190

Finance, Accounting and Business Analysis

Volume 8 Issue 1, 2026

http://faba.bg/

ISSN 2603-5324

DOI:

https://doi.org/10.37075/FABA.2026.1.15

Digital Transformation, Institutional Quality, and Tax Revenue in West

Africa

Jude Igyo Ali

Patricia Lindelwa Makoni

Department of Finance, Risk Management and Banking, College of Economics and Management Sciences,

University of South Africa, Pretoria, South Africa

Department of Finance, Risk Management and Banking College of Economics and Management Sciences,

University of South Africa, Pretoria, South Africa

* Corresponding author

Info Articles

Abstract

History Article:

Submitted 16 February 2026

Revised 21 April 2026

Accepted 9 May 2026

Purpose: The paper examined the individual and combined effects of

digitalization and institutional quality on the mobilization of tax revenue in West

Africa. It aims to understand the interplay of these factors in shaping tax

outcomes in developing economies, with particular attention to distributional

impacts and causal mechanisms.

Design/Methodology/Approach: The mixed-methods quantitative approach

applies to panel data from 14 ECOWAS member countries for 2000-2023. The

analysis employs the fixed effects models, Method of Moments Quantile

Regression (MMQR), and the panel Structural Vector Autoregression (PSVAR)

in measuring the average treatment effects, the heterogeneous effects across the

revenue distribution, and dynamic causal effects between digitalization and

institutional quality on the one hand and tax revenues on the other hand.

Findings: The results indicate that internet penetration, as measured by tax

revenue, has a positive impact, with a stronger effect in high-revenue countries.

The role of institutional quality is consistently positive and significant for tax

mobilization across settings, underscoring the complementarity of technological

diffusion and institutional factors. Although there are increasing returns to

internet distribution, a variance decomposition analysis shows that tax revenues

are more strongly affected by the quality of the institutional environment than by

internet penetration per se, suggesting that the digitalization of the tax system

works optimally only in an environment with strong institutional structures.

Practical Implications: The study advises West African governments to focus

on institutional quality and investments in digital infrastructure. Policymakers

should aim to strengthen governance structures, enhance regulatory uniformity,

and build institutional capacity to ensure that the benefits of digitalization for tax

revenue are fully realized. Different countries with varying levels of revenue must

adopt different approaches, and low-revenue countries must have their

institutional structures in place before digital tax systems will yield high rates.

Originality/Value: The work is relevant as it entails a systematic analysis of the

nexus between digitalization and institutional quality in tax mobilization in the

West African region. In contrast to earlier literature that examined these factors

separately, the current study highlights their interactions and distributional

heterogeneity, yielding subtle policy implications for policymakers in developing

economies seeking to increase fiscal capacity through technological and

institutional change.

Paper Type: Research Paper.

Keywords:

Digital Transformation;

Institutional Quality; Tax

Revenue; West Africa.

JEL: H20, O43, O55

Address Correspondence:

E-mail:

aliji@unisa.ac.za

makonpl@unisa.ac.za

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INTRODUCTION

One of the most serious structural issues in the economies of West African countries, where

sustainable development, fiscal independence, and a reduced reliance on external funding are aimed to be

achieved, is domestic resource mobilization (DRM). Although reforms have been made, revenue collection

has been low, indicating structural and administrative inefficiencies. The tax-to-GDP ratio in Africa was

estimated at about 16% in 2022, whereas ECOWAS countries recorded 13.8-13.9% in 2023, which is not

enough to fund public services, social protection, and infrastructure (OECD 2025a). This ongoing fiscal

imbalance limits policy flexibility as well as increasing susceptibility to external disruptions. Traditional

policy adjustments have not been sufficient without more ground breaking reforms and technical assistance,

underscoring the urgent need to introduce transformative changes in revenue systems (OECD/ATAF/AUC

2024).

Digitization can be a good way to improve taxation systems and increase fiscal space. Digital

instruments (e-tax portals, mobile payments, and digital identification) can help lower compliance costs,

increase transparency, and expand the tax base, as internet penetration in Africa reached 35.7% as of 2025

(ITU 2025). Nevertheless, the extent of these advantages depends on the quality of institutions, especially

regulatory effectiveness, the rule of law, accountability, and the control of corruption. Research has shown

that successful e-government applications can be achieved only with strong legal systems, effective

administration, and proper data management (Kochanova et al. 2020; Junquera-Varela et al. 2022). The

same can be applied to the relationship between GovTech in the public sector and digitalization in the private

sector, which can enhance fiscal benefits (Nose et al. 2025), whereas weak institutions, corruption, and

bureaucratic inefficiency may undermine such benefits (Appiah et al. 2025).

Despite new developments, serious gaps remain in research in West Africa. The available literature

pays little attention to the interaction between digitalization and institutional quality in determining tax

performance and to whether their impacts are complementary or substitutive. Most of them use

methodologically mean-based panel estimators that do not account for regional differences in digital

preparedness, governance, and fiscal performance, in favour of homogeneity across countries. These

strategies do not capture the dynamics of time, lag effects, and possible nonlinearities in the impact of

digitalization. Given the high heterogeneity of West African countries, ranging from those advancing their

digital reforms to those lagging due to institutional bottlenecks, there is a risk that standard empirical models

will conceal significant country-specific variation. To overcome these shortcomings, the present study takes

a localized West Africa approach based on dynamic, distribution-aware approaches. The study examines

the heterogeneous and dynamic impacts of digitalization and institutional quality on tax mobilization using

panel quantile techniques and structural vector autoregression (SVAR). This subtle method provides

context-driven evidence to craft differentiated and effective fiscal digitalization strategies across West Africa.

Against this backdrop, this study examines the individual and combined effects of digitalization and

institutional quality on tax revenue mobilization across 14 ECOWAS member countries for the period 2000-

2023, with particular attention to distributional heterogeneity and dynamic causal mechanisms. Three

principal research hypotheses are tested:

: Internet penetration (as a proxy for digitalization) has a positive and significant effect on tax

revenue mobilization in West Africa.

: Institutional quality (measured by regulatory quality) has a positive and significant effect on tax

revenue mobilization.

: Digitalization and institutional quality are complementary, as the fiscal benefits of digitalization

are significantly larger in countries with stronger governance structures.

These hypotheses align with the institutional economics tradition (North 1990) and the technology-

efficiency hypothesis (Oti-Akenteng et al. 2025), suggesting that digital tools improve revenue collection

most effectively when embedded within robust governance systems.

LITERATURE REVIEW

Digitalization, Institutional Quality and Tax Revenue Mobilization Challenges in West Africa

The relationship between digitalization and revenue mobilization operates through channels that

enhance administrative capacity, expand the tax base, and shape stakeholders' behaviour within the tax

system. Digital tools reorganize fundamental tax core functions: identification of taxpayers, monitoring

compliance by checking transactions, and enforcement by detection mechanisms, which redefine

relationships in administrations (Okunogbe and Santoro 2023) in both developing contexts. The compliance

cost reduction channel describes the increase in revenue resulting from reducing the filing, payment, and

record-keeping costs borne by taxpayers and authorities. Mobile payments and electronic filing improve

transparency, reduce discretion and promote compliance. It has been demonstrated that declarations and

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payments increased revenue in 2022 by widening the tax base (OECD/ATAF/AUC 2024; Kochanova et

al. 2020). The channel for reducing information asymmetry focuses on digitalization's ability to create

verifiable transaction records, thereby limiting opportunities to evade taxes. Cross-verification is provided

by the electronic sales registration system, digital invoicing, and real-time reporting. Empirical data on tax

collection show that management systems and digital billing enhance collection efficiency in West Africa

(El-Manaseer et al. 2023). This is because the tax base expansion channel recognizes the ability of

digitalization to highlight and bring informal economic activities that were hitherto unrecorded into the

formal tax system. Digital identification, geospatial property databases, and mobile money transaction

tracking enable revenue authorities to reach taxpayers who previously existed outside administrative control.

Nevertheless, according to the IMF/ATAF (2025) Africa is estimated to lose about $60 billion each year

due to poor digital tax collection frameworks and illegal financial leakages, and that digitalization is

therefore not the solution but needs to be supplemented by institutional change.

According to the institutional quality philosophy, the efficiency of tax systems is fundamentally

rooted in the governance environment in which they operate. Effective institutions of the rule of law, high-

quality regulation, corruption control, and government effectiveness create a conducive environment for

voluntary compliance, and empirical results across Africa indicate that institutional quality is positively

correlated with tax revenue. As an example, Bah (2024) uses system GMM estimation of 42 sub-Saharan

Africa with 1996-2019 period, which concludes that all six World Governance Indicators (voice and

accountability, political stability, regulatory quality, rule of law, control of corruption, and government

effectiveness) have a positive and significant influence on aggregate tax revenues, direct taxes, income taxes,

and goods and services taxes. The findings are consistent with previous research by Benitez et al. (2023),

who showed that institutional capacity building can raise the tax-to-GDP ratio by strengthening

administrative systems. The institutional quality revenue relationship works in several ways, ensuring that

a well-organized bureaucracy enhances the technical capacity to implement complex tax policies and handle

advanced tax vehicles. Also, the preservation of the rule of law and the protection of property rights promote

formalization and voluntary compliance, as taxpayers are assured that their payments will not be arbitrarily

seized, placing top priority on corruption control to minimize leakage and ensure that the revenues collected

by the government reach their coffers rather than their pockets. Contemporary studies in literature offer

astute facts about such relationships. Nikiema and Zore (2025) studied the concept of tax revenue instability

in sub-Saharan Africa and found that institutional quality influences both revenue levels and revenue

stability as a factor in fiscal planning. Moreover, the moderating effect of democracy has been shown to be

important, as the quality of bureaucracy and democracy are complementary sources of tax revenue, whereas

corruption and the quality of bureaucracy are substitutes that decrease revenue (Nature Communications

2025).

The tax mobilization problems in West African countries, most of which are also members of the

Economic Community of West African States (ECOWAS), are unique due to structural economic factors,

institutional legacies, and integration forces. The economies of the region are also characterized by a large

informal sector (85-90% of the labour force), a high reliance on trade taxes, and high cross-border economic

activity, which makes the countries' revenue bases more complex (Hammond 2023; OECD 2023). Empirical

research on West Africa suggests that tax collection efficiency is highly diverse, as the most common external

tariff regimes and treaty arrangements among WAEMU members create both opportunities and barriers to

revenue mobilization (Quiros-Romero et al. 2021). The West African Tax Administration Forum (WATAF)

was formed in 2011 to promote transparency in tax administration, align regional tax policies, and share

knowledge on improving revenue collection.

In West Africa, efforts to transform digitally indicate good but asymmetrical development. Other

countries have expanded the scope of VAT to cover services delivered via electronic media and improved

tax collection through digital withholding systems, resulting in quantifiable revenue benefits (IMF 2024).

Still, there are issues in the implementation process, especially in terms of coordination with the regional

economic community and the smooth flow of information between government agencies. The level of

institutional quality in West Africa has been identified as highly heterogeneous, and this is relevant to digital

adoption and revenue performance. Investigations that employ System GMM models have shown that

governance systems, openness to trade, and international financial flows interact in intricate ways with the

capacity to produce and the region's economic performance (Ogbuabor et al. 2024). The idea that

institutional quality moderates the relationship between trade and growth, as recent studies in West Africa

have established, can suggest that institutional conditionalities may influence digitalization-revenue

relationships.

Theoretical Framework

The work is supported by a comprehensive theoretical framework grounded in the concept of

mobilizing tax revenue in developing economies and presents the idea of digital governance of taxation as a

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combination of public finance theory, institutional economics, and the digital domain. The classical theory

of public finance has highlighted that generating domestic revenue sustainably can be achieved only by

expanding the tax base, improving administrative efficiency, and enhancing taxpayer compliance (Mishi

and Tshabalala 2023). These circumstances are continually undermined by pervasive informality,

diminished administrative capacity, and indefinable governance failures in most West African and other

Sub-Saharan African settings, leading to low tax buoyancy and an endemic fiscal deficit (Moore 2023). This

means that the preferred framework conceptualizes tax revenue performance not as an outcome of a

technical nature, but as the result of structural economic features interacting with institutional and

technological facilitators (Queku et al 2024).

The concept of digitalization is introduced as an ancillary process that can loosen traditional

restrictions on revenue collection. Digital tools such as electronic filing, digital payments, interoperable

databases, and digital identification systems reduce information asymmetries, lower transaction and

compliance costs, and enhance administrative monitoring, consistent with the technology-efficiency

hypothesis (Oti-Akenteng et al. 2025). These avenues align with the best tax theory, which argues that all

forms of distortion should be minimized while voluntary compliance is maximized. The enforcement aspect

of the Allingham-Sandmo model is also reinforced by digital transformation, which enhances the perceived

likelihood of detection and the effectiveness of sanctions through real-time data access and automated cross-

checking (Krieger 2021). The digital systems would increase the predictability and transparency of how the

tax is imposed, which reduces the chance of rent-seeking and discretionary power, thus transforming the

behaviour of taxpayers.

The framework, however, clearly acknowledges that fiscal digitalization returns require institutional

performance. Using institutional economics, formal rules, the capacity to enforce, and the quality of

regulations and the governance structure, as developed by North (1990), are critical to how technological

reform translates into successful outcomes (Arwani and Priyadi 2024). In a setting typified by the rule of

law, accountability, and corruption control, digital tax systems are more likely to work as intended because

institutions ensure data integrity, limit malfeasance, and provide consistent legal and regulatory services. On

the other hand, the possible benefits of digitalization can be eradicated or even destroyed by weak

institutions. The theoretical framework, as such, assumes a complementary and, possibly, nonlinear

interaction between institutions and digitalization, in which technology improves revenue collection most

effectively when embedded in robust governance systems.

Empirical Review

Empirical studies are increasingly emphasizing the importance of institutional quality in determining

tax revenue mobilization in Sub-Saharan Africa (SSA). There are various ways in which governance

increases fiscal capacity. Bah (2024) estimates that accountability, political stability, regulatory quality, rule

of law, corruption control, and government effectiveness have a positive impact on aggregate and

disaggregate tax revenues across 42 SSA countries, using System GMM. On the same note, Nikiema and

Zore (2025) also find that stronger institutions aim not only to increase revenue levels but also to stabilize

collections, especially direct taxes in countries that meet the minimum governance standards. Furthermore,

Katuka and Mudzingiri (2023) identify the governance thresholds beyond which fiscal space grows at an

essential rate, while Nichelatti and Hiilamo (2024) show that institutional trust is an important variable

associated with voluntary compliance. On the other hand, Bati (2025) finds that political stability and

corruption control have statistically insignificant effects due to weak enforcement and high informality,

reflecting the contextuality of fiscal outcomes.

Like the field of governance, the topic of the fiscality of digitalization is slowly being researched.

Iddrisu (2023) posits that digitalization enhances tax revenues, contending that the impact depends on the

strength of the institution. This interdependence is confirmed in subsequent literature by Ackom et al. (2025),

who conclude that digital benefits depend on culture, infrastructure, and literacy, while Tolossa and Melese

(2024) suggest that the development of e-government significantly increases tax effort when combined across

government. Okunogbe and Santoro (2023) provide qualitative evidence that digital tools are useful in

identifying the tax base and monitoring compliance, even when the implementation is problematic. At the

firm level, Nose et al. (2025) and Mpofu (2022) show that compliance is enhanced by digitalization and state

technological capacity, especially in informal firms. There is an additional complication brought by the ICT

infrastructure. Research indicates that ICT adoption and mobile money fiscal benefits are realized only after

specific penetration levels are reached. However, the fiscal impacts of mobile money are still debated- some

believe that it creates efficiency, whereas others believe that mobile money endangers inclusivity. Although

approaches to this matter have improved, two stylized facts remain: institutional quality and digitalization

co-optimize tax mobilization; the effects of both are nonlinear, threshold-driven, and mediated by the level

of trust in the tax authority. The remaining gaps relate to moderating processes, subnational processes, and

cultural backgrounds needed to comprehend the governance-digitalization synergies towards fiscal capacity

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in SSA.

METHODOLOGY

Research Design

This study adopts a quantitative, post-positivist approach to examine the roles of digitalization and

institutional quality in tax revenue mobilization in West Africa. Adopting panel econometric techniques,

the study addresses issues of heterogeneity, endogeneity, and dynamics that characterize the modern fiscal

literature, which prefers a more subtle, contextual approach to empirical investigation, moving beyond mere

average estimators.

Sample Selection and Data Structure

The data cover 14 West African countries that are members of ECOWAS and WAEMU from 2000

to 2023, yielding 322 balanced country-years. The regional nature of the sample is informed by theoretical

characteristics shared by member nations, such as colonial histories, the CFA franc exchange rate regime,

and harmonized customs rules. The chosen sample consists of economies with high employment informality

rates (85-90%), limited regional administrative capacity, and developing information technologies. The

countries examined in this study are Benin, Burkina Faso, Cabo Verde, Côte d'Ivoire, Gambia, Ghana,

Guinea, Guinea-Bissau, Liberia, Mali, Niger, Nigeria, Senegal, Sierra Leone, and Togo. They account for

95% of the regional population.

Data Sources and Variable Definition

Table 1. Variable Definitions, Measurement, and Data Sources

Variable

Abbreviation

Definition and

Measurement

Unit

Source

Theoretical

Justification

Tax Revenue

Mobilization

TAXREV

Total tax revenue as

a percentage of GDP

% of GDP

IMF

GFS;

OECD

Revenue

Statistics

Captures fiscal

capacity; a standard

measure in

comparative public

finance (Besley and

Persson 2014)

Internet

Penetration

INTERNETPEN

Percentage of

population with

internet access

% of

population

World

Bank

WDI

Proxy for digital

infrastructure

(Okunogbe and

Santoro 2023)

Regulatory

Quality

REGQ

WGI regulatory

quality index

measuring

government's ability

to formulate and

implement sound

policies

Index

(−2.5 to

+2.5)

World

Bank

WGI

Account for

governance

effectiveness for

effective digital tax

administration (Bah

2024)

Financial

Development

CPS

Domestic credit to

the private sector as a

percentage of GDP

% of GDP

World

Bank

WDI

Indicates economic

formalization and

banking penetration

that expand taxable

base (Benitez et al.

2023)

Foreign

Direct

Investment

FDI

Net FDI inflows

% of GDP

World

Bank

WDI

Controls for external

capital flows affecting

fiscal capacity and

institutional

development

Economic

Development

GDPPC

Natural logarithm of

real GDP per capita

Log of

constant

2015 US$

World

Bank

WDI

Captures structural

transformation and

taxable capacity

(Besley and Persson

2014)

Source: Authors’ Summarization 2026

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Model Specification

The empirical strategy is multi-method and sequential, aiming to provide full evidence on average

effects, distributional heterogeneity, and dynamic causal relationships. Such triangulation is beneficial for

strengthening robustness and policy relevance, as it addresses various aspects of the nexus between

digitalization, institutional quality, and tax revenue.

Fixed Effects Interaction Term Regression

The baseline specification employs a two-way fixed effects estimator that controls for time-invariant

country-specific characteristics (α

) and common time shocks (λ

TAXREV

= β

+ β

INTERNETPEN

+ β

REGQ

+ β

(INTERNETPEN × REGQ)

+ β

log(GDPPC)

+ β

CPS

+ β

FDI

+ α

+ λ

+ ε

(1)

The model examines the relationship between digitalization and institutional quality, as both jointly

affect tax revenue. A positive β3 favours complementarity, indicating that digital reforms attract higher tax

revenue in a strong institutional environment, whereas a negative β3 suggests that digitalization

compensates for weak governance. The heterogeneity and endogeneity issues are alleviated by country and

year-specific effects and clustered robust errors.

Panel Quantile Regression

The study explores whether the effects of digitalization and institutional quality vary across countries

with different levels of tax mobilization capabilities using Quantile Regression. This methodology captures

the distributional heterogeneity of tax revenue levels and quantile-specific information while controlling for

unobservable country effects using short panel data (Koenker and Bassett 1978). The conditional quantile is

defined as:

(TAXREV

| X

) = α

(τ) + X

β(τ)

(2)

(

)

TAXREV

it(

)

= β0

(

)

+ β

(τ)INTERNETPEN

+ β

(τ)REGQ

+ β

)

(INTERNETPEN ×

× REGQ)

+ β

)

log(GDPPC)

+ β

)

CPS

+ β

(τ)FDI

+ α

)

+ λ

)

+ ε

it(

)

(3)

Pooled Mean Group (PMG) ARDL Model

The Pooled Mean Group (PMG) ARDL approach is used to explore how the variables interact both

in the short run and over time. It allows each country to adjust differently in the short run, while assuming

that, in the long run, the relationships between the variables are broadly similar across countries.

Long-run form: TAXREV

= θ

+ θ

INTERNETPEN

+ θ

REGQ

+ θ

(INTERNETPEN × REGQ)

+ θ4log(GDPPC)

+ θ5CPS

+ θ6FDI

+ μ

+ λ

+ u

(4)

Short-run (Error Correction Form): ΔTAXREV

= φ

(TAXREV

it-1

- θ

INTERNETPEN

–

– θ

REGQ

- θ

(INTERNETPEN × REGQ)

- θ

log(GDPPC)

- θ

CPS

- θ

FDI

) +

+ΣγΔX

+ α

+ λ

+ ε

(5)

Formal tests of coefficient heterogeneity across quantiles, Wald tests of equality, H0: β(τ1) = β(τ2)

for τ1 and τ2. The null hypothesis is rejected, which therefore provides evidence that the effect of the variable

in the distribution of tax revenue varies significantly, thus policy interventions of the countries are to be

distinguished in terms of their baseline fiscal capacity. Standard errors (500 replications) are bootstrapped,

which is a robust inference in finite samples.

ROBUSTNESS VERIFICATION AND DIAGNOSTIC TESTS

Robust diagnostic tests are used to assess economic validity, including stationarity tests (Pesaranet al.

2001; Maddala and Wu 1999), cointegration tests (Pedroni 1999), and causality tests (Dumitrescu and

Hurlin 2012) to verify the data's dynamic and equilibrium characteristics. Biases associated with endogeneity

and simultaneity are avoided using the internal instruments proposed by Lewbel (2012) and dynamic panel

models that incorporate lagged effects. Other tests are concerned with cross-sectional dependence,

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heteroskedasticity and serial correlation (Besley and Persson 2014).

Table 2 presents the descriptive statistics for the variables used in the study, including their means,

variances, and distributions. This provides a clear picture of the data's nature and how the variables behave

before proceeding with further analysis.

Table 2. Descriptive Statistics

Variable

Mean

Median

Maximum

Minimum

Std. Dev.

Skewness

Kurtosis

TAXREV

10.694

10.590

26.620

2.990

3.894

0.621

4.374

INTERNETPEN

12.880

5.610

72.760

0.020

16.218

1.655

5.302

REGQ

-0.666

-0.590

1.570

-1.860

0.463

-0.128

3.935

CPS

14.818

12.610

68.460

0.640

12.171

2.176

8.302

FDI

138.265

10.400

19293.27

-12089.89

1371.765

6.527

140.304

GDPPC

7.942

7.800

10.480

6.790

0.781

1.260

4.600

Source: Authors’ Computation.

Note: All Jarque-Bera tests reject normality at p<0.01.

The internet penetration rate varies significantly in this respect, with a coefficient of variation of 126%;

rates are barely above zero in some African nations, like Niger, and above 70% in Cape Verde and Ghana.

The mean rate of 12.88% masks this disparity due to low internet connectivity indices in most states, with a

couple making rather impressive progress in this area, in line with disparities in the digital transformation

process within Africa (ITU 2025). On this point too, the mean regulatory quality index of -0.67 points to

deficiencies within regional governments, with a range of -1.86 to 1.57, indicating disparities in regional

governance (Bah 2024). Regression analysis indicates significant positive associations between tax revenue,

financial development, and institutional quality, with a moderate association with internet penetration,

suggesting conditional improvements in fiscal performance through digitalization processes.

Table 3 presents the correlation matrix, offering a preliminary view of the relationships among tax

revenue and the explanatory variables. The results highlight the strength and direction of pairwise

associations, providing useful initial insights before proceeding to more robust econometric analysis.

Table 3. Correlation Matrix

TAXREV

INTERNETPEN

REGQ

CPS

FDI

GDPPC

TAXREV

1.000

INTERNETPEN

0.282***

1.000

REGQ

0.495***

0.170**

1.000

CPS

0.723***

0.535***

0.528***

1.000

FDI

-0.116*

0.038

-0.016

-0.015

1.000

GDPPC

0.068

0.393***

-0.077

0.287***

0.086

1.000

Source: Authors' Computation 2026

Note: ***, **, * denote significance at 1%, 5%, and 10% levels respectively.

Notably, the relationship between internet penetration and regulatory quality is positive but weak (r

= 0.170, p < .01). This indicates that a fair amount of variation exists independently, allowing for the

exploration of the interaction between these variables. The variance inflation factors of all the variables are

below 3.5 and therefore not threatened by multicollinearity.

Panel Unit Root and Cointegration Test

The specification of models is rooted in the time-series characteristics of the data, which is

fundamental to doing inference. Table 4 presents the results of various panel-data unit-root tests: the LLC

test, IPS test, ADF-Fisher test, and PP-Fisher test.

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Table 4. Panel Unit Root Test Result

Variable

LLC

IPS

ADF-Fisher

PP-Fisher

Stationarity

TAXREV

-4.306***

-4.807***

75.719***

208.850***

I(0)

INTERNETPEN

1.854

6.195

10.757

8.863

I(1)

D(INTERNETPEN)

-2.633***

-5.299***

76.380***

132.504***

I(0)

REGQ

-2.123**

-2.414***

49.213***

53.221***

I(0)

CPS

0.498

1.740

22.244

18.473

I(1)

D(CPS)

-12.521***

-12.540***

180.481***

202.946***

I(0)

FDI

-9.682***

-10.815***

157.969***

225.984***

I(0)

GDPPC

-0.856

2.047

34.498

35.309

I(1)

D(GDPPC)

-9.298***

-11.291***

163.152***

179.973***

I(0)

Source: Authors' Computation *Note: ***, ** indicate rejection of unit root null at 1%, 5%, significance.

The unit root results indicate mixed integration orders across the variables, with important

implications for the empirical strategy. Tax revenue (TAXREV) is stationary at a level, indicating a mean-

reverting process likely anchored in stable institutional structures (Nikiema and Zore 2025). Similarly,

regulatory quality (REGQ) is also stationary, suggesting persistence in governance frameworks over time.

In contrast, internet penetration (INTERNETPEN), credit to the private sector (CPS), and GDP per capita

(GDPPC) are integrated of order one, reflecting their evolving and trend-driven nature. This combination

of I(0) and I(1) variables necessitates a careful approach to modelling long-run relationships. To address this,

the study applies panel cointegration techniques. While the Kao test confirms the existence of cointegration,

its assumption that all variables are I(1) introduces some limitations in this mixed-integration context. For

this reason, the analysis is complemented with the Pedroni cointegration tests, which are more flexible in

heterogeneous panels (Pedroni 2004). More importantly, the long-run estimates are obtained using the

Pooled Mean Group (PMG) estimator within an ARDL framework, which is well-suited to variables with

mixed integration orders (Pesaran et al. 2001). The consistency of results from FMOLS further strengthens

confidence in the robustness of the findings.

Cointegration Test

Table 5 presents the results of the panel cointegration tests, employing the Kao residual approach

alongside the within- and between-dimension statistics of the Pedroni framework, to examine the existence

of a long-run equilibrium relationship among the variables under study.

Table 5. Cointegration Test Results

Test

Statistic

p-value

Inference

Kao Residual Cointegration

ADF

-3.397

0.0003***

Cointegration

Pedroni Within-Dimension

Panel PP-Statistic (weighted)

-2.613

0.0045***

Cointegration

Panel ADF-Statistic (weighted)

-3.837

0.0001***

Cointegration

Pedroni Between-Dimension

Group PP-Statistic

-6.032

0.0000***

Cointegration

Group ADF-Statistic

-3.905

0.0000***

Cointegration

Source: Authors’ Computation 2026.

Note: *** denotes significance at 1% level.

The cointegration test results shown in Table 4 above confirm the existence of equilibrium

relationships among tax revenues, digitalization, institutional quality, and control variables. This provides

justification for using level models and even for using the PMG method to model short- and long-run

relationships. While the Kao test assumes all variables are I(1), it was included mainly for transparency

despite this limitation. To address this, more robust methods were applied, including the Pedroni test, which

performs better with mixed data. Most importantly, the analysis relies on the PMG-ARDL approach,

specifically designed for variables with mixed integration orders, making it more appropriate and reliable.

The FMOLS results further support the findings, providing additional confidence in the long-run

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relationships identified in the study.

Panel Causality Analysis

Table 6 presents the results of the Dumitrescu–Hurlin panel causality tests, clearly showing how key

variables such as internet penetration, tax revenue, regulatory quality, credit to the private sector, and GDP

per capita influence one another across the sampled economies.

Table 6. Dumitrescu-Hurlin Panel Causality Tests

Null Hypothesis

W-Statistic

Z-bar

Statistic

p-value

Direction

INTERNETPEN

TAXREV

2.335

2.628

0.009***

INTERNETPEN→

TAXREV

INTERNETPEN

1.662

1.174

0.240

No causality

REGQ ↛ TAXREV

2.744

3.502

0.001***

REGQ → TAXREV

TAXREV ↛ REGQ

1.715

1.285

0.199

No causality

CPS ↛ TAXREV

2.310

2.573

0.010**

CPS → TAXREV

TAXREV ↛ CPS

2.039

1.987

0.047**

TAXREV → CPS

GDPPC ↛ TAXREV

3.331

4.777

0.000***

GDPPC → TAXREV

TAXREV ↛ GDPPC

1.412

0.635

0.525

No causality

REGQ INTERNETPEN

2.456/2.662

2.885/3.330

0.004***/0.001***

Bidirectional

GDPPC INTERNETPEN

3.775/3.555

5.742/5.267

0.000***/0.000***

Bidirectional

Source: Authors Computation 2026 Note: ***, ** denote significance at 1%, 5% levels indicate "does not

Granger-cause"; indicates "Granger-causes”; indicate bidirectional causality

The Dumitrescu-Hurlin panel causality results presented in Table 5 provide clear insight into the

directional relationships among the study variables, offering both empirical depth and practical relevance.

The findings show an unidirectional causal flow from internet penetration to tax revenue (W-Stat = 2.335,

Z-bar = 2.628, p = 0.009), highlighting how digitalization actively supports fiscal performance through

improved tax administration and compliance, consistent with evidence from Sub-Saharan Africa (Okunogbe

and Santoro 2023). More striking is the stronger causal influence of regulatory quality on tax revenue (W-

Stat = 2.744, Z-bar = 3.502, p = 0.001), reinforcing the idea that effective institutions remain central to fiscal

capacity, as emphasized in institutional theory (North 1990; Bah 2024; Nikiema and Zore 2025).

At the same time, the results reveal important feedback mechanisms. Bidirectional causality between

regulatory quality and internet penetration (p = 0.004; p = 0.001) suggests a mutually reinforcing

relationship, where better governance supports digital expansion, while digitalization strengthens

transparency and accountability (Nose et al. 2025). A similar two-way relationship exists between GDP per

capita and internet penetration, reflecting the close connection between economic development and digital

progress (Beck et al. 2000). Additionally, the bidirectional link between credit to the private sector and tax

revenue points to the role of financial deepening in expanding the tax base.

Fixed Effects Regression Result

Results from the baseline fixed-effects panel regression model are presented in Table 7 and serve as

the basic model before exploring heterogeneity and dynamics. The regression model controls for countries

and time fixed effects. The country’s fixed effects help account for unobserved country-specific

characteristics.

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Table 7. Fixed Effects Panel Regression Results

Variable

Coefficient

Std. Error

t-Statistic

p-value

INTERNETPEN

0.0428**

0.0182

2.352

0.019

REGQ

2.3156***

0.4721

4.904

0.000

INTERNETPEN × REGQ

0.0516**

0.0234

2.205

0.028

LogGDPPC

1.8743***

0.4328

4.331

0.000

CPS

0.1647***

0.0241

6.835

0.000

FDI

-0.00031*

0.00017

-1.824

0.069

Constant

-5.2134**

2.1847

-2.387

0.018

Diagnostics

R-squared (within)

0.6847

F-statistic

58.342***

Countries

Observations

319

Country FE

Yes

Time FE

Yes

Source: Authors’ Computation 2026.

*Note: ***, **, * denote significance at 1%, 5%, 10% levels.

The empirical results provide clear evidence that digitalization, institutional quality, and their

interaction are central to shaping fiscal performance. Internet penetration has a positive, statistically

significant effect on tax revenue (β = 0.043, p = 0.019), implying that a 1 percentage point increase in internet

usage raises the tax-to-GDP ratio by 0.043 percentage points. While modest in isolation, this effect becomes

economically meaningful at scale; a 10-50 percentage point increase in penetration, typical of digital

transitions in African economies, translates into approximately 1.7 percentage points increase in tax

revenue, representing about a 16% improvement over the regional average. This finding aligns with

emerging African evidence linking digitalization to enhanced fiscal outcomes (Iddrisu 2023; Tolossa and

Melese 2024).

Institutional quality, particularly regulatory quality, emerges as an even stronger determinant of

revenue mobilization (β = 2.316, p < 0.001). A one-standard-deviation improvement increases tax revenue

by about 1.07 percentage points of GDP, reinforcing the argument that effective governance strengthens

compliance, reduces leakages, and improves administrative efficiency (Bah 2024; Nikiema and Zore 2025).

Importantly, the interaction between internet penetration and regulatory quality is positive and significant

(β = 0.052, p = 0.028), indicating that the fiscal gains from digitalization are conditional on institutional

strength. Marginal effects reveal that in weak governance environments, digitalization yields limited or even

negative returns, whereas in stronger institutional settings, it generates substantial fiscal benefits. This

supports the view that technology and institutions are complementary rather than substitutable (North 1990;

Ackom et al. 2025; Nose et al. 2025). Control variables further reinforce these dynamics. GDP per capita (β

= 1.874, p < 0.001) and financial development (β = 0.165, p < 0.001) positively influence tax revenue by

expanding tax bases and improving transaction traceability, while FDI shows a marginal negative effect (β

= −0.0003, p = 0.069). Overall, the model explains 68.5% of within-country variation, underscoring the

combined importance of digital infrastructure, institutions, and economic development.

Pooled Mean Group (PMG) Estimation Results

To explicitly identify the dynamics of short- and long-run equilibrium relationships and to account

for potential endogeneity, we estimate an Autoregressive Distributed Lag (ARDL) model using the Pooled

Mean Group (PMG) estimator. Table 8 illustrates the outcomes of the ARDL (2,2,2,2,2,2) specification that

was chosen based on the Akaike Information Criterion.

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Table 8. Pooled Mean Group ARDL Estimation Results

Long-Run Coefficients

Coefficient

Std. Error

t-Statistic

p-value

INTERNETPEN

-0.0238***

0.0058

-4.077

0.000

REGQ

-2.0378***

0.3752

-5.431

0.000

CPS

0.0893***

0.0191

4.664

0.000

FDI

-0.0002***

0.0001

-3.410

0.001

GDPPC

7.4079***

0.4510

16.427

0.000

Short-Run Dynamics

Coefficient

Std. Error

t-Statistic

p-value

Error Correction (ECT)

-0.7148***

0.0879

-8.136

0.000

ΔTAXREV

-0.0407

0.1095

-0.372

0.710

ΔINTERNETPEN

0.0533

0.0492

1.084

0.280

ΔINTERNETPEN

0.1785*

0.0905

1.972

0.051

ΔREGQ

1.5616

1.1862

1.316

0.190

ΔCPS

-0.1409

0.1472

-0.957

0.340

ΔCPS

-0.1593**

0.0633

-2.517

0.013

ΔGDPPC

7.4126

7.1396

1.038

0.301

Constant

-35.9284***

4.1230

-8.714

0.000

Model Diagnostics

Log likelihood

-186.001

Observations

289

Countries

Source: Authors Computation 2026.

Note: ***, **, * denote significance at 1%, 5%, 10% levels.

The error-correction estimate of -0.715 (p<0.001) confirms strong cointegration and implies that

about 71.5% of disequilibrium is corrected annually, suggesting a responsive fiscal system with effective

adjustment mechanisms. This rapid mean reversion aligns with evidence from developing regions where

fiscal variables tend to converge quickly to equilibrium (Katuka and Mudzingiri 2023). However, the long-

run dynamics reveal more nuanced relationships than static models suggest. Internet penetration, for

instance, exerts a negative long-run effect on tax revenue (β = -0.024; p < 0.001), despite a weakly positive

short-run impact (β = 0.179; p = 0.051). This suggests that while digitalization initially improves tax

administration, it may later facilitate sophisticated tax avoidance, particularly by multinational corporations

and high-income groups (OECD 2024b). Similarly, regulatory quality shows an unexpected negative long-

run effect (β = -2.038, p < 0.001), possibly reflecting transitional compliance costs and institutional

adjustments.

In contrast, private sector credit (β=0.089, p<0.001) and GDP per capita (β=7.408, p<0.001) continue

to have strong positive long-run effects, reinforcing the importance of financial depth and economic growth.

The divergence between the error-correction and fixed-effects results highlights the importance of capturing

dynamic adjustments. The fixed effects estimates confirm that internet penetration (β=0.043, p=0.019) and

regulatory quality (β=2.316, p<0.001) positively influence tax revenue, consistent with prior studies (Iddrisu

2023; Tolossa and Melese 2024; Bah 2024). The positive interaction term (β=0.052, p=0.028) further shows

that digitalization is more effective in stronger institutional settings, reinforcing the complementarity

between technology and governance (North 1990; Ackom et al. 2025).

Panel Fully Modified OLS (FMOLS) Results

To address endogeneity arising from correlation between regressors and the error term in cointegrated

panel data analysis, and to obtain efficient estimates in cointegrated panel data models, we use the Panel

Fully Modified Ordinary Least Squares (FMOLS) method.

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Table 9. Panel FMOLS Estimation Results

Variable

Coefficient

Std. Error

t-Statistic

p-value

INTERNETPEN

-0.0403***

0.0054

-7.418

0.000

REGQ

1.1153***

0.2011

5.546

0.000

CPS

0.2247***

0.0086

26.066

0.000

FDI

-0.0003***

0.0001

-6.081

0.000

GDPPC

1.0774***

0.0294

36.697

0.000

Model Statistics

R-squared

0.4809

Adjusted R-squared

0.4740

S.E. of regression

2.8295

Long-run variance

1.6422

Observations

303

Source: Authors’ Computation 2026.

Note: *** denotes significance at 1% level.

The FMOLS findings support the most important findings but add some detail. The internet

penetration once again shows a negative long-run coefficient (β = -0.040, p < 0.001), which validates the

PMG result and reinforces the observation that even long-term digital transformation entails complex fiscal

trade-offs. This adverse long-run impact, which is the opposite of the positive contemporaneous impacts in

fixed effects models, implies that digitalization follows a non-monotonic path: the early efficiency gains in

the administration are eventually replaced by problems of digital tax evasion, e-commerce-driven base

erosion, and regulatory arbitrage enabled by digital platforms. In the FMOLS specification, which is fixed

effects, a high positive coefficient (β = 1.115, p < 0.001) is observed for regulatory quality, unlike in PMG.

This positive sign has been recovered, indicating that, with the right approach to endogeneity correction

(FMOLS), the positive effects of institutional quality have become dominant. The fact that the FMOLS

estimator can account for simultaneity between governance and revenue improvements is likely to yield

more valid estimates than dynamic specifications, which can be subject to specification sensitivity.

The largest standardized effect is on credit to the private sector (β = 0.225, p < 0.001), and the very

high t-statistic (t = 26.07) indicates the precision of its estimation. Such a discovery highlights the financial

sector as the best and most consistent predictor of tax revenue mobilization in West African settings, which

operates through formalization, increased transactional traceability, and the development of a stronger

compliance infrastructure. GDP per capita is robustly affecting it (β = 1.077, p < 0.001), while FDI shows a

minimal negative coefficient (β = -0.0003, p < 0.001), but this time it is significant, perhaps due to the

dynamics of tax competition and investment spurring. The FMOLS model explains 48.1 percent of the total

variation (R2=0.481), which is lower than the within-R2 for fixed effects, but is respectable given the cross-

sectional variation in panel data. The small long-run variance (1.642) indicates cointegrating relationships,

with low residual autocorrelation after FMOLS adjustments.

Moment of Moment Quantile Regression (MMQR) Findings

To estimate heterogeneous effects in the conditional distribution of tax revenues and determine

whether digitalization and institutional quality have different effects in low- and high-revenue contexts, we

use the Method of Moments Quantile Regression developed by Machado and Santos Silva (2019). Table 10

presents estimates of the coefficient at the 25th, 50th (Median), and 75th percentiles, and tests of coefficient

equality at the quantiles.

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Table 10. Distributional Heterogeneity in Tax Revenue Determinants Method of Moments Quantile

Regression Estimates

Variable

Low Revenue

(Q25)

Median Revenue

(Q50)

High Revenue

(Q75)

Inter-Quantile

Difference Tests

Coef. (SE)

Q50–Q25

Internet Penetration

0.016

0.039**

0.071***

3.84**

(0.020)

(0.018)

(0.020)

[0.023]

Regulatory Quality

1.842***

2.287***

2.916***

2.91*

(0.521)

(0.459)

(0.510)

[0.058]

Log GDP per Capita

1.452***

1.822***

2.385***

3.12**

(0.468)

(0.420)

(0.476)

[0.047]

Credit to Private

Sector

0.128***

0.162***

0.209***

4.67**

(0.027)

(0.024)

(0.027)

[0.015]

Foreign Direct

Investment

-0.0003

-0.0003*

-0.0004**

0.87

(0.0002)

[0.385]

Constant

-4.127*

-5.893**

-8.245***

(2.410)

(2.158)

(2.439)

Pseudo R²

0.452

0.522

0.586

Observations

322

Source Authors Computation 2026:

*Note: ***, **, * denote significance at 1%, 5%, 10% levels.

The findings of the quantile regression indicate that there is systematic heterogeneity in the economic

impact of digitalization on revenue distributions, between the fiscal effects of digitalization and institutional

capacity, and that technological adoption is therefore of paramount importance. Internet penetration in low-

revenue settings (typically with poor tax systems) has a small, statistically insignificant impact at the 25th

percentile (β = 0.016, p > 0.10), suggesting that digital tools have little revenue-generating capacity in settings

with weak administrative and legal infrastructure.

On these platforms, poor taxpayer registration, insufficient enforcement tools, and immature legal

frameworks limit their value and keep them underused. In comparison, at the median (when the outcome

ranks in the 50

percentile), the coefficient doubles to 0.039 (p=0.029), as there are major fiscal benefits in

the moderately performing systems, where adequate administrative infrastructure enables digitalization to

boost compliance, efficiency, and tax base. The effect is even greater in high-revenue countries at the 75th

percentile (β = 0.071, p < 0.001), as it increases the low-revenue value by 4 times, underscoring that

digitalization increases existing fiscal capacities. These trends have been statistically proven by quantile

difference tests (Q50-Q25 F=3.84, p=0.023; Q75-Q50 F=5.12, p=0.012): digitalization does not necessarily

put fiscal performance on an even footing, but rather produces a so-called Matthew effect: countries with a

better initial institutional and administrative situation disproportionately. Similar results show that variables

such as regulatory quality, GDP per capita, and private-sector credit exhibit significant, monotonically

positive effects across the quantiles, whereas governance, economic development, and financial

formalization, as cornerstones of the fiscal efficacy of digitalization and FDI, are not significant (all

p<0.001). The level of explanation offered by the model increases to 0.452 at Q25 and 0.586 at Q75,

indicating stronger predictability and stability with larger capacity models.

These findings have significant policy implications. Good digitalization policies should be context-

dependent; low-capacity countries can invest in more advanced digitalization strategies only after basic

institutionalization, such as thorough taxpayer registration, legal reforms, and enforcement mechanisms.

Countries in the middle range of fiscal performance can gain moderately with a focus on digital

infrastructure, and high-capacity states can gain the most by incorporating novel GovTech into a well-

developed administrative system. Notably, homogeneous across-the-board regional strategies are dangerous

because they ignore the imperative of existing institutional and fiscal competencies. All the evidence

combined points to the fact that, on the contrary, the process of digitalization does not reduce but increases

structural inequalities in fiscal performance, and it is important to coordinate technology intervention with

the context of governance and development to ensure sustainable increases in revenues.

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SVAR Impulse Response Functions (SVAR-IRFs)

This study uses a Structural Vector Autoregression (SVAR) Impulse Response Function to explore

how digitalization and institutional quality dynamically affect tax revenue. By identifying structural shocks

and tracing their effects over time through impulse response functions, the approach captures how changes

in key variables unfold within the fiscal system. The main results of this analysis are presented in Figure 1.

Source: Authors’ Computation 2026.

Notes: ± 2 S.E. confidence bands (shaded) from Monte Carlo simulation (1,000 replications). Red line = zero baseline.

Navy line = IRF point estimate. Intermediate periods (2, 4, 6-9) linearly interpolated between reported periods 1, 3, 5,

and 10.

Figure 1. Panel SVAR Impulse Response Functions

The impulse response results show, in a very intuitive way, that tax revenue tends to improve most

when the broader system around it works well. When regulatory quality strengthens, tax revenue rises

quickly and remains stable, suggesting that when rules are clear, institutions are credible, and enforcement

is consistent, individuals and firms are more willing and more compelled to comply (Bati 2025; Binh et al.

2024). In much the same way, growth in GDP per capita steadily lifts tax revenue over time, as expanding

economies tend to formalize economic activities and broaden the tax base, making revenue collection more

efficient and sustainable (OECD 2025b; Lengaram 2025). What stands out here is not just the size of these

effects, but their reliability. Strong institutions and sustained economic growth provide a dependable

foundation for fiscal strength (Peprah et al. 2022). The story is slightly different for internet penetration and

financial development, where the benefits take longer to fully emerge. The positive effects are there, but they

build gradually, reflecting the reality that digital tools and financial systems do not transform tax collection

-0,020

0,000

0,020

0,040

0,060

0,080

0,100

0,120

0,140

0,160

1 2 3 4 5 6 7 8 9 10

Response of TAXREV to INTERNETPEN

Shock

Lower Base ±2 S.E. Band

Zero Line IRF Estimate

0,000

0,200

0,400

0,600

0,800

1,000

1,200

1 2 3 4 5 6 7 8 9 10

Response of TAXREV to REGQ Shock

Lower Base ±2 S.E. Band

Zero Line IRF Estimate

0,000

0,100

0,200

0,300

0,400

0,500

0,600

0,700

0,800

1 2 3 4 5 6 7 8 9 10

Response of TAXREV to GDPPC Shock

Lower Base ±2 S.E. Band

Zero Line IRF Estimate

-0,100

0,000

0,100

0,200

0,300

0,400

0,500

0,600

0,700

1 2 3 4 5 6 7 8 9 10

Response of TAXREV to CPS Shock

Lower Base ±2 S.E. Band

Zero Line IRF Estimate

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overnight. Instead, they require time, adaptation, and supportive institutions to be effective. As digitalization

expands, it enhances transparency and improves the traceability of economic activities, while financial

deepening contributes to the formalization of transactions and the expansion of business activity, both of

which ultimately strengthen tax revenue mobilization (Dongmo et al. 2026; Balengla et al. 2026; OECD

2025b). In all, the results suggest a layered process: technology and finance matter, but their full impact

depends on the strength of institutions and the pace of economic development, which ultimately anchor

sustainable revenue mobilization.

Synthesis and Theoretical Integration

This section encapsulates the synthesis and theoretical unification of results from earlier stages of the

research, highlighting the subtle relationship among digitalization, institutional quality, and revenue

outcomes in West Africa. Fixed-effects regressions indicate strong positive contemporaneous effects of

digitalization and institutional quality, and, as a result, the interaction terms show large complements. Both

PMG-ARDL and FMOLS indicate that the dynamics are complex: the short-run benefits of digitalization

are positive, while the long-run changes are negative, suggesting that the initial efficiency gains are

neutralized in the long run by digital tax evasion and regulatory arbitrage. Institutional quality has more

stable positive influences, though dynamic sensitivities are found. Quantile regressions provide evidence of

heterogeneity: digitalization generates significant revenue improvements only when there is a more

developed fiscal basis, which makes leapfrogging assumptions challenging and raises complementary

technology and institutional basis arguments. Panel SVAR analysis shows that time propagation follows

digitalization shocks, producing hump-shaped medium-term events, whereas institutional shocks are larger

and more long-lasting, with a variance decomposition indicating that governance accounts for almost twice

the explanatory power as digitalization.

These trends are consistent with theoretical models combining fiscal capacity, institutional

economics, and technology-efficiency hypotheses. The theory of classical fiscal capacity (Besley and Persson

2014) and the institutional complementarity thesis proposed by North (1990) are confirmed, and it is shown

that digital tools complement rather than substitute for organizational capacity (Nose et al. 2025). The short-

run revenue gains must be working through the mechanisms of reduced compliance costs, reduced

information asymmetry, and expanded tax base, whereas the long-run lowering will be manifested through

taxpayer adaptation, shifting of profits, and tax arbitrage. Institutional quality promotes legitimacy,

bureaucratic capacity, legal predictability, and control over corruption, resulting in permanent fiscal

resources rather than short-term benefits.

CONCLUSION AND POLICY RECOMMENDATIONS

This research presents a rigorous examination of the mutual impact of digitalization and institutional

quality on tax revenue mobilization in West Africa, using panel data from 14 ECOWAS countries from

2000 to 2023. Based on institutional economics, the results reveal that digitalization is associated with an

immediate boost in efficiency, enhanced compliance, and an increased revenue base; however, the effects

are non-linear and short-lived, limited by advanced levels of tax evasion and regulatory arbitrage.

Digitalization is, therefore, a volatile and conditional instrument that must be upgraded and supported by

policies in a revisionist fashion to impact efficient revenue drive in West Africa (Okunogbe and Santoro

2023).

The quality of institutions appears as the dominant and stable driver of fiscal capacity. Digital reforms

exert less extensive and stable effects on public revenues than regulatory and institutional quality upgrades,

suggesting that technological reforms remain promising only when embedded in high-quality institutional

settings. Findings from interaction analyses confirm the complementary nature of institutional and

technological upgrades: digital reforms improve public revenue outcomes in high-quality governance

institutions but exert no or limited effects in weak institutions.

The improvement in finances needs action with the power to enable both governance and the digital

infrastructure. The concept of universalized projects in digitalization carries the threat of inefficiency with

highly situational returns, and the divergences will be accentuated in the absence of supporting institutional

frameworks. The adoption and implementation of the concept of digitalization call for sequencing in reform

actions targeting institutional strengthening and maximizing revenue.

These findings offer policymakers useful insights into leveraging tax mobilization in West Africa's

respective environments. The exhibited complementarity between digitalization and institutional quality

suggests that the sequence of reforms is the most important, and that institutional capacity building will

precede mass digital investments. Jurisdictions in the bottom segment of the revenue distribution need to

focus on basic reforms, such as full taxpayer registration, an effective legal infrastructure for electronic

transactions, adequate administrative capacity, and effective anti-corruption measures. Where institutional

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structures are weak, early digital investments yield low fiscal benefits and can enable the capture and

misallocation of public funds by elites as the contribution margin of digitalization falls below governance-

required critical levels. It is a gradual process of reform thus suggested to begin with, legal and regulatory

provisions should be introduced to acknowledge electronic transactions and enable admissibility of digital

records; administrative systems and human capital should be strengthened with specific training; digital

platforms should be tested in controlled settings to identify operational limitations; proven solutions should

be scaled-up and quality standards need to be maintained; and continuous upgrading mechanisms in

response to change in technology and emerging tax avoidance practices should be institutionalized. Regional

blocs such as ECOWAS, WAEMU, and the West African Tax Administration Forum, rather than enforcing

common standards, offer a wide range of digitalization pathways tailored to each nation's tax-raising

capacity.

The digital tax efforts must incorporate institutional fortification rather than treating governance as

an external element of technology adoption. These should be bundled into project design with

complementary reforms such as legally recognizing electronic evidence, control and auditing mechanisms

that prevent system manipulation, capacity-building of tax officials to operate digitally, formal strategies for

engaging stakeholders so that taxpayers voluntarily comply in trust, independent accountability bodies that

limit elite capture, and sunset provisions mandating periodic performance reviews. The overall positive

correlation between the development of the financial sector and tax revenue, even at the quantile level, also

indicates that software tax reforms should be implemented as part of broader financial inclusion strategies.

The fiscal effectiveness of digitalization can be multiplied by expanding informal operators' access to

banking, expanding the use of mobile money to replace cash, making small-business credit more proactive

to incentivize formal recordkeeping, and investing in digital payment infrastructure to enhance transaction

traceability. Good implementation needs well-developed monitoring and evaluation systems. A high

frequency of panel data collection should enable distributional assessment and experimental and quasi-

experimental designs to isolate the causal effects of a particular intervention. Continuous auditing, feedback,

technological updates, and policy flexibility are key to maintaining revenue gains.

Acknowledgments

The authors acknowledge that no additional support was received beyond the contributions of the authors

and the funding disclosed in this study.

Funding Statement

This study received no financial support. The research, analysis, and publication of the article were carried

out by the authors. The authors received no grants, royalties, consulting fees, or other funding.

Data Availability Statement

The data used in this study are publicly available and can be accessed online through the following websites:

https://data.imf.org/en/datasets/IMF.STA:QGFS

https://databank.worldbank.org/reports.aspx?dsid=2&series=SP.POP.65UP.TO.ZS

https://www.worldbank.org/en/publication/worldwide-governance-indicators

Conflict of Interest

The authors declare that there are no personal or financial interests that could have influenced the results or

interpretation of this research. Therefore, the authors declare no conflict of interest.

AI Tools Statement

The authors disclose that Grammarly’s AI-based language editing tools were used solely to improve the

grammar and clarity of the manuscript.

Author contribution

Igyo Jude Ali, Patricia, and Lindelwa Makoni contributed to the conceptualization, validation, formal

analysis, investigation, resources, writing (original draft preparation, review, and editing), visualization,

supervision, project administration, and funding acquisition of the study. Igyo Jude Ali was responsible for

the methodology and software development, while Igyo Jude Ali and Patricia contributed to data curation.

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