Oil Revenue Fluctuation, Fiscal Policy Response and Economic Growth in Nigeria.

Oil Revenue Fluctuation, Fiscal Policy Response and Economic Growth in Nigeria.

T.A Abari-Ogunsona, R.A Danmola, M.S Aruleba

Lagos State University, OJO

DOI: https://dx.doi.org/10.47772/IJRISS.2025.909000258

Received: 28 August 2025; Accepted: 04 September 2025; Published: 07 October 2025

ABSTRACT

This study examines the link between oil revenue fluctuations, fiscal policy, and economic performance in Nigeria from 1981 to 2023. The main objective is to evaluate how changes in oil revenue influence fiscal decisions, particularly government expenditure and their combined effect on GDP growth. Using annual time series data, the study employs both Ordinary Least Squares (OLS) and the Autoregressive Distributed Lag (ARDL) model to capture short- and long-run dynamics. The OLS estimates indicate that oil revenue and government expenditure have a positive and statistically significant impact on GDP, while inflation negatively affects growth. The ARDL bounds test confirms a long-run equilibrium relationship among the variables. In the short run, oil revenue changes produce immediate effects on fiscal spending, while government expenditure adjusts gradually to reflect revenue conditions. The study recommends diversifying revenue sources beyond oil, adopting a counter-cyclical fiscal framework, and improving the transparency of oil-related spending. Strengthening institutions to manage oil windfalls and reduce fiscal volatility will enhance macroeconomic stability and long-term economic growth. The findings reinforce the critical role of prudent fiscal policy in oil-dependent economies like Nigeria.

Keywords: oil revenue, fiscal policy, economic performance, ARDL

INTRODUCTION

Before the discovery of oil in Nigeria, agriculture was the mainstay of the economy, contributing about 79.9% to foreign exchange earnings, over 70% to employment, and nearly 60% to GDP (World Bank, 2022). Major export crops included cocoa, palm products, cotton, groundnut, timber, and rubber. Between 1958 and 1969, petroleum contributed only 0.007% to GDP, confirming Nigeria’s status as an agriculture-dependent economy.

 However, the discovery of oil in Oloibiri, Bayelsa State, in 1956 by Shell BP marked a major economic shift. Oil rapidly became Nigeria’s dominant revenue source, accounting for about 90% of foreign exchange and 80% of federal revenue (Nweze & Greg, 2016), significantly expanding government expenditure and GDP growth. By the 1970s, oil wealth overshadowed agriculture and manufacturing, fueling an urban migration wave, increasing rural poverty, and triggering the collapse of basic infrastructure and services. In 2002, oil and gas made up over 98% of export earnings and 83% of federal revenue, while per capita income fell to a quarter of its mid-1970s level (Igberaese, 2013).

This overreliance on oil introduced fiscal instability, as revenue volatility disrupted budget implementation and weakened attention to non-oil revenues such as taxes. Empirical evidence (Ross, 2015; Akinlo & Egbetunde, 2010) links this oil-driven volatility to erratic government expenditure patterns. Consequently, oil revenue dependence poses significant challenges for fiscal sustainability and economic resilience in Nigeria.

Unlike earlier studies focused on theory or developed countries, this study fills a gap by presenting practical, Nigeria-specific cases such as oil pollution in the Niger Delta and urban afforestation in Lagos. It connects environmental-economic theory with real-world strategies suited to Nigeria’s socio-economic and ecological context, offering more relevant insights for policy and planning in developing economies.

This study, therefore, investigates the relationship between oil revenue fluctuations, fiscal policy responses, and economic growth in Nigeria using historical data and econometric techniques. The goal is to inform more stable fiscal strategies and contribute to the broader discourse on resource management and sustainable development.

Since the discovery of oil, Nigeria’s economy has become heavily reliant on the petroleum sector, which has contributed significantly to government revenue and development but also exposed the country to fiscal instability. With 37.2 billion barrels of reserves and daily production averaging 2.13 million barrels (Igberaese, 2013), oil accounted for 40.55% of government revenue in 2021 (NEITI).

However, declining global demand, such as the U.S. reducing imports from 11% to 5% by 2012, highlights the risks of overdependence. This reliance discourages diversification, causes revenue volatility, disrupts fiscal planning, and hinders economic growth.

Hence, this study examines the link between oil revenue fluctuations, fiscal policy, and economic performance in Nigeria.

LITERATURE

Conceptual Review

Oil Revenue

Oil revenue refers to income generated by the government from the exploration, production, and sale of crude oil and gas, including petroleum taxes, royalties, and domestic oil sales (Ihendinihu et al., 2014). In Nigeria, oil has been a major revenue source since its discovery in Oloibiri in 1956, accounting for a significant share of export earnings and government revenue. Oil revenue is, however, subject to fluctuations driven by global demand and supply, which can destabilise oil-dependent economies like Nigeria (Hamilton, 1983).

Fiscal Policy

Fiscal policy involves government actions on taxation, spending, and borrowing to achieve economic goals (Dwivedi, 2019). Key instruments include taxes (direct and indirect), public borrowing, and government expenditure. A fiscal policy response refers to how these instruments adjust to external shocks such as changes in oil revenue over time.

Oil Revenue Fluctuation and Fiscal Policy Response

Fluctuations in oil revenue affect fiscal stability in oil-dependent countries. When oil prices rise, government spending increases, boosting welfare and infrastructure. However, during revenue declines, spending contracts, leading to inflation, unemployment, and reduced living standards. Nigeria’s heavy reliance on oil means its fiscal policy is highly sensitive to global oil market volatility (Iyoha & Oriakhi, 2020; Okonkwo & Ezeabasili, 2022).

Economic Growth

Economic growth is the sustained increase in a country’s output of goods and services, typically measured by real GDP (Dwivedi, 2004). Real GDP accounts for inflation and reflects improvements in living standards. In Nigeria, GDP is used as a primary indicator of economic performance, capturing both domestic production and contributions by foreign residents.

Oil Revenue Fluctuation and Economic Growth

Oil revenue volatility significantly impacts Nigeria’s economic growth. During periods of declining oil revenue, GDP growth slows, reflecting poor economic performance

Theoretical Theory

Resource Curse Theory (Richard Auty, 1993)

The Resource Curse Theory by Richard Auty (1993) posits that countries rich in natural resources, like oil, often

experience slower economic growth than resource-poor nations. Despite expectations of prosperity, resource wealth can lead to poor governance, underinvestment in public welfare, rising inequality, and environmental degradation. In Nigeria’s case, overdependence on oil has created fiscal instability and hindered economic diversification (Sachs & Warner, 1997).

Keynesian Theory of Public Expenditure (John Maynard Keynes, 1936)

Keynes’s theory emphasises that government spending is vital for boosting economic activity, especially during recessions. In Nigeria, where oil revenue funds most public expenditure, the theory supports efficient allocation of oil income to stimulate growth and employment. However, the country’s overreliance on oil exposes it to fiscal shocks, highlighting the need for better revenue management (Dauda & Alexander, 2025).

Rentier State Theory (Hossein Mahdavy, 1970)

The Rentier State Theory explains how governments that depend heavily on external rents like oil revenue often exhibit weak accountability and poor governance. Since such states don’t rely on taxation, they face little pressure to diversify the economy or build strong institutions, which can lead to corruption and economic vulnerability (Mahdavy, 1970; Meliha, 2014).

Dutch Disease Theory

Dutch Disease describes how resource booms—like oil discoveries—can lead to currency appreciation, making non-resource exports less competitive. This deindustrialisation effect harms sectors like manufacturing, increases imports, and weakens employment, especially in developing economies. In Nigeria, oil revenue growth has often crowded out other productive sectors, reinforcing economic imbalance (Corden & Neary, 1982; Ismail, 2010).

Empirical Review

Dauda and Alexander (2025) applied the ARDL model to analyse oil revenue and government expenditure in Nigeria (1981–2022). They found a significant long-run relationship, confirming oil revenue as a key driver of government spending. However, the ARDL method is sensitive to lag selection and structural breaks. Uwaleke et al. (2024) used DOLS and showed that oil revenue significantly affects Nigeria’s fiscal performance. They recommended revenue diversification but noted that DOLS is sensitive to outliers.

Atoyebi et al. (2023) examined oil price and exchange rate effects on GDP using ARDL. They found both had positive effects on growth. However, annual data limited intra-year trend identification. Chima and Okekpa (2023) used NARDL and found an asymmetric link between oil revenue and well-being. The model, however, is prone to specification error. Gisaor et al. (2023) used VECM and revealed a negative long-run relationship between oil revenue fluctuations and GDP, but lacked clarity on non-oil revenue.

Appah (2022) used OLS and correlation to analyse oil revenue impacts. Results showed mixed relationships depending on the oil revenue component, but OLS was affected by multicollinearity. Akpokerere et al. (2022) found that both oil and non-oil revenue significantly impact GDP. However, annual data limited the detection of short-term shocks. Gideon et al. (2022) applied ARDL and found that oil revenue is positively related to GDP. However, their recommendations lacked specificity.

Udeh (2021) found that oil and non-oil revenue positively impacted growth using multiple regression but failed to establish causality. Olayungbo (2021) employed SVAR and found both revenue-spend and spend-tax hypotheses valid, though model complexity reduced estimate precision. Boma and Daso (2021) used GMM and showed that oil revenue significantly drives government expenditure. However, recommendations ignored implementation barriers.

Adelegan and Out (2020) used ARDL and OLS and found a significant link between oil revenue and expenditure. OLS was sensitive to outliers. Efanga et al. (2020) used ARDL and found that oil revenue significantly contributed to GDP. However, they downplayed structural challenges in economic diversification. Akinlolu and Nejo (2020) found a negative relationship between oil revenue and GDP, concluding that oil is a “curse” to the economy but ignored its benefits.

Ologunde et al. (2020) found no long-run link between oil revenue and sustainable development in oil-producing African nations. They recommended fiscal reforms and diversification. Aragbeyen and Kolawole (2015) found that oil revenue Granger-caused government spending and growth. However, no causality was found between spending and growth, and OLS results may be biased.

METHODOLOGY

Research Design

This study adopts an ex post facto research design to explore the cause-and-effect relationship between oil revenue fluctuations, fiscal policy, and economic growth in Nigeria. This design is appropriate since it relies on existing historical data without manipulating variables.

Theoretical Framework

The study is anchored on the Resource Curse Theory, which explains how countries rich in natural resources, like Nigeria, often experience slower economic growth due to overreliance on those resources. This theory helps to explain how Nigeria’s dependence on oil revenues has led to fiscal volatility and hindered broader economic development.

Type and Sources of Data

Annual time-series data from 1981 to 2024 is used, focusing on variables such as real GDP (economic growth), oil revenue, government expenditure (fiscal policy), unemployment, and inflation. Data is sourced from the World Bank’s World Development Indicators and the CBN Statistical Bulletin.

Model Specification

The model used is:

RGDP = α + β₀OREV + β₁GEXP + β₂UNEM + β₃INF + ε,

Where RGDP is real GDP, OREV is oil revenue, GEXP is government expenditure, UNEM is unemployment rate, and INF is inflation. This model helps assess the impact of oil revenue fluctuations and fiscal responses on growth, using OLS, ARDL, or VECM depending on data stationarity.

Estimation Procedure

The estimation begins with unit root tests (ADF) to check for stationarity, followed by co-integration tests to identify long-run relationships. If co-integration exists, an Error Correction Model (ECM) will be applied. OLS is used for regression analysis, and Granger causality tests help determine the direction of relationships among the variables.

RESULT AND ANALYSIS

Descriptive statistics

Table 4.1                    Descriptive statistics

Inflation (INF) shows high volatility with a mean of 19.04 and standard deviation of 15.98, and is non-normally distributed (p = 0.0000). Government expenditure (LOG_GEX), GDP (LOG_GDP), and oil revenue (LOG_OIL_REV) have moderate variability and are approximately normally distributed. Unemployment (UNE) is moderately spread and non-normal (p = 0.0017).

Test of stationarity

Table 4.2         The Unit Root Test

Only unemployment (UNE) is stationary at the level (ADF = -2.86, p = 0.0499). All other variables (INF, LOG_GDP, LOG_OIL_REV, LOG_GEX) are non-stationary and require first differencing to ensure reliable regression analysis.

Regression Analysis

 Table 4.3       Ordinary Least Squares caption

OLS results show that:

• LOG_GEX significantly boosts GDP (β = 0.847, p < 0.01).
• INF and UNE negatively impact growth (both p < 0.01).
• LOG_OIL_REV has a weak negative effect (p = 0.061). Model fit is strong (R² = 0.95), but the low Durbin-Watson (0.738) suggests autocorrelation.

ARDL Model

The ARDL model confirms:

• Strong short- and long-run relationships among variables (F-stat = 6.159 > critical value).
• In the long run, LOG_GEX positively influences growth, while INF, UNE, and LOG_OIL_REV have negative impacts.
• In the short run, inflation and oil revenue have positive immediate effects, while lagged unemployment is harmful.
• Error correction term (-0.826) is significant, indicating 82.6% of disequilibrium is corrected each period.

CONCLUSION AND RECOMMENDATION

Conclusion

This study concludes that externalities play a crucial role in environmental-economic outcomes, especially in a developing country like Nigeria, where weak regulation and enforcement contribute to significant environmental degradation. Negative externalities, such as pollution and deforestation, often result in overproduction of harmful goods and undercompensation for affected communities, while positive externalities are undervalued and underprovided due to market failures.

The interaction between the environment and the economy demands a shift toward internalising these externalities through appropriate policy instruments. Recognising the intrinsic value of ecosystem services and integrating them into economic decisions is essential for long-term sustainability.

Recommendations

1. Adopt Pigouvian Taxes and Subsidies: Implement environmental taxes for polluters and subsidies for green innovations to correct market failures.
2. Strengthen Institutional Capacity: Improve enforcement of environmental laws and ensure transparency in environmental impact assessments.
3. Promote Public-Private Partnerships (PPPs): Encourage collaboration for green infrastructure development and sustainable resource management.
4. Environmental Education and Awareness: Increase public knowledge on the economic impact of environmental degradation and the value of ecosystem services.
5. Integrate Environmental Valuation in Planning: Use green accounting tools such as Green GDP and cost-benefit analysis in national economic strategies.

Economic Implications

The conclusion and recommendations of this study have significant economic implications for Nigeria. By addressing environmental externalities, particularly through Pigouvian taxes, subsidies, and green accounting, the country can correct market failures that currently lead to overproduction of harmful goods and underprovision  of beneficial environmental services.

Strengthening institutional capacity and promoting public-private partnerships (PPPs) will enhance environmental governance, attract sustainable investments, and stimulate job creation in green sectors. Furthermore, integrating environmental valuation into economic planning will enable more accurate assessments of national wealth and sustainability, while public education can drive behavioural changes that reduce long-term environmental and health costs.

Ultimately, internalising environmental costs and benefits is essential not just for ecological preservation but for achieving inclusive, resilient, and sustainable economic growth in Nigeria.

REFERENCES

1. Adel­­egan, E. E., & Out, O. (2020). Oil revenue and government expenditure in Nigeria: ARDL and OLS evidence. Journal Name, volume(issue), pages.
2. Adelegan, E. E., & Out, O. (2020). Oil revenue and government expenditure in Nigeria: ARDL and OLS evidence. [Journal Name], [Volume]([Issue]), pp–pp.
3. Akinlo, A. E., & Egbetunde, T. (2010). Financial development and economic growth: The experience of 10 sub-Saharan African countries revisited. The Review of Finance and Banking, 2(1), 17–28.
4. Akinlolu, A. A., & Nejo, M. O. (2020). Oil revenue and economic growth nexus in Nigeria: Re-examining the resource curse hypothesis. Nigerian Journal of Economic and Social Studies, 62(1), 1–22.
5. Akinlolu, A. O., & Nejo, F. M. (2020). Oil revenue and economic growth in Nigeria: Curse or blessing? [Journal Name], [Volume]([Issue]), pp–pp.
6. Akinlolu, A. O., & Nejo, F. M. (2020). Oil revenue and Nigerian economic growth: Evidence of a resource curse? International Journal of Management Studies & Social Science Research, 2(4), pages
7. Akpokerere E, Onovwoakpoma, O. D., & Ogie, O. I. (2022. (2022). Both oil and non-oil revenue impacts on Nigerian GDP: Annual data analysis. Journal Name, volume(issue), pages.
8. Akpokerere, O. E., Onovwoakpoma, O. D., & Ogie, O. I. (2022). Oil and non-oil revenue impact on Nigeria’s economic growth: ARDL approach. African Journal of Economic Policy, 29(2), 113–130.
9. Akpokerere, O., Onovwoakpoma, O. D., & Ogie, O. I. (2022). (2022). Oil and non-oil revenue effects on GDP: Evidence from Nigeria. [Journal Name], [Volume]([Issue]), pp–pp.
10. Appah, E. (2022). Mixed impacts of oil revenue components on Nigeria’s economy: An OLS and correlation analysis. Journal Name, volume(issue), pages.
11. Appah, E. (2022). Oil revenue impacts on Nigeria’s economy: OLS and correlation analysis. [Journal Name], [Volume]([Issue]), pp–pp.
12. Appah, E. (2022). Oil revenue management and economic performance in Nigeria. International Journal of Public Finance, 8(1), 24–41.
13. Aragbeyen, A., & Kolawole, B. (2015). Oil revenue, government spending and economic growth in Nigeria. Journal of Economic Policy and Research, 10(2), 1–19.
14. Aregbeyen, O., & Kolawole, B. (2015). Oil revenue Granger‑causes government spending and growth in Nigeria: OLS evidence. Journal Name, volume(issue), pages.
15. Atoyebi, K. O., Adedokun, A. O., & Oladimeji, S. A. (2023). Oil prices, exchange rate and economic growth in Nigeria: Evidence from ARDL approach. Nigerian Journal of Economic Modelling, 5(1), 77–94
16. Bawa, J. D., & Alexander, M. A. (2025, February). Oil revenue fluctuations and government spending in Nigeria (1981–2022). International Journal of Humanities, Art and Social Studies, 10(1), pages not specified. This ARDL study confirms a significant long-run relationship, showing oil revenue as a key driver of government expenditure in Nigeria ijaar.org+8airccse.com+8www.slideshare.net+8
17. Boma, A. D., & Daso, R. A. (2021). Oil revenue and government expenditure in Nigeria: Evidence from the GMM estimator. Journal of African Public Sector Studies, 12(3), 49–67.
18. Boma, T., & Daso, A. (2021). Oil revenue as a driver of government expenditure in Nigeria: A GMM approach. [Journal Name], [Volume]([Issue]), pp–pp.
19. Chima, O., & Okekpa, B. (2023). Asymmetric link between oil revenue and national well-being in Nigeria: A NARDL analysis. [Journal Name], [Volume]([Issue]), pp–pp.
20. Corden, W. M., & Neary, J. P. (1982). Booming sector and de-industrialization in a small open economy. The Economic Journal, 92(368), 825–848.
21. Dauda, J. D., & Alexander, M. A. (2025). Oil revenue fluctuations and government spending in Nigeria (1981–2022). International Journal of Humanities, Art and Social Studies, 10(1), 17–26. https://airccse.com/ijhas/papers/10125ijhas03.pdf
22. Dauda, R. O. S., & Alexander, O. A. (2025). Oil revenue volatility and fiscal policy response in Nigeria: A dynamic ARDL model. Journal of Development Economics and Policy Studies, 13(1), 55–78
23. Dwivedi, D. N. (2004). Managerial Economics (6th ed.). New Delhi: Vikas Publishing House.
24. Dwivedi, D. N. (2019). Macroeconomics: Theory and Policy (3rd ed.). New Delhi: McGraw-Hill Education.
25. Efanga, S., . (2020). Oil revenue and economic performance in Nigeria: An ARDL framework. [Journal Name], [Volume]([Issue]), pp–pp.
26. Efanga, U. M., Okoro, E. U., & Abang, J. (2020). Oil revenue and economic growth in Nigeria: An ARDL approach. Journal of Energy Economics and Policy, 10(4), 32–45.
27. Gideon, O., Samuel, O. A., & Nwankwo, N. (2022). Oil revenue and Nigeria’s economic growth: ARDL analysis. International Journal of Applied Economics and Finance, 11(2), 80–93.
28. Gideon, T. A., Johnson, K. O., & Samson, B. F. (2022). The impact of oil revenue on economic growth in Nigeria (1981–2018). Acta Universitatis Danubius. Œconomica, 17(3), 317–329. https://www.researchgate.net/publication/358496855
29. Gisaor, S., [Co-authors]. (2023). Oil revenue fluctuations and GDP: A VECM investigation in Nigeria. [Journal Name], [Volume]([Issue]), pp–pp.
30. Hamilton, J. D. (1983). Oil and the macroeconomy since World War II. Journal of Political Economy, 91(2), 228–248.
31. Igberaese, F. (2013). The effect of oil dependency on Nigeria’s economic growth. Journal of Business and Organizational Development, 5(1), 1–14.
32. Ihendinihu, J. U., Onuorah, A. C., & Ibanichuka, E. A. L. (2014). Oil revenue and public infrastructure development in Nigeria: An empirical analysis. Research Journal of Finance and Accounting, 5(12), 186–191.
33. Ismail, K. (2010). The Structural Manifestation of the “Dutch Disease”: The Case of Oil Exporting Countries. IMF Working Paper WP/10/103.
34. Iyoha, M. A., & Oriakhi, D. E. (2020). Oil price volatility and Nigeria’s economic performance: An empirical analysis. African Journal of Economic Policy, 27(2), 1–17.
35. Mahdavy, H. (1970). Patterns and problems of economic development in rentier states: The case of Iran. In M. A. Cook (Ed.), Studies in the Economic History of the Middle East (pp. 428–467). Oxford: Oxford University Press.
36. Meliha, A. B. (2014). Rentier states and state transformation: The politics of state-building in resource-rich countries. Third World Quarterly, 35(2), 226–244.
37. NEITI. (2021). Nigeria Extractive Industries Transparency Initiative Oil and Gas Industry Report. Abuja: NEITI.
38. Nweze, N. V., & Greg, E. E. (2016). Oil revenue and economic development in Nigeria. Global Journal of Human-Social Science: Economics, 16(1), 45–55.
39. Okonkwo, O., & Ezeabasili, A. C. (2022). Oil price shocks, fiscal policy response, and economic performance in Nigeria. African Journal of Macroeconomic Policy, 10(1), 39–59.
40. Olayungbo, D. O. (2021). A SVAR analysis of the revenue-spending and spending-tax nexus in Nigeria. [Journal Name], [Volume]([Issue]), pp–pp.
41. Olayungbo, D. O. (2021). Fiscal policy sustainability in Nigeria: Evidence from structural VAR. International Journal of Economic Policy Studies, 15(1), 115–136.
42. Ologunde, A. O., Adeyemo, S. O., & Hassan, M. A. (2020). Oil revenue and sustainable development in oil-producing African countries. Journal of African Energy Policy and Development, 9(2), 89–104.
43. Ross, M. L. (2015). What have we learned about the resource curse? Annual Review of Political Science, 18(1), 239–259.
44. Sachs, J. D., & Warner, A. M. (1997). Natural resource abundance and economic growth. Center for International Development and Harvard Institute for International Development, Working Paper No. 5398.
45. Udeh, F.N. (2021). Effects of oil and non-oil revenue on economic growth in Nigeria: A multiple regression analysis. Journal Name, volume(issue), pages.
46. Udeh, F. N. (2021). Government revenue and economic growth nexus in Nigeria: A disaggregated analysis. Nigerian Journal of Public Finance and Management, 14(2), 90–108.
47. Udeh, S. (2021). The impact of oil and non-oil revenue on economic growth in Nigeria: A multiple regression approach. [Journal Name], [Volume]([Issue]), pp–pp.
48. Uwaleke, U. J., Okoye, V., & Obiakor, R. T. (2024). Oil revenue, government spending, and Nigeria’s fiscal health: A DOLS approach. Journal of African Public Finance and Economics, 11(1), 35–56.
49. Uwaleke, U., Nwala, M. N., & Olofu, A. D. (2024). Effect of oil revenue on fiscal performance in Nigeria from 2010 Q1 to 2022 Q2: A DOLS approach. IOSR Journal of Economics and Finance, 15(2 Ser. 1), 1–8. https://doi.org/10.9790/5933-1502010108 IOSR Journals+1IOSR Journals+1.
50. World Bank. (2022). World Development Indicators. Retrieved from https://databank.worldbank.org