Data diary

The World Bank published full-year 2024 figures for Nigeria across the macro and debt series. No 2025 data exists yet (every WB series returns null for 2025 as of this pull). The record now runs 1996 to 2024 for economic and debt indicators.

What was added (2024, verified against the WB API)

Indicator	2023	2024	Note
GDP (constant 2015 US$)	$519.8B	$540.9B	+4.1% real growth
GDP (current US$)	~$487B	~$252B	≈ halved in dollar terms, naira float
GDP per capita (constant 2015 US$)	$2,254*	$2,325	modest uptick; still below 2015 peak ($2,584)
Inflation (CPI, annual)	24.7%	33.2%	highest since the 1990s
Agriculture / Manufacturing / Services VA	n/a	$128.7B / $43.0B / $320.0B	all grew modestly
Mobile subscriptions / 100	98.5	70.8	≈ −28%, NIN-SIM deactivation
Life expectancy	54.5	54.6	n/a
FDI (% GDP)	0.38%	0.43%	still near floor
External debt stock (WB IDS)	$102.5B	$108.8B	+$6.3B
External debt (% GNI)	29.0%	60.0%	roughly doubled, mostly a USD-GNI denominator effect from the float
General govt debt (% GDP, IMF WEO)	36.3%	39.3%	n/a

Decisions and caveats (read these before citing 2024)

• Governance (WGI) is NOT extended to 2024. The WGI programme re-estimated its entire history in a methodology revision. The current 2024 WGI figures sit on a different basis than the 1996 to 2023 composite stored here, so appending a 2024 point would fabricate a governance "movement" that is purely a rebasing artifact. Governance therefore stops at 2023. A full re-baseline of the whole WGI series (1996 to 2024) on the current vintage is a separate, deliberate task, it would shift the Aso Rock Index and several headline governance figures and is not done here.
• The Aso Rock Index composite is not extended to 2024, because it depends on the governance component above.
• Current-dollar vs constant-dollar GDP diverged sharply in 2024. Real (constant 2015 US$) GDP grew about 4%; current-dollar GDP fell by roughly a third as the annual-average naira rate reflected the full-year float. Both are correct; we lead with constant dollars, as always.
• Per-capita vintage note (*): WB's current WDI vintage revised 2023 GDP per capita to ~$2,281 (our stored 2023 figure of $2,254 is an earlier vintage; about 1% drift). Historical milestones were left at their original vintage; the 2024 figure ($2,325) is current-vintage. The conclusion, per capita is below its 2015 peak, holds under either vintage.
• Series with no 2024 data (left null, not carried forward): access to electricity (latest 2023), oil rents % GDP (none published past 2021), poverty headcount (latest 2022/2018, survey-dependent), Gini (latest 2022).
• WGI indicator codes were renamed at source (e.g. RL.EST → GOV_WGI_RL.EST under WB source 3). Any pull script using the old codes will silently return nothing and must be updated.
• DMO total public debt: a live, current figure from the Debt Management Office could not be reliably verified at refresh time (their portal is dynamic/PDF-based). The debt series here uses World Bank International Debt Statistics, which is the consistent long-run series and does carry 2024. WB's public-and-publicly-guaranteed external debt (the closest proxy to DMO external public debt) was $50.2B in 2024.

The site examines the relationship between governance quality and economic sector performance in Nigeria from 1996 to the present. Time-series analysis, causal-inference methods, and counterfactual modelling are used to quantify the economic impact of governance fluctuations.

Key data decisions

• Primary governance data: World Bank Worldwide Governance Indicators (WGI)
• Economic sector data: World Bank World Development Indicators (WDI)
• Comparison panel: Nigeria (focus), Brazil, Argentina, South Africa, Egypt
• Composite score: Weighted governance score based on theoretical relevance to economic outcomes

Research questions

#	Question	Data Requirements
1	How have governance peaks and valleys aligned with economic sector performance?	Time series of governance indicators and sector output, sufficient temporal granularity
2	Can we prove causation (not just correlation) between governance and economic outcomes?	Comparison countries for difference-in-differences, controls for confounding factors
3	What would Nigeria's economy look like if governance had stayed at peak levels?	Baseline data, sector-level detail for counterfactual modeling

Primary sources

Source	Dataset	Access Method	URL
World Bank	Worldwide Governance Indicators (WGI)	wbgapi Python library	info.worldbank.org/governance/wgi/
World Bank	World Development Indicators (WDI)	wbgapi Python library	databank.worldbank.org

Why World Bank WGI for governance

1. Methodological rigor: WGI aggregates data from over 30 underlying sources including surveys, expert assessments, and NGO reports, reducing single-source bias
2. Comparability: Standardized methodology across 200+ countries enables cross-country analysis essential for causal inference
3. Academic acceptance: WGI is the most widely cited governance dataset in peer-reviewed economics and political science literature
4. Temporal coverage: Consistent methodology from 1996 onwards, covering Nigeria's entire Fourth Republic
5. Transparency: Full methodology documentation and underlying source disclosure

Why World Bank WDI for economic data

1. Official statistics: WDI compiles data from national statistical offices, central banks, and international organizations
2. Standardization: Consistent definitions (e.g., constant 2015 US$ for value added) enable temporal and cross-country comparison
3. Coverage: Sectoral disaggregation that single national sources do not provide at the same level of consistency.
4. Validation: Cross-validated against IMF, UN, and regional development bank data

Supplementary sources

Source	Usage
V-Dem (Varieties of Democracy)	Used for historical context (1960-1999 pre-WGI period); provides democracy and governance indicators back to independence, enabling analysis of military rule periods
CBN Statistics	Used for supplementary validation; primary analysis uses WDI for cross-country comparability
NBS Nigeria	Used for validation; national definitions may differ from international standards

Sources considered but not used

Source	Reason for Exclusion
Transparency International CPI	Single-dimension (corruption only), different methodology pre-2012, less granular
Mo Ibrahim Index	Africa-only (no comparison countries outside continent), starts 2007

Selected Indicators

We use four primary governance indicators with theoretically-grounded weights reflecting their hypothesized relevance to economic outcomes:

Indicator Code	Indicator Name	Weight	Justification
GE.EST	Government Effectiveness	40%	Most direct measure of state capacity to implement policies affecting economic activity
RQ.EST	Regulatory Quality	25%	Directly affects business environment, investment decisions, and sector development
RL.EST	Rule of Law	20%	Contract enforcement, property rights, and judicial quality are foundational to economic transactions
CC.EST	Control of Corruption	15%	Corruption acts as a tax on economic activity and distorts resource allocation

Composite Score Calculation

Handling Missing Data: For years where any component is missing, the composite score is set to NaN rather than imputed, to maintain data integrity.

Supplementary Indicators (Weight = 0%)

These indicators are collected but not included in the primary composite score. They are available for sensitivity analysis:

Indicator Code	Indicator Name	Reason for Exclusion from Composite
VA.EST	Voice and Accountability	Measures political participation and media freedom; less directly linked to economic management capacity
PV.EST	Political Stability	Important for investment climate but conflates with security issues beyond governance quality

Indicator Scale and Interpretation

• Units: Standard normal distribution (approximately -2.5 to +2.5)
• Mean: 0 (global average)
• Interpretation: Higher values = better governance
• Nigeria's typical range: -1.5 to -0.8 (below global average)

Weight Sensitivity Analysis

Scheme	GE	RQ	RL	CC	Rationale
Primary (used)	40%	25%	20%	15%	Theory-based, economic outcome focus
Equal weight	25%	25%	25%	25%	Agnostic, no a priori assumptions
Corruption focus	20%	20%	20%	40%	For analysis emphasizing rent-seeking
Investment climate	30%	35%	25%	10%	For FDI-focused analysis

Core Sectors (Per Research Design)

Sector	Primary Indicator	Code	Unit	Justification
Oil & Gas Revenue	Oil rents (% of GDP)	NY.GDP.PETR.RT.ZS	% of GDP	Captures petroleum sector's contribution; critical given Nigeria's oil dependence
Agriculture	Agriculture value added	NV.AGR.TOTL.KD	Constant 2015 US$	Largest employer; real value added shows actual output growth
Manufacturing	Manufacturing value added	NV.IND.MANF.KD	Constant 2015 US$	Industrial diversification indicator; sensitive to policy environment
Power Generation	Access to electricity	EG.ELC.ACCS.ZS	% of population	Infrastructure proxy; power access is binding constraint on other sectors
Telecommunications	Mobile subscriptions per 100	IT.CEL.SETS.P2	Per 100 people	Services sector dynamism; rapid growth sector for benchmarking
Non-Oil Exports	Manufactures exports	TX.VAL.MANF.ZS.UN	% of total	Diversification away from oil; structural transformation indicator

Supplementary Sectors

Sector	Primary Indicator	Code	Justification
Services	Services value added	NV.SRV.TOTL.KD	Largest GDP component in modern economies; captures banking, telecom, trade
GDP	GDP constant dollars	NY.GDP.MKTP.KD	Aggregate benchmark; used for normalization and counterfactual baseline
Investment	FDI net inflows (% GDP)	BX.KLT.DINV.WD.GD.ZS	External validation of governance quality; investors respond to institutional environment

Indicator Selection Criteria

1. Availability: Data must exist for Nigeria and comparison countries for the study period
2. Comparability: Consistent definition across countries (World Bank standardization)
3. Relevance: Clear theoretical link to governance quality
4. Granularity: Annual frequency for time series analysis
5. Currency: Updated through 2022-2023 where possible

Comparison Countries

Country	Code	Selection Rationale
Nigeria	NGA	Focus country
Brazil	BRA	Large emerging economy, federal system, commodity exporter, similar governance trajectory periods
Argentina	ARG	Commodity exporter, governance volatility, economic cycles useful for comparison
South Africa	ZAF	Largest African economy post-Nigeria, similar development challenges, governance transition history
Egypt	EGY	Large African/MENA economy, oil/gas sector, governance transitions

Selection Methodology

Comparison countries were selected using the Synthetic Control Method criteria:

1. Structural similarity: Large emerging economies with commodity dependence
2. Governance variation: Countries that have experienced governance quality changes (for causal identification)
3. Data availability: Full WGI and WDI coverage for study period
4. Non-interference: Countries whose economies are not directly causally linked to Nigeria's

Countries Considered but Excluded

Country	Reason for Exclusion
Ghana	Too small relative to Nigeria; governance trajectory too different
Kenya	Smaller economy; different structural composition
Indonesia	Oil exporter but governance trajectory too stable for comparison
Venezuela	Extreme governance collapse creates outlier effects; data quality issues
Saudi Arabia	Not comparable governance structure (monarchy)

Study Period

Primary period: 1996 - 2023 (28 years)

Period	Years	Significance
Pre-democracy baseline	1996-1998	Final military rule years; WGI baseline available
Fourth Republic	1999-2023	Democratic governance period; primary analysis window

Justification for Start Year (1996)

• First year of WGI data availability
• Captures final Abacha regime period for baseline
• Enables before/after analysis of democratic transition (1999)

Justification for End Year (2023)

• Most recent year with substantial WDI data availability
• Captures beginning of Tinubu administration
• Some 2023 data may be preliminary estimates

Data Frequency

Dataset	Native Frequency	Notes
WGI Governance	Annual (biennial pre-2002)	1996, 1998, 2000, 2002 only; annual from 2003
WDI Economic	Annual	Full annual coverage

Implication: Governance data for 1997, 1999, 2001 is unavailable from source. These years are treated as missing (not interpolated) in primary analysis.

Collection Method

Data was collected programmatically using the wbgapi Python library (World Bank API wrapper).

• Script: scripts/pull_worldbank_data.py
• Execution date: January 11, 2026
• Python version: 3.10+

API Parameters

# Governance indicators
wb.db = 3  # WGI database
indicators = ["CC.EST", "GE.EST", "RQ.EST", "RL.EST", "VA.EST", "PV.EST"]

# Economic indicators  
wb.db = 2  # WDI database
indicators = [34 WDI indicators]

# Query parameters
economies = ["NGA", "BRA", "ARG", "ZAF", "EGY"]
time = range(1996, 2024)

Data Processing Pipeline

1. Raw API Response
2. Parse to DataFrame (wide format: years as columns)
3. Reshape to long format (year, economy, indicator, value)
4. Clean year column (extract from "YR2000" format)
5. Remove missing values (NaN)
6. Save to CSV (raw data)
7. Standardization script (scripts/standardize_data.py)
8. Calculate composite scores
9. Merge governance + economic by country-year
10. Add presidential context (Nigeria only)
11. Save processed datasets

Standardization Transformations

Transformation	Purpose	Applied To
Composite score calculation	Create single governance metric	Governance indicators
Pivot to wide format	Enable time series analysis	Master datasets
Presidential tagging	Contextualize findings	Nigeria datasets
Country name mapping	Readability	All datasets

No Transformations Applied

The following transformations were deliberately NOT applied to preserve data integrity:

Transformation	Reason for Exclusion
Interpolation of missing years	Would create artificial data; biennial WGI gaps are documented source limitation
Inflation adjustment	WDI "constant 2015 US$" series already inflation-adjusted
Seasonal adjustment	Annual data; not applicable
Outlier removal	No outliers removed; all values are source-reported
Normalization/scaling	Preserved original units for interpretability

Derived Variables

Variable	Derivation	Purpose
composite_score	Weighted sum of 4 governance indicators	Single governance metric for regression
president	Lookup by year from presidential roster	Contextual analysis
party	Lookup by year from presidential roster	Political economy analysis

Known Limitations

Limitation	Impact	Mitigation
Biennial WGI data (1996-2002)	Missing years for early period	Clearly documented; sensitivity analysis with interpolation
WGI perception-based	Measures perceptions, not objective governance	Industry standard; no superior alternative exists
WGI confidence intervals	Point estimates have uncertainty	Available in source data; can be incorporated in robustness checks
Aggregation across sources	WGI methodology changes over time	Kaufmann et al. designed for comparability; noted as limitation
Preliminary 2023 data	Some economic indicators are estimates	Flag in analysis; may update when final data released
Missing electricity production	API error for EG.ELC.PROD.KH	Use electricity access as proxy; noted limitation for power sector analysis

Data Quality Checks Performed

Check	Method	Result
Temporal continuity	Visual inspection of time series	✓ No unexpected gaps beyond documented biennial years
Cross-country comparability	Summary statistics comparison	✓ All countries have similar coverage
Outlier detection	Z-score analysis	✓ No statistical outliers; large changes reflect real events
Unit verification	Cross-reference with World Bank metadata	✓ All units as expected
Record count validation	Compare expected vs actual	✓ 5,226 total records (governance: 750, economic: 4,476)

Potential Sources of Bias

Bias Type	Concern	Assessment
Selection bias	Choice of comparison countries	Mitigated by systematic selection criteria; sensitivity to country set
Measurement bias	WGI perception data may lag actual governance changes	Acknowledged; year-over-year analysis accounts for this
Survivorship bias	Only examining countries with full data	Not applicable; all major comparison candidates have data
Publication bias	Selecting indicators that show relationships	Mitigated by pre-specifying indicators in research design

Reproduction Steps

To reproduce the data collection and processing:

# 1. Clone repository
git clone [repository-url]
cd nigeria-governance-economic-analysis

# 2. Create virtual environment
python -m venv venv
source venv/bin/activate

# 3. Install dependencies
pip install -r requirements.txt

# 4. Pull World Bank data
python scripts/pull_worldbank_data.py

# 5. Standardize data
python scripts/standardize_data.py

Dependencies

pandas>=2.0.0
wbgapi>=1.0.0
openpyxl>=3.0.0

Version Control

• All scripts are version-controlled in the repository
• Data files are excluded from version control (see .gitignore)
• Raw data should be re-pulled for any reproduction to ensure consistency

President	Party	Start	End	Notes
Olusegun Obasanjo	PDP	1999	2007	First Fourth Republic president; two terms
Umaru Yar'Adua	PDP	2007	2010	Died in office
Goodluck Jonathan	PDP	2010	2015	Completed Yar'Adua term + one term
Muhammadu Buhari	APC	2015	2022	First opposition victory; two terms
Bola Tinubu	APC	2023	Present	Current president

Note: Pre-1999 period under military rule (Sani Abacha until 1998, Abdulsalami Abubakar 1998-1999).

References

1. Kaufmann, D., Kraay, A., & Mastruzzi, M. (2010). The Worldwide Governance Indicators: Methodology and Analytical Issues. World Bank Policy Research Working Paper No. 5430.
2. World Bank. (2024). World Development Indicators. https://databank.worldbank.org/source/world-development-indicators
3. World Bank. (2024). Worldwide Governance Indicators. https://info.worldbank.org/governance/wgi/