Foreign Aid Paradox and Domestic Tax Revenue in Kenya: A Hindrance or a Catalyst for Revenue Mobilization?

Foreign Aid Paradox and Domestic Tax Revenue in Kenya: A Hindrance or a Catalyst for Revenue Mobilization?

Jordan Moses, Yasin Kuso Ghabon

Maseno University, Kenya

 DOI: https://dx.doi.org/10.47772/IJRISS.2025.915EC0039

Received: 02 April 2025; Accepted: 09 April 2025; Published: 28 May 2025

ABSTRACT

Kenya’s tax-revenue-to-gross domestic product has failed to keep up with the relatively growing economy and has been fluctuating over the years. These constraints the ability of the government to meet its obligations and exerts more pressure to meet fiscal deficit targets. Despite measures adopted by the Kenya government towards enhancing revenue mobilization, tax revenue performance remains below the Kenya Vision 2030 targets of 25 percent. Foreign aid is often regarded as essential for financing development and therefore improving domestic revenue mobilization; however, concerns exist about its effect on tax revenue mobilization efforts in Kenya. However, this relationship remains unclear, given the contradictory empirical evidence available. The study therefore sought to examine the effect of foreign aid inflows on incentives for domestic tax revenue mobilization in Kenya. The study adopted correlational research design. The Heller Utility Maximization Model underpinned the study. Using the secondary data from the World Bank Development Indicators for the period 1980-2020 and vector error correction mechanism, the study established that foreign aid inflow has a negative and statistically significant relationship with tax revenue performance in Kenya. This suggests that a 1% inflow in foreign aid reduces tax revenue mobilization effort by 0.25% in the long run. The study concluded that foreign aid inflows reduce incentives for tax revenue mobilization in Kenya. The study recommends that foreign aid should be channelled towards stimulating domestic revenue mobilization activities such as capacity building, technical assistance programmes to revenue policy and administration and activities supporting small and medium sized enterprises in identifying regional market opportunities and anti-corruption reform measures to avoid embezzlement of foreign assistance received. Further, more proportion of foreign assistance should be channelled towards domestic revenue mobilization activities than to other sectors that do not promote revenue generation. Additionally, donor countries should monitor the aid flow and ensure that their assistance are channelled and properly used in appraised productive projects in the recipient economies, which would generate higher revenues in the future.

Keywords: Tax Revenue, foreign aid, VECM, GDP, KRA

INTRODUCTION

Tax revenue mobilization remains an important policy objective because most governments around the world rely on taxation to fund investments in capital, infrastructure, and the delivery of essential services to their citizens like education, healthcare and social security. It should be noted that the ability of the government to provide these services is contingent to sufficient revenues from taxation (IMF, 2011). Considering this significant role of taxes, developing countries especially those in Sub-Saharan Africa find it difficult to provide essential services to their population due to lack of enough tax revenue. These countries have therefore been forced into debt trap as a result of increasing public debt. This is echoed by Piancastelli &Thirwall (2019) who argue that too high debt as a percentage of GDP leads to fiscal crisis and recipient countries find it difficult repaying the debt.

Viewed as an important policy objective, countries around the world have made significant progress in mobilizing domestic financing for development in the twenty-first century. Developing countries on the other hand are still faced with challenges in raising their revenues from domestic sources. These challenges range from a large informal sector, low levels of per capita, small tax base, transfer pricing abuse, low domestic savings and investments to poor governance and capacity, IMF (2021). These developing nations continue to struggle to raise their share of tax revenue in GDP to the required level that can support public spending and spur economic growth. These countries are required to attain at least 15 percent regarded as the minimum threshold for sustainable development. However, many developing countries are still unable to achieve a tax yield of 15 percent due to a limited tax base and a general lack of tax administration capacity (Chongvilaivan & Chooi, 2021).

The share of tax revenue in Gross Domestic Product has failed to keep pace with the relatively growing economy and in recent years the ratio has been fluctuating while fiscal deficit in financing the ever-increasing public expenditure is still a challenge that Kenya faces (KIPPRA, 2020). Failure of the tax revenues to keep pace with the growing economy and steady decline in its share of GDP in recent years implies that Kenya continues to rely on public debts to finance her development expenditures. This has contributed to a growing concessional borrowing leading to increased fiscal deficits and debt vulnerabilities raising doubts of public debt sustainability in Kenya. For instance, in the fiscal year 2019/20 public debt increased to around 66 percent of Gross Domestic Product, up from 62 percent in the 2018/19 fiscal year, IMF (2021). This increase in public debt stock is primarily driven by increased public spending which is exacerbated by insufficient domestic revenue mobilization.

Notwithstanding the magnitude of effort by Kenya, the tax revenue-to-GDP ratio has lagged behind the comparatively growing economy and in recent years the ratio has been declining. This fluctuation and decline in tax revenue-to-GDP ratio was primarily contributed by the changes in the economy’s structure that started in 2014/15, where agriculture gained a sharp increase relative to other sectors of the economy thus leading to a shrinking tax base; changes in discretionary policy that resulted in loss of significant revenue; an abrupt rise in remissions and exemptions in tax that eroded the taxable base (KRA, 2019).

Foreign aid inflows and Tax revenue performance

Foreign aid has long and continues to be seen as part of economic development in developing countries. Since 1960’s these countries have received aid in form of project aid, technical assistance, balance of payment support and budget aid. This is because these countries already lack means to collect sufficient taxes and invest in capital (Morduch & Karlan, 2014).

Proponents of foreign aid argue that aid helps developing countries in releasing binding constraints in revenue mobilization, assist with poverty-reducing spending, strengthen domestic institutions, meeting shortages of technical knowledge, foreign exchange, and capital, because the internal economic structures of these countries are not conducive to bolstering foreign trade and attracting foreign direct investment (Terefe & Teera, 2008); (Workineh, 2016); (Pankaj, 2021). Conversely, concerns have been raised about the negative effect of foreign aid dependency on efforts geared towards domestic revenue mobilization, budget planning and spending programmes, as well as institution-building due to the relatively higher share of foreign assistance towards budgets in some countries, Park (2019); Clement et al. (2004); Njeru (2003). Some researchers such as Kwakye (2010) and Clement et al. (2004) have found substantial connection between aid and the increase in government expenditure which has contributed to huge debt accumulation and debt servicing outflows in many developing countries and has not contributed to them making significant improvements in their development objectives.

As a result of massive economic crisis that hit Kenya in 1980 which resulted in a massive fiscal deficit, a drop in coffee prices, and a rise in the prices of oil, the Kenya government was compelled to seek foreign aid in order to stabilize the economy (Njarara, 2017). Aid has since been an integral part of Kenya’s budgeting process influencing spending programmes, budgeting programmes as well as institution-building (Njeru, 2003).  However, Kenya has experienced volatile and unpredictable aid inflows, where in the 1980’s a dramatic increase in marginal flow of aid was witnessed followed by dwindle in the 1990’s in donor assistance before starting to gain momentum in 2002 (Ojiambo, 2015). This study seeks to establish if the failure by tax revenue to grow in tandem with growing GDP is attributed by aid volatility and unpredictability. Aid effectiveness on tax revenue mobilization has been a subject of study by various scholars. Some found a negative relationship (Benedek et al. 2014) while others believe that foreign aid has a positive contribution (Terefe & Teera, 2018); (Workineh, 2016). Given the substantial role that foreign aid plays in the country’s spending programme and budgeting process, this study considers foreign aid to influence tax revenue mobilization and therefore, this study aims to determine the effect that aid has on tax revenue mobilization in Kenya.

LITERATURE REVIEW

This study focuses on a number of studies have been carried out on foreign aid inflows and tax revenue performance in different countries and used varieties of methodologies using different determinant variables.

Terefe & Teera (2018) used a novel of dataset spanning 1992 to 2015 to establish the factors that determine tax revenue in East African countries. The panel data co-integration method was used in the study. Both the FGLS and dynamic panel data GMM models were also used to estimate the model. The study established that foreign aid positively and significantly impacted tax revenue in East African countries for the period under study. Foreign aid was found to impact tax revenue both in the FGLS and GMM models, at one percent and 5 percent significance levels, respectively. The study used panel data analysis from East African countries which may not give a clear picture of how this factor affects tax revenue in performance in Kenya. Therefore, this current study sought to use analysis based on time series data to establish the effect of foreign aid on tax revenue in Kenya.

Thornton (2014) investigated whether foreign aid reduces tax revenue by using panel data from 93 countries from 1984 to 2009.  The model for the study was estimated using OLS. The study established that foreign aid reduces domestic revenue mobilization. Thorton’s study used panel data analysis from a variety of Sub-Saharan Africa, the Middle-East/ North Africa, Latin America and Asia. The study omitted some variables that are included in this current study which are important to developing countries in revenue mobilization, such as agriculture and trade openness.

Neog & Gaur (2020) investigated how macroeconomic factors influence tax revenue in India by using time series data from 1981 to 2016. Explanatory variables used in the study include foreign aid, agriculture, and the degree of openness and rate of growth. The study employed dynamic three-stage least square estimator to aid in tracing potential channels for improving tax revenue performance. The study established that foreign aid positively and significantly affected tax revenue efforts in India under the study period. One percent increases in aid cause a 1.12 percent increase in tax revenue in India. While the study by Neog and Gaur used dynamic three-stage least square estimator, this current study employed VECM estimation mechanism which is suitable for analyzing time series data that exhibit both short and long run cointegration.

Ayenew (2016) empirically investigated factors that determine tax revenue in Ethiopia. The researcher used maximum likelihood approach of Johansen. To capture the relationship that exists between independent and the dependent variables, the study used descriptive and econometric analysis. Annual time series data for the period ranging from 1975 to 2013 were used in the study. Findings of the study established that foreign aid had positive and significant impact on tax revenues as a share of GDP in Ethiopia. A one percent increase in foreign aid causes an upsurge in tax revenue by 0.97 percent, implying that aid inflows is a major determining factor in tax revenue in Ethiopia for the period under study.

Gaalya (2015) carried out a study on the relationship between tax revenue and trade liberalization in Uganda. The study used annual time series data for the period 1994-2012. Random effects models were used in the study in determining performance of tax revenue. The study used exchange rates, trade openness, agriculture, industry and foreign aid as explanatory variables. The study findings indicated that foreign aid had a positive impact on total revenue performance. This positive substantial effect is because foreign aid in GDP impacted revenue performance during the period under study.

Teera (2003) conducted a study to examine factors that influence tax revenue share in Uganda. Time series data from 1975 to 2000 were employed in this study. Tax evasion, aid share in GNP, agriculture in GDP, manufacturing share and population density were identified as potential factors affecting tax revenue in Uganda. Foreign aid was established to have a positive effect on tax revenue because aid in Uganda has always supported exports particularly raw materials.

Data Type and Source

The annual time series data for this study were sourced from the World Bank Development indicators for the period of 1980 to 2020.

Econometric Models

Model Specification

The model specification for this study adopted regression approach based on theoretical framework. This approach reflects the works of (Tanzi, 1992; Piancastelli, 2001; Teera, 2002; Murunga, 2016 and Mwangi, 2019). The theoretical framework is translated into a functional relationship as shown:

= f (V) + ε

Vector Error correction Model (VECM)

To estimate the short-run and long-run effects of the time series data, VECM was employed. Furthermore, this model allows for the possible estimation of speed of adjustment coefficient even if there is only one co-integrating relationship.

k– is the lag length

 = short-run dynamic coefficients of the model

= the speed of adjustment parameter with a negative sign. Measures the rate at which tax returns to equilibrium after changes in agric, open and faid

 = The long-run co-integrating equations’ lagged OLS residuals

= Stochastic error terms

RESULTS AND DISCUSSIONS

Table 1: Descriptive Statistics Results

Source: Author’s Computation.

The descriptive statistics results indicate the mean values of tax revenue share, trade openness share, foreign aid share and agriculture share to be 9.60%, 53.09%, 6.09% and 24.41% respectively. The variables’ respective maximum and minimum values are equally shown indicating variations over the study period for the respective series. The difference between the maximum and minimum values for the variables, 9.00, 45.62, 14.54 and 13.61 respectively are significantly high. The results indicate that tax revenue, foreign aid and agriculture sector are not spread out from the mean i.e. they have smaller standard deviations except the variable of standard deviation of 10.44. It can further be noted that the standard deviations of the variables are less than their means. This indicates that there are no outliers in the series hence the variables are likely to be normally distributed. The further confirmation by the Jacque-Bera test indicates the series to be normally distributed. Conversely, the variable of foreign aid is shown not to be normally distributed. However, this is not a problem since the error term of the series is normally distributed.

Stationarity Test

The study performed a combination of the Augmented Dickey Fuller and Phillips-Perron tests on levels and first difference for each study variable. The Augmented Dickey Fuller (ADF) and the Phillips-Perron (PP) tests suggested similar results of stationarity after first difference leading to a rejection of the null hypothesis of non-stationarity at 5% significance level. Results indicate that the variables of tax revenue share, agriculture share, trade openness share and foreign aid share of GDP are integrated of order 1, I (1), i.e. they became stationary after first differencing.

Table 2: Unit Root Test Results

Note: When p-value is higher than 5% level, null hypothesis of a unit root cannot be rejected, implying non-stationarity. Test equations included intercept.

Note: When p-value is higher than 5% level, null hypothesis of a unit root cannot be rejected, implying non-stationarity. Test equations included intercept.

Source: Author’s Computation.

Lag Length Selection

According to Mc Millin & Ozcicke (2001), VAR models are commonly used in forecasting and therefore selection of an optimal lag length is a crucial aspect when specifying vector Autoregressive models. Accordingly, determination of appropriate and an optimal lag length is a crucial step in the estimation of VAR models. In the light of this, if a higher order lags length than the true lags length is chosen, an increase in the mean square forecast errors of the VAR and autocorrelation may be experienced, whereas including too few lags also leads to specification errors, (Lutkepohl, 1993). Hence, it was necessary to decide on the optimal lag length to be employed before estimation of a time series equation. Although Wooldridge (2013) suggests appropriate of 1 or 2 lags for annual data, 1 to 8 lags for quarterly data and 6, 12 or 24 lags for monthly data, selection of optimal lags is basically an empirical issue and the most common practice is by some statistical procedures. SC and HQ suggest an optimal lag of 1 while LR, FPE and AIC suggest an optimal lag of 2.

Source: Author’s Computation.

Johansen Cointegration Test

The study performed the Johansen cointegration test to establish the long run relationship. Cointegration test was performed based on the null hypothesis of no cointegration. Ssekuma, (2011) asserts that Johansen cointegration test has the ability to estimate more than one cointegrating relationship, if data set contains two or more time series. Both Trace test and maximum eigenvalue results indicate that there is one (1) cointegrating relationship. The study therefore, rejects the null hypothesis of no cointegration relationship at 5% level of significance.

Table 4.5: Johansen Cointegration Test Results

denotes rejection of the hypothesis at the 0.05 level

Max-eigenvalue test indicates 1 cointegrating eqn(s) at the 0.05 level

denotes rejection of the hypothesis at the 0.05 level

MacKinnon-Haug-Michelis (1999) p-values

Source: Author’s Computation.

VECM Estimation Results

Table 5: Results of Long Run Estimates

Note: Standard error () & t-statistics [ ]

Source: Author’s Computation.

The long run (normalized) equation is derived from the cointegrating coefficients. Therefore, the estimated long run equation is illustrated as:

     (4.1)

       (4.2)

Results in equation 4.2 indicate that there is statistically and significant negative relationship between foreign aid share in GDP and tax revenue performance in the long run and this finding does not conform to a priori expectation. This was based on the null hypothesis (H₀₃) that foreign aid share has no significant effect on tax revenue performance in Kenya. As clearly shown in the equation, the coefficient of foreign aid share is (-0.25) with a t-statistics of 4.98 (t>1.96). This implies that a 1% increase in foreign aid share contributes to 0.25% decrease in tax revenue performance in Kenya. Based on these findings, the study rejects the null hypothesis (H₀₃) given the established statistically significant relationship between foreign aid share and tax revenue performance in Kenya. The result of this study is consistent with the findings of Muthoora (2013), Thorton (2014) and Addison & Levin (2012) who found negative and significant effect of foreign aid on tax revenue of countries in Sub-Saharan Africa, Middle-East/North Africa, Latin America and Asia. While the study by Thorton (2014) found negative effect, the studies by Terefe and Teera (2018), Neog and Gaur (2020), Ayenew (2016), Gaalya (2015) and Teera (2003) all found positive effect of foreign aid on tax revenue performance which is inconsistent with the findings of this study. According to Muthoora (2013), Clist & Morrisey (2008), official development assistance in the form of grants is associated with lower tax revenue performance while official development assistance in the form of loans is not. This is because foreign aid received in the form of loans comes with the burden of future loan repayments to recipient countries, thus, may induce policy makers to mobilize higher taxes. In addition, ODA channelled towards activities stimulating tax revenue mobilization are low compared to other activities and sectors. Nampewo (2016) asserts that the proportion of official development assistance towards domestic resource mobilization activities is small compared with overall official development assistance volumes to other activities.

Vector Error Correction Model Short-Run Estimates

Table 6: Vector Error Correction Model Estimates (Short-run)

Note: Standard errors (), t-statistics [ ] & * denotes statistical significance at 5% level of significance.

Source: Author’s Computation.

Based on the VECM results in Table 6, the study obtains the short run equation estimated as follows;

Short-Run effect of foreign aid on tax revenue performance in Kenya

From the short run equation, VECM one lagged period foreign aid share has positive and insignificant effect on the current period tax revenue at 0.05 and 0.1 significance levels in the short run with coefficient and p-value of 0.059527 and 0.4311 respectively. This result indicates that a percentage increase in foreign aid is associated with 0.06% increase in tax revenue on average ceteris paribus in the short run.

Error Correction Estimate

The ideal coefficient of error correction term is required to be negative and statistically significant. This is because a positive coefficient (speed of adjustment) means that the VECM continues to move away from the long-run equilibrium after experiencing a shock, instead of converging to it. The coefficient of the error correction term (-0.27) is negative and statistically significant with p-value of 0.0163. This implies that the tax revenue’s previous period’s deviation from the long-run equilibrium is corrected in the current period at an adjustment speed of approximately 27%.

Causality Test

Cointegration established indicates a possibility of existence of a causal relationship between the study variables. The study therefore, conducted pairwise granger causality test to examine causality linkage between tax revenue performance, foreign aid, trade openness and agriculture share in GDP in Kenya. This test was based on the null hypothesis of no causality and the results presented.

Note: The lag length p =2, * implies rejection of the null hypothesis of no causality at 5%.

Source: Author’s Computation.

The no causality relationship running from foreign aid share in GDP to tax revenue performance and from tax revenue performance to foreign aid share in GDP is consistent with the findings of Sakurai (2021) who investigated fiscal effects of foreign aid in Thailand and Tesso & Goshu (2016) who examined foreign aid resources inflows and domestic revenue mobilization in Ethiopia. Considering that the various studies established diverse findings, the results of no causality between foreign aid share in GDP and tax revenue performance in Kenya implies that foreign aid and tax revenue performance in Kenya are independent.

CONCLUSIONS AND RECOMMENDATIONS

Generally, the study findings show that foreign aid and tax revenue have a negative correlation, become stationary after first difference i.e. integrated of order one, long run relationship exists among the study variables, deviation in tax revenue from the long run equilibrium is correcting at approximately 27%. The study concludes that there is existence of a negative long-run relationship between; foreign aid inflow and tax revenue performance in Kenya. Granger causality established no causal relationship between foreign aid and tax revenue performance in Kenya. More proportion of foreign assistance should be channelled towards domestic revenue mobilization activities than to other sectors that do not promote revenue generation. Additionally, donor countries should monitor the aid flow and ensure that their assistance are channelled and properly used in appraised productive projects in the recipient economies, which would generate higher revenues in the future.

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