Senior non-oil Revenue Forecasting/Tax Incidence Analysis required in Nigeria

Title: Support to non-oil revenue forecasting and tax incidence analysis

Background

Nigerian economic and fiscal outlook continues to be vulnerable to shocks and oil-dependence. In recent years, the economy has been hit by the COVID-19 pandemic, a fall in global oil prices, increasing insecurity, and weak domestic oil production as well as low agricultural output. The fiscal space is limited by the need to service debts (101.5% of revenues in 2022) and vulnerable to fully realizing the fiscal transfers from the oil and gas sector, thus restricting public investments.  Despite recent reforms, Nigeria’s non-oil tax revenues underperform due to low tax rates, poor compliance, a narrow tax base, and high tax expenditures. Reforms introduced in 2020-2021 increased non-oil tax revenues from 2.3 percent of Gross Domestic Product (GDP) in 2020 to 3.7 percent of GDP in 2023 due to a rise in Value-Added Tax (VAT) rates, improvements in tax digitalization, and the unification of the exchange rate in 2023. Despite this increase, tax revenues in Nigeria remain very low compared to peers. Gaps at the level of the tax policy still exist. For example, the current VAT rate of 7.5% is the lowest rate in Africa. 

Global objective  
Currently, the department uses a cashflow forecasting model that primarily incorporates historical trends, GDP, and inflation to predict future revenue outcomes. However, this model has limitations, particularly in its ability to accommodate a broader range of variables and to align with the ongoing restructuring efforts within FIRS. Furthermore, for this model to be more accurate the FIRS team needs a more comprehensive understanding of tax incidence is essential to ensure that tax policies are equitable and do not disproportionately affect vulnerable populations. The objective of this assignment is to enhance the Department's capabilities in both revenue forecasting and tax incidence analysis.  

 Specific objective(s)    
The specific objectives are twofold:  - 
Result 1: To provide technical input and advice for improved accuracy and reliability of the tax revenue forecast system and tools in place (tool adequacy and methodology in place) - 

Result 2: Inform policy recommendations to enhance the equity and efficiency of the tax system, aligning with broader goals of sustainable development

The support, in the shape of assessment and recommendations, is expected to contribute to the 
optimisation of the existing software (R and Excel), to improve the accuracy of revenue forecasts 
and tax incident analysis that provides deeper insights into the distributional impacts of tax policies.

Location: Abuja, Nigeria

Start Date: 10/02/2025

End Date: 10/06/2025

Language: English

REQUIREMENTS 
Expertise 
Qualifications and skills required for the team: 
o At least, a Master degree in Economics, Finance, Data Science, Public Finance, or a related 
field; 
o Evidence of professional experiences in developing econometric modelling, forecasting methods, and data analysis tools using advanced statistical and econometric software (e.g., Excel, STATA, R, Python) and revenue forecasting models including machine-learning algorithms for economic forecasting; 
o Excellent communication and presentation skills, with the ability to convey complex technical information to non-specialist audiences. 

General professional experience of the team: 
o Minimum 12 years of professional experience in revenue forecasting, public finance management, or tax policy analysis within government institutions, international organizations, or academic settings; 

o At least, three proven experiences in conducting capacity assessments and developing training programs to improve forecasting and analysis skills, particularly in developing country contexts; 

o At least, one experience working in improving tax systems and revenue administration with senior government officials in West Africa, will be an advantage. 

Specific professional experience of the team: 
o Revenue Forecasting 
 Proven experience in evaluating and designing forecasting tools as well as assessing the capacity of revenue authorities or statistical departments; 
 Knowledge and application of machine-learning techniques for predictive modelling and pattern recognition to improve revenue forecasting accuracy will be an advantage. 

If you are interested, please submit your cv and daily fee rate to eu-fwc-siea@vjwinternational.coM.

Deadline for applications: 19th December 2024 @ 14:30PM GMT