Review Reports

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

1. Abstract

The abstract is well-structured but fundamentally misleading. It claims to study "digital finance taxation," but the empirical analysis actually uses general "taxes on goods and services (excise duties)." The abstract presents the counter-intuitive finding that indirect taxes increase digital finance adoption without clarifying that this is an artifact of using general macroeconomic tax data rather than specific digital levies (like Ghana's e-levy).

2. Introduction

The introduction provides a good theoretical grounding (public finance, institutional economics, fiscal legitimacy). The identification of the research gap is adequate. However, the introduction sets up an expectation that the paper will analyze specific digital finance taxes (e.g., "mobile money levies, direct digital services taxes"), which the methodology completely fails to deliver.

3. Literature Review

The literature review is comprehensive but contains a fatal disconnect. Section 2.1 extensively reviews studies on specific digital finance taxes (e.g., Ghana's e-levy, specific mobile money transaction taxes) and correctly summarizes that they hinder adoption. However, the empirical section suddenly pivots to using general indirect taxes (VAT and excise duties) as the independent variable. The authors do not theoretically justify how a general tax on goods and services acts as a proxy for digital finance taxation.

Note: The section heading "Littérature review" (French) is a sloppy editing error for an English-language journal.

4. Data and Methodology

This section contains the most severe flaws of the manuscript:

Independent Variable Mismatch (Fatal Flaw): The authors measure "digital finance taxation" using the UNU-WIDER dataset variable tax_gs_excises (Taxes on goods and services, of which excise duties). This is a measure of general consumption taxation (VAT on physical goods, fuel excise, alcohol, etc.), NOT a tax on digital finance. Using this to proxy for digital finance taxation invalidates the entire study.

Dependent Variable Measurement: Measuring "digital finance adoption" as a binary 0/1 variable (1 if the population adopts, 0 if not) destroys the variance in the data. Mobile money adoption grew from 0% to over 40% across Africa; treating this as a binary outcome rather than a continuous rate introduces massive measurement error.

Timeframe Anomaly: The study uses a panel from 1980–2023. M-Pesa (the pioneer of African mobile money) launched in 2007. Including data from 1980 to 2006 to study "digital finance adoption" is statistically nonsensical and suggests a fundamental misunderstanding of the data or purely mechanical data-merging without cleaning.

5. Results and Discussion

Because the baseline model is misspecified, the results are spurious. The finding that general indirect taxes increase digital finance adoption is simply capturing a time-trend spurious correlation: as African economies developed between 2007 and 2023, both general tax revenues and mobile money adoption increased simultaneously.

The authors' post-hoc explanation for this (a "substitution effect" where taxes on formal goods push people to digital finance) is theoretically weak, especially since VAT and excise duties also apply to mobile airtime and digital devices in most African countries. The moderation analysis suffers from the same foundational misspecification.

6. Conclusion & Policy Implications

The policy implications are generic. Furthermore, the authors make a chronological error, stating that the Central Bank of West African States (BCEAO) launched the PI-SPI platform on "September 30, 2025." Unless the authors are writing from the future, this is factually impossible and heavily detracts from the paper's credibility.

Limitations and Negative Aspects

Severe Construct Validity Failure: The core assumption of the paper—that general consumption taxes (VAT/Excise) represent "digital finance taxation"—is academically indefensible.

Massive Endogeneity / Omitted Variable Bias: The positive relationship between general taxation and digital finance adoption is almost entirely driven by omitted variables (e.g., GDP growth, technological infrastructure, urbanization over time). The authors fail to adequately address endogeneity (e.g., using instrumental variables or lagged dependent variables in a dynamic GMM model, which is standard for macro-panel adoption studies).

Inappropriate Data Inclusion: Using data from the 1980s and 1990s for a dependent variable that did not exist until the late 2000s ruins the panel data structure.

Binary DV for a Continuous Phenomenon: Reducing the rich GSMA mobile money data to a country-level 0/1 dummy variable wastes analytical power.

Author Response

All the comments are incorporated into the new version. The changes are in colour.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

This paper empirically analyzes the impact of taxation on digital finance adoption in Africa. I think this paper has problems in several aspects. I state my detailed comments and suggestions below.

(1) Line 5 on Page 1: It is stated that “The aim of this study is to investigate ... the impact of digital finance taxation on the adoption of digital finance...”. However, the independent variable in the empirical study is the “tax revenue”. Where is the “digital finance” taxation reflected in this study? This is confusing.

(2) Line 81 on Page 3: “Littérature” should be “Literature”. Please check that.

(3) Line 195 on Page 5: Should “Empirical evidence from financial inclusion” be numbered as section 2.3? Please check.

(4) Line 244-245 on Page 6: It is stated that “we measure digital finance adoption through the share of population that adopts mobile money”. The dependent variable appears to be a proportion between 0 and 1. However, the empirical analysis uses a probit model, which implies that the dependent variable should be a binary 0/1 variable. Is there a contradiction here?

(5) Line 259-260 on Page 6: It is stated that “the source of our primary dependent variable: tax revenue”. Should “dependent variable” be “independent variable”? Please check that.

(6) Line 292-293 on Page 7: It is stated that “Education is measured by the average number of years of secondary schooling completed by individuals”. However, according to Table 1 on Page 8, the mean value of educ is 93.197. Why is this value so large?

(7) Figure 2 on Page 14: Do the error bars in the figure represent 90% confidence intervals or 95% confidence intervals? Please clarify.

(8) The reference style is inconsistent with the journal’s requirements. Please check.

Author Response

All the comments are incorporated into the new version. The changes are in colour.

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

Overall, this manuscript addresses a timely and policy-relevant research question by examining the interplay between taxation, governance quality, and digital finance adoption in African economies. The study demonstrates clear potential for contribution by integrating public finance and institutional economics perspectives and by employing a relatively rich panel dataset covering 41 countries over an extended period. The empirical findings—particularly the counterintuitive positive association between taxation and digital finance adoption and the moderating role of governance dimensions—are interesting and potentially impactful. However, despite these strengths, the paper requires major revisions before it can meet the standards of an international academic journal.

The introduction section provides a relevant and timely motivation by highlighting the rapid expansion of digital finance in Africa and its implications for financial inclusion and fiscal capacity. However, it would benefit from greater conceptual clarity, stronger theoretical integration, and a more precise articulation of the research gap. While the authors appropriately cite prior studies documenting both the benefits of digital finance (e.g., financial inclusion and resilience) and the potentially adverse effects of taxation (e.g., Diouf et al., 2024; Pobee et al., 2023), the narrative remains somewhat descriptive and lacks a clear synthesis that positions the study within a well-defined debate. In particular, the claim that existing literature treats taxation as “institutionally neutral” should be more rigorously substantiated with targeted citations and contrasted explicitly with institutional economics arguments (e.g., North, 1990; Williamson, 1985) already mentioned in the text. Moreover, the introduction section would be strengthened by clearly distinguishing between different types of taxation (e.g., transaction taxes vs. indirect taxes) and their expected behavioural effects, as the current framing risks conceptual ambiguity. The research question is relevant but could be sharpened by explicitly stating the expected direction of effects and the underlying mechanisms (e.g., trust, fiscal legitimacy per Levi, 1988), thereby improving alignment with the empirical design.

The literature review section provides a broad and relevant overview of the relationship between taxation, digital finance adoption, and governance quality. However, it requires substantial refinement to achieve stronger theoretical coherence and analytical depth. While the section appropriately draws on public finance theory (e.g., Atkinson & Stiglitz, 1980), institutional economics (e.g., North, 1990), and financial inclusion literature, the integration of these strands remains largely descriptive rather than analytical. The discussion of taxation effects is comprehensive, highlighting both negative impacts on usage (e.g., Silue, 2022; Pobee et al., 2023) and broader fiscal motivations, yet it lacks a clear synthesis that reconciles these conflicting findings into testable expectations. Similarly, the subsection on governance quality correctly identifies its moderating role, but the mechanisms (e.g., trust, transparency, compliance) are not sufficiently formalized or linked explicitly to the empirical hypotheses. The review would benefit from a more structured progression—moving from theory to empirics and then to hypothesis development—rather than presenting studies in a fragmented manner. In addition, there is some redundancy across subsections (e.g., repeated references to cost barriers and institutional quality), which could be streamlined to improve clarity. The inclusion of frameworks such as the technology acceptance model and innovation diffusion theory is valuable, but their connection to taxation and governance remains underdeveloped.

The data and methodology section provides a generally appropriate empirical framework and draws on credible data sources, including the GSMA database for digital finance and the World Development Indicators and World Governance Indicators for macroeconomic and institutional variables. However, it requires significant clarification and methodological strengthening to ensure transparency and rigor. First, the construction and measurement of the dependent variable—digital finance adoption as a binary indicator—needs clearer justification, particularly given the potential loss of information compared to a continuous measure (e.g., share of users), and the implications this choice has for interpretation. Second, while the selection of taxation variables (e.g., taxes on goods and services, excises) is well motivated, the conceptual link between these proxies and “digital finance taxation” remains indirect and should be more explicitly justified. Third, the econometric choice of a random-effects probit model is not sufficiently defended. The authors should discuss why this specification is preferred over fixed-effects alternatives and formally test the underlying assumptions (e.g., exogeneity of individual effects), especially given potential unobserved heterogeneity across countries. Moreover, the section does not adequately address key econometric concerns such as endogeneity (e.g., reverse causality between digital finance adoption and taxation), omitted variable bias, and dynamic effects, which are particularly relevant in a long panel setting. The inclusion of interaction terms with governance variables is appropriate, but the interpretation of these nonlinear effects should be better anticipated and formally explained. Additionally, more detail is needed regarding data coverage (e.g., missing observations, unbalanced panel issues), variable transformations, and diagnostic checks.

The results and discussion section presents a coherent set of empirical findings and offers an initial interpretation of the relationships between taxation, governance quality, and digital finance adoption. However, it requires deeper analytical rigor and clearer theoretical integration to strengthen its contribution. While the baseline results indicate a positive and statistically significant effect of taxation on digital finance adoption across specifications, the discussion of this counterintuitive finding remains largely speculative and insufficiently grounded in the theoretical framework outlined earlier (e.g., substitution effects, fiscal legitimacy, or institutional trust). The authors should more systematically reconcile these results with the dominant literature that documents negative effects of taxation on financial inclusion (e.g., Silue, 2022), thereby clarifying whether their findings reflect context-specific dynamics or methodological differences. Additionally, although the inclusion of control variables and sensitivity analyses (Table 3) enhances robustness, the discussion does not fully exploit these results to provide deeper economic insights or heterogeneity patterns. The interpretation of interaction effects with governance variables (Table 4) is a strong element of the paper, yet it would benefit from a more structured explanation of marginal effects and nonlinearities, as well as clearer linkage to institutional theory. Furthermore, the section lacks a critical assessment of potential biases (e.g., endogeneity, measurement error) that may influence the estimates, and robustness checks are not sufficiently elaborated. Presentation-wise, the discussion tends to reiterate results rather than critically interpret them, and the transition between empirical findings and policy implications is somewhat abrupt.

Author Response

All the comments are incorporated into the new version. The changes are in blue (literature review) and red (methodology and results).

We believe these revisions have substantially improved the manuscript and eliminated the misspecification concerns you rightly raised. We are grateful to the reviewer for the detailed, constructive, and insightful comments. We have carefully considered all the points raised and have substantially revised the manuscript accordingly.

All the reviewer’s requests and suggestions have been fully integrated into the new version of the paper.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

I would like to thank the authors for carefully addressing the comments and suggestions provided during the review process. The revisions have improved the quality of the manuscript considerably. Based on the implemented modifications, the manuscript is now likely suitable for acceptance, subject to the editor’s final decision.

Reviewer 2 Report

Comments and Suggestions for Authors

The authors have revised the manuscript. I have no further comment.

Reviewer 3 Report

Comments and Suggestions for Authors

The revised version of the manuscript demonstrates substantial improvement and adequately addresses the major concerns raised during the initial review process. The authors have significantly strengthened the theoretical framing by more clearly integrating public finance theory, institutional economics, and fiscal legitimacy perspectives, while also providing a more precise articulation of the research gap, hypotheses, and moderating mechanisms associated with governance quality.