IMF-尼日利亚的财政预测错误（英）-2025.7_16页_1mb

Fiscal Forecasting Errors in Nigeria: Summary

Core Content

This paper analyzes fiscal forecasting errors in Nigeria from 2011 to 2023, focusing on total revenues, expenditures, and the fiscal deficit. It highlights the persistent optimism bias in budget projections and its impact on fiscal policy credibility and public finances.

Main Points and Key Findings

1. Revenue Forecasting Errors

• Consistent Optimism Bias: Revenue forecasts consistently overestimated actual outturns, with the exception of 2020.
• Magnitude of Errors: On average, revenue forecast errors were 1.8% of GDP or 36% of actual revenues.
• Recent Trends: Errors decreased slightly in recent years to 1.1% of GDP or 28% of revenues.
• Primary Cause: Errors in oil revenue projections were the main driver, due to overly optimistic oil production forecasts.
• Subsidies and Forecast Errors: Large oil subsidies in certain years (e.g., 2011, 2021–2022) may have contributed to forecast errors through unbudgeted fiscal deductions.

2. Oil Revenue Forecast Errors

• Overestimation: Oil revenue forecasts were consistently higher than actual outturns, except in 2020.
• Error Size: Average forecast errors were 1.1% of GDP and 61% of oil revenues.
• Heterogeneity: Errors varied significantly over the years, with smaller errors in 2012–2016 and larger errors in 2017–2019.
• Reasons for Shortfall: Shortfalls were attributed to low oil lifting volumes, crude oil theft, pipeline vandalism, and illegal bunkering. However, the budget reports lacked detailed breakdowns of these factors.
• Benchmark Price: The benchmark price used for oil revenue projections was more conservative than actual global oil prices, which helped offset some forecast optimism.

3. Non-Oil Revenue Forecast Errors

• Taxes as Main Source: Non-oil revenues are primarily derived from VAT, CIT, and Customs taxes.
• VAT Forecast Errors: Prior to 2020, VAT forecasts were optimistic, but performance reversed after that.
• CIT Forecast Errors: CIT forecasts showed optimism bias until 2020, followed by a surge in actual revenues not captured in projections.
• Customs Revenue: Customs revenue forecasts remained optimistic, but actual outturns did not match these projections, especially in 2022 and 2023.
• Net Non-Oil Revenues: Forecast errors in net non-oil revenues were larger than those in tax revenues, suggesting that non-tax revenue streams also contributed to optimism bias.

4. Expenditure Forecasting Errors

• Positive Forecast Errors: Federal government expenditure forecasts were consistently optimistic, with an average error of 0.8% of GDP.
• Capital Expenditures: Capital expenditure forecasts were particularly optimistic, with average errors exceeding 70% of actual outturns.
• Underutilization: Capital budgets were often underutilized, leading to the use of concurrent budgets. This reflects capacity constraints among MDAs to execute capital projects.
• Expenditure Compression: The government frequently reduced recurrent expenditures to offset revenue shortfalls, which limited the impact of revenue optimism on the fiscal deficit.

5. Fiscal Deficit Forecast Errors

• Trend in Errors: Forecast errors in the fiscal balance increased during 2017–2021 but have since decreased.
• Underperformance of Expenditures: A significant part of the shrinking forecast errors was due to underexecution of expenditures, not necessarily due to higher revenues.
• Central Bank Financing: Large forecast errors in the fiscal balance coincided with increased use of central bank financing for the deficit, indicating potential reliance on emergency measures.

Policy Recommendations

• Enhance Forecasting Capacity: Strengthen the macro-fiscal unit's ability to produce accurate forecasts.
• Publish Performance Reviews: Regularly publish internal and external forecasts performance reviews to improve transparency and accountability.
• Improve Data Sharing: Ensure coordination between fiscal departments and formalize data exchange mechanisms through memoranda of understanding.
• Staff Training: Provide training and tools that align with the skill sets of forecasting staff.
• Political Commitment: Increase political commitment to budget targets through periodic reviews and external assessments to reduce political pressure on forecasters.
• Institutional Reforms: Implement institutional reforms to improve public financial management, such as electronic payroll systems and Treasury Single Account usage.

Conclusion

• Impact of Forecast Errors: Persistent optimism in revenue and expenditure forecasts undermines the credibility of the budget as a policy guide.
• Need for Realism: Realistic fiscal forecasts are essential for effective resource allocation, fiscal discipline, and public trust.
• Cross-Country Insights: Other African countries, such as Kenya and Malawi, have improved forecasting accuracy through ex post assessments and transparency measures.

Key Information

• Period Analyzed: 2011–2023
• Main Aggregates: Total revenues, expenditures, fiscal deficit
• Sources: Nigeria Ministry of Budget and Economic Planning, IMF staff calculations
• JEL Codes: E62; H61; H68
• Keywords: Budget forecasting; forecasting errors; budget projections; fiscal forecasting

Visual Aids

• Figure 1: Revenue Forecast Errors (Total Revenues)
• Figure 2: Oil Price Forecast Errors
• Figure 3: Oil Revenue Forecast Errors and Subsidies
• Figure 4: VAT and Non-Oil Revenue Forecast Errors
• Figure 5: Nominal GDP Forecasts vs. WEO Estimates
• Figure 7: Recurrent Expenditures Forecast Errors
• Figure 8: Capital Expenditures Forecast and Outturn
• Figure 9: Fiscal Balance Forecast and Outturn
• Figure 10: Fiscal Balance Forecast Errors and Use of Ways and Means
• Figure 11: Average Revenue Forecast Errors (2012/13–2018/19)

References

• Battersby, B., & Lienert, M. I. (2021). Macro-Fiscal Management Practices in Eastern and Southern Africa. International Monetary Fund.