Determining the Relationship Between Exchange Rate and Gross Debt Loan in South Africa

Abstract

High public debt makes the conditions for effective fiscal policy more difficult and, at the same time, causes difficulties in seeking financial resources on the capital markets. There are many conflicting findings on factors contributing to increase on gross loan debt of government. Therefore, this study aims to determining the Relationship Between Exchange Rate and Gross debt loan. This empirical study was based on a quantitative research methodology. The study used the Auto Regressive Distributed Lag (ARDL) model to test the relationship between gross loan debt and exchange rate. Results found weak non-significant positive relationship between gross loan debt and all the foreign exchange rates. Appreciating or depreciating exchange rates can impact the burden of gross debt loan, and the level of gross debt loan can also impact exchange rates. It is therefore essential to consider the broader economic context and factors affecting both exchange rates and gross debt loan when analysing their relationship.

1. Introduction

The exchange rate and gross debt loan of a country can have a complex relationship, as they can impact each other in various ways. An appreciating exchange rate, where a country’s currency gains value relative to other currencies, can reduce the burden of gross debt loan. As the local currency strengthens, it takes fewer domestic currency units to repay the same amount of debt denominated in foreign currency. This can result in a decrease in the overall debt burden for the country. For example, studies have shown that an appreciation of the domestic currency can lower the debt-to-GDP ratio, making debt repayment more manageable [1].

On the other hand, a depreciating exchange rate, where a country’s currency loses value relative to other currencies, can increase the burden of gross debt loan. As the local currency weakens, it takes more domestic currency units to repay the same amount of debt denominated in foreign currency, leading to a higher overall debt burden. Studies have shown that a depreciation of the domestic currency can increase the debt-to-GDP ratio, making debt repayment more challenging [2].

According to [3], the South African government manages its budgets and finances its spending primarily through the collection of tax revenues and the taking out of loans. When a nation’s economic growth is combined with increased tax compliance on the part of both individuals and businesses, the result is an increase in the amount of tax income collected by the country’s fiscal authorities. Since South Africa’s transition to democracy in 1994, the country’s monetary authorities have been tasked with the difficult task of removing the country’s social evils [4]. This has proven to be a difficult assignment. Overall, economic growth is one of the strategies that is claimed to have had a robust influence in reducing government and external debt in the region [5]. This is one of the most popular methods that is suggested to have had this effect.

2. Foreign-exchange rate

An exchange rate, also known as a foreign-exchange rate (forex rate) between two currencies is the rate at which one currency will be exchanged for another [6]. It is expressed as a relative price of one currency in terms of another currency or a group of other trading currencies. The exchange rate is influenced by several variables such as interest rates, political stability, public debt, balance of trade and many more. Based on these factors, many theories have been formulated to determine the rate of exchange between different currencies. The exchange rate can be measured in three ways: bilateral exchange rate, cross exchange rate and trade-weighted index [7]. A country may choose to operate from different exchange rate regimes: freely floating, and/or fixed-rate regime using a hard peg.

Foreign debt is one of the main sources of financing for the development of resources in developing countries, where it is appropriate for the governments to borrow to meet financial necessities in the cases of deficit to close the gap between saving and investment [8]. External debt is perceived to be an important source of finance on which governments depend to meet public objectives. At 10.03%, the share of foreign debt as a percentage of total gross loan debt was lower by 1.21 percentage points at the end of 2020/21 than in the previous year. This decline could be attributed to the stronger rand and the redemption of one Japanese yen-denominated bond [9]. One study investigating whether the exchange rate determine foreign debt in Indonesia using the Auto Regressive Distributed Lag (ARDL) approach found that, in the long-run, the foreign exchange reserves have no significant effect on foreign debt, while the exchange rate has a positive significant effect on foreign debt [10].

3. Exchange rate regimes

There are two types of exchange rate regimes which countries can operate, namely, freely floating, and fixed-rate regime using a hard peg [7].

3.1 Pegged regime

Under a pegged regime (also known as a fixed regime), the monetary authority ties its official exchange rate to another nation’s currency [7]. Thus, the monetary authority buys and sells currency in the foreign exchange market to minimise fluctuations and keep the currency close to its target (or within its target band). The monetary authority’s independence is limited under a pegged exchange rate regime as it restricts the use of its popular policy tool, the interest rates, and requires it to hold substantial foreign currency reserves for intervention purposes.

3.2 Floating regime

In a floating regime, exchange rates are determined by the market forces of demand and supply of one currency relative to the other [7]. Relative to the pegged regime, a floating exchange rate can result in larger and more frequent fluctuations in the currency. For open economies like South Africa that actively engage in international trade, the exchange rate is an important economic variable. Thus, movements in the value of the rand against other trading currencies affect economic activity, inflation, and the nation’s balance of payments. The external debt of South Africa will become expensive to service or grow in nominal value if the rand becomes weaker (depreciates); the inverse is true if the rand becomes stronger (appreciates). However, the monetary authority has the option to intervene if market conditions are disorderly, to affect the level of exchange rate.

4. Relationship between foreign-exchange rate and national debt

Foreign debt is one of the main sources of financing for the development of resources in developing countries, where it is appropriate for the governments to borrow to meet financial necessities in the cases of deficit to close the gap between saving and investment [8]. External debt is perceived to be an important source of finance on which governments depend to meet public objectives. At 10.03%, the share of foreign debt as a percentage of total gross loan debt was lower by 1.21 percentage points at the end of 2020/21 than in the previous year. This decline could be attributed to the stronger rand and the redemption of one Japanese yen-denominated bond [9].

The results of the study by Omar and Ibrahim [11], using the Auto Regressive Distributed Lag (ARDL) model and cointegration test, established that the exchange rate has a significant and positive effect on external debt in the long-run. One study investigating whether the exchange rate determine foreign debt in Indonesia using the ARDL approach found that, in the long-run, the foreign exchange reserves have no significant effect on foreign debt, while the exchange rate has a positive significant effect on foreign debt [10].

According to Morina and Misiri [12], a budget deficit occurs when the amount of money spent exceeds the amount of money brought in by the government. This causes a difference between the two that is known as a revenue disparity. The government may resort to borrowing, which would result in an increase in debt, or it could increase the tax brackets (personal income tax, corporate income tax, and/or value-added tax) in order to collect the necessary revenue in order to balance the books. According to Knapkova et al. [13], high levels of public debt not only make it more challenging to implement an effective fiscal policy but also make it more challenging to acquire the necessary financial resources through the capital markets. There are various data that contradict one another about the elements that contribute to the rise in the gross loan debt of the government. As a result, the purpose of this study is to analyse the connection between the gross loan debt and exchange rate of the national government throughout the post-apartheid era in South Africa.

5. Research design and methodology

Correlational research was followed to determine the extent of a relationship between gross loan debt and the macro-economic variables using statistical data between 1994 and 2022. Secondary data in the form of quarterly time series for the period 1994–2022 was used for this study. Quarterly time series were chosen because of their high frequency nature and assisted in the analyses to make meaningful findings. The macroeconomic variables investigated in this study are compiled by different statistical agencies in South Africa. It is therefore important to note that taxation statistics are compiled by South African Revenue Services (SARS), while budget balance and debt statistics are compiled by the National Treasury. The inflation, GDP, and unemployment statistics are compiled at Stats SA. The foreign exchange- and interest rates are both compiled at the South African Reserve Bank (SARB). The SARB follows the international statistical compilation guidelines prescribed in the statistical manual such as the 2014 GFSM, 2008 System of National Accounts (2008 SNA), Monetary and Financial Statistical Manual 2016 (2016 MFSM) as well as the Balance of Payments Manual (BPM6) in the process of compiling macroeconomic statistics. Thus, the SARB compiles high-quality economic and financial statistics in accordance with the international best practise for use by policymakers, financial market participants and the general public [14]. The SARB data is disseminated to the IMF in fulfilment and compliance with the subscription of the Special Data Dissemination Standard (SDDS) of the IMF. In addition, the SARB statistical data are disseminated to the World Bank, Organisation for Economic Co-operation and Development (OECD), and Bank of International Settlement (BIS) for participation in the international forum and fulfilment of its commitment to data dissemination.

The Economic Statistics Department of the SARB collects and compiles macro-economic statistical data from SARS, Stats SA and National Treasury and other stakeholders for policy decision making and to inform local, regional, and international stakeholders on the state of the South African economy. Therefore, this resonates well with the principle of data reliability. The SARB uses different platforms such as surveys, email correspondence and other platforms such as Bloomberg on a subscription basis for the collection of the macroeconomic statistical data. The frequencies of data collection vary with the lowest and highest data collection frequencies being daily, monthly, quarterly, and annually. Therefore, the SARB data is considered valid. Validity expresses the degree to which a measurement measures what it purports to measure [15]. It explains how well the collected data covers the actual area of investigation.

The data are stored in the central database of the SARB and disseminated online; hence the SARB online-statistical-query portal was used as a download tool to collect the data for use in this study. The data collected from the SARB are consistent, reliable and valid. Data went through rigorous verification and validation before are published or disseminated to various stakeholders (Table 1).

Variable	Measurement	Frequency	Source	Abbreviation
Gross loan debt	ZAR million	Quarterly	SARB	GLDebt
Foreign exchange rates	Middle rates in cents (R1 = 100 cents) per foreign currency unit	Quarterly	SARB	Forex

Table 1.

List of variables and data sources.

Source: South African Reserve Bank [14].

The SARB data is consistent with data from Stats SA, SARS, and other statistical agencies, but the Bank usually goes an extra mile in certain area to improve the quality to make it fit for purpose. Choosing the SARB as a one-stop data hub was primarily driven by the high-quality standard and time-series accessibility.

6. Model specification

This empirical study employed the ARDL model to test the hypotheses. The ARDL cointegration technique is regarded as one of the important revelations of the twentieth century solution to the analysis of series with one cointegrating vector and, it does not require pretesting of unit root.

The following ARDL model is specified:

$$\Delta LGLDeb{t}_t={\alpha }_0++\sum _{\iota =1}^n{\beta }_{1i}\Delta LFore{x}_{t-i}++{\epsilon }_i$$

Where: ΔLGLDebt = Natural logarithm of Gross loan debt at time (t),

ΔLForex = Natural logarithm of Foreign exchange rates at time (t),

In the current study ARDL bounds tests were used to investigate the long-run relationship between gross loan debt and the independent variables. The decision to accept or reject the null hypothesis of no cointegration or of the existence of a long-run relationship was based on the F-statistic. If the F-test is lower bound, then the null hypothesis cannot be rejected. If the F-test lies between the lower and upper bounds, conclusive decision inference cannot be made.

6.1 Unit root

The study uses time-series data and therefore it is important to test for stationarity of the variables. The data-generating processes of the variables in the study are known before-hand, implying that the presence of unit roots must be tested. The Augmented Dickey-Fuller (ADF) unit root test was used to test for stationarity. The test was developed by statisticians called Dickey and Fuller in the 1970s. If there is unit root, then there is non-stationarity, hence the variable would be stationary at first differences. If there is no unit root, this will imply that the variable is stationary at a level. The results of the Augmented Dickey-Fuller (ADF) unit root test will determine the model to be employed to test for the long-run relationship between the variables. The ARDL model was used to test for cointegration between those variables because the variables can be integrated at either order I(0), I(1) or jointly at I(0) and I(1).

7. Results

7.1 Foreign exchange (USD)

The US dollar accounted for the majority total gross foreign debt of national government. The fluctuation of the USD shows the volatility (weak/strong) of the local currency (the Rand). The upward slope of the graph indicates weaker Rand, by contrast the downward slope indicates the stronger Rand. In 2001/02, the Rand/Dollar exchange rate reached a peak of R11.5, before declining and reaching R5.73 at the end of December 2004. The government foreign currency denominated debt increases when the Rand depreciates and declines when the Rand appreciated. Thus, the revaluation effects of the exchange rate have a negative relationship with the stock of foreign debt. By end of March 2022, the Rand/Dollar exchange rate was R14.979.

7.2 Foreign exchange (Euro)

The Euro/Rand exchange rate reached R3.973 as at 31 March 1995. Similarly, the USD/Rand exchange rate, the exchange rate revaluation value determines the stock of foreign debt post revaluation. Thus, the stock of foreign debt increases when the Rand depreciates, and the opposite is true. Assuming if everything stays constant, at R17.839 at the end of March 2021, the stock of Euro/Rand debt was higher compared with R16.55 at the end of March 2022.

7.3 Foreign exchange (Yen)

The exchange rate of the Rand against the Japanese yen increased from R0.033 as at 31 March 1994 to R0.043 as at 30 June 1995. The exchange rate of the Rand/Yen is volatile and was R0.126 as at 31 March 2022, declining from R0.138 as at 31 March 2021. This decline is a demonstration of the strength of the Rand against the Yen. Put differently, R1 was equivalent to ¥7.253 as at 31 March 2021 compared with ¥7.916 as at 31 March 2022. Nonetheless, national government debt issued in Japanese yen was redeemed in August 2021.

7.4 Foreign exchange (Pound)

The exchange rate of the British pound against the Rand increased from R5.150 as at 31 March 1994 to a R10.295 as at 30 September 1998. Although movements between the two currencies is volatile, there is a long-term increase. The Pound/Rand exchange rate reached R19.731 as at 31 March 2022, declining from R20.778 as at 31 March 2021. This decline is a demonstration of the strength of the Rand against the Pound. Notwithstanding this, national government debt issued in British pound was redeemed in March 2020.

7.5 Foreign exchange (Krona)

The fluctuation of the Swedish krona against the Rand increased from R0.436 as at 31 March 1994 to R1.134 as at 30 September 2002, signalling the appreciation of the Krona. The Krona/Rand exchange rate reached R1.564 as at 31 March 2022, declining from R1.754 as at 31 March 2021. This decline is a demonstration of the strength of the Rand against the Krona. Notwithstanding this, national government issued in British pound was redeemed in March 2020.

7.6 Foreign exchange (XDR)

National government foreign debt was first issued in IMF XDR in July 2020. The fluctuation of the XDR against the Rand declined from R23.622 as at 30 September 2020 to R20.731 as at 31 March 2022. This decline is the sign of the appreciation of the Rand against the XDR.

7.7 Correlation analysis

The Pearson correlation coefficient was used to test for relationships between the variables (Table 2).

FOREX_USD	Correlation coeficient	0.115
	p-value	0.226
FOREX_EURO	Correlation coeficient	0.124
	p-value	0.193
FOREX_YEN	Correlation coeficient	0.073
	p-value	D.442
FOREX_POUND	Correlation coeficient	0.109
	p-value	0.251
FOREX_KRONA	Correlation coeficient	0.130
	p-value	0.171
FOREX_SDR	Correlation coeficient	0.132
	p-value	0.166

Table 2.

Correlations for determinants of gross loan debt.

There is a weak positive relationship between gross loan debt and all the foreign exchange rates. The relationships are however not statistically significant.

8. Unit root test results

The Augmented Dickey-Fuller test (ADF) was founded by Dickey and Fuller [16]. The null hypothesis for the test is non-stationarity; thus, if the test statistic is statistically significant then the series is stationary.

Table 3 presents the results of the unit root tests results.

Variable	t-stats	p-value	Order of integration
GLDEBT	−3.755890	0.0229**	I(1)
FOREX_USD	−9.490279	0.0000*	I(1)
FOREX_EURO	−9.410451	0.0000*	I(1)
FOREX_YEN	−10.15237	0.0000*	I(1)
FOREX_POUND	−9.629972	0.0000*	I(1)
FOREX_KRONA	−8.664518	0.0000*	I(1)
FOREX_XDR	−9.556240	0.0000*	I(1)

Table 3.

Augmented Dickey-Fuller unit root tests.

Note: *denotes significance at 1%, **denotes significance at 5%.

Source: Author’s compilations using EViews version 12.

The results show that GDP and Consumer Price Inflation (CPI) are stationary at level {I(0)}. The other variables are stationary either at first difference {I(1)}.

This section presents the bound testing, long- and short-run analysis.

The results of the bounds test are summarised in Table 4.

Variable	t-stats	p-value
Dependent variable: GLDEBT
F-statistic	10.04001
Critical value bounds	I(0) Bound	I(1) Bound
10%	1.76	2.77
5%	1.98	3.04
2.5	2.18	3.28
1%	2.41	3.61

Table 4.

Autoregressive distributed lag bounds test.

Source: Author‘s compilation-computation using EViews version 12.

The null hypothesis for the long-run relationship analysis is that no long-run relationship exists. The results show that the F-value of 10.04001 is above the upper bound critical value of the 5% level of significance. A long-run relationship between gross loan debt and its key drivers is therefore evident (Table 5).

Variable	Coefficient	Std. error	t-Statistic	p-value
D(FOREX_USD)	23,933.16	17,987.51	1.330544	0.1866
D(FOREX_EURO)	13,051.51	216,37.07	0.603201	0.5478
D(FOREX_YEN)	−2,174,884.0	1,199,283.0	−1.813487	0.0730
D(FOREX_POUND)	−12,674.73	10,884.10	−1.164518	0.2472
D(FOREX_KRONA)	141,456.9	171,708.6	0.823819	0.4122
D(FOREX_XDR)	−7,707.037	21,245.18	−0.362766	0.7176
C	−19,720.43	16,248.17	−1.213702	0.2279

Table 5.

Long-run estimation results.

Source: Author‘s compilation-computation using EViews version 12.

9. Long-run Equation

$$\begin{array}{l}EC=\text{D}\left(\text{GLDEBT}\right)+{23933.1623}^{\ast }\text{D}\left(\text{FOREX}\_USD\right)\\ +{13051.5070}^{\ast }\text{D}\left(\text{FOREX}\_\text{EURO}\right)\\ -{2174883.8421}^{\ast }\text{D}\left(\text{FOREX}\_YEN\right)-{12674.7317}^{\ast }\text{D}\left(\text{FOREX}\_\text{POUND}\right)\\ +{141456.8661}^{\ast }\text{D}\left(\text{FOREX}\_\text{KRONA}\right)-19720.4286\end{array}$$

A positive insignificant relationship exists between gross loan debt and USD exchange rate. A one-unit increase in USD exchange rate results in a 23,933.16 unit decrease in gross loan debt.

A positive insignificant relationship exists between gross loan debt and EURO exchange rate. A one-unit increase in EURO exchange rate results in a 13,051.51 unit increase in gross loan debt.

A negative insignificant relationship exists between gross loan debt and YEN exchange rate. A one-unit increase in YEN exchange rate results in a 2,174,884 unit increase in gross loan debt.

A negative insignificant relationship exists between gross loan debt and POUND exchange rate. A one-unit increase in POUND exchange rate results in a 12,674.73 unit increase in gross loan debt.

A positive insignificant relationship exists between gross loan debt and KRONA exchange rate. A one-unit increase in KRONA exchange rate results in a 141,456.9 unit increase in gross loan debt.

A negative insignificant relationship exists between gross loan debt and XDR exchange rate. A one-unit increase in XDR exchange rate results in a 7,707.037 unit increase in gross loan debt (Table 6).

Variable	Coefficient	Std. Error	t-Statistic	p-value
D(GDP)	0.159834	0.053216	3.003487	0.0034
D(TAXR,2)	−0.900033	0.065081	−13.82940	0.0000
D(FOREX_KRONA,2)	−19,269.21	35,971.40	−0.535682	0.5935
D(FOREX_XDR,2)	8,400.719	2,875.724	2.921254	0.0044
CointEq(−1)*	−0.508519	0.034713	−14.64915	0.0000

Table 6.

Error correction model regression.

Source: Author‘s compilation-computation using EViews version 12.

The results also show a positive relationship between gross loan debt and XDR. A one-unit increase in XDR results in an 8,400.719 unit increase in gross loan debt.

In general terms, the exchange rates have a positive relationship effect on gross loan debt. The correlation results of the ARDL model indicated the following:

1. A positive insignificant relationship exists between gross loan debt and US Dollar exchange rate. A one-unit increase in dollar exchange rate results in a 2268.11 unit decrease in gross loan debt.

2. A positive insignificant relationship exists between gross loan debt and EURO exchange rate. A one-unit increase in EURO exchange rate results in a 13,760.81 unit increase in gross loan debt.

3. A positive insignificant relationship exists between gross loan debt and Japanese YEN exchange rate. A one-unit increase in YEN exchange rate results in a 2,443,380 unit decrease in gross loan debt.

4. A positive insignificant relationship exists between gross loan debt and British POUND exchange rate. A one-unit increase in POUND exchange rate results in a 624.63 unit increase in gross loan debt.

5. A positive insignificant relationship exists between gross loan debt and Swedish KRONA exchange rate. A one-unit increase in KRONA results in a 26,992.01 unit increase in gross loan debt.

6. A positive insignificant relationship exists between gross loan debt and IMF XDR exchange rate. A one-unit increase in XDR exchange rate results in a 17,176.22 unit increase in gross loan debt.

External debt is the component of gross loan debt. Any changes to the external debt have a positive relationship to gross loan debt. The findings are also supported the study by Wahyuni et al. [10] investigating whether the exchange rate determine foreign debt in Indonesia using the ARDL approach and the results found that, in the long-run, the foreign exchange reserves have no significant effect on foreign debt, while the exchange rate has a positive significant effect on foreign debt [10].

10. Conclusion

The relationship between exchange rates and gross debt loan can be intertwined and influenced by various factors. Appreciating or depreciating exchange rates can impact the burden of gross debt loan, and the level of gross debt loan can also impact exchange rates. It’s essential to consider the broader economic context and factors affecting both exchange rates and gross debt loan when analysing their relationship.