1. Introduction

Lending is among the oldest financial practices, with documented origins dating to around 300 BC (Collins English Dictionary). In contemporary financial systems, lending refers to the process by which financial institutions, including banks, credit unions, mortgage lenders, and microfinance institutions, provide funds to borrowers who incur debt repayable with interest over an agreed period. Collateral is frequently pledged to secure loans, reducing risk for the lender and potentially lowering interest costs for the borrower. Beyond lending, microfinance institutions also provide a broad range of financial services, including deposit-taking, payment services, money transfers, and insurance, to low-income households and micro-enterprises at affordable rates. In Cameroon, there are over 850 registered MFIs, reflecting the significant role of this sector in the national financial landscape (RKCS, 2021).

Under Section 93(h) of the General Tax Code of the Republic of Cameroon, Category I microfinance institutions, which are classified as non-profit organisations, are exempted from certain taxes such as the business licence fee, company tax, and land tax. However, they remain liable to registration fees, stamp duties, income tax on investment, and related levies. In 2017, Law Decree No. 2017/021 of December 2017 further introduced a Value Added Tax (VAT) of 19.25% on loan interest charged on loans exceeding FCFA 2,000,000 granted by Category I MFIs to their members. This provision was subsequently enacted as part of the 2018 Finance Law. The reform specifically repealed the VAT exemptions previously granted under Sections 128(25) and 546 of the General Tax Code, which had exempted loan interest payments and graduated stamp duties on loans extended by Category I MFIs. The primary motivation for the reform was to broaden the tax base and increase government revenue, given the recognised yield potential and administrative simplicity of VAT relative to other consumption-based taxes such as customs and excise duties.

Despite the fiscal rationale underlying its introduction, the VAT on microfinance lending has attracted widespread criticism from practitioners, policymakers, and members alike. There is a risk that, because the tax burden is ultimately borne by the final consumer, the reform may adversely affect the financially excluded and low-income populations who rely on MFIs as their primary source of formal credit. Critics argue that the tax may deter members from accessing larger loans, increase default rates due to higher debt-service costs, and reduce the competitiveness of Category I MFIs relative to Category II and III institutions that are not subject to the same VAT obligations. In a context already characterized by the protracted Anglophone socio-political crisis and the economic disruptions of the COVID-19 pandemic, the additional tax burden on MFIs raises important questions about the sustainability of these institutions and the welfare of their members.

This study is motivated by the limited empirical evidence on the effects of VAT on the lending operations of microfinance institutions in Cameroon. While existing research has examined corporate income tax and turnover tax on MFI performance in Kenya and elsewhere (Wangeci, 2018; Wanjiru, 2015), none has addressed the specific implications of VAT on MFI lending in the Cameroonian context. This study therefore examines the effect of the 2018 VAT reform on the volume of loans granted, loan patronage, and loan delinquency among Category I MFIs in Bamenda. Specifically, the study pursues the following objectives:

• To assess the effect of Value Added Tax on the volume of loans granted by MFIs;
• To investigate the effect of Value Added Tax on loan patronage of MFIs; and
• To ascertain the effect of Value Added Tax on loan delinquency levels of MFIs.

The remainder of this article is structured as follows. Section 2 reviews the relevant theoretical and empirical literature. Section 3 describes the research methodology, including data sources, variable definitions, and model specification. Section 4 presents and discusses the empirical results. Section 5 concludes the paper and offers policy recommendations.

2. Literature Review

2.1 Theoretical Review

2.1.1 The Benefit Theory of Taxation

The benefit theory of taxation, developed by Erik Lindahl in his seminal work The Justness of Taxation (1919), holds that individuals should contribute to public finances in proportion to the benefits they derive from government-provided goods and services. The theory rests on two interrelated propositions: first, as a descriptive principle of tax incidence, it suggests that the tax burden should reflect the distribution of public benefits; second, as a normative principle, it advocates that the design of tax systems should align fiscal contributions with corresponding public benefits received (Saleemi, 2011).

Critics have raised several objections to the benefit principle. Most fundamentally, estimating the benefit any individual or organisation derives from public expenditure is practically impossible, since many government services, such as national defence, infrastructure, and social protection, are non-excludable and non-rival in consumption (Odongo, 2016). Applying the benefit principle in a society where the poor are disproportionately dependent on public services would also impose heavier tax burdens on those least able to pay (Wasao, 2014). In the context of VAT, both the wealthy and the poor pay at the same statutory rate, making it difficult to establish any meaningful link between the tax burden and individual public benefit.

This theory is relevant here because Category I MFIs argue that imposing VAT on their lending activities conflicts with the benefit principle. These institutions, which primarily serve low-income populations, contend that their members receive limited direct benefit from public services, many relying on private alternatives, and that the additional tax burden undermines rather than reflects any government benefit accrued.

2.1.2 The Ability-to-Pay Theory of Taxation

The ability-to-pay theory, associated with the work of Kendrick (1939) and extended by subsequent scholars, holds that taxes should be levied in accordance with the taxpayer’s capacity to pay. Income is widely regarded as the most objective and equitable indicator of taxable capacity (Grassi, 2015). The theory distinguishes between horizontal equity, the principle that persons with equal capacity to pay should bear equal tax burdens, and vertical equity, the principle that those with greater financial ability should bear proportionally heavier tax obligations (Kabinga, 2015). VAT, being a flat-rate tax on consumption, is generally considered to conflict with vertical equity, as it tends to consume a higher proportion of income for lower-income households than for wealthier ones, thereby reinforcing rather than mitigating inequality.

In this context, the ability-to-pay framework is directly relevant because VAT on loan interest at MFIs increases the cost of borrowing for the poorest segments of the population, those with the least capacity to absorb additional financial burdens. Category I MFIs occupy a distinct position in Cameroon’s financial architecture as non-profit organisations mandated to serve the financially excluded, and subjecting their lending activities to VAT raises legitimate questions about the equity and appropriateness of this tax measure.

2.1.3 Ibn Khaldun’s Theory of Taxation

Ibn Khaldun’s theory of taxation, elaborated in his Muqaddimah (14th century) and discussed extensively by Ishlahi (2006), anticipates what later became known as the Laffer Curve relationship between tax rates and tax revenue. The theory distinguishes between two effects of tax rate changes. The arithmetic effect holds that a reduction in VAT rates will reduce VAT revenue proportionally, while an increase in rates will raise revenue proportionally. The economic effect, by contrast, recognises that lower tax rates stimulate economic activity, increasing output, employment, and taxable transactions, which may ultimately generate greater total revenue despite the lower rate. Conversely, excessively high tax rates may penalise productive economic activities, contracting the tax base to such a degree that total revenue declines (Ishlahi, 2006).

Applied to the present context, this framework suggests that the imposition of a 19.25% VAT on MFI loan interest may, by discouraging borrowing and reducing lending volumes, ultimately diminish the government’s fiscal returns from the microfinance sector. If the economic effect dominates the arithmetic effect, as Ibn Khaldun’s theory predicts at high tax rates, the VAT reform may prove counterproductive from both fiscal and developmental perspectives.

2.2 Empirical Literature Review

Wangeci (2018) examined the effect of income tax on the growth and profitability of microfinance institutions in Voi Sub-County, Kenya, focusing on the specific impacts of corporation tax, withholding tax, and instalment tax. Using a descriptive survey design and questionnaire-based primary data collection, the study found that income tax has a significant negative effect on the growth and profitability of MFIs. The study recommends that governments set tax rates at levels that allow SMEs and financial intermediaries to expand their operations while meeting their tax obligations, and that comprehensive tax literacy campaigns be conducted to improve compliance.

Otwani, Simiyu, and Makokha (2017) investigated the effect of corporate income tax on the financial performance of companies listed on the Nairobi Securities Exchange in Kenya. Employing a mixed-methods design incorporating both qualitative and quantitative approaches, the study found that corporate income tax exerts a significant influence on firm financial performance through its effects on cash flow, working capital, and profitability. The study recommends prompt payment of corporate tax obligations and prudent financial planning as mechanisms for managing tax-related performance risks.

Wanjiru (2015) investigated the effects of turnover tax on the financial performance of microfinance institutions in Bamenda, Cameroon. The study focused on three dimensions of tax-related costs: administration costs, compliance costs, and penalties and fines. Using a descriptive research design and questionnaire-based data collection, the study found a significant negative relationship between these cost categories and MFI financial performance. The study recommends improvements in record-keeping standards, targeted tax literacy campaigns, and structured pathways for transitioning MFIs from simplified tax regimes to standard compliance frameworks.

Ngong (2015) examined the effects of taxation on the performance of micro-enterprises in the Njinikom Sub-Division of Cameroon. Using both qualitative and quantitative research designs, the study found that micro-enterprise performance is significantly affected by tax-related variables including the volume of stock, capital employed, daily sales turnover, and the average annual tax payment. The study recommends reforms in tax collection methods, business community education on applicable tax rates, and the introduction of instalment-based tax payment schemes to ease the compliance burden on micro-enterprises.

Gambacorta, Ricotti, Sundaresan, and Wang (2017) reviewed the effect of corporate taxation on bank liability structure, with specific attention to microfinance institutions and commercial banks. Using a comparative research design, the study found that while the effect of taxation on commercial banks’ liability structure is statistically insignificant, the effect on microfinance institutions is significantly negative. The study attributes this asymmetric effect to the limited economies of scale enjoyed by MFIs, which makes compliance with tax reporting and administrative obligations disproportionately costly relative to larger commercial banking institutions.

Salia (2016) examined the effect of VAT on corporate cash flow in Ghana using secondary financial data from listed companies. The study found that VAT significantly reduces corporate cash flows, particularly for small and medium-sized enterprises that lack the liquidity buffers available to larger corporations. These findings are particularly relevant to the Cameroonian context, as they suggest that even modest VAT rates can have material adverse effects on the operational cash flows of financial intermediaries serving low-income populations.

This review points to several gaps in the literature. First, most studies have focused on corporate income tax, withholding tax, or turnover tax rather than VAT as a specific instrument affecting MFI operations. Second, while some studies have examined VAT’s impact on corporate cash flows in Ghana and Nigeria, none has empirically investigated its effect on the lending operations of Category I microfinance institutions in Cameroon. Third, the Cameroonian microfinance context has distinctive features, including the non-profit orientation of Category I MFIs, the ongoing Anglophone socio-political crisis, and post-COVID-19 economic disruptions, that may produce outcomes not comparable to studies from other Sub-Saharan African contexts. This study addresses these gaps through the first systematic empirical analysis of VAT’s effect on MFI lending operations in Bamenda.

3. Methodology

3.1 Research Design and Scope

This study adopts an ex-post facto research design, which is appropriate for investigating the causal effects of a policy event, the 2018 VAT reform, on outcomes that have already occurred, without the possibility of experimental manipulation. The study focuses on the lending operations of Category I MFIs in Bamenda, the administrative headquarters of the Mezam Division of the North West Region of Cameroon. Secondary data were retrieved from the audited annual financial reports, specifically the balance sheets and profit and loss accounts, of six licensed Category I MFIs for the period 2015 to 2022, yielding an eight-year panel dataset that spans both the pre-VAT period (2015–2017) and the post-VAT implementation period (2018–2022). The six sampled institutions are:

• Bamenda Police Cooperative Credit Union Ltd (BAPCCUL)
• Victoria Cooperative Credit Union Ltd (VITCCUL)
• AZIRE Cooperative Credit Union Ltd (AZICCUL)
• MITAYEN Cooperative Credit Union Ltd (MITACCUL)
• NTARIKON Cooperative Credit Union Ltd (NTACCUL)
• TIKAR Cooperative Credit Union Ltd (TICCUL)

These institutions were selected because they maintain head offices in Bamenda and have complete financial records for the study period. The independent variable is the VAT indicator (a binary variable denoting whether VAT was applicable in a given year), while the dependent variables are the volume of loans granted, loan patronage, and loan delinquency.

3.2 Model Specification

Panel regression analysis is employed to examine the effects of VAT on the three dimensions of lending operations. Lending operations are modelled as a function of VAT, institutional membership, and the Anglophone socio-political crisis, which has affected the North West and South West Regions since 2016. The crisis is captured by a dummy variable coded 0 for the pre-crisis period (2015–2016) and 1 for the crisis period (2017–2022). The functional relationships are expressed as follows:

Lending Operations = f(VAT, Membership, Crisis) ………… (3.1)

Incorporating the error term and the constant, the three estimable econometric models are:

VLOᵢₜ = α₀ + α₁VATᵢₜ + α₂MEMᵢₜ + α₃CRsᵢₜ + εᵢₜ ……………………… (3.2)

LOPᵢₜ = β₀ + β₁VATᵢₜ + β₂MEMᵢₜ + β₃CRsᵢₜ + εᵢₜ ……………………… (3.3)

LODᵢₜ = λ₀ + λ₁VATᵢₜ + λ₂MEMᵢₜ + λ₃CRsᵢₜ + εᵢₜ ……………………… (3.4)

where VLO denotes the volume of loans granted (in logarithmic form), LOP denotes loan patronage (number of loans granted divided by total membership), and LOD denotes the loan delinquency rate. VAT is a binary indicator of VAT application (0 = pre-VAT, 1 = post-VAT); MEM denotes total institutional membership; and CRs is the binary crisis dummy. The subscripts i and t denote the institution and the year, respectively. The parameters α₀, β₀, and λ₀ are intercept terms; α₁–α₃, β₁–β₃, and λ₁–λ₃ are slope parameters to be estimated; and εᵢₜ is the idiosyncratic error term.

3.3 Variable Definition and Measurement

Table 1: Variable Definitions, Measurement, and Expected Signs

3.4 Estimation Techniques

Descriptive statistics, including measures of central tendency (mean), dispersion (standard deviation), and distributional shape (skewness and kurtosis), are computed to characterise the variables and assess the appropriateness of parametric estimation. For inferential analysis, panel regression is employed given the balanced panel structure of the dataset (six institutions over eight years). The choice between the fixed effects (FE) and random effects (RE) estimators is guided by the Hausman specification test. Under the null hypothesis, both FE and RE are consistent but RE is more efficient; rejection of the null favours the FE estimator. The Variance Inflation Factor (VIF) is computed to diagnose multicollinearity among the regressors. By convention, VIF values below 5 indicate acceptable levels of collinearity, while values exceeding 10 signal potentially problematic multicollinearity. All analyses are conducted using STATA 16 with Microsoft Excel used for preliminary data organisation.

4. Presentation and Discussion of Results

4.1 Pre-Estimation Diagnostic Tests

4.1.1 Normality Test

The normality of variable distributions was assessed using skewness and kurtosis statistics, supplemented by Kernel density plots for visual inspection. Skewness values for all variables are positive and below 1 in absolute value, indicating mild right skewness with observations concentrated to the right of the mean. All kurtosis values fall below 3, indicating platykurtic distributions. These diagnostics confirm that the study variables do not deviate substantially from normality, supporting the use of parametric panel regression techniques.

4.1.2 Descriptive Statistics

Table 2 presents the summary descriptive statistics for all variables included in the analysis.

Note: ln = natural logarithm; VAT and Crisis are binary indicator variables. Source: Author’s computations (2023)

The natural logarithm of total loans (ln Loans) has a mean of 22.24 (SD = 0.95), with values ranging from 20.16 to 24.12, indicating moderate heterogeneity in loan volumes across institutions and over time. Loan patronage ranges from 0.27 to 0.58, with a mean of 0.41, suggesting that, on average, approximately 41% of members accessed loans in any given year. Loan delinquency ranges from 0.12 to 0.58, with a mean of 0.32, reflecting the challenging repayment environment in the region. The VAT and crisis indicators confirm that 63% and 75% of the institution-year observations fall within the post-VAT and crisis periods, respectively, consistent with the sample coverage of 2015 to 2022.

4.1.3 Correlation Analysis

Table 3 presents the pairwise correlation matrix for the study variables. Membership, VAT, and the crisis dummy are all positively correlated with the volume of loans and loan patronage, while they exhibit negative correlations with loan delinquency. This preliminary evidence supports the hypothesised directions of the relationships. Notably, the correlation between loans and deposits (0.931) is high, reflecting the complementary roles of asset and liability mobilisation in MFIs. The correlation between VAT and crisis (0.436) is moderate, indicating that while these two events overlap temporally, they are not redundant in the model. No pairwise correlation exceeds 0.95, suggesting that severe multicollinearity is unlikely to distort the regression estimates.

Table 3: Pairwise Correlation Matrix

Note: All values are Pearson correlation coefficients. Source: Author’s computations (2023)

4.2 Regression Results

4.2.1 Effect of VAT on the Volume of Loans Granted (Hypothesis 1)

The Hausman specification test produced a p-value greater than 0.05, indicating that the null hypothesis of no systematic difference between the fixed effects and random effects estimators cannot be rejected. The random effects (RE) model is therefore the preferred and more efficient specification for testing the first Hypothesis.

Table 4: Random effect regression on the fefect of VAT on Loan Granting Volume

The RE regression results indicate that VAT exerts a positive and statistically significant effect on the volume of loans granted by MFIs in Bamenda at the 1% level of significance. Membership is also positive and significant at the 1% level, consistent with the expectation that larger institutional membership supports greater loan disbursement. The crisis variable is negative but statistically insignificant, suggesting that while the socio-political crisis exerted a dampening influence on loan volumes, its independent effect is not precisely estimated in this specification.

The positive and significant effect of VAT on loan volumes is an unexpected finding that requires careful interpretation. One plausible explanation is that VAT, by raising the cost of each loan transaction, prompted MFIs to increase average loan sizes to offset fixed administrative costs and maintain viability, thus pushing up total loan volumes even as the number of individual borrowers fell. Alternatively, wealthier members, less affected by the 19.25% surcharge, may have continued taking large loans in the post-VAT period, inflating the aggregate loan volume figures. Both explanations align with the disaggregated findings on loan patronage and delinquency discussed below.

4.2.2 Effect of VAT on Loan Patronage (Hypothesis 2)

The Hausman test for the loan patronage model produced a p-value of 0.1377, which exceeds the 0.05 threshold, again confirming that the random effects estimator is appropriate.

Table 5: Random effect regression on the effect of VAT on Loan loan patronage of MFIs

b - consistent under Ho and Ha; obtained from xtreg

B - inconsistent under Ha, efficient under Ho; obtained from xtreg

Test: Ho: difference in coefficients not systematic

chi2(2) = (b-B)'[(V_b-v_B)^(-1)](b-B)

         =    0.31

Prob>chi2 =  0.8563

This finding aligns partially with Wanjiru (2015), who found a significant negative relationship between compliance costs and MFI performance in Bamenda. Where Wanjiru focused on the cost-side effects of taxation on institutional performance, this study captures a broader behavioural dimension by examining how tax-induced changes in the cost of borrowing affect loan demand among MFI members.

4.2.3 Effect of VAT on Loan Delinquency (Hypothesis 3)

For the loan delinquency model, the Hausman test again produced a p-value exceeding 0.05, confirming the appropriateness of the random effects estimator.

Table 6: Random effect regression on the effect of VAT on loan delinquency rate of MFIs