Nigeria Prime Lending Rate data was reported at 17.960 % pa in Mar 2025. This records a decrease from the previous number of 18.350 % pa for Feb 2025. Nigeria Prime Lending Rate data is updated monthly, averaging 16.540 % pa from Jan 2006 (Median) to Mar 2025, with 231 observations. The data reached an all-time high of 19.660 % pa in Nov 2009 and a record low of 11.130 % pa in Mar 2021. Nigeria Prime Lending Rate data remains active status in CEIC and is reported by Central Bank of Nigeria. The data is categorized under Global Database’s Nigeria – Table NG.M003: Lending Rates.

Key information about Nigeria Exchange Rate against USD

• Nigeria Exchange Rate against USD averaged 1,443.350 (USD/NGN) in Nov 2025, compared with 1,459.041 USD/NGN in the previous month.
• Nigeria Exchange Rate against USD data is updated monthly, available from Jan 1957 to Nov 2025.
• The data reached an all-time high of 1,670.276 in Nov 2024 and a record low of 0.530 in Nov 1980.

CEIC calculates monthly average Exchange Rate against USD from daily average Exchange Rate. Central Bank of Nigeria provides average Exchange Rate against USD. Exchange Rate against USD prior to January 2002 is sourced from the International Monetary Fund.


Key information about Nigeria Exchange Rate against USD

• In the latest reports, Nigeria Short Term Interest Rate: Month End: NIBOR: 3 Months was reported at 26.358 % pa in Oct 2025.
• The cash rate (Policy Rate: Month End) was set at 27.000 % pa in Nov 2025.

This dataset is comprised of raw data from the NERC-funded, full waveform terrestrial laser scanner (TLS) deployed at sites on three continents, multiple countries and plot locations. Plot CBN-02 is part of the Global Ecosystem Monitoring (GEM) and is located in the rainforests of Malaysian Borneo. Please note that this data is not registered and therefore there are no rotation matrices.

The TLS data were collected on a 10 m x 10 m grid where at each position the scanner captured data in an upright and tilted position. The scanner was set to an angular step of 0.04 degrees for all scans. In between each scan position, a set of retro-reflective targets were positioned to be used as tie-points between scans. For more information on TLS acquisition refer to Wilkes et al. (2017). Scan data were coregistered using RiSCAN Pro, the 4x4 rotation transformation matrices to transform the point cloud data into a common reference coordinate system can be found in the "matrix" directory.

The Cubic Boron Nitride (CBN) Insert market has evolved into a vital segment of the advanced materials industry, primarily due to its exceptional hardness and thermal stability, which make it an ideal choice for precision machining and cutting operations, especially in the automotive and aerospace sectors. CBN inser

Inflation Rate in Nigeria decreased to 16.05 percent in October from 18.02 percent in September of 2025. This dataset provides - Nigeria Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

This data is built for learning, to get insight and to solve infectious diseases pandemic and also to discover a way to predict the effect of the outbreak on the Nigeria economy.

This data is built from data sourced from Nigeria Centre for Disease Control daily situation report, World Health Organisation COVID-19 daily situation report, Central Bank of Nigeria, Bloomberg, Nigeria Stock Exchange and Accuweather.

The dataset comprises of 20 columns. Id, date, confirm case(nigeria), new case(nigeria), total case(nigeria), death case(nigeria), global confirmed case, percentage on confirmed case, global new case, percentage on global new case, global death case, percentage on global death case(nigeria), weather(lagos), Exchange rate(naira to USD) (buying rate, central rate, selling rate), all share index(nigeria), global oil price(USD) and External reserves (gross and liquid)(nigeria).

Acknowledgements A deep appreciation goes to Nigeria Centre for Disease Control and the effort of the Federal government of Nigeria for their unrelented effort to battle the outbreak of the novel Corona Virus Pandemic and sincere appreciation goes to World Health Organisation COVID-19 daily situation report, Central Bank of Nigeria, Bloomberg, Nigeria Stock Exchange and Accuweather for their open data. https://www.accuweather.com/en/ng/lagos/4607/april-weather/4607?year=2020 https://ng.investing.com/indices/nse-all-share-historical-data https://www.cbn.gov.ng/IntOps/Reserve.asp?MoveDate=4/3/2020%208:11:54%20PM https://www.who.int/emergencies/diseases/novel-coronavirus-2019/situation-reports https://www.bloomberg.com/quote/CO1:COM https://www.cbn.gov.ng/rates/ExchRateByCurrency.asp https://covid19.ncdc.gov.ng/

Nigeria Real Estate – Housing Estates

  Dataset Description

Synthetic Real Estate Development data for Nigeria real estate sector. Category: Real Estate DevelopmentRows: 40,000Format: CSV, ParquetLicense: MITSynthetic: Yes (generated using reference data from PropertyPro, Knight Frank, NBS, CBN, FMBN)

  Dataset Structure





  Schema

id: string date: string city: string value: float category: string

  Sample Data

| id | date | city… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/nigerian_realestate_housing_estates.

Nigeria Real Estate – Neighborhood Amenities

  Dataset Description

Synthetic Infrastructure & Amenities data for Nigeria real estate sector. Category: Infrastructure & AmenitiesRows: 80,000Format: CSV, ParquetLicense: MITSynthetic: Yes (generated using reference data from PropertyPro, Knight Frank, NBS, CBN, FMBN)

  Dataset Structure





  Schema

id: string date: string city: string value: float category: string

  Sample Data

| id | date… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/nigerian_realestate_neighborhood_amenities.

Abstract

The Geneal Household Survey is a brainchild of the National Bureau of Statistics (NBS) and is often referred to as Regular survey carried out on quarterly basis by the NBS over the years. In recent times, starting from 2004 to be precise, there is a collaborative effort between the NBS and the CBN in 2004 and 2005 and in 2006, 2007and 2008, the collaboration incorporated Nigerian Communications commission (NCC).

The purpose of the surveys or collaboration include among others: (i) To conduct multipurpose surveys to generate social and economic data series for 2009 and the first quarter of 2010

(ii) To enable NBS/CBN/NCC fulfil their mandate in production of current and credible statistics to monitor and evaluate the State of the economy and the various government programmes such as NEEDS, MDGs and 7 Point Agenda.

The key objectives of the survey include:

i) Collection of relevant statistics to facilitate the production of GDP

ii) Production of data to aid economic analysis on non-oil outputs such as Manufacturing, Agriculture and Services

iii) Production of State and Local Government Finance Statistics, Producer Price Index (PPI), Oil Sector Statistics and Flow of Funds

Collection of current socio-economic statistics in Nigeria to assist in policy formulation and aid the monitoring and evaluation of various government programmes at National and sub-national levels

Geographic coverage

National Zone State Local Government

Analysis unit

Household Analysis

Universe

Household

Kind of data

Sample survey data [ssd]

Sampling procedure

The General Household Survey and the National Agricultural Sample Survey designs derived from NBS 2007/12 NISH sample design. The 2007/12 NISH sample design is a 2-stage, replicated and rotated cluster sample design with Enumeration Areas (EAs) as first stage sampling units or Primary Sampling Units (PSUs) while Households constituted the second stage units (secondary sampling units). The households were the Ultimate Sampling Units for the multi-subject survey.

Generally, the NISH Master Sample in each State is made up of 200 EAs drawn in 20 replicates. A replicate consists of 10 EAs. Replicates 10-15, subsets of the Master Sample were studied for modules of the NISH.

The GHS was implemented as a NISH module. three replicates were studied per State including the FCT, Abuja. With a fixed-take of 15 HHs systematically selected per EA, 450 HHs thus were selected for interview per State including the FCT, Abuja. Hence, nationally, a total of 16,650 HHs were drawn from the 1,110 EAs selected for interview for the GHS. The selected EAs (and hence the HHs) cut across the rural and urban sectors.

Sampling deviation

Variance Estimate (Jackknife Method) Estimating variances using the Jackknife method will require forming replicate from the full sample by randomly eliminating one sample cluster [Enumeration Area (EA) at a time from a state containing k EAs, k replicated estimates are formed by eliminating one of these, at a time, and increasing the weight of the remaining (k-1) EAs by a factor of k/(k-1). This process is repeated for each EA.

For a given state or reporting domain, the estimate of the variance of a rate, r, is given by k Var(r ) = (Se)2 = 1 S (ri - r)2 k(k-1) i=1

where (Se) is the standard error, k is the number of EAs in the state or reporting domain.

r is the weighted estimate calculated from the entire sample of EAs in the state or reporting domain.
ri = kr - (k - 1)r(i), where

r(i) is the re-weighted estimate calculated from the reduced sample of k-1 EAs.

To obtain an estimate of the variance at a higher level, say, at the national level, the process is repeated over all states, with k redefined to refer to the total number of EAs (as opposed to the number in the states).

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire for the GHS is a structured questionnaire based on household characteristics with some modifications and additions. The House project module is a new addition and some new questions on ICT.

The questionnaires were scaned.

This section were divided into eleven parts.

Part A: Identification code, Response status, Housing characteristics/amenities and Information communication Technology (ICT). Part B: Socio-demographic characteristics and Labour force characteristics Part C: Information about the people in the household who were absent during the period of the survey. Part D: Female contraceptive only, and children ever born by mothers aged 15 years and above Part E: Births of children in the last 12 months, and trained birth attendant used during child delivery. Part F: Immunization of children aged 1 year or less and records of their vaccination Part G: Child nutrition, exclusive breast feeding and length of breast feeding. Part H: Deaths in the last 12 months, and causes of such deaths. Part I: Health of all members, of the household and health care providers. Part J: Household enterprises, income and profit made from such activities. Part K: Household expenditure, such as school fees, medical expenses, housing expenses, remittance, cloth expenses, transport expenses and food expenses.

Cleaning operations

The data editing is in 2 phases namely manual editing before the questionnaires were scanned. This involved using editors at the various zones to manually edit and ensure consistency in the information on the questionnaire.

The second editing is the computer editing, this is the cleaning of the already scanned data by the subject mater group. The questionnaires were processed at the zones. On completion, computer editing was also carried out to ensure the integrity of the data. .

Response rate

At National level ,out of the expected 1,110 EAs, all were covered which showed 100% retrieval rate. (by the table 1.12 on page 196 of the report)

At household level, out of the 16,650 expected to be covered, 16,355 were canvassed which showed 98% retrieval.

At sector level (Urban/Rural), 28.4% were recorded for Urban while Rural recorded 71.6%.

Sampling error estimates

No sampling error estimate

Data appraisal

The Quality Control measures were carried out during the survey, essentially to ensure quality of data. There were three levels of supervision involving the supervisors at the first level, CBN staff, NBS State Officers and Zonal Controllers at second level and finally the NBS/NCC Headquarters staff constituting the third level supervision. Field monitoring and quality check exercises were also carried out during the period of data collection as part of the quality control measures

Foreign Exchange Reserves in Nigeria increased to 44560 USD Million in November from 43150 USD Million in October of 2025. This dataset provides - Nigeria Foreign Exchange Reserves - actual values, historical data, forecast, chart, statistics, economic calendar and news.

This dataset supports a study of how disaggregated health-financing segments viz. health expenditure per capita, recurrent health expenditure, capital health expenditure, and out-of-pocket health spending, relate to social sustainability in Nigeria, measured by life expectancy at birth and infant mortality rate. By separating recurrent vs capital government spending and household out-of-pocket payments from per-capita spending, the data enable clean tests of financing composition effects on population health.Variables (what each column means)/source sitesYEAR: Calendar year.LEX_years: Life expectancy at birth, total (years).Source site: World Bank WDI → https://data.worldbank.orgIMR_per_1000: Infant mortality rate (deaths under age 1 per 1,000 live births).Source site: World Bank WDI → https://data.worldbank.orgHEXPc_USD: Current health expenditure per capita (current US$).Source site: World Bank WDI (from WHO GHED) → https://data.worldbank.orgOPHS_percent: Out-of-pocket spending as a % of current health expenditure (households’ direct payments).Source site: World Bank WDI / WHO Global Health Expenditure Database → https://data.worldbank.org ; https://apps.who.int/nha/databaseRHEX_Naira_billion: Federal Government Recurrent health expenditure (₦ billions).Source site: CBN Statistical Bulletin → https://www.cbn.gov.ng (Statistics ▸ Statistical Bulletin ▸ Public Finance)CHEX_Naira_billion: Federal Government Capital health expenditure (₦ billions).Source site: CBN Statistical Bulletin → https://www.cbn.gov.ng (Statistics ▸ Statistical Bulletin ▸ Public Finance)Notes: Spending series from WDI/WHO typically have strongest coverage from 2000 onward; earlier years may be NA. RHEX/CHEX are nominal ₦ billions from CBN Public Finance functional tables (Health).

Money Supply M2 in Nigeria increased to 119028285.58 NGN Million in October from 117774240.75 NGN Million in September of 2025. This dataset provides - Nigeria Money Supply M2 - actual values, historical data, forecast, chart, statistics, economic calendar and news.