exchange, international reserves, and external debt in Indonesia: Evidence from an ARDL approach
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Ref: RJAP-2021-0284R1
The nexus between foreign exchange and external debt in Indonesia: Evidence from linear and nonlinear ARDL approaches
Journal of the Asia Pacific Economy Dear Nazam,
Reviewers have now commented on your paper. You will see that they are advising that you revise your manuscript. If you are prepared to undertake the work required, I would be pleased to review a revision.
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Dear Dr. Nazamuddin
Many thanks for your revised paper. Although reviewers' are satisfied with your revisions, the reviewer 1 still has some minor concerns (please see below).
Therefore, we invite you to address these remaining issues. In addition, the Editors also require you to elaborate on policy implications. As you should know that JAPE is a policy oriented journal. Here I copy JAPE's aims and scope, "JAPE has a broad readership, which makes papers concerned with narrow and detailed technical matters inappropriate for inclusion. In addition, papers should not be simply one more application of a formal model or statistical technique used elsewhere. Authors should note that discussion of results must make sense intuitively, and relate to the institutional and historical context of the geographic area analyzed. We particularly ask authors to spell out the practical policy implications of their findings for
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Currently, you have a short concluding para which mentions policy implications in a very generic manner. This is not sufficient for JAPE. I do hope you can elaborate policy implications of your research.
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REVIEWER 1
The author(s) have undertaken major revision on the manuscript. I found that most of my comments and suggestions as written in my first review have been addressed accordingly.
The analysis in the current draft focuses on two variables, namely foreign exchange and external debt, instead of three—by omitting international reserves variable. This allows the author(s) to carry out more detailed modeling and discussions. They have updated the time series observations by adding eight more quarters, and re-run all the necessary statistical tests and estimations. In terms of modeling the author(s) have added a non-linear ARDL approach, from which an asymmetric effects of exchange rate on external debt could be evaluated. Robustness check has been undertaken as suggested, and limitations of the study have been formulated
accordingly at the end of Section 4. Furthermore, discussions have been enriched, for example by relating the results to fiscal management side in Section 5.
There are however three small points need be addressed as follows.
1) In subsection 4.1, second paragraph, the author(s) write that the speed of adjustment is relatively low. How does this speed of adjustment magnitude compare to other developing countries’? What are factors possibly leading to this slow
adjustment speed? A short answer or explanation might be useful to enrich the discussion.
2) In evaluating the asymmetric effects of exchange rate on external debt, the author(s) provide some explanations on differing magnitude of the effects. My
question is, why depreciation and appreciation of Rupiah exchange rate both lead to
to indicate level of statistical significance. For instance, under Table 1, an asterisk is used to indicate 5% significance level, under Table 2 as well as Table Appendices 1 and 7 an asterisk is used for 1% significance level. Moreover, Table Appendix 3 has used no asterisk to indicate the statistical significance levels, and Table Appendix 7 has some errors on the asterisks or on the notes under it. These should be corrected by the author(s).
To sum up this second review, I recommend that the editor to accept this manuscript with minor revision.
Reviewer #2: Author(s) have addressed reviewer's comments.
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Ref: RJAP-2021-0284R2
The nexus between foreign exchange and external debt in Indonesia: Evidence from linear and nonlinear ARDL approaches
Journal of the Asia Pacific Economy Dear Nazam,
I am pleased to tell you that your work has now been accepted for publication in Journal of the Asia Pacific Economy.
It was accepted on Mar 14, 2022
Comments from the Editor and Reviewers can be found below.
Thank you for submitting your work to this journal.
With kind regards Anis Chowdhury, Ph.D.
Associate Editor
Journal of the Asia Pacific Economy
Comments from the Editors and Reviewers:
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2054153
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Tue, Mar 22, 7:11 AM to me, RJAP-production, informa.journalsManuscript Title: The nexus between foreign exchange and external debt in Indonesia: Evidence from linear and nonlinear ARDL approaches
Manuscript DOI: 10.1080/13547860.2022.2054153 Journal: Journal of the Asia Pacific Economy
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Edit Summary
The nexus between foreign exchange and external debt in
Indonesia: evidence from linear and nonlinear ARDL approaches
Left running head: B. S. NAZAMUDDIN ET AL.
Short title : Journal of the Asia P acific Economy AQ0
AQ17 B. S. Nazamuddin1 Sri Sukma Wahyuni1 F. Fakhruddin1 Fitriyani Salamuddin1
1Department of Development Economics, the Faculty of Economics and Business, Universitas Syiah Kuala – Jl. Teuku Nyak Arief, Kopelma Darussalam, Banda Aceh, Indonesia
B.S. Nazamuddin is an Associate P rofessor of Economics at the Department of Development Economics, the Faculty of Economics and Business, Universitas Syiah Kuala, Banda Aceh, Indonesia. His primary research areas include macroeconomics, poverty, development, and econometrics.
Sri Sukma Wahyuni is an assistant lecturer at the Department of Development Economics, the Faculty of Economics and Business, Universitas Syiah Kuala, Banda Aceh, Indonesia. She has been involved in numerous research projects with the t h e {Comment by Author: The article "the" appears twice, please delete one of them.}university's Insitute of Research and Community Service and Bank of Indonesia.
F. Fakhruddin is a senior lecturer at the Department of Development Economics, the Faculty of Economics and Business, Universitas Syiah Kuala, Banda Aceh, Indonesia. His research interest includes monetary and international economics.
Fitriyani Salamuddin a lecturer and active researcher at the Department of Development Economics, the Faculty of Economics and Business, Universitas Syiah Kuala, Banda Aceh, Indonesia. Her research interest includes macroecomics and econometrics.
CONTACT B. S. Nazamuddin [email protected] Abstract
We examine the long- and short-term effects of foreign exchange on Indonesia's external debts. Employing an autoregressive distributed lag (ARDL) bounds testing on quarterly data from 2010 to 2019 and testing for effect asymmetry, we found a long-run cointegrating relationship between the two variables. We also found a slow adjustment to an equilibrium state following a shock. Foreign exchange demonstrates a positive long-run effect on Indonesia's external debt, while in the short-run the effect is negative. Furthermore, we found an
asymmetry in the elasticities of external debt with respect to rupiah-to-US dollar exchange rate fluctuations.
T he positive effect of Indonesian rupiah volatility on Indonesian external debt would be more severe when the rupiah appreciates against the dollar compared to a situation of rupiah depreciation. T herefore, although a depreciation of rupiah against the US dollar under a floating foreign exchange regime adopted by Indonesia since 1997 would in the long-run increase external debt, the impact is moderate. Any short-run movement of Indonesia's external debt following a shock would be pulled back to its long-run equilibrium path. We recommend that Indonesia should maintain a floating exchange regime and allow rupiah to depreciate at a moderate rate in the long-run.
Keywords: External debt; foreign exchange; ARDL; NARDL; Indonesia
B22; F31; H63
1. Introduction
Recent studies on developing countries have primarily centred on examining external debts in relation to currency crises (Brkić 2021), GDP and government expenditures (Llorca 2017; K. and R.A.M 2018
{Comment by Author: This should be replaced with "Gokmenoglu and Rafik 2018"}), as well as economic growth (Qureshi and Liaqat 2020; Karimah and Nasrudin 2020; Hashim, Mohamad, and Sifat 2019; Zue 2020; Edo, Osadolor, and Dading 2020). While several previous empirical studies have focused on sovereign debt (Brkić 2021;
Chung-Yeea, Wana Ismail, and Ai-Lian 2020; Ahmed, Aizenman, and Jinjarak 2021), several others have focused on private sector debt (Jena and Sethi 2021; Kidemli and Yamacli 2020). Meanwhile, extensive studies have investigated the effects of external debt on output growth and its relationship with the government budget deficit (Edo, Osadolor, and Dading 2020; Qureshi and Liaqat 2020; Karadam 2018; Lim 2019; Kim and Zhang 2021). T he afore-mentioned studies have treated external debt as the determinant of macroeconomic indicators; nevertheless, there is limited literature that shows how external debt is affected by currency exchange rates.
In the aftermath of the 1997 Asian financial crisis, many emerging market economies, such as Indonesia, adopted more painstaking policies toward external debt risks and consequently succeeded in avoiding severe financial and fiscal impacts of the 2008 crisis (Kilci 2019). Nevertheless, knowledge of how exchange rate affects Indonesia's external debt after the 1997 and 2008 crises is lacking. Although external debt management plays a key role in influencing macroeconomic resilience in the Indonesian emerging economy, its relationship with foreign exchange has not received adequate attention in the existing literature.
Tambunan (2010) compared the degrees of resilience of the Indonesian economy to the 1997 Asian financial crisis and 2008 global economic crisis and found that the country was more resilient to the latter crisis, as reflected by positive growth and lower poverty rate. T he rupiah depreciation against foreign currencies, in which Indonesian debt was mainly denominated, led to a rise in the private external debts. However, it is uncertain whether the effect of rupiah depreciation on the total, or only the private, external debt is also positive in the post-crisis situation. Besides, whether the effect is symmetric in the case of rupiah appreciation remains to be questionable. T he asymmetry of the effect may exist. Tang, Tan, and Naseem (2013)
investigated the effect of external debt on exports and found that high depreciation of domestic currency during the 1997 Asian crisis did not lead to an export boom. T he degree of depreciation determines how external debt affects exports. T he greater the depreciation of the local currency, the more detrimental it is to exports. Currency depreciation is likely to have a favourable effect on exports, and hence GDP, only if it depreciates at a moderate rate. T hus, a moderate depreciation of the rupiah may also help reduce Indonesia's external debt.
Indonesian rupiah depreciated at a moderate pace after the 1997 and 2008 crises; therefore, as suggested by Tang, Tan, and Naseem (2013), it affects the economy positively by boosting exports. It is critical to investigate its effects on external debt to determine the magnitudes and directions of these long- and short-run effects. For this reason, we examine both dynamic long-run and short-run relationships with external debt as a dependent variable. Hence, it provides a different perspective of total external debt in relation to foreign exchange as an important dynamic factor influencing an open emerging economy such as Indonesia. Hence, it contributes to the scarce prior literature on the issue.
Our chosen methodology, the linear and nonlinear autoregressive distributed lag model (ARDL and NARDL) approaches, have been widely used in recent studies to assess long-run macroeconomic relationships (Dissou and Nafie 2019; Rotimi, Adelakun, and Babatunde 2019; Attard 2019; Stoian and Iorgulescu 2020; Ahmed 2 020; Al-hajj, Al-Mulali, and Solarin 2018; Sharaf 2021 {Comment by Author: Delete this citation}; Makun 2021). Yet, there is a dearth of analyses examining short- and long-run effects of foreign exchange on external debt using those approaches. T his study is also motivated by these inadequacies.
T he remainder of this paper is organized as follows. Section 2 reviews the related literature. Section 3 outlines the data and method. Section 4 presents the results and discussion. Section 5 provides an overview of Indonesia's debt and fiscal management. Finally, Section 6 gives the conclusion and implications of the study.
2. Related literature
For many upper-middle-income countries, external debt remains to be an important source of funding, due to its positive association with income growth in the long run (Qureshi and Liaqat 2020; Hashim, Mohamad, and Sifat 2019). For some countries, this positive effect occurs only up to a certain threshold, wherein higher debt accumulation tends have a negative effect (Zue 2020). Meanwhile, in the short-run, external debt may have no significant impacts on economic growth (Edo, Osadolor, and Dading 2020). T he need for external debt is generally twofold; namely to finance the budget deficit in the short term, and to fill the domestic public savings gap. However, increasing public debt is an indication of a problematic fiscal condition, which sometimes leads to lower incomes and higher prices (Maitra 2019).
A number of recent studies have focused on the effects of external debt on output growth and its relationship with the government budget deficit. Some examples are Edo, Osadolor, and Dading (2020), Qureshi and Liaqat (2020), Karadam (2018), Lim (2019), and Kim and Zhang (2021). T hese studies suggest that the effects of debt on output often vary. Conversely, for lower- and upper-middle-income countries, Qureshi and Liaqat (2020) found the impact to be positive, while Karadam (2018) and Lim (2019) reported a negative
effect. T he cross-country study Edo, Osadolor, and Dading (2020) indicated an insignificant long-run impact of debt on growth rate. However, for an open economy, foreign exchange volatility has a crucial influence on sustaining output growth through continuous external debt management. Foreign currency-denominated external debt is susceptible to the volatility of foreign exchange; thereby maintaining fiscal stability is crucial to the achievement of sustained growth. Moreover, foreign exchange volatility disrupts such growth in crises.
Because external debt sustainability is related to other macroeconomic goals, it is essential to develop more insights into the dynamics of external debt as fulfilling fiscal gaps when currency crises occur. Capital flows to emerging economies are considered an important determinant of growth. Foreign direct investment responses to exchange rate fluctuations vary (Olani 2020), thereby making it critical to examine how the changes exert dynamic impacts on external debt.
T he increased accumulation of short-term external debt has been frequently associated with the rise in the likelihood of financial crises (Koh et al. 2020). Economic crises generally lead to rising public debt issuance in developing countries, and this is often linked to inflation and a local currency depreciation (Gomez-Gonzalez 2 019). Economic downturns drive the government to increase local currency debt as a substitution for external debt. Such substitution is usually aimed at reducing the risks of foreign exchange fluctuations (Insukindro 201 8). Although considerable domestic borrowing by the government has a crowding-out effect on private investment (Chung-Yeea, Wana Ismail, and Ai-Lian 2020), increasing demand for domestic public debt is preferable and leads to lower external debt. Real exchange rate movement has been demonstrated to exert a negative effect on long-run economic growth (Arestis and Baltar 2019). T herefore, its real exchange rate fluctuation increases external debt while simultaneously impeding long-run growth. T his partly explains the reason for which many developing countries substitute domestic debt for external debt.
T he literature on the empirical determinants of external debts during the tranquil period is lacking compared with the large body of theoretical and previous empirical work on the relationship between current account and budget deficit as well as debt and the related economic crises. Moreover, recent studies examining the effect of foreign exchange on external debt in emerging economies have mixed results. Fisera, Workie Tiruneh, and Hojdan (2021) indicate that in emerging countries the long-run effect of exchange rate depreciation on external debt is consistently significant. In higher-income emerging economies, the depreciation of domestic currency produces advantages in the form of lower external debt to GDP ratio. It may occur because there is a persistently positive relationship between nominal exchange rate depreciation and trade in goods, at least as found for Indonesia (Lubis and Abdul Karim 2021). Conversely, exchange rate appreciation can result in a shift from external debt to domestic currency-denominated debt typical in emerging economies (Wu 2020) and domestically-sourced debts, thereby also reducing total external debts. T he above- mentioned mixed empirical results motivate further research questions. First, does a long-run equilibrium relationship between external debt and foreign exchange exist? Second, if it exists, is there an asymmetry in the direction of the effects. By taking Indonesia as the case, this study investigates those issues, which have been underexplored in the prior literature in the area.
Furthermore, in the previous studies on external debt, multiple approaches were used. Several studies have used logit and probit models with different purposes (Ciarlone and Trebeschi 2005; Kraay and Nehru 2006), Johansen cointegration test, error correction model and vector error correction model (K. and R.A.M 2018
{Comment by Author: This should be replaced with "Gokmenoglu and Rafik 2018"}; Ahmed et al. 2000), panel data analysis (Llorca 2017), and ARDL approach (Cahyadin and Ratwianingsih 2020). T his study; however, employed linear and asymmetric nonlinear ADRL approaches to further contribute to the body of knowledge on dynamic long-run and short-run movements of Indonesia's external debt.
3. Data and method 3.1. Data
T he quarterly data on external debt and exchange rates from 2010q1 to 2019q4 used in this study were sourced from the Bank of Indonesia, the World Bank, and CEIC. External debt is broadly defined as all liabilities owed by Indonesian residents to non-residents (Bank Indonesia 2020) {Comment by Author: Add citation link.Bank Indonesia. (2020). External Debt Statistics of Indonesia. Retrieved from https://www.bi.go.id/en/iru/economic-data/external- debt/Pages/SULNI-April-2020.aspx
}. T he external debt comprises three parts: government external debt—of both central and local governments, central bank external debt, and private sector external debt—of both financial and non-financial institutions.
Government debt is usually used to fill the fiscal gap and to finance particular needs not covered in the regular budget, such as government loans to state-owned enterprises and subnational governments; loan guarantee for loans used for the provision of public goods—to both state-owned enterprises and the private sector; and equity to state-owned enterprises and other institutions. In general, the external debts of the Indonesian government are mainly allocated toward accelerating economic growth, improving public services—education, health, and social spending—and promoting development equality across the nation, such as transfers to regions and transfers for village funds (BAP P ENAS. 2015; Indonesian Ministry of Finance 2017 , ).
Meanwhile, the central bank’s debt is allocated to supporting the balance of payment and maintaining international reserves, as well as protecting funds deposited by non-residents in the Bank of Indonesia fund certificate (SBI) and other forms of liabilities. P rivate sector debt constitutes multiple liabilities of residents toward non-residents in the form of business loans, cash, and deposits—in both rupiah and foreign currency.
Such debt belongs to non-residents and are held in financial and non-financial Indonesian institutions, including the securities issued in Indonesia and owned by foreigners (Indonesian Ministry of Finance 2018).
T he broad definition of external debt used in this study is consistent with that of Kim and Zhang (2021), suggesting that the relationship between output and debt is systematic, regardless of whether it is sovereign or private debt. Assuming a similar association of external debt, irrespective of its borrowers, with the factors affecting it, we use the data on total external debt, which includes sovereign, private, and central bank debt. It is expressed in USD million, whereas the foreign exchange rate is expressed as rupiahs per USD. All variables are transformed into logarithmic form; namely LOGEXD for log external debt, and LOGFER for log foreign exchange rates.
3.2. Method
We followed several necessary steps to fulfil requirements for the validity of ARDL model estimation, and they are as follows. First, to ensure that the two underlying variables are integrated of either zero, I(0), or one,
I(1), and none is I(2), we performed P hillips-P erron testing for stationarity of the series, both at the level and at first-difference. Second, we imposed deterministic restrictions to ARDL specification. T hird, we determined the lag structure of the model. Fourth, we employed ordinary least squares to estimate the ARDL with specified lag structure. Fifth, we performed tests for serial correlation and heteroskedasticity. Sixth, we performed the Bounds testing for cointegration. Finally, given the cointegration test result, we estimated the speed of adjustment to equilibrium relationship.
T he steps above are necessary to ensure that the variables have cointegrated relationships. T he steps used to test for stationarity, lag length selection, and cointegration is described in the following subsections. Based on ARDL bounds tests results, we then performed diagnostic and model stability tests. T he ARDL estimation results are presented in the subsequent section. T he stationarity test and lag selection results are shown in Appendices 1 and 2 {Comment by Author: Provide links to this appendices.}, respectively. T he ARDL long-run regression estimation and Bounds testing results are shown in Appendices 3 and 4 {Comment by Author: Provide links to this appendices.}, respectively. Diagnostic tests results are illustrated in Appendix 5, while stability test results are shown in Appendix 6. In addition, we also performed the robustness check, and its result is presented in Appe ndix 10.
Bounds tests for cointegration
To examine the existence of cointegration between the variables, we used the ARDL approach of P esaran and Shin (1999) which are based on simple standard F-statistic and t-statistic. Because the tests are consistent, we then used them to test the significance of the underlying variables in lagged levels as proposed by P esaran, Shin, and Smith (2001). Investigating the long-term relationships among the variables of this study also requires an assessment of the stationarity of those variables. T herefore, we performed a non-parametric P hillips-P erron tests (P P ) for stationarity to determine the order of integration for each variable. T his step is required to determine whether the ARDL bounds testing approach is appropriate. It is also imperative to determine the best model specification, including the identification of lag length. Because not-so-unusual monetary events occurred during the 2010–2019 period observed, we assumed the absence of structural breaks in the time series. To ensure it, Cumulative Sum (CUSUM) and Cumulative Sum of Squares (CUSUMSQ) of the recursive residuals to test for the nonexistence of structural breaks were plotted. It is a test for parameter stability with the null hypothesis of no structural break.
If the required mix of degrees of integration for the series from the P P stationarity testing is fulfilled, then, in most cases, it provides robust results even for a small sample (Jalil and Rao 2019). If the variables are of different orders of integration and none is I(2) or a higher order, then applying the ARDL model in this study is justified. One of the advantages of ARDL technique is the ability to assign different lags to different variables, and it is more efficient for a small and finite number of observations. Hence, the ARDL estimation results lead to a relatively high probability of rejecting a null hypothesis (Nguyen and Ngoc 2020; Nkoro and Uko 2016; Gamal et al. 2019; Nadeem et al. 2020).
T he ARDL model with the intertemporal dynamics represented in the lags and the contemporaneous effects of the dependent and independent variables of LOGEXD and LOGFER was specified as follows:
(1)
where ( =1, 2,…, ) denote the lags of the dependent variable ( =0, 1, 2,…, ) denote the lags of the explanatory variable, and t represents time. represents a restricted constant; represent the coefficients of the lagged explanatory variable. denotes a random disturbance term with zero mean and constant variance. T he incorporation of an intercept in equation (1) implies that the mean value of LOGEXD series is not equal to zero. T he constant is the only deterministic restriction that enters into the cointegrating relationship, and it is also represented in the conditional error correction representation of the ARDL model described below.
From the estimation of equation (1), we derived the error correction representation of the long-run relationship to examine how the dependent variable LOGEXD and the independent variable LOGFER relate in the short- run if a long-run cointegrating relationship exists. T herefore, we formulated a conditional (unconstrained) one- equation error correction model in accordance with P esaran, Shin, and Smith (2001), as follows:
(2)
where and are as defined previously. D is the first-difference, is a constant, and denote long-term coefficients, and and are short-term coefficients. and are the lag lengths and are the error terms. T he null hypothesis is that a relationship between the regressand and the regressor does not exist, regardless of the orders of integration.
Furthermore, we then conducted a cointegration test on the model to examine the long-run relationships among the variables and their short-run dynamics. Based on the relevant error correction terms in equation (2), we performed the ARDL bounds testing for the null hypothesis of the nonexistence of cointegration, against the alternative that is not true. T he bound tests for cointegration introduced by P esaran and Shin (1999), based on simple standard F-statistic and t-statistic, are consistent, and can be used to test the significance of the underlying variables in lagged levels (P esaran, Shin, and Smith 2001). If the F- statistic lies above the upper bound, then the cointegration can be concluded.
Seven advantages of the ARDL method have been extensively suggested in the literature, more recently including Nguyen and Ngoc (2020), Nkoro and Uko (2016), Gamal et al. (2019), and Nadeem et al. (2020).
First, the order of integration is not necessarily identical for all the underlying variables. Second, different lag lengths can be assigned to different variables. T hird, it is more efficient for a small and finite number of observations; therefore, the estimation results lead to a relatively high probability of rejecting a false null hypothesis. It provides unbiased estimates of the long-run relationships if cointegration among the underlying variables exists. Fourth, it simultaneously provides estimates of both short- and long-run coefficients as well as the variance-covariance matrix. Furthermore, even without assuming the existence of a vector relationship, it
provides powerful tests for cointegrating coefficients. Fifth, residual correlation is unlikely; therefore, there exists no endogeneity bias, because the lagged regressors are serially uncorrelated. Sixth, it is easy to interpret the results of a single-equation ARDL model estimation. Seventh, when a cointegrating relationship between the underlying variables is existent, the ARDL long-run estimation result is robust, even for a small-sized sample.
A nonlinearity of impacts of LOGFER on LOGEXD is possible; therefore, we employed a nonlinear autoregressive distributed lag (NARDL) method to take into account the possible asymmetry of the effects.
T he details of its procedures are presented in the subsequent separate section.
Lag length selection and tests for serial correlation and heteroskedasticity
We specified the best model to be the one that minimizes the values of the information criteria, namely the numbers of lags, and that balance between the number of appropriate coefficients, hence not losing their power - and the probability of having omitted variable bias. Following the Akaike information criterion (AIC) procedure, we selected the appropriate number of lags for the dependent and independent variables and Khim and Liew (2004) demonstrate that for a small sample case, AIC can minimize the chance of underestimation while maximizing the chance of calculating the true lag length. T he selection of lags in an autoregressive model is unimportant because, when the independent variable does not Granger-cause the dependent variable, no lagged independent variables should be significant. However, the optimal autoregressive model can be identified using an information criterion. For quarterly data, 4 or 8 lags can typically be used (Wooldridge 2020). T herefore, we have relied on the AIC criterion to select the appropriate number of lags. AIC penalizes models using more parameters and chooses the lowest number of parameters that best fit the data. T his means AIC automatically selects the best specification, i.e. the one with the lowest AIC score, from a set of several possible model specifications (possible combinations of lags).
After determining the number of lags, we rigorously followed the necessary steps specific to ARDL methodology to ensure the validity of our results. Furthermore, we conducted the Breusch-Godfrey serial correlation LM and Breusch-P agan-Godfrey heteroskedasticity tests to ensure that the residuals are not serially correlated and not heteroskedastic.
Testing for the asymmetry
Equations (1) and (2) are used to determine the linear long-run effect of LOGFER on LOGEXD. T he positive long-run impact of Indonesian rupiah depreciation on its external debt is true only if the foreign exchange moves from low to high rates. Nevertheless, the effect can be reversed, supposing the foreign exchange changes occur in the opposite direction, namely the rupiah appreciation. T herefore, following Y Shin and Yu (2004), as further advanced by {Comment by Author: Delete this phrase} Yongcheol Shin, Yu, and Greenwood-Nimmo (2011), we formulated our asymmetric nonlinear cointegration equation as follows:
(3)
T he regressors are decomposed into the partial sum of positive changes in i.e.
and the partial sum of negative changes in i.e. and are the long-run parameters associated with and respectively. Both regressors are defined as follows:
(4)
(5)
From equation (3), we then obtain the asymmetric nonlinear ARDL error correction model representation as follows:
(6)
Similar steps such stationarity testing, model specification, and cointegration bounds testing as well as residual and stability diagnostics are applied as in the symmetric analysis.
4. Results and discussion
From the results of stationarity testing, lag length selection, residual diagnostic and stability tests, shown in Appendices 1 through 6 {Comment by Author: Provide links to this appendices.}, we conclude that the application of ARDL(1,2) model is justified. Based on the results of the ARDL(1,2) level equation estimation, we reject the null hypothesis of no long-run equilibrium. In other words, there is a cointegrating relationship between the dependent variable LOGEXD and the explanatory variable LOGFER. T he cointegration exists even at the 1% significance level. Its coefficient estimates are stable during the sample period.
4.1. Long-run and short-run effects
T he estimated long-run coefficients resulting from the selected ARDL(1,2) model and short-run coefficients resulting from its error correction representation are reported in Tables 1 and 2 respectively. T he results provide the long-run relationships and the short-run dynamics of the foreign exchange and external debt variables. We show that, in the long run, the coefficient of the log of foreign exchange rate (LOGFER) is significantly positive. T his finding suggests the critical nature of foreign exchange rate as important factors in determining external debt. T he statistically significant positive coefficient of LOGFER indicates that an increase in foreign exchange rate, i.e. the depreciation of Indonesian rupiah against the dollar, by 1% leads to an increase in Indonesia’s external debt by 0.62%.
Table 1. Estimated long-run coefficients of log of external debt.
Regressors Coefficient
Constant 7.054886 (0.0197)
LOGFER 0.620720 (0.0425)**
**Significant at the 5% significance level p-values in parentheses.
Table 2. Error Correction Representation of the selected ARDL (1,2) model estimation.
Regressors Coefficient Standard Error p-value
D(LOGFER) −0.303764 0.089622 0.0018*
D(LOGFER(-1)) 0.159076 0.090470 0.0880***
CointEq(-1)* −0.075284 0.007968 0.0000*
D(LOGFER) and D(LOGFER(-1)) are the first differences of the logarithms of the current level foreign exchange rate and one- period lagged foreign exchange rate respectively.
*Indicates statistical significance at the 1%.
***Indicates statistical significance at the 10%.
Furthermore, Table 2 shows that the coefficient of the error correction term, CointEq(-1), has a significantly negative sign with a value of −0.075284. T his implies that around 7.5% of any deviation from equilibrium between the dependent variable LOGEXD and the explanatory variable LOGFER is corrected within one- quarter. In other words, it is likely to take approximately 13 quarters (more than 3 years) for LOGEXD to return to its long-run equilibrium path when a shock causes long-run external debt to deviate from an equilibrium state. However, its speed of adjustment is relatively slow. Several previous studies have also shown slow adjustments for correcting an external debt disequilibrium. T he adjustment is slower in several developing countries in Asia and Africa than in European countries. For example, it takes two and a half years in Ethiopia (Beyene and Kotosz 2020), almost three and a half years in Nigeria (Abdullahi, Abu Bakar, and Hassan 2015), and around five years in Srilanka (T hahara and Vinayagathasan 2017). However, in 25 European Union countries, the adjustment takes less than two years (Attard 2019). T he slow adjustments in some developing countries are partly attributable to the relatively high outstanding debts, which tend to cause exchange rate depreciation, putting pressure on their debt servicing. Many poor and developing countries continue to face the depreciation of their currencies (Fisera, Workie Tiruneh, and Hojdan 2021). T he situation is partly associated with 'original sin' (Eichengreen and Hausmann 1999) when development projects are financed through foreign-currency-denominated debts, whereas the generated revenues are in domestic currency. It also arises because short-term debts are utilized for long-term projects. Although Indonesia performed relatively well in the post-1997 Asian financial crisis (see Section 5), there is still an 'original sin' due to the first phenomenon. In 2019 Indonesia's long-term external debt accounted for 84.4% of the total (Bank Indonesia 2019); almost 90% is sovereign external debt. Sovereign external debt denominated in foreign currency is mainly used to finance long-term government projects. T he generated revenues are rupiah-
denominated because the public expenditure in education, healthcare, and construction is non-tradable.
Consequently, the condition leads to a slow adjustment in the long-run external debt equilibrium.
T he one-quarter period lagged effect of LOGFER is significantly positive, which implies that any increase in the exchange rate at a particular quarter leads to an instant increase in the subsequent quarter's external debt.
However, after adjustment, it later decreases, as reflected in the significant negative coefficient of D(LOGFER). T he short-run coefficients of the forcing variable LOGFER shown in Table 2 account for fluctuations in Indonesia’s external debt, apart from any deviation from an equilibrium caused by a shock. In a reverse manner, the decline in external debt is attributable to rupiah appreciation, and this needs to be proved by the nonexistence of asymmetry. We present and discuss the results of the nonlinear ARDL estimation in subsection 4.2.
T he shift toward a greater share of domestic borrowings can also reduce the need for more external debt. It is evidenced from this study that the short-term debt fluctuates in the short-run and returns to its long-run equilibrium path when associated with fluctuations in foreign exchange rates. Indonesia's short-term debts are generally used to fulfil short-term cash flow needs due to rupiah depreciation, and the change in that short- term debt does not occur instantly, but after one quarter.
Indonesia has successfully shifted from the domination of foreign-currency-denominated debt to that of rupiah-denominated debt, thereby reducing the risk of increased outstanding debt due to its rupiah depreciation. T his sort of shift in debt shares has been common in many emerging economies since 1990 (Wu 2020). In addition, Indonesia, which has since 1997 switched to a floating exchange rate regime, has experienced long-term rupiah depreciation. Although its external debt also has an upward trend, the country's long-term external debt sustainability has increased. T his is because the floating foreign exchange regime has moderated external debt shock. T he depreciation of the domestic currency has in the past given rise to higher competitiveness of Indonesia's exports of tradable goods, as found in many developing countries with stable macroeconomic stability (Ames et al. 2001 {Comment by Author: The following citation should be added.Ames, B., Brown, W., Devarajan, S., & Izquierdo, A. (2001). Macroeconomic Policy and Poverty Reduction. Retrieved from https://www.imf.org/external/pubs/ft/exrp/macropol/eng/#1
}), yet this tends to occur only when the rupiah depreciation is moderate.
T he results imply that stabilizing the Indonesian economy in the event of weakening rupiah does not require a drastic policy intervention such as tight monetary measures to strengthen the rupiah, thereby lowering the risk of the accumulation of external debts. T his implication is in congruence with the monetary policy adopted by the Bank of Indonesia, as suggested by P rabheesh, Anglingkusumo, and Juhro (2021). T hey examined the differences in impacts of global financial cycles on domestic economies in Indonesia and India and found that the spillover effects of the global financial cycle transmitted in both countries differ.
4.2. Asymmetric effects
I n Appendix 7 we show the results of nonlinear ARDL estimation based on equation (6) specification. All independent variables, at level and first difference, as well as their selected lags are significant. We calculated the nonlinear long-run coefficients, and the results are shown in Table 3. T he long-run coefficient of
LOGFER_P OS is +0,40072, while that of LOGFER_NEG is −2,27602. Both coefficients are the elasticities of external debt with respect to rupiah-to-dollar exchange rate fluctuations.
Table 3. Calculated nonlinear ARDL long-run coefficients.
Calculation* Calculated long-run coefficient
LOGFER_POS= - (0.171760)/(-0.428627)= +0,40072
LOGFER_NEG= - (-0.975562)/(-0.428627)= −2,27602
*From Appendix 9.
We then conducted a test for a joint null hypothesis of no cointegration by using the Wald Test by restricting all the three coefficients of LOGEXD(-1), LOGFER_P OS(-1), LOGFER_NEG(-1) variables to zero. As we show in Appendix 9, the F-statistic 7.682616 is larger than the upper-bound I(1) critical value given by P esaran, Shin, and Smith (2001) at 5% with k = 1 (the number of long-run regressors). T herefore, the Wald test rejects the joint null hypothesis of no cointegration. We conclude there exists a joint cointegration among the three variables LOGEXD(-1), LOGFER_P OS(-1), and LOGFER_NEG(-1). In other words, there is a long-run cointegrating relationship.
T he presence of asymmetry was tested by the Wald test. We restricted the equality between the positive long- run coefficient and the negative one, that is from equation (6). T he asymmetry does not exist, assuming the two coefficients are equal. T he West test result, shown in Appendix 7, indicates that it strongly rejects the null hypothesis of equality of positive and negative coefficients; therefore, the influence of currency exchange on external debt is asymmetric.
T he effect of LOGFER on LOGEXD differs in magnitudes according to the direction of changes in LOGFER. T he significantly positive coefficient of LOGFER_P OS suggests straightforwardly that a 1%
increase in the Indonesian currency exchange rate (rupiah depreciation) leads to a 0.4% rise in its external debt. Meanwhile, the significantly negative coefficient of LOGFER_NEG indicates that a 1% change in the foreign exchange rate in the opposite direction, i.e. rupiah appreciation, leads to a 2.27% decline in external debt. T he first result is in contrast to Fisera, Workie Tiruneh, and Hojdan (2021), which shows that small depreciations in relatively developed emerging countries reduce the long-term external debt burden. However, the second result is consistent with Wu (2020) that domestic currency appreciation has a negative effect on total external debt.
We can interpret the negative magnitude of −2.27602 for LOGFER_NEG as the positive (upward) movement of the rupiah exchange rate (i.e. the negative of negative). Accordingly, we construe both coefficients as the depreciation of the rupiah exchange rate. We then demonstrate that the absolute value of the LOGFER_NEG coefficient is more considerable than LOGFER_P OS. T hus, the effect of Indonesian rupiah volatility on Indonesian external debt is more severe in the case of rupiah exchange rate appreciation compared to a situation of rupiah depreciation.
T his study has two policy implications for Indonesia's external debt management and macroeconomic resilience. T he first implication is that the rupiah exchange rate stability should be maintained; however, it should be allowed to depreciate at a moderate pace in the long run. Although rupiah depreciation leads to a rise in external debt, the economy can withstand any external shock in the long run. Rupiah has been increasingly stable in the past two decades, notably after adopting a floating exchange rate in 1997. T herefore, foreign exchange market intervention by the Bank of Indonesia should be geared towards further strengthening liquidity in the economy. High volatility of foreign exchange could reduce uncertainty for long- term growth sustainability. Any short-term external shock that leads to a drastic movement of the domestic currency could severely hinder Indonesia's long-term economic growth. From the experience of the 2008 global crisis, the rupiah exchange rate depreciated sharply, and the economy's liquidity became tight due to precautionary actions taken by the households and businesses, leading to low aggregate spending. In addition, the banking sector reduced loans to avoid the risk of losses. Similarly, the government had difficulty financing the budget deficit (Bank Indonesia 2009). T herefore, although the short-term exchange rate fluctuates intermittently, an increasingly stable rupiah exchange rate in the long term is vital to maintaining Indonesia's long-term steady economic growth, partly supported by long-term external debt. Even though a short-term shock could raise the level of external debt, the Indonesian economy is capable of absorbing the short-term impact. In the event of such an external debt shock, a long-term equilibrium relationship between exchange rate and external debt would be reattained.
T he second policy implication is that Indonesia should avoid excessive rupiah appreciation. A mixed policy of restricting imports, encouraging foreign capital inflows, and maintaining a high level of international reserves (Bank Indonesia 2018a) that leads to a high rate of the rupiah exchange rate could be counterproductive. A constant long-term rupiah strengthening could increase Indonesia's long-term external debt more rapidly than long-term rupiah depreciation. As a result, it not only threatens Indonesia's current account balance but also weakens its long-term macroeconomic resilience in general. In light of this, tolerating moderate depreciation of the rupiah is less risky than preserving the rupiah appreciation for sustaining Indonesia's long-term growth.
Bank of Indonesia has frequently used several monetary policy instruments under a floating exchange rate system and a free foreign exchange regime. For example, Bank of Indonesia tends to sell foreign exchange when the rupiah depreciates. At the same time, to maintain liquidity in the economy and accommodate the government's budget deficit, the Bank of Indonesia usually purchases government bonds (SBN). Moreover, other monetary instruments such as domestic non-delivery forward (DNDF), first introduced in 2018, are also used (Bank Indonesia 2020a) to expand the domestic financial transactions in rupiah denominations. Short- term monetary policy instruments mentioned above are more frequently conducted when the rupiah depreciates. It implies that rupiah appreciation tends to be preferred because it is believed to have less impact on external debt. However, the domestic currency's continual appreciation may lead to a higher increase in long-term external debt. In the long run, the need for foreign debt remains because a remarkable gap exists between investment needs and national savings (Kusumasari 2020). In addition to foreign direct investment, the government's and private sector's long-term debt and portfolio investment are still essential. T herefore, a more appropriate policy is to allow the rupiah to depreciate at a level that is not at high risk of disrupting economic fundamentals. An increase in long-term external debt is not problematic provided that three
conditions are satisfied: 1. the long-term external debt is utilized for long-term public and private investments;
2. the total sovereign debt is persistently maintained below the maximum limit of 60% of GDP stipulated by law; and 3. the total external debt does not exceed the 48 percent threshold of the external debt-GDP ratio (Karimah and Nasrudin 2020).
Robustness check
Essentially, an ARDL cointegration method is robust when there exists a single long-run relationship between the underlying variables in a small sample size (Nkoro and Uko 2016). M. H. P esaran and Shin (1999) and M. Hashem P esaran, Shin, and Smith (2001) suggest that ARDL models are capable of handling cointegration with intrinsic robustness to misspecification of integration orders of relevant variables. We have shown from the stationarity test results that the underlying variables used in this study are a mix of I(0) and I(1) series, and both are cointegrated. T herefore, it directly implies the reliability and precision for OLS estimation, namely its results are robust. T his is in accordance with Banerjee et al. (1993). {Comment by Author:
Please add the reference and citation link here.Banerjee, A., Dolado, J. J., Galbraith, J. W., & Hendry, D. (1993). Co-integration, Error Correction, and the Econometric Analysis of Non-Stationary Data. Clarendon Press.
}
Furthermore, to further ensure the robustness of our ARDL estimation results, we conducted a Fully Modified OLS (FMOLS) estimation proposed by P hillips and Hansen (1990) {Comment by Author: Reference and citation link should be added.Phillips, P. C., & Hansen, B. E. (1990). Statistical inference in instrumental variables regression with I (1) processes.
Review of Economic Studies, 57, 99–125. https://doi.org/10.2307/2297545
}, which is essentially to check for robustness for a single cointegrating vector. FMOLS eliminates the problems caused by a long-run relationship between the cointegrating equation and stochastic regressors innovations. As suggested by the recent study of Olanrewaju et al. (2021), besides providing a check for robustness of the results, FMOLS estimates are reliable for a small sample size such as this present study.
We show from FMOLS estimation results summarized in Appendix 10 that the contemporaneous effect of LOGFER on LOGEXD is significantly positive, consistent with this study's results for the estimated ARDL long-run coefficients, shown in Table 1.
Limitations of the study
T here are two limitations of this present study that could offer more knowledge on the long- and short-run movement of external debts. First, it only uses the foreign exchange independent variable and estimates the one-equation ARDL model. Incorporating other macroeconomic variables such as GDP or economic growth is likely to give different results in terms of model selection to be employed and the number of cointegrating relationships. Second, this study does not disaggregate external debts into sovereign, private, and central bank external debts. Disaggregating external debts into government, central bank, and private debts has the ability to provide more insight into Indonesia's macroeconomic and, in particular, debt policies. T he coefficients of the long- and short-run effects of the foreign exchange on the disaggregated external debts are likely to be different in sign and magnitude. Future studies in the area can address the issues.
5. Indonesia's external debt and fiscal management
Following the 1997–1998 Asian financial crises, macroeconomic structural reforms have led to more robust financial stability and fiscal sustainability in Indonesia. Furthermore, the nation experienced a sustained annual growth of 5% during the 2011–2019 period. Furthermore, the shifting from a managed to a flexible foreign exchange regime in 1997 resulted in less volatile foreign exchange. T he immediate impact of the 1997 Asian economic crisis was the rise in the Indonesian rupiah exchange rate against the US dollar from 2,909 rupiahs in 1997 to 10,013 rupiahs in 1998. It was an unprecedented change in the country's foreign exchange, compared with the pre-crisis average annual rate of rupiah depreciation of only 7.9% during the period from 1970 to 1996. Nevertheless, during the 1999–2020 period the average annual depreciation went down to only 2.2%. T he 2010–2019 duration is important because it was not a crisis period for Indonesia during which long-term macroeconomic indicators have shown better performance, reflected by less volatile exchange rates.
As a result, the average quarterly change from 2010q1 to 2020q4 was only 1.07% and at one standard deviation of 2183, which reduces the likelihood of excessively high growth of external debts.
T he Indonesian central bank has more frequently aimed its monetary intervention at liquidity management under the floating foreign exchange regime (Bank Indonesia 2004). T he adoption of a floating foreign exchange policy has been effectively influential in the achievement of macroeconomic stability and growth goals through an inflation-targeting monetary policy (Rajan 2012). International reserves have also accumulated. Nevertheless, due to minimal domestic public savings, the risks of increasing external debts still persist, negating the solid macroeconomic fundamentals gained after the 2008 crisis. A persistent positive trend is notable in Indonesian external debt over the period from 2010 to 2019 as shown in Figure 1 and Appendix 8. T he sum of central government and central bank debts has increased, on average, parallel to the private sector debt. However, Indonesia is still facing a double-deficit problem (Handoyo, Erlando, and Astutik 2020), making it difficult to accelerate economic growth amid low public savings. Ahmed, Aizenman, and Jinjarak (2021) also stated that an increase in the exchange rate in some emerging market economies leads to the acquisition of more public debt, partly derived from external sources.
Notwithstanding the above-mentioned achievements and risks, Indonesia has taken a more cautious approach to external debt management. Its external debt is mainly geared towards accelerating economic growth, improving public services – education, health and social spending, and promoting development equality across the nation such as intergovernmental transfers and village development funding (BAP P ENAS. 2015;
Indonesian {Comment by Author: Change citation to the following.Indonesian Ministry of Finance. (2022). Transfer ke daerah dan dana desa.
Retrieved March 21, 2022, from http://www.data-apbn.kemenkeu.go.id/Dataset/Details/1013 } Ministry of Financ).
Although some studies reveal that public external debt negatively affects economic growth (Qureshi and Liaqat 2020), Indonesia performs relatively better in terms of government debt-to-GDP ratio, compared with several other countries in southeast Asia, as shown in Figure 2. T he relatively low central government debt-to- GDP ratio reflects a well-managed fiscal capacity to pay back debts from increased government tax revenues generated from a growing economy. Although Indonesia's external debt stock in terms of its ratio to Gross National Income is relatively higher than T hailand and the P hilippines, it is less than 48%. According to Karimah and Nasrudin (2020), the external debt-GDP ratio above the threshold tends to negatively affect Indonesia's economic growth. In addition, Indonesia's debt to GDP ratio greatly reduced from 95% in 2000 to only 24.7% in 2005 (World Bank 2005).
Figure 1. Indonesia's external debt by group of borrower (millions of USD).Source: Bank Indonesia (2020a).
As is the case in many developing countries where external debt plays an important role in financing the budget deficit (Gnimassoun and Santos 2020), the Indonesian government debt is, to a large extent, determined by the magnitude of its budget deficit. Indonesia's deficit financing, in general, takes the form of government bonds, known as Surat Berharga Negara (SBN). SBN, consisting of Surat Utang Negara (SUN) and Surat Berharga Syariah Negara (SBSN), is issued mainly in the denominations of rupiah, US dollars, euro, yen, and SDR. SBN cash inflow is preferred to other forms of borrowings as a source of deficit financing because the former is a more flexible source of financing, as distinguished from project-based borrowings for which its uses are pre-determined.
Table 4 presents the trend in Indonesian budget deficit as percentage of GDP. From 2016 to 2019, the budget deficit never exceeded 3% of GDP – the maximum limit stipulated in the Indonesian Law Number 17 of 2003 on State Finance. Moreover, the total outstanding debt also remains within the limit stipulated by the law, which is below the maximum limit of 60% of gross domestic product. For example, in
Table 4. Indonesia's Gross Domestic Product and budget deficit, 2016–2019.
2016 2017 2018 2019
GDP at current prices (trillion rupiahs)
12,401.7 13,589.8 14,838.3 15,833.9
Figure 2. Ratios of central government debt to GDP and external debt to GNI of selected southeast Asian countries.Source: IMF (2020) and World Bank .
Government revenue (trillion rupiahs)
1,822.5 1,750.3 1,894.7 2,165.1
Government expenditure (trillion rupiahs)
2,095.7 2,080.5 2,220.7 2,461.1
Budget deficit (trillion rupiahs)
273.2 330.2 326.0 296.0
Budget deficit as % of GDP*
2.2% 2.4% 2.2% 1.9%
2016 2017 2018 2019
Source: BPS (2020), Ministry of Finance (2020) {Comment by Author: Should be replaced with "Indonesian Ministry of Finance (2022)"Indonesian Ministry of Finance. (2022). Realisasi APBN. Retrieved March 21, 2022, from https://www.kemenkeu.go.id/informasi- publik/realisasi-apbn/
}.
*Authors' calculation.
2018 the ratio of central government debt to GDP was 32,18%. Nevertheless, there is an indication that government debt crowds out other borrowings by the central bank and private businesses. From 2010 to 2015, the ratio of government bonds to GDP increased from 15.5% to 19%, while the ratio of total borrowings to GDP dropped from 9% to 5.7% (BAP P ENAS. 2015).
T he Indonesian government fiscal policies have been geared towards maintaining fiscal sustainability to allow for more room for economic growth. Conversely, efforts to reduce the dependence on debts are made by decreasing the yearly budget deficit (Bank Indonesia 2018b). Besides, the country has adopted a strategy to substitute domestic for external debt to avoid foreign exchange risks. External debt vulnerability has substantially lowered as a result of the changed currency composition of the debt, thereby strengthening fiscal sustainability (Insukindro 2018). Moreover, short-term debt has been greatly reduced, from around 25% in 1996 to only 12.6% in 2018 as shown in Figure 3. However, there is always a risk of increased short-term debt capable of being affected by exchange rate increases.
Global interest rates increase lead to short-term external debts, in particular when government bonds (SBN) denominated in foreign currency are issued. On average the interest rate of SBN is twice higher than the average rate of direct external borrowings. However, SBN issuance has been a preferable source of deficit financing due to its relative flexibility because its target can be adjusted to the changing needs during the budgeting process. T his is contrary to direct project-based loans that require a longer time to acquire due to planning time lags. T herefore, in recent years preference has been given to SBN and domestic rupiah- denominated borrowings (Indonesian Ministry of Finance 2018). In 2017, for example, as much as 80.4% of Indonesian debt used to finance budget deficit was sourced from SBN issuance and only 19.6% is from direct borrowings. Out of 384.7 trillion rupiahs of SBN issued in 2017, only 21.4% is in foreign currency denominations, while the remaining 59% is rupiah-denominated. Consequently, the risk and impacts of external shocks, such as foreign exchange fluctuations, is dampened when they occur.
6. Conclusion and implications
Indonesia has experienced two big crises and taken more precautious policies to avoid other potential crises.
Figure 3. Indonesia's short-term debt and total debt service.Source: (World {Comment by Author: Source should be replaced with World Bank (2022).The World Bank. (2022). External debt stocks - % of GNI. Retrieved March 21, 2022, from https://data.worldbank.org/indicator/DT.DOD.DECT.GN.ZS?locations=ID-TH-MY-SG-PH
} Ban). {Comment by Author: Source should be replaced with World Bank (2022).The World Bank. (2022). External debt stocks - % of GNI.
Retrieved March 21, 2022, from https://data.worldbank.org/indicator/DT.DOD.DECT.GN.ZS?locations=ID-TH-MY-SG-PH }
