Nigeria's Economy,
Rendered in Data

Nigeria is Africa's largest economy by nominal GDP, yet it is also one of the most volatile. Over the decade from 2014 to 2024, it passed through a historic GDP rebasing that briefly made it the largest economy on the continent, two separate recessions, an oil price collapse, a global pandemic, a catastrophic oil theft crisis that drove production to a thirty-year low, and a sweeping foreign exchange reform that cut the dollar value of the economy nearly in half within eighteen months. Understanding any one of these events in isolation is hard enough. Understanding them together, as a connected economic story, is the challenge this dashboard was built to address.

The Nigeria GDP Analytics Dashboard is an eight-page interactive application that brings together annual and quarterly GDP data, sector-by-sector composition analysis, oil production and revenue figures, macroeconomic indicators including foreign exchange rates and inflation, digital economy metrics covering telecoms and fintech, and an interactive scenario builder that lets users model how different policy and commodity conditions would affect growth through 2029. Every piece of data is drawn from primary institutional sources and structured for direct exploration rather than static reading.

This writeup documents the full technical construction of the dashboard: the data sources and why they were chosen, how the application is structured, what each page is designed to reveal, and what the numbers themselves say about Nigeria's economic trajectory over the most turbulent decade in its post-oil history.

Data Sources and Methodology

Building a ten-year economic dashboard requires navigating a fragmented data landscape. Nigeria's statistical infrastructure involves multiple publishing bodies with different methodologies, release schedules, and levels of granularity. This section documents where each dataset came from, why it was preferred over alternatives, and how it was structured in the application.

World Bank Open Data

The World Bank's open data portal at data.worldbank.org provided the foundational annual GDP figures in current US dollars, real GDP growth rates, and GDP per capita. The World Bank uses Nigeria's own National Bureau of Statistics figures as inputs but normalises them to internationally comparable methodologies, making them the appropriate source for cross-temporal analysis. One important caveat is that nominal USD figures are sensitive to the exchange rate used for conversion, which explains the dramatic fall in Nigeria's 2023 and 2024 figures following the FX unification policy.

IMF World Economic Outlook

The International Monetary Fund's World Economic Outlook database, published biannually in April and October, provided two critical inputs: the inflation rate series used throughout the macro indicators page, and the baseline GDP growth projections for 2025 through 2029 used in the forecast page. The October 2024 edition was the primary reference. The IMF also provided cross-validation for the World Bank growth figures where methodological differences appeared.

Central Bank of Nigeria Statistical Bulletin

The CBN's annual statistical bulletin is the definitive source for Nigerian monetary and financial data. The dashboard draws on it for the exchange rate series, external reserves figures, foreign direct investment inflows, and public debt-to-GDP ratios. The CBN publishes data with a nominal USD conversion using the official exchange rate, which creates the apparent paradox visible in the data where oil revenue fell sharply in 2023 despite stable global oil prices, because the revenue base was recalculated at a much weaker naira.

NBS Quarterly GDP Reports

The National Bureau of Statistics publishes quarterly GDP growth figures in their GDP Report series, disaggregated by oil and non-oil sectors. The dashboard uses twenty consecutive quarters from Q1 2020 through Q4 2024, which is the period for which complete and consistent quarterly data is available and which covers the most analytically interesting period including COVID recovery, the oil theft crisis, and the reform-era volatility.

# Quarterly GDP data — oil vs non-oil split
# Source: NBS Quarterly GDP Report Series
QUARTERLY_GDP = [
    {"quarter": "Q2 2020", "growth": -6.10, "oil": -12.61, "non_oil": -5.44},
    {"quarter": "Q3 2021", "growth":  4.03, "oil":  -9.23, "non_oil":  5.44},
    {"quarter": "Q1 2022", "growth":  3.11, "oil": -26.04, "non_oil":  6.11},
    # ... 17 more quarters
]

NNPC Annual Reports and OPEC Data

Oil production figures in millions of barrels per day came from NNPC's annual reports supplemented with OPEC's Nigeria quota and production tracking data. This combination was necessary because NNPC's own reported production figures and OPEC's assessments sometimes differ due to terminal metering disputes. The dashboard uses the average of both sources where they diverge, and the accompanying narrative on the oil page notes this uncertainty.

NCC Annual Reports

Nigeria's telecoms and internet penetration data, used on the digital economy page, came from the Nigerian Communications Commission annual reports. The NCC publishes quarterly data on active mobile subscriptions, internet subscribers, and broadband penetration that is not available from any international aggregator at comparable granularity. Fintech company counts were sourced from CBN licensing data and industry reports by EFInA (Enhancing Financial Innovation and Access).

Application Architecture

The dashboard separates its concerns cleanly across three layers. Data lives in one place, chart-building logic lives in another, and page content lives in a third. This structure means that updating a figure, changing a chart style, or adding a new analytical page each require touching exactly one file rather than searching across the entire codebase.

The Forecast Page Design

The most technically involved page is the forecast page, which implements a parametric growth model driven by six Streamlit slider widgets. The model starts from a baseline growth rate of 3.5 percent, then applies additive adjustments for each lever: oil price deviation from the $80 baseline, oil production deviation from 1.6 million barrels per day, foreign exchange stability score, reform implementation pace, security index, and agricultural investment level. Each lever is converted to a growth point impact using coefficients derived from historical sensitivity analysis of the Nigerian economy.

# Parametric scenario model
base_growth   = 3.5
oil_factor    = (oil_price - 80) * 0.02 + (oil_output - 1.6) * 1.2
reform_factor = (reform_pace - 5) * 0.3
fx_factor     = (fx_stability - 5) * 0.15

scenario_growth = [
    round(base_growth + oil_factor + reform_factor + fx_factor + i * 0.15, 2)
    for i in range(5)
]

The result is displayed as a three-way chart showing the user's custom scenario alongside the IMF baseline projection and a shaded confidence band, with the ten-year historical trace for continuity. A live average growth metric updates instantly as sliders move, with colour-coded labels ranging from "Strong" through "Moderate" to "Recession Risk" depending on the output.

Dashboard Pages and Chart Choices

Each of the eight pages was designed around a primary analytical question. Chart types were chosen not for visual variety but for whether they made the specific pattern or relationship in that data as immediately legible as possible.

Key Findings

Tools and Technology