In 2023, the national gross income per capita in Nigeria stood at ***** U.S. dollars. Between 2008 and 2023, the figure dropped by ** U.S. dollars, though the decline followed an uneven course rather than a steady trajectory.

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.

Nigeria NG: GDP: USD: Gross National Income per Capita: Atlas Method data was reported at 2,080.000 USD in 2017. This records a decrease from the previous number of 2,450.000 USD for 2016. Nigeria NG: GDP: USD: Gross National Income per Capita: Atlas Method data is updated yearly, averaging 325.000 USD from Dec 1962 (Median) to 2017, with 56 observations. The data reached an all-time high of 2,980.000 USD in 2014 and a record low of 100.000 USD in 1968. Nigeria NG: GDP: USD: Gross National Income per Capita: Atlas Method 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. GNI per capita (formerly GNP per capita) is the gross national income, converted to U.S. dollars using the World Bank Atlas method, divided by the midyear population. 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. GNI, calculated in national currency, is usually converted to U.S. dollars at official exchange rates for comparisons across economies, although an alternative rate is used when the official exchange rate is judged to diverge by an exceptionally large margin from the rate actually applied in international transactions. To smooth fluctuations in prices and exchange rates, a special Atlas method of conversion is used by the World Bank. This applies a conversion factor that averages the exchange rate for a given year and the two preceding years, adjusted for differences in rates of inflation between the country, and through 2000, the G-5 countries (France, Germany, Japan, the United Kingdom, and the United States). From 2001, these countries include the Euro area, Japan, the United Kingdom, and the United States.; ; World Bank national accounts data, and OECD National Accounts data files.; Weighted average;

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.

Nigeria National Disposable Income (NDI) data was reported at 227,265,815.579 NGN mn in 2023. This records an increase from the previous number of 194,056,784.066 NGN mn for 2022. Nigeria National Disposable Income (NDI) data is updated yearly, averaging 106,031,229.942 NGN mn from Dec 2010 (Median) to 2023, with 14 observations. The data reached an all-time high of 227,265,815.579 NGN mn in 2023 and a record low of 52,913,490.930 NGN mn in 2010. Nigeria National Disposable Income (NDI) data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under Global Database’s Nigeria – Table NG.A014: SNA 2008: National Disposable Income: Annual.

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.

Abstract

The Lagos Household Survey 2006, also reffered to as service delivery assesment survey, was the first Baseline Survey under the World Bank assisted Lagos Metropolitan Development and Governance Projects (LMDGP) which started a year earlier in 2005. The household survey was a key component of the Baseline Projects which also consisted of five major economic surveys.

The survey's objectives was to provide reliable data on a timely basis for monitoring changes in the welfare status by local government areas in the State, provides estimates at local government level , assess the social and economic situation in the State and provides relevant data required to monitor growth and development in the state ,as well as building the socio-economic database.

Geographic coverage

State Local Government Wards

Analysis unit

Individuals, households, and communities.

Universe

Household members

Kind of data

Sample survey data [ssd]

Sampling procedure

A sample of 6000 respondents were selected using a combination of probability proportional to size and equal size sample i.e (mix Design) in appreciation of the spread and peculiarities of the state inhabitants and landscapes.

The entire twenty (20) Local government Areas (LGAs) in the state was divided into two Zones: ( North comprising 9 LGAs and South having 11 LGAs) with sample size of 3052 respondents and 2948 rspondents respectively.

The first level of stratification comprised the Local Government Areas, with each of them divided into Political Wards (between 10 and 25). These wards formed the second level of stratification.

Sampling deviation

No deviation from sample design

Mode of data collection

Face-to-face [f2f]

Research instrument

The Questionaire was made up of fifteen (15) modules namely,

Section 1: Household charasteristics and household listing Section 2: Types of Housing
Section 3: Land and Tenure Section 4: Access to Infrastructure - Stormy Water Drainage Section 5: Access to Infrastructure - Sanitation Section 6: Access to Infrastructure - Water Section 7: Access to Infrastructure - Solid Waste Removal Section 8: Access to Infrastructure - Energy and Electricity Section 9: Access to Infrastructure - Telephone Section 10: Transportation & Local Roads Section 11: Education Section 12: Health Section 13: Emergency and policing Services Section 14: Community Preferences Section 15: Household income and expenditure.

The questionaire was published in English language and was based on the generic one prepared by the world bank but modified to suit the Nigeria/ Lagos state environment. The head of the household was the key respondent in the households , individual members and community level information are included in the instrument. The questionaires is provided as external resources.

Cleaning operations

The Perseus Software Solution 6 Software which was used to upload survey instruments into the palmtop had in built capacity to download the completed questionaire from the palmtop into the designated laptop for the survey throgh microsoft active synching.

No data entry involved. however the downloaded dataset are then edited for cleaning and quality checks.

The data set wasc later transfered/exported to SPSS for more robust analysis.

Response rate

At both levels of stratification ie Local government Areas (LGAs) and Political Wards, the response rates were 100 percent respectively.

Sampling error estimates

Not calculated

Data appraisal

Some indicators such as average Household size, room density, access to portable water.

The national minimum wage for federal workers in Nigeria reached ****** Nigerian naira (NGN) in 2024, which equaled about ** U.S. dollars. On July 23, 2024, this minimum wage of ****** NGN was passed into law, increasing from the previous amount of ****** NGN. According to most recent data, the monthly cost of living for an individual in Nigeria amounted to ****** NGN on average, whereas this figure added up to over ******* NGN for a family. Dependency ratio In 2023, the labor dependency ratio in Nigeria was estimated at *** percent, showing no significant change since 2012. This metric represents the proportion of dependents who are either not part of the workforce or are unemployed, in relation to the total employed population. Nigeria's compensation trends and workload statistics In 2023, individuals working in executive management and change roles garnered the highest average annual salary in Nigeria at ****** U.S. dollars. In the same year, the employed workforce in Nigeria contributed to a collective weekly workload exceeding *** billion hours. Two years earlier, the workload was estimated at about *** billion hours.

Nigeria NG: Proportion of Population Spending More Than 25% of Household Consumption or Income on Out-of-Pocket Health Care Expenditure: % data was reported at 8.920 % in 2009. This records an increase from the previous number of 3.833 % for 2003. Nigeria NG: Proportion of Population Spending More Than 25% of Household Consumption or Income on Out-of-Pocket Health Care Expenditure: % data is updated yearly, averaging 6.376 % from Dec 2003 (Median) to 2009, with 2 observations. The data reached an all-time high of 8.920 % in 2009 and a record low of 3.833 % in 2003. Nigeria NG: Proportion of Population Spending More Than 25% of Household Consumption or Income on Out-of-Pocket Health Care Expenditure: % 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: Poverty. Proportion of population spending more than 25% of household consumption or income on out-of-pocket health care expenditure, expressed as a percentage of a total population of a country; ; Wagstaff et al. Progress on catastrophic health spending: results for 133 countries. A retrospective observational study, Lancet Global Health 2017.; Weighted Average;

The study examined child development and family human capital investment decisions in Nigeria. The study focused on household per capita income and family structure using the Nigeria living standard survey for 2018/2019 for the secondary data analysis and a field survey conducted by the researchers in six states in each of the geopolitical zones in Nigeria for the primary data analysis. The study was anchored on household utility maximization theory using the ordinary least squares (OLS) method to analyse the secondary data. Four different results were obtained. First, the result of findings from the OLS estimate revealed that per capita income had no significant impact on Family Human Capital Investment Decisions (FHCID) and male perception of the cost of education had a significant positive impact on FHCID. On the contrary, multi-dimensional poverty index and female perception of the cost of education had an inverse significant impact on FHCID. The second result revealed that average household size, family residence from 1 to 30 minutes proximity to school and 31 minutes and above proximity to school had no significant impact on FHCID. Dependency ratio showed an inverse significant impact on FHCID and family literacy level showed a significant positive impact on FHCID. The third result from the binary logistics regression showed that age, occupation and place of residence of the household head had no significant impact on FHCID. Gender (female-headed household) and education showed an inverse significant impact on FHCID. However, household head years in business or paid employment showed a positive impact on FHCID. The fourth result from the binary logistics regression revealed that marital status had no significant impact on FHCID; family size had a significant negative impact on FHCID; and family structure (type of parents) and number of girl child in the household had a direct impact on FHCID. This study showed complementarities in the home utility function, such that the marginal product of investments rises as family living standards rise. These findings highlight lifetime inequalities and necessitates a special focus on treatments for low-income households. Understanding human capital development and how diverse elements interact is critical to combating poverty and its intergenerational transmission. As a result, this study made several recommendations. First, the importance of persistent action by the government and other donor agencies such as the United Nation Children’s Fund (UNICEF) and The World Bank to address the problems of income inequality and pervasive poverty ravaging Nigeria’s economy. The study strongly recommends that family, especially parents, maintain justice and fairness within the home, to foster constructive, sympathetic and peaceful home, encouraging most children to exhibit excellent academic performance. Third, government agencies and hospitals, especially in rural areas, intensify family planning and birth control campaign to help reduce household size. Fourth, children of the poor be given opportunities for paid employment, to enhance their performance in the school. Fifth, children from poor homes be provided with access to scholarships, free instructional materials and books. Sixth, government and its agencies on education intensify sensitization and campaign for families to embrace Western education, especially in the northern region, promote compulsory primary basic education for all children and prosecute parents of out-of-school children or child labour to serve as a deterrent to others. Finally, the study recommends that non-governmental and religious organizations preach peace and tolerance within the family for the well-being and human capital development of their wards.

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.

Nigeria NG: Proportion of Population Spending More Than 10% of Household Consumption or Income on Out-of-Pocket Health Care Expenditure: % data was reported at 24.770 % in 2009. This records an increase from the previous number of 14.514 % for 2003. Nigeria NG: Proportion of Population Spending More Than 10% of Household Consumption or Income on Out-of-Pocket Health Care Expenditure: % data is updated yearly, averaging 19.642 % from Dec 2003 (Median) to 2009, with 2 observations. The data reached an all-time high of 24.770 % in 2009 and a record low of 14.514 % in 2003. Nigeria NG: Proportion of Population Spending More Than 10% of Household Consumption or Income on Out-of-Pocket Health Care Expenditure: % 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: Poverty. Proportion of population spending more than 10% of household consumption or income on out-of-pocket health care expenditure, expressed as a percentage of a total population of a country; ; Wagstaff et al. Progress on catastrophic health spending: results for 133 countries. A retrospective observational study, Lancet Global Health 2017.; Weighted Average;

BackgroundMany low and middle-income countries are increasingly cognisant of the need to offer financial protection to its citizens through pre-payment schemes in order to curb high out of pocket expenditure and catastrophic spending on healthcare. However, there is limited rigorous contextual evidence to make decisions regarding optimal design of such schemes. This study assesses the willingness-to-pay (WTP) for the recently introduced state contributory health insurance scheme (SHIS) in Nigeria.MethodsThe study took place in 6 local government areas in Kaduna state, North-west Nigeria. Data were collected from a household survey using a three-stage cluster sampling approach, with each household having the same probability of being selected. Interviews were conducted with 4000 individuals in 1020 households. Contingent valuation was used to elicit the willing to pay (WTP) for the household using the bidding game technique. The relationship between socioeconomic status and WTP was also examined using logistic regression models.FindingsAbout 82% of the household heads were willing to pay insurance premiums for their households, which came to an average of 513 Naira (1.68 USD) per month per person. The average amount individuals were willing to pay was lower in rural areas (611 Naira) compared to urban areas (463 Naira). These results were influenced by household size, level of education, occupation and household income. In addition, only 65% of the households had the ability to pay the average premium.ConclusionSocioeconomic factors influence individuals’ WTP for contributory health insurance schemes. It is important to create awareness about the benefits of the insurance scheme, especially in rural areas, and in both the formal and informal sectors in Nigeria. WTP information can inform the amount of insurance premiums. However, it is important to consider differences between the WTP and the cost of benefits package to be offered, as the premium amount may need to be subsidized with public financing.

Abstract

Despite the significant growth experienced in Nigeria in recent years, poverty has been on the rise, particularly in rural areas. The National Social Safety Nets Project (NASSP) was designed to provide poor and vulnerable household’s access to targeted transfers and to pilot scalable livelihoods interventions to support sustainable income generating activities and graduation out of poverty. To assess the impacts of the livelihood pilot activities, a sample of households was interviewed for the baseline data collection before the introduction of these interventions. These households will then be re-interviewed after the completed implementation of the livelihood package in a random subset of communities, to evaluate any resulting changes in household welfare and to gain insights about the most cost-effective approaches to deliver the livelihood package at scale.

Geographic coverage

8,035 NASSP beneficiary households from 460 communities in 12 local government areas (LGAs) in the six livelihood pilot states: Anambra, Bauchi, Cross River, Jigawa, Niger and Oyo.

Sampling procedure

The survey used a multistage sampling procedure. Stage 1: Six states were selected for the pilot study, one from each geopolitical zone, to ensure it represents national diversity. The states also satisfied the following criteria: availability of a State Beneficiary Register (SBR); participation in the Community and Social Development Project (CSDP) and/or Fadama; and adoption of the co-responsibility component of the NASSP project. Stage 2: Local Government Areas (LGAs) were selected from each state. Both LGAs were rural, to ensure the livelihood works in the most challenging of environments. Not more than one LGA was selected in each senatorial district to ensure widespread representation. Stage 3: Pilot communities were selected based on these factors: 12 to 56 households per community (for implementation feasibility); at least 3 communities per ward (to allow stratification of treatment arms within wards); at least 2 wards per LGA. Stage 4: Households were randomly sampled from each community, proportionate to the coverage of the NASSP project.

Research instrument

The baseline survey questionnaire was programmed into the SurveyCTO application on Android tablets and trained enumerators administered the survey to household respondents in face-to-face interviews conducted during household visits.

The survey questionnaire was developed in English language by the research team and translated into Hausa, Igbo, Yoruba, Nupe and Pidgin by professional translators. Heads of households and caregivers were the main target respondents and separate sections of the survey were targeted to each of them. If a household head was unavailable, the caregiver responded on their behalf (7.5% of household). If the caregiver was unavailable, the alternate responded (2.5% of households). Questions were also asked to economically active members in each household when available. The average interview duration was 3 hours.

The survey questionnaire was divided into the following sections: household composition, employment, agriculture, livestock, business activities, program participation, safety nets, other income, remittances, consumption, finances, shocks, food security, dwelling type, household assets, psychosocial wellbeing, household dynamics, and time use.