [Dataset]. http://doi.org/10.25403/UPresearchdata.23634333.v1
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    xlsxAvailable download formats
    Dataset updated
    Oct 31, 2023
    Dataset provided by
    University of Pretoria
    Authors
    Chioma Amaechi; Adrino Mazenda; Stellah Nambalirwa Lubinga
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Nigeria
    Description

    This dataset focuses on the social protection policy responses to poverty in Nigeria. It provides comprehensive information on various aspects of living conditions, demographics, and socio-economic factors of 204 respondents from the Bwari, Kuje, and Gwagwalada Area Councils in Abuja, Nigeria. The data was collected and analysed using SPSS, and descriptive statistics were used to explore the variables of interest. The dataset has been extrapolated to Excel for easy accessibility. The dataset includes descriptive results on several key aspects. It covers the education level of the respondents, the distribution of household heads among them, the types of dwellings they live in, the health conditions within their households, access to medical care, accommodation types, and waste distribution. The dataset also provides key variables of insights into the poverty levels and perceptions among the respondents. The "MPI" (Multidimensional Poverty Index) measures multidimensional poverty, while "povertylevel" indicates the poverty level of the respondents. In addition to the key variables, the dataset includes additional rows that highlight different combinations of variables related to living conditions. These combinations include dwelling types, sources of tap water, sanitation facilities, lighting sources, access to radio, television, and telephone, as well as information regarding meal skipping, healthcare access, and employment status. The dataset also includes socio-demographic characteristics that were considered in the study. These characteristics include sex, age, education level, employment income, household head, type of dwelling, waste distribution, and source of energy.

  12. Distribution of gross domestic product (GDP) across economic sectors Nigeria...

    • statista.com
    • ai-chatbox.pro
    Updated Jan 30, 2025
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    Statista (2025). Distribution of gross domestic product (GDP) across economic sectors Nigeria 2023 [Dataset]. https://www.statista.com/statistics/382311/nigeria-gdp-distribution-across-economic-sectors/
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    Dataset updated
    Jan 30, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Nigeria
    Description

    In 2023, agriculture contributed around 22.72 percent to Nigeria’s GDP, 32.58 percent came from industry, and 42.77 percent from the services sector. Economic sectors The most common breakdown of economic activity in a country is looking at three economic sectors: The primary sector, which involves agriculture, forestry, and fishing, the secondary sector, industry, that includes manufacturing, processing, or transforming goods, and finally, the tertiary sector, services, i.e. providing information or services to consumers, such as in IT, tourism, or banking. A country’s contribution to GDP, and thus its own economy, is easily visible when looking at the performance of these three sectors. Soaring services in NigeriaLike in most thriving economies nowadays, the services sector is gaining momentum in Nigeria, because more and more people are moving from the countryside to the cities to find jobs. Nigeria is a mixed economy which focuses mainly on telecommunications, financial services, and technology, a strategy that is likely to pay off in the future and will see its GDP soaring. Nigeria’s reliance on oil is also an important contributor to its economic success; between 2001 and 2010, it was one of the countries with the highest GDP growth worldwide. However, oil prices are also responsible for a GDP growth slump in 2016 and for the first trade deficit in over a decade.

  13. Nigeria NG: Income Share Held by Highest 10%

    • ceicdata.com
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    CEICdata.com, Nigeria NG: Income Share Held by Highest 10% [Dataset]. https://www.ceicdata.com/en/nigeria/poverty/ng-income-share-held-by-highest-10
    Explore at:
    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 1985 - Dec 1, 2009
    Area covered
    Nigeria
    Description

    Nigeria NG: Income Share Held by Highest 10% data was reported at 32.700 % in 2009. This records an increase from the previous number of 29.800 % for 2003. Nigeria NG: Income Share Held by Highest 10% data is updated yearly, averaging 31.400 % from Dec 1985 (Median) to 2009, with 5 observations. The data reached an all-time high of 40.700 % in 1996 and a record low of 28.200 % in 1985. Nigeria NG: 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 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.; ; 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.

  14. T

    Nigeria GDP per capita

    • tradingeconomics.com
    • pl.tradingeconomics.com
    • +13more
    csv, excel, json, xml
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    TRADING ECONOMICS, Nigeria GDP per capita [Dataset]. https://tradingeconomics.com/nigeria/gdp-per-capita
    Explore at:
    json, xml, csv, excelAvailable download formats
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 31, 1960 - Dec 31, 2023
    Area covered
    Nigeria
    Description

    The Gross Domestic Product per capita in Nigeria was last recorded at 2416.36 US dollars in 2023. The GDP per Capita in Nigeria is equivalent to 19 percent of the world's average. This dataset provides the latest reported value for - Nigeria GDP per capita - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  15. w

    General Household Survey, Panel 2023-2024 - Nigeria

    • microdata.worldbank.org
    • microdata.nigerianstat.gov.ng
    • +2more
    Updated Nov 21, 2024
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    National Bureau of Statistics (NBS) (2024). General Household Survey, Panel 2023-2024 - Nigeria [Dataset]. https://microdata.worldbank.org/index.php/catalog/6410
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    Dataset updated
    Nov 21, 2024
    Dataset authored and provided by
    National Bureau of Statistics (NBS)
    Time period covered
    2023 - 2024
    Area covered
    Nigeria
    Description

    Abstract

    The General Household Survey-Panel (GHS-Panel) is implemented in collaboration with the World Bank Living Standards Measurement Study (LSMS) team as part of the Integrated Surveys on Agriculture (ISA) program. The objectives of the GHS-Panel include the development of an innovative model for collecting agricultural data, interinstitutional collaboration, and comprehensive analysis of welfare indicators and socio-economic characteristics. The GHS-Panel is a nationally representative survey of approximately 5,000 households, which are also representative of the six geopolitical zones. The 2023/24 GHS-Panel is the fifth round of the survey with prior rounds conducted in 2010/11, 2012/13, 2015/16 and 2018/19. The GHS-Panel households were visited twice: during post-planting period (July - September 2023) and during post-harvest period (January - March 2024).

    Geographic coverage

    National

    Analysis unit

    • Households • Individuals • Agricultural plots • Communities

    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 original GHS‑Panel sample was fully integrated with the 2010 GHS sample. The GHS sample consisted of 60 Primary Sampling Units (PSUs) or Enumeration Areas (EAs), chosen from each of the 37 states in Nigeria. This resulted in a total of 2,220 EAs nationally. Each EA contributed 10 households to the GHS sample, resulting in a sample size of 22,200 households. Out of these 22,200 households, 5,000 households from 500 EAs were selected for the panel component, and 4,916 households completed their interviews in the first wave.

    After nearly a decade of visiting the same households, a partial refresh of the GHS‑Panel sample was implemented in Wave 4 and maintained for Wave 5. The refresh was conducted to maintain the integrity and representativeness of the sample. The refresh EAs were selected from the same sampling frame as the original GHS‑Panel sample in 2010. A listing of households was conducted in the 360 EAs, and 10 households were randomly selected in each EA, resulting in a total refresh sample of approximately 3,600 households.

    In addition to these 3,600 refresh households, a subsample of the original 5,000 GHS‑Panel households from 2010 were selected to be included in the new sample. This “long panel” sample of 1,590 households was designed to be nationally representative to enable continued longitudinal analysis for the sample going back to 2010. The long panel sample consisted of 159 EAs systematically selected across Nigeria’s six geopolitical zones.

    The combined sample of refresh and long panel EAs in Wave 5 that were eligible for inclusion consisted of 518 EAs based on the EAs selected in Wave 4. The combined sample generally maintains both the national and zonal representativeness of the original GHS‑Panel sample.

    Sampling deviation

    Although 518 EAs were identified for the post-planting visit, conflict events prevented interviewers from visiting eight EAs in the North West zone of the country. The EAs were located in the states of Zamfara, Katsina, Kebbi and Sokoto. Therefore, the final number of EAs visited both post-planting and post-harvest comprised 157 long panel EAs and 354 refresh EAs. The combined sample is also roughly equally distributed across the six geopolitical zones.

    Mode of data collection

    Computer Assisted Personal Interview [capi]

    Research instrument

    The GHS-Panel Wave 5 consisted of three questionnaires for each of the two visits. The Household Questionnaire was administered to all households in the sample. The Agriculture Questionnaire was administered to all households engaged in agricultural activities such as crop farming, livestock rearing, and other agricultural and related activities. The Community Questionnaire was administered to the community to collect information on the socio-economic indicators of the enumeration areas where the sample households reside.

    GHS-Panel Household Questionnaire: The Household Questionnaire provided information on demographics; education; health; labour; childcare; early child development; food and non-food expenditure; household nonfarm enterprises; food security and shocks; safety nets; housing conditions; assets; information and communication technology; economic shocks; and other sources of household income. Household location was geo-referenced in order to be able to later link the GHS-Panel data to other available geographic data sets (forthcoming).

    GHS-Panel Agriculture Questionnaire: The Agriculture Questionnaire solicited information on land ownership and use; farm labour; inputs use; GPS land area measurement and coordinates of household plots; agricultural capital; irrigation; crop harvest and utilization; animal holdings and costs; household fishing activities; and digital farming information. Some information is collected at the crop level to allow for detailed analysis for individual crops.

    GHS-Panel Community Questionnaire: The Community Questionnaire solicited information on access to infrastructure and transportation; community organizations; resource management; changes in the community; key events; community needs, actions, and achievements; social norms; and local retail price information.

    The Household Questionnaire was slightly different for the two visits. Some information was collected only in the post-planting visit, some only in the post-harvest visit, and some in both visits.

    The Agriculture Questionnaire collected different information during each visit, but for the same plots and crops.

    The Community Questionnaire collected prices during both visits, and different community level information during the two visits.

    Cleaning operations

    CAPI: Wave five exercise was conducted using Computer Assisted Person Interview (CAPI) techniques. All the questionnaires (household, agriculture, and community questionnaires) were implemented in both the post-planting and post-harvest visits of Wave 5 using the CAPI software, Survey Solutions. The Survey Solutions software was developed and maintained by the Living Standards Measurement Unit within the Development Economics Data Group (DECDG) at the World Bank. Each enumerator was given a tablet which they used to conduct the interviews. Overall, implementation of survey using Survey Solutions CAPI was highly successful, as it allowed for timely availability of the data from completed interviews.

    DATA COMMUNICATION SYSTEM: The data communication system used in Wave 5 was highly automated. Each field team was given a mobile modem which allowed for internet connectivity and daily synchronization of their tablets. This ensured that head office in Abuja had access to the data in real-time. Once the interview was completed and uploaded to the server, the data was first reviewed by the Data Editors. The data was also downloaded from the server, and Stata dofile was run on the downloaded data to check for additional errors that were not captured by the Survey Solutions application. An excel error file was generated following the running of the Stata dofile on the raw dataset. Information contained in the excel error files were then communicated back to respective field interviewers for their action. This monitoring activity was done on a daily basis throughout the duration of the survey, both in the post-planting and post-harvest.

    DATA CLEANING: The data cleaning process was done in three main stages. The first stage was to ensure proper quality control during the fieldwork. This was achieved in part by incorporating validation and consistency checks into the Survey Solutions application used for the data collection and designed to highlight many of the errors that occurred during the fieldwork.

    The second stage cleaning involved the use of Data Editors and Data Assistants (Headquarters in Survey Solutions). As indicated above, once the interview is completed and uploaded to the server, the Data Editors review completed interview for inconsistencies and extreme values. Depending on the outcome, they can either approve or reject the case. If rejected, the case goes back to the respective interviewer’s tablet upon synchronization. Special care was taken to see that the households included in the data matched with the selected sample and where there were differences, these were properly assessed and documented. The agriculture data were also checked to ensure that the plots identified in the main sections merged with the plot information identified in the other sections. Additional errors observed were compiled into error reports that were regularly sent to the teams. These errors were then corrected based on re-visits to the household on the instruction of the supervisor. The data that had gone through this first stage of cleaning was then approved by the Data Editor. After the Data Editor’s approval of the interview on Survey Solutions server, the Headquarters also reviews and depending on the outcome, can either reject or approve.

    The third stage of cleaning involved a comprehensive review of the final raw data following the first and second stage cleaning. Every variable was examined individually for (1) consistency with other sections and variables, (2) out of range responses, and (3) outliers. However, special care was taken to avoid making strong assumptions when resolving potential errors. Some minor errors remain in the data where the diagnosis and/or solution were unclear to the data cleaning team.

    Response

  16. Nigeria - HungerMap data

    • data.humdata.org
    csv
    Updated Jun 13, 2025
    + more versions
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    WFP - World Food Programme (2025). Nigeria - HungerMap data [Dataset]. https://data.humdata.org/dataset/wfp-hungermap-data-for-nga
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    csv(2283376), csv(958894)Available download formats
    Dataset updated
    Jun 13, 2025
    Dataset provided by
    World Food Programmehttp://da.wfp.org/
    License

    http://www.opendefinition.org/licenses/cc-by-sahttp://www.opendefinition.org/licenses/cc-by-sa

    Area covered
    Nigeria
    Description

    HungerMapLIVE is the World Food Programme (WFP)’s global hunger monitoring system. It combines key metrics from various data sources – such as food security information, weather, population size, conflict, hazards, nutrition information and macro-economic data – to help assess, monitor and predict the magnitude and severity of hunger in near real-time. The resulting analysis is displayed on an interactive map that helps WFP staff, key decision makers and the broader humanitarian community to make more informed and timely decisions relating to food security.

    The platform covers 94 countries, including countries where WFP has operations as well as most lower and lower-middle income countries (as classified by the World Bank).

  17. d

    Data from: A 2006 Social Accounting Matrix for Nigeria: Methodology and...

    • search.dataone.org
    • dataverse.harvard.edu
    Updated Nov 21, 2023
    + more versions
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    Manson Nwafor; Xinshen Diao; Vida Alpuerto (2023). A 2006 Social Accounting Matrix for Nigeria: Methodology and Results [Dataset]. http://doi.org/10.7910/DVN/LHXP97
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    Dataset updated
    Nov 21, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Manson Nwafor; Xinshen Diao; Vida Alpuerto
    Area covered
    Nigeria
    Description

    The 2006 Nigeria SAM is a comprehensive, economy-wide data framework, representing the structure of the Nigerian economy; the links among production activities, income distribution, consumption of goods/services, savings and investment, and foreign trade of the economic agents in year 2006. This 2006 Nigeria SAM is a 61 sector square matrix table with the column and row beginning with activities account, followed by commodities account and thereafter accounts for the economic agent in the Nigerian economy. Each cell in the matrix represents the flow of economic activities in monetary terms from a column account (expenditure or outflow) to a row account (income or inflow). Also, each activity and commodity account begins with letter 'a ' and 'œc' respectively. This 2006 SAM was built for the dynamic CGE (DCGE) model that examined the growth and investment options available in the agricultural sector for reducing poverty in Nigeria, and was an integral part of the Agricultural Policy Support Facilites activities for strengthening evidence-based policymaking in Nigeria. Given the agricultural policy analysis focus of the SAM and DCGE model, 34 sector of the SAM are under agriculture and included key cash and food crops as well as livestock sub-sector. The 2006 Nigeria SAM also includes 12 manufacturing (such as beef, textiles, and wood products); 2 mining sector (including crude petroleum and natural gas); and 13 service sectors (such as building and construction, electricity and water, and hotels and restaurants). While the total number of sector for the SAM is 61, the commodities account is 62 as fertilizer was treated as commodity rather than activity. The 2006 SAM data files comprise two worksheets; one for the SAM data and the other containing legend to the SAM data. The value for each of the cell entries is reported in naira million (2006 prices). The data used for building this SAM were obtained from various sources including but not limited to publications of the National Bureau of Statistics (NBS), the Central Bank of Nigeria (CBN), and the Federal Ministry of Agriculture and Water Resources (FMAWR). Data from an earlier SAM of the country developed by United Nations Development Programme (UNDP), 1995 are also used, and was balanced using the cross entropy estimation method. The SAM was built following the International Food Policy Research Institute (IFPRI) standard format (Lofgren et al. 2001).

  18. M

    Nigeria GDP Per Capita 1960-2025

    • macrotrends.net
    csv
    Updated Apr 30, 2025
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    MACROTRENDS (2025). Nigeria GDP Per Capita 1960-2025 [Dataset]. https://www.macrotrends.net/global-metrics/countries/nga/nigeria/gdp-per-capita
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    csvAvailable download formats
    Dataset updated
    Apr 30, 2025
    Dataset authored and provided by
    MACROTRENDS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 1960 - May 30, 2025
    Area covered
    Nigeria
    Description
    Nigeria GDP per capita for 2023 was $1,621, a 25.04% decline from 2022.
    <ul style='margin-top:20px;'>
    
    <li>Nigeria GDP per capita for 2022 was <strong>$2,163</strong>, a <strong>4.69% increase</strong> from 2021.</li>
    <li>Nigeria GDP per capita for 2021 was <strong>$2,066</strong>, a <strong>0.43% decline</strong> from 2020.</li>
    <li>Nigeria GDP per capita for 2020 was <strong>$2,075</strong>, a <strong>11.11% decline</strong> from 2019.</li>
    </ul>GDP per capita is gross domestic product divided by midyear population. GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in current U.S. dollars.
    
  19. Nigeria NG: Income Share Held by Second 20%

    • ceicdata.com
    Updated May 15, 2018
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    CEICdata.com (2018). Nigeria NG: Income Share Held by Second 20% [Dataset]. https://www.ceicdata.com/en/nigeria/poverty/ng-income-share-held-by-second-20
    Explore at:
    Dataset updated
    May 15, 2018
    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 1985 - Dec 1, 2009
    Area covered
    Nigeria
    Description

    Nigeria NG: Income Share Held by Second 20% data was reported at 9.700 % in 2009. This records a decrease from the previous number of 10.400 % for 2003. Nigeria NG: Income Share Held by Second 20% data is updated yearly, averaging 9.700 % from Dec 1985 (Median) to 2009, with 5 observations. The data reached an all-time high of 10.400 % in 2003 and a record low of 7.700 % in 1996. Nigeria NG: Income Share Held by Second 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.

  20. Distribution of GDP in Nigeria 2023, by sector

    • statista.com
    Updated Sep 30, 2024
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    Statista (2024). Distribution of GDP in Nigeria 2023, by sector [Dataset]. https://www.statista.com/statistics/1207951/gdp-distribution-across-sectors-in-nigeria/
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    Dataset updated
    Sep 30, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Nigeria
    Description

    In the second quarter of 2023, the agricultural sector generated about 21 percent of Nigeria's GDP. Other key activities for the country's economy were manufacturing, trade, mining and quarrying, and telecommunication. Moreover, around seven percent of Nigeria's GDP was covered by the mining and quarrying sector. In particular, the largest contribution was from crude oil and natural gas. Nigeria is one of the key oil-producing countries and largest exporters in the world. Indeed, the country has one of the main oil reserves in the world.

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CEICdata.com (2012). Nigeria NG: Income Share Held by Highest 20% [Dataset]. https://www.ceicdata.com/en/nigeria/poverty/ng-income-share-held-by-highest-20
Organization logo

Nigeria NG: Income Share Held by Highest 20%

Explore at:
Dataset updated
Apr 18, 2012
Dataset provided by
CEIC Data
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Time period covered
Dec 1, 1985 - Dec 1, 2009
Area covered
Nigeria
Description

Nigeria NG: Income Share Held by Highest 20% data was reported at 49.000 % in 2009. This records an increase from the previous number of 46.000 % for 2003. Nigeria NG: Income Share Held by Highest 20% data is updated yearly, averaging 49.000 % from Dec 1985 (Median) to 2009, with 5 observations. The data reached an all-time high of 56.500 % in 1996 and a record low of 45.000 % in 1985. Nigeria NG: Income Share Held by Highest 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.

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