The Causal Relationship Between Foreign Debt and Economic Growth: Evidence from Commonwealth Independent States

Abstract

This study investigates the relationship between external borrowing and economic growth in the Commonwealth Independent States during the period 1995–2018. Autoregressive distributed lag (ARDL) model is employed to determine the co-integration relationship among the series and then vector error correction model (VECM) is used to analyse the causality between external debt and income. The obtained results suggest that there is a negative long-term unidirectional causal relationship running from external debt to GDP presenting a strong evidence of existence of debt overhang hypothesis. The possible reasons for this unidirectional causal relationship can be explained by poor management of provided financial resources and incomplete governance in economic transition process along with structural rigidities and immature institutions in these countries which, in the long term, resulted in insufficient capital charged to service external debt. The policymakers in these post-Soviet countries should not use foreign loans to capitalise the deficits in the economies; instead, they should be more determined in employing these funds in the areas that will create national value-added production and, thus, future income.

JEL Classification: C10, F34, H63

Keywords

Foreign Debt Transition Economies CIS Panel Unit Root ARDL Causality

Introduction

With the integration of developing economies into the world trade system, especially from the late 1970s and early 1980s, most of the developing countries have to afford their income and save shortage with external funds. Unbalanced distribution of production resources along with technological development and international political relations between countries cause domestic resources of developing countries to become insufficient in financing economic development process. Over the time, since foreign debt transactions become the major share of public revenues in developing economies, external borrowing and its economic effects have been a main concern of increasing number of studies.

In the framework of deep historical discussion on the impacts of foreign capital, one point can be stated clearly that external indebtment has both cost and benefit effects on the economy. To overcome the financial challenge of economic growth process, most of the developing countries have started to import capital goods remarkably, which enable them to increase the efficiency of production process notably, reaching self-sustainable economic growth. However, the major cost of borrowing is repayment of debt with the interest which limits economic growth process, thus causing an increase in the tax rates. These incompatible outcomes of debt commonly lead to uncertain net impact of borrowing on economic growth process depending on the rate of interest payment and how effectively borrowed resources are employed (Lin & Sosin, 2001).

Our primary objective in this study is to analyse the effect of foreign debt stocks on economic growth process of the Commonwealth of Independent States (CIS), which are transforming from a centrally planned economy to a free-market system. To achieve this goal, firstly, we employed panel unit root tests to decide whether the observed series are stationary or not. Then, autoregressive distributed lag (ARDL) was estimated to investigate whether foreign debt and GDP series are correlated in the long term or not. Finally, the panel vector error correction model (VECM) was estimated to investigate the significance of the short-term and long-term causal effects. The main finding of this study is that external loan has a negative impact on national income presenting statically significant evidence of existence of debt overhang hypothesis for the observed emerging countries.

Concise Review of Literature

The correlation between economic growth and indebtedness series has been one of the well-investigated subjects in the economic literature for decades. As Rais and Anwar (2012) state, foreign borrowing may have both positive and negative impacts on national income, especially in developing economies. External loan may play a constructive role in economic development and growth process if these funds are mobilised by policymakers to investment-oriented projects, such as power generation and supply, production and agriculture sectors. However, it may also have a harmful effect on national income if it is directed to economic activities that do not generate any return.

Initial studies in this field were based on the examination of impact of increasing economic aid on economic growth towards the end of 1970s after the oil crises; for instance, Papanek (1973) argues that there is a positive correlation between international aid and economic growth, whereas the findings of Chase-Dunn (1975) and Pfister and Suter (1987) do not coincide with this result. As Glasberg and Ward (1993) state, the main reason for these inconsistent findings is different data specifications that are employed in these studies, such as stock loans against the flow measures of foreign aid. According to the results of this study, the flows of foreign loans initially stimulate economic growth. However, in the long term, the stock of these loans affects the national income in developing economies negatively. Additionally, Glasberg and Ward (1993) empirically demonstrate that the varied types of loans may have different impacts on economic growth, that is, concessional loans may inspire economic growth process, while non-concessional ones undermine this process. Similar findings are obtained by Cunningham (1993) who analyses the influence of debt burden on GDP for 16 highly indebted economies arguing that growth of a nation’s debt burden seriously affects the efficiency of labour and capital, and that is why, it may have a negative impact on the economic growth process.

Cohen (1993, 1996), Deshpande (1997) and Iyoha (1999) investigate the correlation between foreign debt and investment rate by employing ordinary least squares (OLS) estimation techniques, insisting that there is a negative correlation running from foreign finance to investment. By employing multivariate regression analysis based on particular dependent variables such as export, inflation, saving, government expenditure, foreign direct investment (FDI) and population, Ahmed et al. (2000), Chowdhury (2001), Clements et al. (2003), Mohamed (2005), Bilginoglu and Aysu (2008) and Panizza and Presbitero (2014) also argue that international loans affect economic growth process negatively.

Dritsaki (2013), Puente-Avojín and Sanso-Navarro (2015) and Gamez-Puig and Sosvilla-Rivero (2015) examine the relationship between the dynamics of external debt and economic growth by employing Granger’s concept of causality; they obtain differential results for different country groups and time periods. According to the results of the first two studies, there is statistically significant evidence of causality running from financial debt to income. However, Gamez-Puig and Sosvilla-Rivero (2015) argue that there is a unidirectional causality running from exports to national income and from national income to government loans.

As it can be inferred from studies above, consequence of external debt and economic growth process is a deeply studied subject in the economic literature. However, to the best of our knowledge, there are no known studies which investigate this causal relationship for the CIS economies. Hence, this study attempts to fill the gap in the existing empirical literature by investigating the causal relationship between external debt and GDP for the CIS country group by employing recently improved applied techniques.

Theoretical Framework

The economic philosophy of external debt arises from Keynesian paradigm which basically suggests that governments’ intervention in economic activity may stimulate economic growth. Structural limitations faced by policymakers, especially in developing economies, emphasise the importance of foreign loans in terms of economic development and growth processes. Furthermore, foreign loans may encourage national investment and, thus, income and economic growth (see Amoateng & Amoako-Adu, 1996; Hejazi & Safarian, 1999; Rahman & Shahbaz, 2013; Srikanth & Kishore, 2012; Yusoff & Nuh, 2015). In this way, Keynes criticises the neoclassical economist’s approach which states that an economy will return to equilibrium on its own (Kara, 2001).

The prominent hypotheses inferred from the theoretical literature that describe a possible relationship between foreign loan and economic growth can be listed as follows: first is the intertemporal borrowing/lending model, which is an expansion of the intertemporal optimisation theory. It basically argues that accessing foreign financial instruments provides an opportunity for related economies to attract more investment and increase welfare of masses by the expansion in the consumption level (Nissanke & Ferrarini, 2001).

Second is the growth-cum-debt model, which essentially focuses on sustainability of debt; it suggests that any country is inclined to borrow only if the borrowed funds stimulate the economic growth process. Indeed, at the first stage of investment process, insufficient domestic saving rates may lead to an increase in borrowing, which leads to an acceleration of external indebtedness. These loans are usually used not only in financing of investment but also in the payment of loan amortisation and interest. At the second stage of development which starts with covering national investment with domestic savings, the increase in savings again is not sufficient to fully cover the amortisation and interest payments of the accumulated debts, but this increase is slower compared to the first stage. At the final stage, national investment will be financed by domestic savings which also will be sufficient to refund the accumulated external debt (Avramovic, 1964).

Third and final is the debt overhang approach which suggests that since investors assume that future taxes on returns to capital will be charged to service the loan, high debt ratio in any economy has a negative impact on the investment motivation. Particularly, expectation of deflector precautions to service the debt, such as devaluation or inflationary policy along with increasing uncertainties in consequence of debt rescheduling negotiations in deeply indebted countries, also may have a negative impact on investment by discouraging funding (Moss & Chiang, 2003).

External Debt in Commonwealth Independent States

CIS includes 12 transition economies with different economic features and was established in 1991 immediately after the collapse of the Soviet Union¹. As Korhonen and Wachtel (2006) state, CIS consists of both large-scale and small-scale economies as well as countries which are energy-rich and energy-importing states. According to Otoo and Sattar (2004), two of the main features of external indebtedness in most of the CIS countries are mainly being guaranteed by the public sector and being long term in nature.

From the early 1990s through the middle of the decade, an economic recession was observed in most of these countries which was consistent with the challenges that these economies faced in the building process of new states, democratic institutions and free market systems. During this period, in order to achieve a macroeconomic stabilisation and to meet financial needs, these new independent states had to import financial recourses, which is evident from the plot of data presented in Figure 1. However, for many of these states, the debt-servicing capacity has not progressed to the desired extent, and many of these countries are starting to struggle with critical debt issues. According to Brada et al. (2011), for the economies of major CIS countries, investment level significantly decreases in the first 15 years of the transition process, which causes a shortage of national funds for productive investments, thus hindering economic growth and development progress almost in all related countries. As it can be observed from Figure 1, although the foreign debt stocks of these countries have decreased from time to time, it has never equalled to zero, and over time, the maturities of new foreign financing commitments realised by these countries exceed an average of 30 years.

Figure 1.

Source: Word Bank Data Bank. https://data.worldbank.org/indicator

The dynamics of external debt accumulation and its characterising trends in the CIS countries may be divided into several stages. In the first stage which covers the period 1992–2000, a significant increase was experienced in gross foreign debt, especially in public and publicly guaranteed debts; for instance, the share of external liabilities of governing body ranged between 72% and 75% of gross external debt in Russia and Tajikistan, 80% in Moldova and Kyrgyzstan and 99% in Armenia (Linn & Belanger, 2002). The second stage which corresponds to 2001–2007 may be characterised by a decrease in the amount of government loans and their share in gross external debt against a significant increase in the debt level of commercial banks and the non-financial private sector. In this period, external debts of commercial banks in Moldova and Russia increased more than 11 times and, in Armenia, almost 5 times, whereas external borrowing of non-financial companies in Russia increased more than 11 times, in Kazakhstan, 6 times, in Belarus, 3 times and in Moldova, more than 2 times. In the third stage which coincides with the period of global financial crises of 2008–2011, degree of public and publicly guaranteed foreign debt as well as the debt of central banks and commercial banks increased significantly nearly in all CIS countries (Golodova & Ranchinskaya, 2014). The period that started in 2012 can be considered as the final stage, which continues till present. During this phase, the external debt of commercial banks and private non-financial companies in related economies has continued to increase.

We can conclude that although external debt plays a crucial role in all CIS countries, especially in terms of covering the costs of economic transition process, there is a substantial risk that should be taken into consideration. Foreign borrowing may undermine the efforts of the developing countries to transform the economy and its institutions. So, the balance between benefits of foreign debt in terms financing transition process and not employing these funds in inefficient economic areas which may slow transition process, should be maintain carefully (Odling-Smee & Zavoiceo, 1998).

Data and Applied Methodology

In this article, we analyse the causal relationship between foreign debt and economic growth series for CIS countries during the period 1995–2018 by implementing panel data research techniques. The data which are employed in this study are obtained from the World Bank’s World Development Indicators. The external debt stocks data are expressed as percentage of Gross National Income (GNI) and economic growth as percentage of annual growth of GDP.

It is well known from the applied literature that in the standard case, the findings obtained from regression models, which are based on OLS estimation, contain reliable information about the variables. However, according to the simulations results obtained by Granger and Newbold (1974), if one’s variables are random walks, or near random walks, and one involves in regression equations variables which should not be involved, then it will lead to spurious correlation between the indicators. Panel data analysis, which examines the cross-sectional observations over the time, may also carry time series features and problems.

In this study, the first-generation panel stationarity tests such as Breitung (2000), Levin et al. (2002), Im et al. (2003), Maddala and Wu (1999) and Choi (2001) are initially employed to analyse whether the foreign debt and income series contain a unit root or stationery. These analyses suppose that cross-sectional units of the panel are independent and based on the assumption whether the shock on one of the units of panel affects all cross-sectional units at the same level or not. The first-generation panel unit root tests are divided into two groups such as homogeneous and heterogeneous.

Breitung (2000) and Levin et al. (2002) insist on homogeneity across the series by testing the presence of common unit root process in panel data set and assume that the lag order ρ_i is identical (ρ_i = ρ) for all cross-sectional units. However, the null hypothesis of Im et al. (2003), Choi (2001), Maddala and Wu (1999) allows for the heterogeneity in the dynamics of autoregressive coefficients by realising that the alternative hypothesis of ρ_i is the same for all series. All these analyses are based on the null hypothesis of non-stationarity.

On the other hand, it is well known in applied literature that if a co-integration relationship exists among the variables observed, the regression analysis based on time series which contain a stochastic trend may reflect the real relationship among these series. To analyse the possible co-integration relation among the time series, there are two co-integration tests that are conventionally employed: Engle and Granger (1987) and Johansen (1988) and Johansen and Juselius (1990). These analyses are implementable if the variables observed are stationary at the level or have the same order of integration, whereas the panel ARDL model suggested by Pesaran et al. (2001) is preferable for investigation of time series which are integrated of different order, I(0), I(1) or combination of both. This methodology is also powerful if there is a single long-run correlation among the series in a small sample size (Nkoro & Uko, 2016).

The ARDL model, which may be estimated by OLS, is illustrated bellow

Δ Y_{t} = \propto_{10} + \sum_{i = 1}^{n} β_{1 i} Δ Y_{t - i} + \sum_{i = 1}^{m} γ_{1 i} Δ X_{t - i} + σ_{1 Y} Y_{t - 1} + σ_{1 X} X_{t - 1} + ε_{1 t}

(1)

Δ X_{t} = \propto_{20} + \sum_{i = 1}^{n} β_{2 i} Δ Y_{t - i} + \sum_{i = 1}^{m} γ_{2 i} Δ X_{t - i} + σ_{2 X} X_{t - 1} + σ_{2 Y} Y_{t - 1} + ε_{2 t}

(2)

where n and m represent maximum lag orders, σ refers to the long-run relationship, β symbolises the short-run dynamics of the model; X represents foreign debt and Y represents economic growth. Here, the null hypothesis of non-existence of co-integration may be represented as H₀: σ_iX = σ_iY = 0 and the alternative hypothesis which assumes a long-run relationship among the series may be supposed as H₁: σ_iX ≠ σ_iY ≠ 0 for i = 1, 2. Instead of employing typical Wald test, Pesaran et al. (2001) suggest two categories of critical values; upper (for I(1)) and lower (for I(0)) bound statistics. Lower critical bound demonstrates that there is no co-integration relationship among the series. However, upper critical bound allows for co-integration between observed variables. If calculated F-statistics is higher than the upper critical value, then the series are co-integrated, and the null hypothesis can be rejected. Also, if achieved test statistics is below the lower bound critical value, it denotes that there is co-integration relationship among the observed variables and the null hypothesis cannot be rejected. Finally, if computed F-statistics run into the I(1) and I(0) bounds, then the confusing results may be obtained from ARDL estimation process.

On the other hand, if the variables under consideration are co-integrated, then there will be not less than a unidirectional causality among these variables. Then, to analyse this causal relationship, VECM, which is demonstrated below and included in both short-run and long-run information among the series, should be employed (Engle & Granger, 1987).

Δ Y_{t} = \propto_{10} + \sum_{i = 1}^{n} β_{1 i} Δ Y_{t - i} + \sum_{i = 1}^{m} γ_{1 i} Δ X_{t - i} + δ_{Y} E C_{t - 1} + u_{1 t}

(3)

Δ X_{t} = \propto_{20} + \sum_{i = 1}^{m} γ_{2 i} Δ X_{t - i} + \sum_{i = 1}^{n} β_{2 i} Δ Y_{t - i} + δ_{X} E C_{t - 1} + u_{2 t}

(4)

Here, EC_t–1 represents the error correction term (ECT) and demonstrates the speed of adjustment to the long-term equilibrium after a shock to the model in the long-term regression process. If coefficient of this ECT, that is, δ_X or δ_Y, is positive, then we may conclude that observed series diverge from each other, whereas a negative coefficient implies a convergence process between these variables. According to Telatar (2015), the F-value on coefficient of the lagged dependent variables of above-represented equations demonstrates the significance of the short-term effects, whereas the t-value on the lagged ECT demonstrates the significance of the long-term causal impact.

Regression Results

We begin our empirical analysis by evaluating the stationarity features of the observed series. For this purpose, panel unit root tests such as Maddala and Wu (1999), Choi (2001), Breitung (2000), Levin et al. (2002) and Im et al. (2003) are used in this study. The obtained results are summarised in Table 1.

Taking into account the results represented in Table 1, it can be concluded that there is no particular finding about the stationarity properties of the panel data. Some test results imply that observed variables are stationary in the level, for example, foreign debt and economic growth series are integrated of order 0. Nevertheless, other panel unit root test findings demonstrate that series contain a unit root and follow first-order stationarity process leading to discrepancy in the order of integration of the external borrowing and GDP series.

Table 1.

Panel Unit Root Tests.

Variables	Levin et al. (2002)		Im et al. (2003)		ADF—Fisher		PP—Fisher		Breitung (2000)
Variables	Intercept	Intercept + Trend	Intercept	Intercept + Trend	Intercept	Intercept + Trend	Intercept	Intercept + Trend	Intercept + Trend
External debt	–1.752**	–0.976	–1.627***	–1.934***	30.447	33.635***	22.206	18.611	–3.558*
GDP	–9.182*	–8.208*	–7.380*	–5.079*	100.336*	72.813*	169.359*	328.877*	–1.076
ΔExternal debt	–5.212*	–3.313*	–5.417*	–2.993*	69.613*	42.697*	94.557*	64.476*	–2.020***
ΔGDP	–13.064*	–11.881*	–13.263*	–11.653*	174.893 *	141.564 *	628.598 *	997.195 *	–5.805*

Source: The author.

Note: *, **, and *** Denote rejection of the null hypothesis of unit root at 1%, 5%, 10% significance levels, respectively.

To explore the potential co-integration relation among the observed series we employ ARDL technique in two different wise, owning to the fact that this methodology is applicable irrespective of the series under estimation are integrated of the same order. Initially, we assume external debt as an independent variable than as a dependent variable. We use chi-squared test statistic to test the null hypothesis which can be summarised as follows: there is no co-integration relationship among the observed variables. The relevant lag lengths are determined according to the Schwarz information criterion (SIC).

From the results obtained, which are summarised in Table 2, it is observed that a long-run relationship exists between external debt and GDP series in both cases. It presents an obvious indication of co-integration relationship among the observed variables.

Table 2.

Co-integration Tests.

F-statistic
ARDL_{External Debt} š_GDP	15.872*
	(0.000)
ARDL_GDP š_{External Debt}	4.101*
	(0.018)

Source: The author.

Note: * Indicates significance at the 5% level.

In order to analyse the dynamics of short-term and long-term relation among the series, VECM is implemented in this study. The appropriate lag lengths are specified based on SIC.

From the results obtained, as presented in Table 3, it is evident that if we assume external debt as an independent variable, then the t-statistic of ECT and the Wald-test statistic of the relevant coefficients of the observed variable are statistically significant at an alpha level of 0.05. Moreover, the summary of coefficients of independent variables is negative implying that there is a negative relationship among the series; this in turn implies that an increase in external debt slows down the economic growth process. On the contrary, when external debt is assumed as a dependent variable, then the t-value on the lagged ECT is not statistically significant at the relevant alpha level.

Table 3.

Panel Causality Tests.

	Long Run	Short Run
External Debt š GDP	–5.641*	5.548(–)
	(0.000)	(0.004)
GDP š External Debt	–1.443
	(0.151)

Source: The author.

Note: * Indicates significance at the 5% level. The parenthesis implies the sum of the coefficients.

Concluding Remarks

In this study, we examine the consequence of international borrowing and economic growth regarding CIS for the period 1995–2018 by employing improved panel estimation techniques such as ARDL and VECM. The main finding of the research is that external loan has a negative impact on GDP growth presenting a strong evidence of existence of debt overhang hypothesis for observed emerging countries. This finding corresponds with the results of studies conducted by Akram (2011), Rais and Anwar (2012), Presbitero (2012), Calderon and Fuentes (2013), Mbah et al. (2016) and Kharusi and Mbah (2018) which have investigated this causal relationship for several developing countries.

Theoretically, the results obtained contradict the Keynesian macroeconomic theory, but they conform to the neoclassical theory which basically suggests that foreign debt crowds out private investment restraining economic growth process. The possible reasons for this evidence in the observed developing countries can be explained by poor management of imported financial resources and incomplete governance in economic transition process along with structural rigidities and immature institutions in these countries which in the long term resulted in insufficient capital charged to service external debt.

Considering that the main driving force of economic growth process in some of these transition economies is resource-intensive sectors’ exports and total consumption in the others, from the point of policy implication of this study, it can be said that foreign capital is not used efficiently in most CIS countries. The policymakers in these post-Soviet states should not use foreign loan to capitalise the deficits in the economies; instead, they should be more determined in directing these funds to the areas that will create national value-added production and, thus, future income. Moreover, As Otoo and Sattar (2004) indicate, most of these countries achieve considerable progress in the transition process from planned economic system to market economic structure. However, in order to achieve broad-based growth of employment and production levels, CIS should also be more insistent in reinforcing the stabilisation gains and address structural reforms in the economy.

Footnotes

Appendix

Table A1.

List of the CIS Countries.

1	Armenia
2	Azerbaijan
3	Belarus
4	Georgia
5	Kazakhstan
6	Kyrgyzstan
7	Moldova
8	Russian Federation
9	Tajikistan
10	Turkmenistan
11	Ukraine
12	Uzbekistan

Source: The author.

Declaration of Conflicting Interests

The author declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The author received no financial support for the research, authorship and/or publication of this article.

Note

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