In Keynesian theory, indebtedness in general does not entail costs for either present or future generations, due to the investments it generates. The global approach and the multiplier and gas pedal effects are fundamental features of the Keynesian theory of government indebtedness. In addition, Ricardian Equivalence Theory ([33]) postulates that the effect of public spending on the economy is totally independent of the way in which the spending is financed and, in particular, of the choice between taxation (immediate payment), borrowing (future payment), or even money creation. [3] extended the analysis to intergenerational transfers. [5] applied the principle to Keynesian economic policies, demonstrating their ineffectiveness. Indeed, other theoretical studies have shown that financing the economy through debt would have a short-term effect, by stimulating domestic consumption and investment, resulting in a growth rate higher than that of the real interest rate on bonds ([35]). Other theoretical findings support the view that financing public deficits through debt has fewer distortionary effects than financing through seigniorage, due to inflationary pressures, or through higher compulsory levies, due to lower household purchasing power and reduced corporate financing capacity ([34]; [35]).

Similarly, Official Development Assistance (ODA) is one of the most important sources of development funding. Its role as a source of external funding dates back to the 1940s, with the work of [8]. Their findings helped determine the level of aid needed to achieve the goal of balanced growth, in which ODA increased investment and consequently economic growth. Further work along the same lines emerged in the 1980s with the contributions of [24]. This work evolved into endogenous growth models following Romer, in which the hypothesis of increasing returns to scale for capital and endogenous technical progress would lead to greater aid effectiveness in countries with sound macroeconomic policies, thereby improving the well-being of the entire population ([25]).

There is a wealth of empirical work examining the link between external debt and economic growth. [22] examine the impact of high public debt on economic growth across a panel of advanced and emerging economies over the period 1970-2007. The results show the negative linear effect of public debt on economic growth. In the long term, economists appear to be at least theoretically unanimous on the negative impact of public debt on economic growth. Indeed, [32] determined, for a sample of developed countries, the existence of a public debt threshold (relative to GDP) of 90% ([22]; [32]; [23]). In the short term, they could be appreciated in a fiscal policy context about Keynesian multipliers ([30], [31]; [2]; [7]; [31]).

Empirical studies aimed at illustrating the relationship between Official Development Assistance (ODA) and growth have produced a variety of results. Authors such as ([24]; [9]) have concluded that the ODA-Economic Growth relationship is either non-existent or complex. In the same vein, [4] made use of the cointegration approach of [28] and the causality of [37] to study the link between aid and growth in the UEMOA zone over the period 1970-2012. [21] estimated a model using the Difference Generalized Moment Method (Diff-GMM) and the Dynamic Panel Method (Sys-GMM). Incorporating the anti-corruption index of [20] into the estimated model, aid has a non-significant impact on growth in over fifty developing countries. On the contrary, a significant positive effect of public aid on growth has been demonstrated by certain authors ([13]; [6]). [12] confirmed these results by considering 41 countries over the period 1986 to 1992. [29] noted the irrelevance of directly studying the effectiveness of total aid, and broke total aid down into short-term aid, long-term aid, and food aid.

In the present work, we seek to estimate the relationship between the growth rate of GDP per capita (dependent variable) and public external financing variables using the ARDL model based on the ARDL model by [28]. The choice of this model lies in the fact that estimates of the Growth rate from time series have generally been influenced by time and the econometric results obtained, although high coefficients of determination and Student-Fisher coefficients are unreliable. Most studies of growth estimation using time series have also been influenced by time, and the econometric results are not always reliable due to the lack of prior verification of the stationarity hypothesis, which limits the validity of econometric results in the context of dynamic modeling of economic growth behavior.

The ARDL model was chosen because it allows the estimation of both short- and long-run relationships even when the variables are integrated of different orders,I(0) and I (1). This flexibility makes it particularly suitable for macroeconomic data series that often exhibit mixed integration orders.

The ARDL model is therefore estimated according to the following functions:

If we want to capture the short-run and long-run effects of the above explanatory variables on the growth rate of GDP per capita, the ARDL representation of function (1) will be:

Referring to the literature, several tests of cointegration are available, including that of [11], [18], and [28]. Thanks to the [28] procedure, error-correction models can help confirm the existence or otherwise of cointegration between variables. In the case of public external financing, the model will take the following form in this study:

This study includes data covering the period from 1980 to 2023, due to the availability of data from the World Bank’s World Development Indicators ([40]). In fact, the macroeconomic and financial data come not only from the World Bank, but also from the database of the United Nations Commission for Trade and Economic Development ([39]).

Dependent variable: GDP per capita growth rate (CPIBH): this variable is designed to take account of the convergence process, as the neoclassical economic model indicates that low-income countries with lower initial technological and financial levels will tend to grow faster than more advanced countries. Variables of interest: Official Development Assistance (ODA), the expected sign here is positive; Public External Debt (PED), the expected sign here is positive; Investment Rate (INV): measured by Gross Fixed Capital Formation (GFCF) relative to GDP, this variable is expected to be positively related and significantly correlated with economic growth; Trade Openness (OUV); Inflation Rate (Tx_Infla) measured by the Consumer Price Index (CPI) to assess changes in the cost of living over time; Population Growth Rate (Tpop) (Table 1).

Table 1. Public external financing and economic growth.

Source: Author, based on data for WDI 2023.

Over the last few decades, Cameroon’s public debt has evolved. It has risen from 1485 million FCFA in 1980 to 8554 billion FCFA in 2023. Prior to the early 1980s, the moderate acceleration of Cameroon’s external debt compared with other countries at the same level of development, reflects the prudence of Cameroon’s economic policy in making external debt a determining factor in financing its development. Like outstanding debt and debt servicing, Cameroon’s DEBT/GDP ratio has evolved in line with economic conditions. It rose from 2.7% in 1983 to 91.2% fifteen years later, before dropping to 24.90% in 2018. Today, this ratio stands at 32% of GDP. In 2023, the level of Cameroon’s external debt has boomed compared with 2018 (Table 2).

Table 2. Five-year trend in the ratio of external public debt to GDP, 1983-2023 (in millions of dollars).

Source: Author, based on data for WDI 2023.

The rapid increase in the ratio during the 80s is linked to the economic crisis that shook the world during that decade. The doubling of the ratio in the 90s was largely due to the devaluation of the local currency in 1994, which rendered Cameroon’s debt unsustainable, leading to debt relief in the early 2000s. Following these major debt restructurings, notably from 2006 onwards, this ratio fell drastically, as shown in the table (7.10% in 2008). However, we have seen a rapid rise in this ratio over the last two decades, no doubt due to major government programs and projects financed by debt.

Official development assistance (ODA) is a crucial source of funding for Cameroon, despite its relatively modest contribution to the country’s GDP (see Table 3).

Table 3. Trends in the ratio of official development assistance to GDP, 1982-2023 (in millions of dollars).

Source: Author, based on data for WDI 2023.

The amount of overall aid has seen significant growth in recent years. It increased from $257 million in 2008 to over $472 million by 2016. However, this figure dropped sharply in 2017 to $11.67 million, a decline that may be attributed to various crises, departures, and other factors. Notably, aid rose from $597 million in 2012 to more than $715 million in 2017—a nearly 37% increase—and is projected to reach $1 billion by 2023. This funding encompasses diverse sectors, including health, education, and infrastructure, as well as agriculture, which is one of the key growth sectors in Cameroon.

To identify the optimal lag, the Schwarz Information Criterion (SIC) was utilized to select the ARDL model that delivers statistically significant results with the fewest parameters (Table 4).

Table 4. Post-estimation hypothesis tests.

Source: Author, based on data for WDI 2023.

Table 5 indicates that there is no first-order autocorrelation of errors in this model. As a result, the estimated ARDL model is statistically robust in explaining the impact of public external financing on economic growth in Cameroon. Additionally, it captures the dynamics of GDP per capita from 1980 to 2023.

Table 5. Cointegration test by [28].

Source: Author, based on data for WDI 2023.

Based on the Fisher statistic, the results in this table show the existence of cointegration for both models. Indeed, the observed values of the Fisher statistic are above the tabulated critical upper bounds at all thresholds.

Correlation and causality between model variables

Observation of the simple correlation matrices below reveals that the link between GDP per capita growth rate and public external financing variables (Official Development Assistance, public external debt) does not appear to be significant. Moreover, the degrees of correlation between these variables are very weak (below 0.5). However, they are very strong between GDP per capita growth rate, GFCF and trade openness (LOUV) (degree of linkage >0.5) (Table 6).

The results presented in this table indicate the existence of cointegration for both models, based on the Fisher statistic. This finding allows us to differentiate between the long-term and short-term effects of financial factors that influence the growth rate of GDP per capita in Cameroon.

Table 6. Results of the Todo-Yamamoto causality test for the link between external public financing and economic growth.

Source: Author, based on data for WDI 2023. *Significant at the 5% level, **Significant at the 1% level.

Long-Term Relationship Between GDP Per Capita Growth Rate and Public External Financing

The long-term relationships are summarized in the table below. It shows that Official Development Assistance (ODA), public external debt, moderate inflation, and trade openness significantly impact the GDP per capita growth rate at the 5% significance level (p-value < 5%). Additionally, Gross Fixed Capital Formation (GFCF) appears to have a significant effect on this growth rate at the 10% significance level.

Table 7. Long-term relationship between GDP per capita growth rate and public external financing.

Source: Author, based on data for WDI 2023.

The next step is to assess the robustness of this long-term relationship. Recall force measures the speed at which we return to long-term equilibrium, and understanding its significance is essential for utilizing this relationship for forecasting purposes. The coefficient of recall force, which indicates the speed of the return to equilibrium, is significantly negative (as shown in Table 7) at the 5% threshold. This implies that any imbalance in the growth rate of GDP per capita—caused by a surplus of public external financing relative to the long-term equilibrium—will be corrected by a downward adjustment in the growth rate of GDP per capita in the subsequent period. Specifically, this imbalance is corrected by a decline in the growth rate of GDP per capita of 85.78.

In this long-term relationship, all coefficients have the expected and significant signs, except for the inflation rate, which presents a positive sign and is therefore difficult to interpret. These variables account for 97.161% of the growth rate in GDP per capita. Consequently, we observe that the growth rate of GDP per capita in Cameroon increases more significantly when public development aid, external public debt, investment (Gross Fixed Capital Formation—GFCF), and trade openness rise. Specifically, when official development assistance (ODA), public external debt (PED), investment (GFCF), and trade openness (OUV) each increase by 1%, the growth rate of per capita GDP will increase by 2.152%, 3.51%, 9.154%, and 21.77%, respectively, assuming inflation remains constant. Conversely, a 1% increase in the population growth rate (TPOP) will reduce the growth rate of per capita GDP by 2.54%, all else being equal.

Short-term relationship between GDP per capita growth rate and public external financing(Table 8)

Table 8. Short-term relationship between GDP per capita growth rate and public external financing.

Source: Author, based on data for WDI 2023.

The next step is to assess the stability of this long-term relationship. Specifically, a 1% increase in each of these rates is associated with an increase in the growth rate of GDP per capita by 1.846%, 3.01172%, and 12.645%, respectively, assuming all other factors remain constant. Conversely, a 1% increase in the gross fixed capital formation (GFCF) rate, the inflation rate, and the trade openness rate from the previous year tends to decrease the per capita GDP growth rate by 9.83%, 0.162%, and 5.28%, respectively, again assuming all other factors remain constant.

The positive long-run impact of inflation and the negative short-run effect of lagged investment may appear counterintuitive. This could be explained by structural rigidities, time lags in investment realization, and inflation reflecting demand-driven growth during certain periods. Nevertheless, these findings should be interpreted with caution as they highlight potential areas for further research.

Unlike [22], who found a negative debt-growth relationship in advanced economies, Cameroon’s experience suggests that debt may still foster growth when properly managed and channelled into productive investments. This divergence may stem from differences in institutional quality, governance effectiveness, and the nature of external financing sources.