Nigeria GDP per capita for 2023 was $1,597, a 25.37% decline from 2022.

<ul style='margin-top:20px;'>

<li>Nigeria GDP per capita for 2022 was <strong>$2,139</strong>, a <strong>6.05% increase</strong> from 2021.</li>
<li>Nigeria GDP per capita for 2021 was <strong>$2,017</strong>, a <strong>0.12% decline</strong> from 2020.</li>
<li>Nigeria GDP per capita for 2020 was <strong>$2,020</strong>, a <strong>10.84% 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.

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.

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.

Nigeria NG: GNI per Capita: USD: 2015 Price data was reported at 2,519.086 USD in 2015. Nigeria NG: GNI per Capita: USD: 2015 Price data is updated yearly, averaging 2,519.086 USD from Dec 2015 (Median) to 2015, with 1 observations. The data reached an all-time high of 2,519.086 USD in 2015 and a record low of 2,519.086 USD in 2015. Nigeria NG: GNI per Capita: USD: 2015 Price 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: Gross Domestic Product: Real. GNI per capita is gross national income divided by midyear population. GNI (formerly GNP) 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 constant 2015 U.S. dollars.;World Bank national accounts data, and OECD National Accounts data files.;Weighted average;

GDP per capita (constant 2015 US$) in Nigeria was reported at 2416 USD in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Nigeria - GDP per capita (constant 2000 US$) - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.

Nigeria NG: GDP: Real: GNI per Capita data was reported at 362,909.895 NGN in 2016. This records a decrease from the previous number of 376,642.214 NGN for 2015. Nigeria NG: GDP: Real: GNI per Capita data is updated yearly, averaging 199,140.702 NGN from Dec 1981 (Median) to 2016, with 36 observations. The data reached an all-time high of 376,642.214 NGN in 2015 and a record low of 160,042.424 NGN in 1987. Nigeria NG: GDP: Real: GNI per Capita 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: Gross Domestic Product: Real. GNI per capita is gross national income divided by midyear population. GNI (formerly GNP) 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 constant local currency.; ; World Bank national accounts data, and OECD National Accounts data files.; ;

Nigeria NG: Adjusted Net National Income per Capita: USD: 2015 Price data was reported at 2,241.012 USD in 2015. Nigeria NG: Adjusted Net National Income per Capita: USD: 2015 Price data is updated yearly, averaging 2,241.012 USD from Dec 2015 (Median) to 2015, with 1 observations. The data reached an all-time high of 2,241.012 USD in 2015 and a record low of 2,241.012 USD in 2015. Nigeria NG: Adjusted Net National Income per Capita: USD: 2015 Price 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: Gross Domestic Product: Real. Adjusted net national income is GNI minus consumption of fixed capital and natural resources depletion.;World Bank staff estimates based on sources and methods in World Bank's 'The Changing Wealth of Nations: Measuring Sustainable Development in the New Millennium' (2011).;Weighted average;

Key information about Nigeria GDP Per Capita

• Nigeria Gross Domestic Product (GDP) per Capita reached 2,057.020 USD in Dec 2021, compared with 2,072.338 USD in Dec 2020.
• Nigeria GDP Per Capita data is updated yearly, available from Dec 1981 to Dec 2021, with an average number of 1,868.471 USD.
• The data reached an all-time high of 3,136.832 USD in Dec 2014 and a record low of 492.767 in Dec 1999.
• CEIC calculates GDP per Capita from annual Nominal GDP and annual Population and converts it into USD. The National Bureau of Statistics provides Nominal GDP in local currency, at basic prices. The Central Bank of Nigeria provides Population. The Central Bank of Nigeria average market exchange rate is used for currency conversions. GDP per Capita prior to 2000 is calculated from Mid-year Population sourced from the International Monetary Fund.

• In the latest reports, Nigeria GDP expanded 3.518 % YoY in Dec 2022.
• Nigeria Nominal GDP reached 128.609 USD bn in Dec 2022.
• Its GDP deflator (implicit price deflator) increased 11.269 % in Dec 2022.
• Gross Savings Rate of Nigeria was measured at 32.735 % in Dec 2021.

Nigeria NG: GDP: Growth: GNI per Capita data was reported at -3.646 % in 2016. This records a decrease from the previous number of 0.856 % for 2015. Nigeria NG: GDP: Growth: GNI per Capita data is updated yearly, averaging 1.027 % from Dec 1982 (Median) to 2016, with 35 observations. The data reached an all-time high of 31.220 % in 2004 and a record low of -14.983 % in 1987. Nigeria NG: GDP: Growth: GNI per Capita 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: Gross Domestic Product: Annual Growth Rate. Annual percentage growth rate of GNI per capita based on constant local currency. Aggregates are based on constant 2010 U.S. dollars. GNI per capita is gross national income divided by midyear population. GNI (formerly GNP) 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.; ; World Bank national accounts data, and OECD National Accounts data files.; Weighted average;

Nigeria NG: GDP: Growth: Adjusted Net National Income per Capita data was reported at -10.898 % in 2016. This records a decrease from the previous number of -5.348 % for 2015. Nigeria NG: GDP: Growth: Adjusted Net National Income per Capita data is updated yearly, averaging 3.024 % from Dec 1982 (Median) to 2016, with 35 observations. The data reached an all-time high of 25.440 % in 1995 and a record low of -35.901 % in 1993. Nigeria NG: GDP: Growth: Adjusted Net National Income per Capita 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: Gross Domestic Product: Annual Growth Rate. Adjusted net national income is GNI minus consumption of fixed capital and natural resources depletion.; ; World Bank staff estimates based on sources and methods in World Bank's 'The Changing Wealth of Nations: Measuring Sustainable Development in the New Millennium' (2011).; Weighted average;

Nigeria NG: GDP: USD: Adjusted Net National Income per Capita data was reported at 1,830.842 USD in 2016. This records a decrease from the previous number of 2,242.151 USD for 2015. Nigeria NG: GDP: USD: Adjusted Net National Income per Capita data is updated yearly, averaging 349.028 USD from Dec 1970 (Median) to 2016, with 47 observations. The data reached an all-time high of 2,630.354 USD in 2014 and a record low of 68.541 USD in 1993. Nigeria NG: GDP: USD: Adjusted Net National Income per Capita 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: Gross Domestic Product: Nominal. Adjusted net national income is GNI minus consumption of fixed capital and natural resources depletion.; ; World Bank staff estimates based on sources and methods in World Bank's 'The Changing Wealth of Nations: Measuring Sustainable Development in the New Millennium' (2011).; Weighted Average;

As of 2023, the GDP of Africa was estimated at roughly 3.1 trillion U.S. dollars. This was the highest value since 2010 when the continent's GDP amounted to approximately 2.1 trillion U.S. dollars. The GDP value in Africa generally followed an upward trend in recent years and was estimated to exceed 4.2 trillion U.S. dollars by 2027.

Leading the charge: the three leading African economies

Among the African countries, in 2021, Nigeria had the highest GDP with approximately 442 billion U.S. dollars. South Africa and Egypt followed. These three countries have the largest economies for various reasons. The most notable factors are their population size, natural resources, and level of economic development. Furthermore, Africa was projected to have a real GDP growth rate of 3.9 percent in 2023. Libya was the economy experiencing the highest growth rate in that year.

The Sub-Saharan African economy on the rise

A global comparison showed that Sub-Saharan Africa had the smallest GDP among all world regions in 2021, amounting to 1.87 trillion U.S. dollars. A closer look revealed that Sub-Saharan Africa had a GDP per capita of 1,626.3 U.S. dollars in 2021, again the lowest worldwide. However, the region's economy was forecast to experience continued growth in the following years, with the real GDP increasing by 3.7 percent in 2023.

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.

Abstract

The Nigerian General Household Survey (GHS) is implemented in collaboration with the World Bank Living Standards Measurement Study (LSMS) team as part of the Integrated Surveys on Agriculture (ISA) program and was revised in 2010 to include a panel component (GHS-Panel). The objectives of the GHS-Panel include the development of an innovative model for collecting agricultural data, inter-institutional collaboration, and comprehensive analysis of welfare indicators and socio-economic characteristics. The GHS-Panel is a nationally representative survey of 5,000 households, which are also representative of the geopolitical zones (at both the urban and rural level). The households included in the GHS-Panel are a sub-sample of the overall GHS sample households.

GHS-Panel households were visited twice: first after the planting season (post-planting) between August and October and second after the harvest season (post-harvest) between February and April. All households were visited twice regardless of whether they participated in agricultural activities. Some important factors such as labour, food consumption, and expenditures were collected during both visits.

Geographic coverage

National coverage

Analysis unit

• Household
• Individual
• Community

Universe

The survey covered all de jure households excluding prisons, hospitals, military barracks, and school dormitories.

Kind of data

Sample survey data [ssd]

Sampling procedure

A multi-stage stratified sample design was used for the GHS and the Panel Survey. The GHS-Panel sample is fully integrated with the 2010 GHS Sample. The GHS sample is comprised of 60 Primary Sampling Units (PSUs) or Enumeration Areas (EAs) chosen from each of the 37 states in Nigeria, a total of 2220 EAs nationally. Each EA contributes 10 households to the GHS sample, resulting in a sample size of 22,200 households. Out of these 22,000 households, 5,000 households from 500 EAs were selected for the panel component and 4,916 households completed their interviews in the first wave. Given the panel nature of the survey, some households had moved from their location and were not able to be located by the time of the Wave 3 visit, resulting in a slightly smaller sample of 4,581 households for Wave 3.

For further details of the sample design, see Section 1.2 of the final report.

Mode of data collection

Face-to-face [f2f]

Research instrument

The GHS-Panel Wave 3 consists 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 provides information on demographics; education; health (including anthropometric measurement for children and child immunization); labour and labour data collection options; food and non-food expenditure; household nonfarm income-generating activities; food security and shocks; safety nets; housing conditions; assets; information and communication technology; and other sources of household income. Household location is geo-referenced in order to be able to later link the GHS-Panel data to other available geographic data sets. The labour module of the Household Questionnaire introduced four different variants to test the sensitivity of labour statistics to how labour modules are designed.

GHS-Panel Agriculture Questionnaire: The Agriculture Questionnaire solicits 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; and household fishing activities.

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

Cleaning operations

Data Entry The household and agricultural components of the survey were conducted using concurrent data entry approach. In this method, the fieldwork and data entry were handled by each team assigned to the state. Each team consisted of a field supervisor, 2-4 interviewers and a data entry operator. Immediately after the data were collected in the field by the interviewers and supervisors (the supervisors administered the community questionnaires and collected data on prices), the questionnaires were handed over to the supervisor to be checked and documented. At the end of each day of fieldwork, the questionnaires were then passed to the data entry operator for entry. After the questionnaires were entered, the data entry operator generated an error report which reported issues including out of range values and inconsistencies in the data. The supervisor then checked the report, determined what should be corrected, and decided if the field team needed to revisit the household to obtain additional information. The benefits of this method are that it allows one to: - Capture errors that might have been overlooked by a visual inspection only, - Identify errors early during the field work so that if any correction required a revisit to the household, it could be done while the team was still in the EA

The CSPro software was used to design the specialized data entry program that was used for the data entry of the questionnaires.

Historical chart and dataset showing Nigeria gdp growth rate by year from 1961 to 2023.

Abstract

Panel data possess several advantages over conventional cross-sectional and time-series data, including their power to isolate the effects of specific actions, treatments, and general policies often at the core of large-scale econometric development studies. While the concept of panel data alone provides the capacity for modeling the complexities of human behavior, the notion of universal panel data – in which time- and situation-driven variances leading to variations in tools, and thus results, are mitigated – can further enhance exploitation of the richness of panel information.

The Basic Information Document (BID) provides a brief overview of the Nigerian General Household Survey (GHS) but focuses primarily on the theoretical development and application of panel data, as well as key elements of the universal panel survey instrument and datasets generated by the four rounds of the GHS. As the BID does not describe in detail the background, development, or use of the GHS itself, the wave-specific GHS BIDs should supplement the information provided here.

The Nigeria Universal Panel Data (NUPD) consists of both survey instruments and datasets from the two survey visits of the GHS - Post-Planting (PP) and Post-Harvest (PH) - meticulously aligned and engineered with the aim of facilitating the use of and improving access to the wealth of panel data offered by the GHS. The NUPD provides a consistent and straightforward means of conducting user-driven analyses using convenient, standardized tools.

The design of the NUPD combines the four completed Waves of the GHS Household Post-Planting and Post-Harvest Surveys – Wave 1 (2010/11), Wave 2 (2012/13), Wave 3 (2015/16), and Wave 4 (2018/19) – into pooled, module-specific survey instruments and datasets. The panel survey instruments offer the ease of comparability over time, with modifications and variances easily identifiable as well as those aspects of the questionnaire which have remained identical and offer consistent information. By providing all module-specific data over time within compact, pooled datasets, panel datasets eliminate the need for user-generated merges between rounds and present data in a clear, logical format, increasing both the usability and comprehension of complex data.

Geographic coverage

National

Analysis unit

• Households
• Individuals

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

Please see the GHS BIDs for each round for detailed descriptions of the sample design used in each round and their respective implementation efforts as this is a compilation of datasets from all previous waves.

Mode of data collection

Face-to-face [f2f]

Research instrument

The larger GHS-Panel project consists of three questionnaires (Household Questionnaire, Agriculture Questionnaire, Community Questionnaire) for each of the two visits (Post-Planting and Post-Harvest). The GHS-NUPD only consists of the Household Questionnaire.

GHS-Panel Household Questionnaire: The Household Questionnaire provides information on demographics; education; health (including anthropometric measurement for children); labor; food and non-food expenditure; household nonfarm income-generating activities; food security and shocks; safety nets; housing conditions; assets; information and communication technology; and other sources of household income.

The Household Questionnaire is 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.

Cleaning operations

Please see the GHS BIDs for each round for detailed descriptions of data editing and additional data processing efforts as this is a compilation of datasets from all previous waves.

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

Nigeria NG: GNI: PPP: GNI per Capita data was reported at 5,680.000 Intl $ in 2017. This records a decrease from the previous number of 5,740.000 Intl $ for 2016. Nigeria NG: GNI: PPP: GNI per Capita data is updated yearly, averaging 2,750.000 Intl $ from Dec 1990 (Median) to 2017, with 28 observations. The data reached an all-time high of 5,880.000 Intl $ in 2015 and a record low of 1,710.000 Intl $ in 1993. Nigeria NG: GNI: PPP: GNI per Capita 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: Gross Domestic Product: Purchasing Power Parity. GNI per capita based on purchasing power parity (PPP). PPP GNI 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. GNI 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 based on the 2011 ICP round.; ; World Bank, International Comparison Program database.; Weighted average;

Nigeria NG: GDP: 2010 Price: USD: Adjusted Net National Income per Capita data was reported at 1,617.312 USD in 2016. This records a decrease from the previous number of 1,815.132 USD for 2015. Nigeria NG: GDP: 2010 Price: USD: Adjusted Net National Income per Capita data is updated yearly, averaging 974.817 USD from Dec 1981 (Median) to 2016, with 36 observations. The data reached an all-time high of 1,917.697 USD in 2014 and a record low of 487.298 USD in 1993. Nigeria NG: GDP: 2010 Price: USD: Adjusted Net National Income per Capita 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: Gross Domestic Product: Real. Adjusted net national income is GNI minus consumption of fixed capital and natural resources depletion.; ; World Bank staff estimates based on sources and methods in World Bank's 'The Changing Wealth of Nations: Measuring Sustainable Development in the New Millennium' (2011).; Weighted average;

Nigeria NG: GDP: Growth: Adjusted Net National Income data was reported at -8.534 % in 2016. This records a decrease from the previous number of -2.816 % for 2015. Nigeria NG: GDP: Growth: Adjusted Net National Income data is updated yearly, averaging 5.790 % from Dec 1982 (Median) to 2016, with 35 observations. The data reached an all-time high of 28.602 % in 1995 and a record low of -34.276 % in 1993. Nigeria NG: GDP: Growth: Adjusted Net National Income 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: Gross Domestic Product: Annual Growth Rate. Adjusted net national income is GNI minus consumption of fixed capital and natural resources depletion.; ; World Bank staff estimates based on sources and methods described in 'The Changing Wealth of Nations 2018: Building a Sustainable Future' (Lange et al 2018).; Weighted average;