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The Impact of Redistribution of Income on Nigeria Economic Growth
and Stability
Monsuru Adedeji, Olukotun
1
Lukumon Akande, Salahudeen
2
Olufemi Olaniyi, Shoboyede
3
1
Directorate of Academic Planning, Lagos State University, Ojo, Lagos, Nigeria
2
Economics Department, Lagos State University, Ojo, Lagos, Nigeria
3
Roshallom International School, Lagos, Nigeria
DOI:
https://doi.org/10.51583/IJLTEMAS.2026.150500134
Received: 05 May 2026; Accepted: 11 May 2026; Published: 08 June 2026
ABSTRACT
This study examines the impact of income redistribution on Nigeria’s economic growth and stability. Annual
data covering the period 1990 to 2025 were sourced from the World Bank, National Bureau of Statistics, World
Development Indicators and the Central Bank of Nigeria. The variables analysed include Real GDP, Personal
Income Tax (PIT), the Gini coefficient, Inflation Rate, Health, and Hosing. Methodologically, the study employs
Autoregressive Distributed Lag (ARDL) framework to analyze both short-run and long-run dynamics. The
Bounds Test confirms the existence of a long-run cointegrating equilibrium, while the Error Correction Model
(ECM) estimates approximately 88.8% speed of adjustment within a year. The empirical findings reveal a
positive long-run relationship between economic growth and PIT, health expenditure, and housing. Specifically,
PIT demonstrates a significant positive impact on economic growth in the long run but exhibits a negative effect
in the short run. Conversely, inflation acts as the primary inhibitor of macroeconomic stability, depicts a
persistent negative impact on economic growth. High inflation further worsens income disparity by widening
the gap between the rich and the poor. This structural pressure emphasises the key role of Personal Income Tax
as a stabilizing mechanism to foster economic growth in Nigeria. Based on these findings, the study offers three
primary recommendations. First, policymakers must strengthen PIT administration by widening the tax base,
mitigating evasion, and enforcing compliance within the informal sector. Second, public expenditure on health
and housing must be expanded and efficiently managed. Targeted investments in healthcare infrastructure and
affordable housing are vital to build human capital, enhance labour productivity, and stimulate long-term growth.
Finally, inequality-reduction policies must prioritize vulnerable, low-income households to ensure inclusive
growth and social cohesion.
Keywords: Redistribution of Income, Progressive tax (as PIT), Economic Growth and Stability, GDP, Gini Co-
efficient, ARDL, Health Expenditure, Housing, Inflation, Nigeria.
INTRODUCTION
According to the seminal framework of Musgrave (1959), income redistribution entails the strategic reallocation
of economic resources across societal groups via fiscal instruments specifically taxation and public welfare
programs to mitigate systemic economic inequality and foster social justice. This conceptualization aligns
closely with Rawlsian distributive justice (Rawls, 1971), which posits that the institutional distribution of wealth
and income must be structured to optimize aggregate societal well-being rather than concentrating benefits
among a privileged elite. In operational terms, contemporary redistribution policies typically manifest through
three interconnected fiscal mechanisms. These include progressive taxation, wherein higher-income brackets
face higher marginal tax rates to generate public revenue while reducing post-tax income disparities (Saez &
Diamond, 2011); means-tested benefits, which involve the targeted allocation of financial assistance strictly to
households falling below specified income thresholds (Blank, 2002); and broader social welfare programs
designed to provide an institutional safety net for vulnerable populations such as the elderly, disabled, and
frictionally unemployed (Esping-Andersen, 1990; Stiglitz, 2012).
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The primary macroeconomic objective of these combined redistributive configurations is to simultaneously
suppress poverty, curb widening inequality, and mitigate social unrest, thereby creating a stable domestic
environment conducive to long-run economic growth and stability (Kakwani & Pernia, 2000). In modern
economic governance, understanding the empirical transmission channels of these policies has assumed
heightened critical importance.
A progressive tax is a tax system where the tax rate increases as the taxpayer's income increases. In other words,
the more you earn, the higher tax rate you pay while means-tested benefits are government-provided benefits or
services that are targeted towards individuals or families with limited financial resources example is building
low-cost housing for the masses especially the poor ones. Another example is construction healthcare centers
that are used by the poor people. Eligibility is determined by assessing their income, assets, and expenses.
It is paramount to know that social welfare, programs are government initiatives that provide support to
vulnerable populations, such as the poor, elderly, disabled, and unemployed. When income is well distributed,
poverty rate will obviously reduce and this will bring about low Gini-coefficient. These programs aim to improve
their well-being, alleviate poverty, and promote social justice while Income inequality metrics are statistical
measures used to assess the distribution of income within a population. These metrics help quantify the gap
between the rich and the poor, providing insights into economic disparities. Redistribution of income will
increase consumption of low-income households who tend to spend a larger porting of their income. It also
increases human capital development, that is, targeted transfers (e.g. education, healthcare) can improve
productivity and earning potential, driving long-term growth. Redistributing income can equally increase labour
force participation, especially among marginalized groups.
This study explores the impact of redistribution of income, specifically through means-tested benefits like
building low-cost housing units, social welfare programs like building an healthcare centers, income inequality
metrics like gini-coefficient, and poverty rates, on economic growth and stability.
This study evaluates the impact of income redistribution mechanisms on economic growth and stability, with
following specific objectives, to:
a. examine the impact of progressive taxation (Personal Income Tax) on GDP growth;
b. influence of progressive tax on social welfare spending (Health and Housing expenditure) on
economic growth;
c. analyze the relationship between progressive taxation (Personal Income Tax) and income
inequality (Gini Coefficient);
d. determine how income redistribution policies influence economic stability (Inflation Rate).
2. This following research questions were asked in this study:
a. How does the Personal Income Tax-to-GDP ratio influence economic growth?
b. To what extent is the influence of progressive tax on government investments in health and
housing (as means-tested benefits) contribute to economic growth?
c. How significant is the impact of Personal Income Tax on reducing the Gini Coefficient?
d. Does the redistribution of income through fiscal policy significantly affect the inflation rate?
LITERATURE REVIEW
Few theories were reviewed in this research work to see the importance of redistribution of income in fostering
economic growth and stability.
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Progressive taxation theory is often attributed to 19
th
century economist and philosopher John Stuart Mill,
particularly in his work Principles of Political Economy (1848). However, the concept itself has roots in earlier
thinkers like Adam Smith and even ancient civilizations. The idea gained significant traction in the late 19th and
early 20th centuries with economists like J.A. Hobson and Arthur Cecil Pigou further developing the theory. The
theory suggests that those who earn more should be taxed at a higher rate to reduce income inequality.
Social Welfare Economics: Jeremy Bentham's work on utilitarianism, which laid the groundwork for social
welfare theory, was published in: An Introduction to the Principles of Morals and Legislation (1789). He
introduced the concept of the greatest happiness principle which posits that actions are right if they promote the
greatest happiness for the greatest number of people. In summary, the theory argues that economic policies
should aim to maximize social welfare, which can be achieved through redistributive policies.
Empirical Theory
Ediri et al. (2022) examined the impact of tax revenue on Nigeria's economy from 1995 to 2020. Using Ordinary
Least Squares (OLS) and Granger causality tests, the study found that: Company Gain Tax (CGT) has an
insignificant positive impact on GDP , Customs and Import Duties (CID) has an insignificant positive impact on
GDP, Companies Income Tax (CIT) has an insignificant positive impact on GDP, Petroleum Profit Tax (PPT)
has an insignificant negative impact on GDP, Value Added Tax (VAT) has an insignificant negative impact on
GDP.The study concluded that tax revenue is a source of income to fill the gap for non-tax revenue in the long-
run.
Chetty et al. (2017): "The Fading American Dream: Trends in Absolute Income Mobility Across the US".
Analysis of tax data and mobility rates using regression analysis and mobility tables. The study finds that income
inequality in the US has increased significantly over the past few decades, and that social mobility has decreased.
The authors suggest that progressive taxation and social welfare policies can help mitigate these trends and
promote greater economic equality.
METHODOLOGY
This study adopted a quantitative research design using annual time-series data covering 36-year period (1990–
2025), Autoregressive Distributed Lag (ARDL) cointegration framework was used to examine the long-run and
short-run impacts of income redistribution effects on economic growth and stability in Nigeria.
Model Specification
Following the theoretical frameworks of Musgrave (1959) and the social welfare theories of Pigou (1920), the
impact of income redistribution on economic growth and stability is modeled as a function of progressive
taxation, social welfare expenditures, inequality, and macroeconomic stability. The structural functional
relationship is expressed as:
ln
GDP
PIT
HEALTH
HOUSING
GINI
INFLATION
To capture both the short-run dynamics and long-run cointegrating relationships simultaneously, this functional
form is operationalized within an Autoregressive Distributed Lag (ARDL) framework. Based on the model
selection, the specific econometric baseline ARDL model is specified as:
GDP
GDP
PIT
PIT
HEALTH
HOUSING
GINI
GINI
INFLATION
The model accounts for major historical and institutional turning points in Nigeria's macroeconomic history by
incorporating two deterministic structural dummy variables. The first, denoted as
, captures the country’s
landmark transition to democratic governance and is assigned a value of 1 for the year 1999 onward, and 0
otherwise. The second, represented by
, controls for the profound structural shifts brought about by the
2005 Paris Club debt relief agreement and the comprehensive banking sector consolidation program; it takes a
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value of 1 for all years from 2005 onward, and 0 otherwise. Consequently, the parameters
and
serve as
the corresponding coefficients that mathematically measure the direction and magnitude of these critical pivot
years on Nigeria's economic growth path and
is the white-noise error term.
To implement the bounds testing procedure for cointegration, the dynamic baseline model is operationalized
within an Unrestricted Error Correction Model (UECM) framework. To ensure structural consistency across our
estimations, the two deterministic dummy variables (
and
) are integrated into the system to capture
the institutional shifts without differencing. The complete UECM specification is expressed as follows:
Where:
– natural logarithm
– first-difference operator (capturing short-run dynamics)
– intercept constant / drift component
– optimal lag lengths selected for the dependent and respective independent variables
– short-run dynamic coefficients of the model
– long-run multipliers (establishing the cointegrating relationship)
– structural dummy variable for the transition to democratic governance
and otherwise)
– structural dummy variable for the Paris Club debt relief and banking sector consolidation
Year , and otherwise)
– coefficients measuring the deterministic structural shifts in economic growth during those
critical pivot years
– white-noise stochastic error term
Data Sources and Description
Data for this study were obtained from secondary sources, including the World Bank’s World Development
Indicators (WDI) and national statistical records from the Central Bank of Nigeria (CBN) and National Bureau
of Statistics (NBS). Only the real GDP was transformed into natural logarithms (), while the explanatory
variables (\mathrm{, and \mathrm{) are already inherently expressed as rates/ percentages and
kept strictly in their linear forms.
Table 3.1: Description of the Variables
Variable Name
Symbol
Theoretical Proxy & Operational Definition
Source
Real Gross
Domestic Product
GDP
Economic Growth: Logarithm of Real GDP at constant basic
prices (Dependent Variable).
WDI /
NBS
Personal Income
Tax
Progressive Taxation: Total personal income tax revenue
expressed as a percentage of GDP.
CBN /
FIRS
Health
Expenditure
Social Welfare: Public budgetary expenditure on health
services as a percentage of GDP.
CBN /
NBS
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Housing
Expenditure
Means-tested Welfare: Public investment in social housing
and critical infrastructure as a percentage of GDP.
CBN /
NBS
Income Inequality
Income Distribution: The Gini Coefficient index bounded
between 0 and 100.
World
Bank
Inflation Rate
Macroeconomic Stability: Annual consumer price index
inflation rate.
CBN /
NBS
RESULTS
The following test were carried out to ensure robustness of the result, descriptive statistics, Ramsey Reset test,
Linear model and its associative diagnostic tests which include Normality test, unit root test, the Autoregressive
Distributive Lag (ARDL) model, Bond test, Stability test, Serial Correlation test, Heteroscedasticity test,
Causality Test based on Error Correction Model.
Table 4.1: Summary of Descriptive Statistics
Statistic
Personal tax
Health
Housing
Gini Coeff
Inflation
GDP ($)
Mean
0.43
3.46
0.96
37.70
19.04
270 billion
Median
0.42
3.37
0.98
35.40
13.49
265 billion
Maximum
0.72
5.05
2.07
52.00
72.84
574 billion
Minimum
0.20
2.16
0.12
29.20
5.39
521 billion
Std. Dev.
0.16
0.69
0.62
6.33
15.52
165 billion
Skewness
0.19
0.18
0.27
1.06
2.10
0.11
Kurtosis
1.61
2.45
1.53
3.08
6.70
1.64
Jarque-Bera
3.12
0.65
3.68
6.78
46.89
2.87
Probability
0.21
0.72
0.16
0.03
0.00
0.24
Sum
15.56
124.70
34.71
1357.30
685.41
9.71Trillion
Sum Sq.
7.63
448.75
46.72
52576.35
21479.59
35.7 Trillion
Sum Sq. Dev.
0.91
16.83
13.25
1402.37
8429.97
952 Trillion
Observations
36
36
36
36
36
36
Source: Author’s Computation using EViews 14.0
Over the 36-year period in Nigeria, the average GDP stood at approximately $270 billion, reflecting the
substantial economic scale of the country. Personal Income Tax, a primary tool for income redistribution,
maintained a mean of 0.43, while social welfare indicators such as Health (3.46) and Housing (0.96) show
relatively lower budgetary allocations. The average Gini Coefficient of 37.70 indicates a moderate to high level
of income inequality, revealing a clear justification for investigating redistribution tools in Nigeria.
However, the Jarque-Bera test for normality reveals that Personal Income Tax, Health, Housing, and GDP follow
a normal distribution, as their probability values exceeding the 0.05 threshold. Although, Inflation (p=0.0000)
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and the Gini Coefficient (p=0.0336) depart from normality, these may be as results of unstable prices in Nigeria,
which in return complicate long-run redistribution efforts.
Consequently, all variables exhibit positive skewness, indicating that the distributions are tilted with longer tails
toward higher values, suggesting that periods of exceptionally high inflation or spiked inequality are more
frequent than significantly low periods, this analysis, therefore, provides a robust empirical foundation for the
ARDL modelling afterwards.
Table 4.2: Multicollinearity Diagnostic (Variance Inflation Factors)
Variable
Coefficient Variance
Uncentered VIF
Centred VIF
INFLATION
2.60E-05
4.008938
1.57337
HOUSING
0.012717
4.257306
1.20759
HEALTH
0.010225
32.88144
1.23344
GINI
0.000165
62.0196
1.65425
PIT
0.211646
11.57743
1.38025
C (Constant)
0.451257
116.4126
NA
Source: Author’s computation using EViews 14.
Table 3 reveals that, the Centred VIF values for all explanatory variables (Inflation, Housing, Health, Gini, and
Personal Income Tax) range from 1.20 to 1.65. These values are significantly below the conservative threshold
of 10.0 (and even the stricter threshold of 5.0). The results suggest that there is no evidence of multicollinearity
among the regressors, each independent variable provides unique and independent information to the model.
Table 4.3: Pairwise Granger Causality Test Results (Selected Pairs)
Null Hypothesis
Obs
F-Statistic
Prob.
Decision
PIT does not Granger Cause L_GDP
34
6.43868
0.0049
Reject
L_GDP does not Granger Cause HOUSING
34
3.37448
0.0481
Reject
Inflation Does Not Granger Cause Gini
34
8.13197
0.0016
Reject
Health Does Not Granger Cause Inflation
34
3.06634
0.0619
Fail to Reject*
Gini does not Granger Cause L_GDP
34
0.07755
0.9256
Fail to Reject
Source: Author’s computation using EViews 14. Note: Significance level at 5%.
The significant causality from PIT to L_GDP justifies the use of L_GDP as dependent variable in the ARDL
framework.
It confirms that the tax-related redistribution variable is not just correlated with growth but possesses significant
predictive precedence, reinforcing the structural validity of this report.
Lag selection model
The optimal lag length for both the Unit Root analysis and the ARDL estimation was determined using the
Schwarz Information Criterion (SIC). This choice was deliberate to ensure model parsimony and to maximize
the degrees of freedom given the 36-year scope of the study.
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Unit root test
Table 4.4: Unit Root Test Results (Augmented Dickey-Fuller Test)
Variable
Level I(0)
First Difference I(1)
Order of
Integration
Remark
ln(GDP)
-1.7731 (0.3871)
-5.005*** (0.0003)
I(1)
Stationary at 1
st
difference
PIT
-2.4795 (0.1289)
-5.7945*** (0.0000)
I(1)
Stationary at 1
st
difference
Health
-2.9961** (0.0451)
–
I(0)
Stationary at level
Housing
-1.7669 (0.3901)
-6.5545 (0.0000)
I(1)
Stationary at 1
st
difference
Gini
-2.2052 (0.2081)
-4.4010*** (0.0014)
I(1)
Stationary at 1
st
difference
INF
-2.2753 (0.1852)
-5.8284*** (0.0000)
I(1)
Stationary at 1
st
difference
Source: Author’s computation using EViews 14.
Note: *,**, *** indicate significance at 10%, 5%, and 1% levels respectively
Augmented Dickey-Fuller (ADF) test was employed to ascertain the study’s variables stationarity level. The
results reveal mixed integration results of
and
which is the primary justification for using ARDL
Bounds testing for further analyses. Government expenditure on Health was the only series found to be stationary
at its level (I(0)), with an ADF statistic of -2.9961 and p-value of 0.0451 at 5% significance level. The core
economic growth and redistribution variables were all stationary at 1% significance level with p-values of
0.0003, 0.0000, 0.0014 and 0.0000 respectively. Specifically, the status of the Gini Coefficient and ln(GDP)
suggests that, there is a potential for a long-run equilibrium relationship between inequality and growth.
Table 4.5: Lag selection criteria
Lag
LogL
LR
FPE
AIC
SC
HQ
0
-297.601
NA
2.297209
17.85886
18.12821
17.95071
1
-206.796
144.2197*
0.094760*
14.63503*
16.52054*
15.27804*
2
-172.911
41.85731
0.132354
14.75947
18.26113
15.95364
Source: Author’s computation using EViews 14. Note: * indicates lag order selection by the criterion at the 5%
significance level. LR: sequential modified LR test statistic; FPE: Final prediction error; AIC: Akaike
information criterion; SC: Schwarz information criterion; HQ: Hannan-Quinn information criterion.
To determine the optimal lag length for the ARDL estimation and prevent model from serial correlation issues,
a VAR lag order selection test was conducted. As presented in Table 4.5, the model evaluated a maximum of
two lags using annual data spanning from 1990 to 2025. The empirical results reveal unanimous consensus across
all statistical selection metrics. Specifically, the LR, FPE, AIC, SIC, and HQ all uniquely select an optimal lag
order of one (Lag 1) at the 5% significance level. Consequently, a baseline maximum lag length of 1 is chosen
as the foundational dynamic structure for the subsequent bounds testing and ARDL cointegration analysis,
ensuring a parsimonious model that preserves statistical degrees of freedom.
Table 4.6: ARDL Estimation Results
Variable
Coefficient
Std. Error
t-Statistic
Prob.
L_GDP(-1)
0.1122
0.219
0.5124
0.6133
PIT
-0.6205
0.4837
-1.2828
0.2124
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PIT(-1)
1.1516
0.5188
2.2196
0.0366*
HOUSING
0.0854
0.1312
0.6506
0.5218
HEALTH
0.0175
0.0506
0.3462
0.7323
GINI
-0.0081
0.0077
-1.0498
0.3047
GINI(-1)
0.0576
0.0205
2.8157
0.0098*
INFLATION
-0.0135
0.0045
-2.9963
0.0064*
C
20.3971
5.7363
3.5558
0.0017*
@YEAR>=2005
1.0455
0.2208
4.734
0.0001*
Diagnostic Statistics
Value
Test Type
Bound/Crit.
CONCLUSION
F-Bounds Test
5.4216
Cointegration
4.443
Confirmed
R-squared
0.6842
Fit Quality
—
Substantial
F-statistic
4.5297
Joint Sig.
0.0011
Pass
Durbin-Watson
2.3336
Serial Corr.
—
Optimal
Source: Author’s computation using EViews 14.
Note: * denotes significance at the 5% level. Model selected: ARDL(1, 1, 0, 0, 1, 0) based on SIC.
The ARDL result demonstrates a substantial goodness of fit, with an R
2
of 0.6842, indicating that approximately
68.4% of the variations in GDP are explained by the independent variables. The F-statistic (4.53, p = 0.0011)
confirm the joint statistical significance of the model at the 1% level.
The results reveal that Personal Income Tax (PIT) has a significant positive impact on GDP with a one-year lag
(1.1516, p = 0.0366). This suggests that while taxation may not yield immediate growth, the reinvestment of tax
revenue contributes significantly to economic expansion in the subsequent year. Similarly, the Gini Coefficient,
representing income redistribution, shows a significant positive lagged effect (0.0576, p = 0.0098). This implies
that shifts in income distribution patterns in Nigeria have a delayed but statistically significant influence on
economic growth and stability.
Inflation poses a significant negative pressure on economic growth (-0.0135, p = 0.0064). This result aligns with
macroeconomic theory, suggesting that rising price levels reduces purchasing power and increase production
costs, thereby dampening GDP growth. For every 1% increase in inflation, GDP is expected to decrease by
approximately 0.013%, holding other factors constant.
The model highlights a profound structural shift starting in 2005. The dummy variable for this period is positive
and highly significant (1.0455, p = 0.0001), likely indicating a substantial positive shift in the GDP trend after
2005, the period identified by Paris Club Debt Relief and the comprehensive Banking Sector Consolidation in
Nigeria. Furthermore, the @TREND variable (0.0247, p = 0.0979) suggests a marginal long-term upward path
in growth, significant at the 10% level.
Interestingly, current-level spending on Housing and Health did not yield statistically significant results in the
specific short-run. This reveals that the impact of these variables is either captured through other channels or
requires a different lag structure to manifest fully in the national accounts. To ensure the validity of these
inferences, the model utilized Newey-West (HAC) standard errors, making the results robust to
heteroskedasticity and autocorrelation. The Durbin-Watson statistic (2.33) suggesting that there is no severe
first-order autocorrelation in the residuals, supporting the reliability of the estimated coefficients for policy
recommendations. The F-statistic (4.5297) is highly significant ( ), confirming that the model is
robust and the variables jointly influence GDP.
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Table 4.7: Heteroskedasticity Test Results (Breusch-Pagan-Godfrey)
Test Type
Statistic Value
df / Chi-sq
Probability
F-statistic
1.4226
(8, 26)
0.2339
Obs*R
2
10.6558
8
0.222
Scaled explained SS
3.4721
8
0.9013
Source: Author’s computation using EViews 14.
These results indicate that the model successfully passes the diagnostic check for heteroskedasticity. The F-
statistic (1.4226) yields a p-value of 0.2339, which is significantly higher than the standard 5% () threshold.
Similarly, the Obs*R
2
(the LM statistic) shows a p-value of 0.2220. Consequently, we fail to reject the null
hypothesis of homoskedasticity, and confirm that the standard errors, -statistics, and subsequent -values are
not biased. The Durbin-Watson statistic (1.85) in the test equation also indicates that the residuals of the variance-
check model are well-behaved and nearly.
Table 4.8: ARDL Bounds Test for Long-Run Relationship
Test Statistic
Value
I(0) Bound
(5%)
I(1) Bound
(5%)
CONCLUSION
F-statistic
5.4216
3.037
4.443
Cointegration
t-statistic
-4.0539
-2.86
-4.19
Inconclusive (Borderline)
Heteroskedasticity (White)
29.0945
20
0.0859
No Hetero
Heteroskedasticity (ARCH)
1.185
1
0.2763
No ARCH
F-statistic (Overall Model)
4.5297
(11, 23)
0.0011
Significant
Source: Author’s computation using EViews 14.
The calculated F-statistic of 5.4216 comfortably exceeds the upper bound critical value of 4.443 at the 5%
significance level, this shows no levels relationship between the variables, confirming that Personal Income Tax,
Inflation, and Income Inequality move together with GDP in a stable, long-term path. While the t-statistic (-
4.0539) falls slightly between the
and
bounds, the strong F-statistic remains the primary and sufficient
evidence for cointegration in this framework.
The White Heteroskedasticity Test yielded a p-value of 0.0859, and the ARCH test showed a p-value of 0.2763.
In both instances, we fail to reject the null hypothesis of homoskedasticity.
More importantly, while political events like the Paris Club debt relief or the Finance Acts cause immediate
changes, their effects stick to the economy over time. The presence of cointegration justifies the use of the ARDL
framework to further analyze the long-run coefficients and the Error Correction Term (ECT), which shows how
quickly the Nigerian economy corrects itself back to equilibrium following a shock.
Error Correction Model (ECM)
The short-run dynamic relationships and the speed of adjustment back to long-run equilibrium are
operationalized within an Error Correction Model (ECM) framework. Based on the selected ARDL model
specification, the short-run equation is specified as follows:
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GDP
GDP
PIT
HEALTH
HOUSING
GINI
INFLATION
ECT
where ECT
represents the lagged error correction term, which measures the speed at which the system adjusts
back to long-run equilibrium following a short-run shock, and is its corresponding negative and statistically
significant parameter. To maintain structural consistency with the baseline model, the framework integrates two
deterministic structural dummy variables (
) to capture the immediate short-run impacts of the
1999 democratic transition and the 2005 Paris Club debt relief/banking consolidation, respectively, with
and
acting as their impact coefficients, while
represents the white-noise residual term.
Table 4.9: ARDL Error Correction Representation (Short-Run Dynamics)
Variable
Coefficient
Std. Error
t-Statistic
Prob.
COINTEQ (-1)
-0.8878
0.1623
-5.4712
0.0000*
D(PIT)
-0.6205
0.4587
-1.3528
0.1869
D(GINI)
-0.0081
0.0073
-1.1134
0.275
C
20.3971
3.6866
5.5328
0.0000*
@TREND
0.0247
0.011
2.2385
0.0333*
@YEAR>=1999
-0.3079
0.1421
-2.1667
0.0389*
@YEAR>=2005
1.0455
0.2049
5.1011
0.0000*
R-squared
0.6842
F-statistic
10.1098
0.0000*
Adjusted R-squared
0.6165
Durbin-Watson
2.3336
Note: * denotes significance at the 5% level. Model: ARDL(1,1,0,0,1,0).
The most critical result is the COINTEQ (-1) coefficient of -0.8878, which is highly significant ( ),
which suggests a remarkably high speed of adjustment, approximately 88.8% of the deviation from the long-run
equilibrium is corrected within a single year. For Nigeria, this implies that the economic system is robust; even
when hit by massive shocks such as oil price collapses or radical policy shifts the economy possesses a strong
internal mechanism that pulls it back toward its steady-state growth path.
Interestingly, changes in Personal Income Tax (D(PIT)) and the Gini Coefficient (D(GINI)) do not show a
statistically significant impact on GDP growth. This suggests that fiscal policy adjustments and shifts in income
redistribution in Nigeria require time to filter through the economic system before their positive impact are felt
in the economic system.
Structural dummy for 1999 marking the return to democratic rule is significant and negative (-0.3079, p =
0.0389), possibly reflecting the initial volatility and restructuring costs of the transition. Conversely, the 2005
dummy remains exceptionally strong and positive (1.0455, p = 0.0000), solidifying the argument that mid-2000s
economic reforms provided a significant increase to Nigerian economic growth. Furthermore, the significant
time trend () indicates an autonomous growth rate of approximately 2.47% annually, independent of the
other variables, representing the consistent expansion of the Nigerian labour force and basic productivity.
With an Adjusted R
2
of 0.616, the model explains over 61% of the short-term fluctuations in Nigerian GDP
growth. The F-statistic (10.11, p < 0.01) confirms the joint significance of the regressors. Additionally, the
Durbin-Watson statistic (2.33) indicates that the residuals are well-behaved, further validated using HAC
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(Newey-West) robust estimation to ensure that any potential serial correlation or heteroskedasticity does not bias
the findings.
The findings reveal a highly stable economic environment where nearly 89% of annual disequilibria are
corrected, ensuring that short-term fiscal volatility does not lead to long-term instability. While immediate
increases in Personal Income Tax (PIT) may trigger a brief decrease in output level, the high speed of adjustment
ensures that the economy quickly absorbs these shocks, and moves toward the positive growth path identified in
the long-run analysis.
Serial Correlation
To ensure the validity of the estimated parameters, the Breusch-Godfrey Serial Correlation LM test was applied
to confirms that the model is statistically sound and that the standard errors are unbiased.
Table 4.10: Breusch-Godfrey Serial Correlation LM Test Results
Test Type
Statistic
d.f.
Probability
F-statistic
0.6759
(2, 21)
0.5194
Obs*R-squared
2.1169
2
0.347
Source: Author’s computation using EViews 14.
The diagnostic results from the Breusch-Godfrey Serial Correlation LM Test indicate that the ARDL model is
free from the presence of serial correlation. As shown in Table 4.9, the F-statistic of 0.6759 has a corresponding
p-value of 0.5194, while the Obs*R-squared statistic of 2.1169 yields a p-value of 0.3470. Since both p-values
are significantly greater than the standard 0.05 (5%) level of significance indicating that there is no serial
correlation in the residuals.
This result is further supported by the Durbin-Watson (DW) statistic of 1.958, which is very close to the ideal
value of 2.0, this confirms that the errors are independently distributed and the model does not suffer from
autocorrelation. Consequently, the coefficients and standard errors reported in the primary ARDL model support
the assertion that progressive taxation (Personal Income Tax) impact GDP growth; social welfare spending
(Health and Housing expenditure) do not affect economic stability in the short-run. Therefore, the impact of
Personal Income Tax on Income Inequality are not just temporary but are fundamentally linked to the long-term
route of economics growth and stability in Nigeria.
Table 4.11: Normality Test Results (Residuals)
Statistic
Value
Jarque-Bera
0.5977
Probability
0.7417
Skewness
-0.2055
Kurtosis
2.5091
The Jarque-Bera (JB) statistic is 0.5977 with a corresponding p-value of 0.7417. Since the p-value is significantly
greater than the 0.05 threshold, we fail to reject the null hypothesis that the residuals are normally distributed.
Furthermore, the Skewness of -0.20 (near zero) and Kurtosis of 2.51 (near the ideal value of 3) indicate that the
distribution is symmetric and has an appropriate peakedness, further confirming the normality of the data. It
means that the conclusions drawn about the significant impact of Inflation and Personal Income Tax (PIT) are
mathematically sound.
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Table 4.12: Correlation Matrix of the Variables
Variable
GDP
GINI
HEALTH
HOUSING
INFLATION
PIT
GDP
1
-0.4516
0.2528
0.877
-0.3939
0.3938
Gini
-0.4516
1
-0.3349
-0.4023
0.5269
-0.3312
Health
0.2528
-0.3349
1
0.2164
-0.2464
0.3639
Housing
0.877
-0.4023
0.2164
1
-0.2023
0.1903
Inflation
-0.3939
0.5269
-0.2464
-0.2023
1
-0.451
Pit
0.3938
-0.3312
0.3639
0.1903
-0.451
1
While there is a strong positive correlation between GDP and Housing (0.877), the remaining correlations fall
well below the critical 0.80 threshold. This confirms that your variables are distinct enough to be used together
in a single regression model without suffering from significant multicollinearity.
There is a moderate positive correlation between Personal Income Tax (PIT) and GDP (0.3938). This supports
the long-run ARDL finding that progressive taxation is positively associated with economic growth in Nigeria.
Furthermore, PIT shows a negative correlation with Inflation (-0.4510), suggesting that higher direct tax
collection may assist in reducing inflationary pressures, and thereby contributing to macroeconomic stability.
More importantly, Personal Income Tax (PIT) is positively correlation to Health and Housing. This shows that
one percent (1%) increment in PIT, will bring about 0.36% in Health expenditure and 0.19 in Housing.
The result reveals a significant positive correlation between the Gini Coefficient and Inflation (0.5269). This
statistically reinforces that inflation is a major driver of income inequality in Nigeria as reported above.
Conversely, GINI is negatively correlated with GDP (-0.4516), suggesting that as inequality rises, general
economic performance tends to suffer, this forms a key justification for the redistribution policies analyzed in
this study.
The correlation between Health (0.2528), Housing (0.8770) and GDP is positive, as expected, however, the
extremely high correlation for Housing suggests it is more of a luxury sector that grows when the economy
grows, rather than an independent driver of that growth, which aligns with the Granger Causality results state
above.
Table 4.13: Ramsey RESET Test for Functional Form
The Ramsey RESET (Regression Specification Error Test) was conducted to verify that the functional form of
the model is correctly specified and that there are no omitted variables that might bias the results.
Test Statistic
Value
Degrees of Freedom
Probability
t-statistic
1.2475
22
0.2253
F-statistic
1.5563
(1, 22)
0.2253
Likelihood Ratio
2.3923
1
0.1219
To confirm the robustness of the model's functional form, the Ramsey RESET test was employed. The test
returned an F-statistic p-value of 0.2253, confirming that the model is correctly specified and free from omitted
variable bias at the 5% level of significance. Along with the absence of serial correlation and the normality of
residuals, this final diagnostic confirms that the ARDL framework used is a highly reliable instrument for
analyzing Nigeria's income redistribution and economic stability.
Granger causality test
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Figure 1: CUSUM Stability Test Result
Based on the figure 1, the blue line represents the cumulative sum of recursive residuals, while the two red dotted
lines represent the 5% significance boundaries. For most of the study period (from 2006 to approximately 2021),
the blue line remains firmly within the critical boundaries. This indicates that the relationship between income
redistribution and economic growth was structurally stable for over 15 years, providing a reliable basis for long-
term economic modelling. However, 2022–2025 deviation signifies structural instability, the plot shows that
starting around 2022, the blue line crosses the lower 5% significance boundary.
It suggests that the old economic relationships in Nigeria were disrupted by the significant macroeconomic
shocks of the mid-2020s, such as the 2023 FX unification and removal of fuel subsidy. The model is highly
stable for the historical analysis of the 1991–2021 period, meaning the results on the long-run benefits of
Personal Income Tax (PIT) as major income redistribution tool and the negative impact of Inflation on economic
stability are valid as presented. Meanwhile, the recent crossing of the boundary suggests that Nigeria’s economic
stability is currently under severe pressure. The redistribution mechanisms that worked in the past may need to
be recalibrated to account for the current high-volatility environment in Nigeria.
DISCUSSION OF FINDINGS
The result of this finding identifies a significant long-run positive relationship between Personal Income Tax
(PIT) as redistribution tool and economic growth. However, the short-run dynamics reveal a contractionary
effect. This indicates that while immediate tax increases may temporarily reduce consumer spending, the
resulting fiscal space allows for long-term productive investments that drive national output.
Government expenditure on Health and Housing does not significantly promote economic growth in Nigeria.
This transmission failure suggests that, these redistribution mechanisms are currently insufficient efficiency to
catalyze measurable economic expansion. Stability is primarily threatened by Inflation, which shows a highly
significant negative impact on GDP. This confirms that redistribution policies significantly affect economic
stability. Any fiscal redistribution that inadvertently triggers inflation will likely undermine the very growth it
seeks to achieve.
The Error Correction Term (COINTEQ) proves that the Nigerian economy is remarkably resilient, correcting
nearly 89% of annual disequilibria. This high speed of adjustment provides a stable foundation for the
government to implement long-term redistribution reforms. The diagnostic tests confirm the model is statistically
sound, with no serial correlation, normally distributed residuals, and a correct functional. However, the CUSUM
of Squares plot indicates a recent crossing of the 5% significance boundary starting in 2023, suggests that while
the model is historically stable, the recent radical policy shifts in Nigeria (such as FX unification and fuel subsidy
removal) have introduced new structural instabilities that require careful policy monitoring.
The structural integrity of the ARDL model is affirmed by the F-Bounds test, where the calculated statistic
exceeds the upper critical bound at 5%, formally establishing a cointegrating relationship. Supplementary
diagnostics, including White and ARCH tests, confirm the absence of heteroskedasticity, thereby validating the
efficiency and reliability of the long-run growth coefficients.
The Correlation Matrix reveals a strong positive correlation between GDP and Housing highlights the pro-
cyclical nature of the real estate sector in Nigeria. Recent studies by Oseni and Salami (2021) corroborate this,
suggesting that while housing reflects economic expansion, it is often a beneficiary rather than a primary driver
of growth due to its sensitivity to disposable income levels. Conversely, the moderate positive correlation
between Personal Income Tax (PIT) and GDP aligns with the findings of Muhammad and Ibrahim (2024), who
demonstrate that every 1% increase in total tax revenue correlates with a 0.234% rise in real GDP.
Subsequently, the significant positive correlation between Inflation and the Gini Coefficient, reinforces the
regressive tax nature of inflation. In a recent study by the Central Bank of Nigeria (2025), reveals that price
instability is a primary driver of income disparity, as it disproportionately erodes the real wages of low-income
earners compared to asset-holding elites. Furthermore, the negative correlation between PIT and Inflation
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suggests that progressive taxation may act as a stabilizing counterweight, potentially reducing excessive liquidity
that drives cost-push inflation.
Perhaps, the relatively weak correlation between Health spending and GDP, reflects a persistent transmission
gap in Nigerian fiscal policy. While Enaberue et al. (2024) argue that increased health expenditure should reduce
poverty and boost human capital, the correlation matrix suggests these benefits are currently under-realized. This
mirrors broader findings that Nigeria’s tax-to-GDP ratio remains below 10%, well under the Sub-Saharan
average of 18%, leaving social sectors critically underfunded even during periods of GDP growth. The
correlations matrix suggests that for the 2025–2026 tax reforms to succeed, the positive link between taxation
(PIT) and output must be harnessed to fund the social sectors (Health) more effectively, thereby decoupling
inflation from inequality.
While the CUSUM test confirms long-term parameter stability, the CUSUM of Squares indicates a structural
shift starting in 2023, likely reflecting the impact of recent radical policy changes like FX unification.
The Progressive Taxation (Personal Income Tax) and GDP Growth
This finding reveals the presence of a J-curve relationship between Personal Income Tax (PIT) and GDP growth
in Nigeria. Specifically, PIT demonstrates a significant positive impact on economic growth in the long run,
while exerting a negative effect in the short run. This result is consistent with the findings of Tanchev (2021),
who, in examining the long-run equilibrium between personal income tax and economic growth in Bulgaria,
established the existence of a long-run equilibrium relationship but found no significant short-run association
between PIT and growth.
Based on this results, it can be inferred that Personal Income Tax serves as an effective instrument for income
redistribution and the promotion of sustainable economic growth in Nigeria. In addition, short-run empirical
evidence by Tala (2024) indicates that positive changes in PIT have a statistically significant negative effect on
economic growth. For instance, a one percent increase in PIT is associated with a 1.8% decline in the growth
rate, suggesting a linear short-run relationship between PIT and GDP.
Similarly, Maganya (2020) provides empirical support for a negative relationship between income taxes (both
personal and corporate) and economic growth in the short run. Earlier evidence by Barro (1990) also aligns with
this position, arguing within the neoclassical framework that taxation can adversely affect growth during the
transition to a new steady state, particularly through the savings-investment transmission mechanism. While
initial tax reforms may yield temporary contractionary pressure, they are vital for long-term fiscal sustainability
and expansion, Buthelezi (2025) reported that, progressive tax reforms that focus on wealth and income
redistribution may be necessary to ensure fiscal sustainability without harming low- and middle-income groups.
Progressive Tax on Social Welfare Spending (Health and Housing Expenditure) and Economic Growth
These findings demonstrate a positive long-run relationship between Personal Income Tax (PIT), Health
expenditure, Housing and economic growth, meaning that a well-structured progressive tax system will increase
the creation of more Health care centers, construction of low-cost housing units for the masses and also provides
the necessary fiscal space to fund public goods that accelerate development. This result aligns with Optimal
Taxation Theory and the work of Appiah (2023), who reported that direct tax revenues are more sustainable than
commodity-based revenues for long-term growth in emerging markets.
In contrast, social welfare spending on Health and Housing exhibited statistical insignificance in relation to
growth, this highlights a transmission gap where budgetary allocations fail to translate into human capital
development. This mirrors the Institutional Leakage Theory and findings by Sala-i-Martin and Subramanian
(2013) regarding the resource curse in Nigeria, where social spending often suffers from poor absorptive
capacity. Additionally, the weak correlation between Health spending and GDP corroborates broader findings
that social sectors remain underfunded.
Inflation was identified as the primary inhibitor of stability, showing a significant negative impact on growth.
Research was reported that inflationary shocks, function as a regressive hidden tax, eroding the purchasing power
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of low-income households who spend up to 70% of their income on basic needs. This supports the Fisherian
Stability Theory and reports from Punch Nigeria (2026), which indicate that price instability drives income
disparity, as evidenced by the significant positive correlation between inflation and the Gini Coefficient.
Progressive Taxation (Personal Income Tax) and Income Inequality
The results on the relationship between progressive taxation, particularly Personal Income Tax (PIT), and income
inequality in Nigeria reveal that income inequality remains closely linked to broader macroeconomic conditions
and institutional inefficiencies rather than taxation alone. It was found that inequality significantly affects
economic growth, while inflation and social spending emerged as the major drivers of inequality in Nigeria.
This implies that inequality in the country is largely a systemic outcome of persistent macroeconomic instability,
weak welfare transmission mechanisms, and limited redistributive efficiency of fiscal policy. Although,
progressive taxation is theoretically designed to reduce inequality through income redistribution, the Nigerian
experience suggests that the effectiveness of PIT is constrained by poor tax compliance, a large informal sector,
inflationary pressures, and weak public expenditure management.
This finding supports the position of development economists that taxation alone cannot significantly reduce
inequality without effective social protection systems and stable macroeconomic conditions. Recent empirical
evidence by Voto and Ngepah (2024) showed that personal income taxation contributes to income redistribution
in Sub-Saharan Africa when supported by strong fiscal institutions and effective social transfers. Similarly, Bello
(2025) found that increasing the progressivity of PIT in Nigeria could reduce inequality and improve household
welfare, particularly among low-income groups, but the redistributive outcomes depend heavily on government
capacity and targeted welfare implementation.
This result is also consistent with the findings of Appah and Omesi (2021), who reported that personal income
tax has a redistributive effect capable of reducing income inequality in Nigeria, although the magnitude of its
impact remains weak due to structural inefficiencies in the economy. In contrast, Anyaduba and Otulugbu (2019)
argued that indirect taxes such as Value Added Tax tend to worsen inequality because they disproportionately
burden low-income households, whereas direct taxes such as PIT are relatively more equitable instruments for
redistribution.
Furthermore, international evidence provided by Eydam and Qualo (2023) supports the argument that tax
progressivity can only reduce inequality effectively when accompanied by stable macroeconomic policies and
inclusive public spending. Therefore, this study concludes that reducing income inequality in Nigeria requires
not only progressive PIT reforms but also effective inflation control, improved social spending efficiency,
institutional accountability, and stronger welfare delivery systems.
Income Redistribution Policies and Economic Stability
This study reveals that inflation demonstrate a strong negative effect on economic growth, and that redistribution
policies do not affect economic stability. This suggests that, although, fiscal redistribution policies such as
taxation, subsidies, and public spending are intended to improve welfare and reduce inequality, their
effectiveness becomes constrained when inflationary pressures persist. In Nigerian, rising inflation weakens
purchasing power, reduces the real value of government transfers, and limits the stabilizing role of fiscal
interventions. Consequently, fiscal redistribution policies may fail to achieve their intended welfare outcomes
when macroeconomic instability is not adequately controlled.
This finding aligns with Keynesian fiscal policy theory, which argues that government spending and taxation
influence aggregate demand and macroeconomic stability. Recent empirical evidence by Akabua, et. al. (2025)
found that fiscal policy instruments significantly affect inflation dynamics in Nigeria, with government
expenditure and fiscal deficits playing major roles in determining price stability. Their study further emphasized
that productive government expenditure can stabilize prices when efficiently managed.
Similarly, Okeke (2024) reported that taxation and government expenditure significantly influence inflation in
Nigeria. it was argued that poorly managed public spending and excessive money supply expansion can intensify
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inflationary pressures, thereby weakening the welfare effects of redistribution policies. The present finding is
also consistent with the work of Oyeleke and Onatunji (2024), who observed that fiscal policy shocks
significantly affect macroeconomic stability in Nigeria. Furthermore, Opayinka (2025) found that inflation
negatively affects economic growth despite the positive role of fiscal policy. Therefore, this study concludes that
redistribution policies significantly influence inflation and economic stability, but their effectiveness depends
on prudent fiscal management, inflation control, institutional efficiency and the productive allocation of public
expenditure.
CONCLUSION AND RECOMMENDATIONS
This study examined the impact of income redistribution policy on economic growth and stability in Nigeria
between 1990 and 2025, focusing on progressive taxation, social welfare spending (Housing expenditure),
income inequality, and inflation rate. The outcome of this study revealed that progressive taxation, particularly
Personal Income Tax, plays an important role in influencing economic growth and redistribution income through
construction of more Health care centers and housing units in Nigeria, although, its effectiveness is constrained
by structural weaknesses, poor tax compliance, and economic instability. Furthermore, the study found that
income inequality in Nigeria is largely driven by persistent inflation, weak welfare transmission mechanisms,
and institutional inefficiencies, thereby limiting the redistributive effectiveness of fiscal policy.
The study concludes that fiscal policy serves as a dual-edged sword in the Nigerian economic environment. The
ARDL model empirical results revels that, Personal Income Tax (PIT) is a significant driver of long-run
economic growth, suggesting that progressive taxation creates the necessary fiscal space for development.
However, this potential is currently eroded by severe transmission gap, as social welfare expenditures in Health
and Housing remain statistically insignificant in driving output. Therefore, effective income redistribution can
promote inclusive economic growth and economic stability in Nigeria when supported by prudent fiscal
management, efficient public expenditure, strong institutions, and stable economic conditions.
Based on the empirical findings of this study, the following evidence-based recommendations were proposed to
enhance the effectiveness of income redistribution mechanisms and promote sustainable economic growth in
Nigeria:
The Federal Government should legally mandate the allocation of a significant portion of PIT collections
to capital expenditure in critical infrastructure within a strict 12-month fiscal window to guarantee
growth.
To effectively widen the tax base and reduce evasion under the PIT framework, the Federal Inland
Revenue Service (FIRS) and State Internal Revenue Services (SIRS) must pivot from traditional
collection to digital infrastructure. Specifically, the government should:
Deploy Mobile Taxation Systems: Partner with telecommunications providers to launch USSD- and SMS-
based tax assessment and payment platforms tailored for informal traders and artisans.
Enforce Integrated TIN Registration Programs: Link Tax Identification Number (TIN) registrations directly
with the National Identity Number (NIN) and Bank Verification Number (BVN) databases. Registration centers
should be deployed in major informal commercial hubs (e.g., Alaba, Balogun, and Main Market clusters) to
capture unrecorded economic activities.
Government should carryout a rigorous administrative and financial audit of processes within the
Ministries of Health and Housing to eliminate bureaucratic bottlenecks, leakages, and procurement
delays, ensuring that public disbursements efficiently yield measurable human capital and physical
infrastructure. Because, the short-run coefficients for current expenditure on Housing and Health are
statistically insignificant, revealing a critical policy transmission gap where immediate budgetary
allocations fail to translate into immediate aggregate output.
Inflation shows a highly significant negative pressure on economic growth, acting as a regressive tax that
erodes real income. To protect the purchasing power of low-income earners and preserve the positive
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lagged redistribution effects captured by the Gini coefficient, social safety net disbursements and
minimum wage frameworks must be dynamically indexed to core inflation trends.
To mitigate the destabilizing impact of sudden macroeconomic shocks, such as the recent 2026 energy
price spikes, policymakers must be proactive in their analysis. The Central Bank of Nigeria (CBN) and
the Ministry of Finance should integrate machine learning architectures (such as LSTM networks and
XGBoost algorithms) alongside traditional econometric frameworks to achieve high-frequency GDP and
inflation Nowcasting, facilitating swift, data-driven fiscal responses.
Nigeria Government should targeted investments in healthcare infrastructure and affordable housing to
build human capital, enhance labour productivity, and stimulate long-term growth.
inequality-reduction policies must prioritize vulnerable, low-income households to ensure inclusive
growth and social cohesion. This should could be accomplished by shifting from untargeted subsidies to
direct, well-monitored social welfare spending.
REFERENCES
1. Akabua, C. A., Metu, A. G., Nzeribe, G. E., & Nwokoye, M. O. (2025). Does fiscal policy have any
influence on inflation dynamics in Nigeria? Journal of Economic Studies, 21(2).
2. Anyaduba, J. O., & Otulugbu, P. O. (2019). Taxation and income inequality in Nigeria. Accounting and
Finance Research, 8(3), 118–129.
3. Appah, E., & Omesi, I. (2021). Taxes and income inequality in Nigeria: Cointegration and error correction
mechanisms evidence from 1980–2018. BW Academic Journal.
4. Atkinson, A. B., & Stiglitz, J. E. (1980). Lectures on Public Economics. McGraw-Hill.
5. Barro, R.J. (1990), Government spending in a simple model of endogeneous growth. Journal of Political
Economy, 98(5), 103-125.
6. Bello, M. A. (2025). Tax policy reforms and income redistribution in Nigeria: A computable general
equilibrium approach. Efficiens: Journal of Management Science and Operations, 1(1), 1–11.
7. Blank, R. M. (2002). Evaluating welfare reform in the United States. Journal of Economic Literature,
40(4), 1105-1166.
8. Buthelezi, E. M. (2025). Evaluating government debt thresholds and fiscal consolidation: insights from
Organisation for Economic Co-operation and Development countries. Macroeconomic Dynamics, 29,
e116. doi:10.1017/S1365100525100205
9. Central Bank of Nigeria. (2025). Macroeconomic stability and the inflation-growth trade-off in West
Africa. CBN Press.
10. Chetty, R., Grusky, D., Hell, M., Hendren, N., & Narang, J. (2017). The fading American dream: Trends
in absolute income mobility since 1940. Science, 356(6336), 398–406.
https://doi.org/10.1126/science.aal4617
11. Ediri, U. J., Stephen, E., Uzoma, E. R., & Tennyson, O. (2022). Tax revenue and the Nigerian economy:
An empirical approach, 1995-2020. Academy of Accounting and Financial Studies Journal, 26(6), 1–13.
12. Enaberue, M., Musa, A., & Magaji, S. (2024). Role of poverty reduction initiatives in advancing
sustainable development in Nigeria. International Journal of Innovative Finance and Economics Research,
13(3).
13. Esping-Andersen, G. (1990). The three worlds of welfare capitalism. Princeton University Press.
14. Eydam, U., & Qualo, H. (2023). Income inequality and taxes: An empirical assessment. Applied
Economics Letters, 31(14), 1828–1835.
15. John, S.M. (1948). Principles of Political Economy (Great Minds Series). www.amazom.com/principles-
politcal-economy-great-minds/dpl1591021510
16. Kakwani, N., & Pernia, E. M. (2000). What is pro-poor growth? Asian Development Review, 18(1), 1-16.
17. Keynes, J. M. (1936). The General Theory of Employment, Interest and Money. Macmillan.
18. Maganya, M.H. (2020), Tax revenue and economic growth in developing country: An autoregressive
distribution lags approach. Central European Economic Journal, 7(54), 205-217.
19. Muhammad, S., & Ibrahim, Y. (2024). The impact of tax revenue on real GDP growth: Evidence from
Nigeria (1994–2022). African Scholar Publications.
20. Musgrave, R. A. (1959). The theory of public finance. McGraw-Hill.
Page 1713
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21. Okeke, C. (2024). Effectiveness of fiscal and economic policy in monitoring inflation in Nigeria. FUDMA
Journal of Accounting and Finance Research, 2(3), 110–117. https://doi.org/10.33003/fujafr-
2024.v2i3.105.110-117
22. Opayinka, T. K. (2025). The interplay between fiscal policy, inflation and economic growth in Nigeria:
An ARDL approach. International Journal of Research and Innovation in Social Science.
23. Oseni, I. O., & Salami, B. A. (2021). Tax revenue and government expenditure: Implications for
sustainable development goals in Nigeria. ResearchGate.
24. Oyeleke, O. J., & Onatunji, O. G. (2024). Macroeconomic effects of fiscal policy shocks in Nigeria: A
new proof from mixed-frequency vector autoregression approach. Vision: The Journal of Business
Perspective. https://doi.org/10.1177/09721509241295837
25. Pigou, A. C. (1920). The Economics of Welfare. Macmillan.
26. Punch Nigeria. (2026, April 16). Nigeria’s inflation rebounds after US-Iran war shocks hit households.
Punchng.com.
27. Rawls, J. (1971). A theory of justice. Harvard University Press.
28. Saez, E., & Diamond, P. (2011). The case for a progressive tax: From basic research to policy
recommendations. Journal of Economic Perspectives, 25(4), 165-190.
29. Sala-i-Martin, X., & Subramanian, A. (2013). Addressing the natural resource curse: An illustration from
Nigeria. Journal of African Economies, 22(4), 570–615. https://doi.org/10.1093/jae/ejs033
30. Sen, A. K. (1970). Collective Choice and Social Welfare. Holden-Day.
31. Stiglitz, J. E. (2012). The price of inequality: How today's divided society endangers our future. W.W.
Norton & Company.
32. Tala, L. (2024). Economic Growth Effects of Fiscal Policy in South Africa: Empirical Evidence from
Personal Income Tax. International Journal of Economics and Financial Issues.
https://doi.org/10.32479/IJEFI.15795
33. Tanchev, S. (2021). Long-run equilibrium between personal income tax and economic growth in
Bulgaria. Journal of Tax Reform. 2021. 7(1), 55-67.
34. Voto, T. P., & Ngepah, N. (2024). Personal income tax, redistribution and income inequality in Sub-
Saharan Africa. International Review of Economics, 71(2), 205–223.
