The widening of the north-south divide: Debt sustainability in a world weakened by COVID-19

Bernardo, Sandra; Jacquinet, Maria Luísa; Rocha, Fátima Article The widening of the north-south divide: Debt sustainability in a world weakened by COVID-19 Economies Provided in Cooperation with: MDPI – Multidisciplinary Digital Publishing Institute, Basel Suggested Citation: Bernardo, Sandra; Jacquinet, Maria Luísa; Rocha, Fátima (2023) : The widening of the north-south divide: Debt sustainability in a world weakened by COVID-19, Economies, ISSN 2227-7099, MDPI, Basel, Vol. 12, Iss. 2, pp. 1-27, https://doi.org/10.3390/economies12020042 This Version is available at: https://hdl.handle.net/10419/328969 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may be saved and copied for your personal and scholarly purposes. You are not to copy documents for public or commercial purposes, to exhibit the documents publicly, to make them publicly available on the internet, or to distribute or otherwise use the documents in public. If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ Citation: Bernardo, Sandra, Maria Luísa Vasconcelos, and Fátima Rocha. 2024. The Widening of the North– South Divide: Debt Sustainability in a World Weakened by COVID-19. Economies 12: 42. https://doi.org/ 10.3390/economies12020042 Academic Editor: Francesco Schettino Received: 30 December 2023 Revised: 26 January 2024 Accepted: 1 February 2024 Published: 6 February 2024 Copyright: © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). economies Article The Widening of the North–South Divide: Debt Sustainability in a World Weakened by COVID-19 Sandra Bernardo 1,2,* , Maria Luísa Vasconcelos 1,2 and Fátima Rocha 1,2 1Faculty of Human and Social Sciences, Fernando Pessoa University (FCHS-UFP), 4294-004 Porto, Portugal; [email protected] (M.L.V.); [email protected] (F.R.) 2Centro de Estudos Políticos, Económicos e Sociais (CEPESE—Centre for the Study of Politics, Economy and Society), 4200-365 Porto, Portugal *Correspondence: [email protected] Abstract: This research compares the global debt trends in the aftermath of the COVID-19 pandemic, focusing on economies that frame the North and South divide. The research centers on debt ratios, which serve as indicators of countries’ ability to finance recovery and development projects. The study period runs from 2015 to 2022 and follows the IMF’s country classification, which divides the world into advanced economies (AE) and emerging market and developing economies (EMDE). The research employs panel data regressions to assess three key debt ratios—external debt to Gross Domestic Product (GDP), external debt to exports, and public debt to GDP—against various pandemic-related indicators and control variables. The analysis provides three major contributions. Firstly, an examination of external and public debt burdens is conducted, showing that escalated external and public debt burdens in EMDE contrast with increasing public debt in AE, primarily due to fiscal stimulus. Secondly, it is argued that the ongoing pandemic has intensified the widening economic gap between the North (AE) and the south (EMDE). Thirdly, a review is presented of both orthodox and heterodox policies identified in existing literature that are considered capable of mitigating external vulnerabilities in EMDE. Findings highlight the critical need for multifaceted measures to address debt vulnerability and promote sustainable economic recovery in a post-pandemic world. Keywords: COVID-19; globalization; indebtedness; inequalities; north–south divide 1. Introduction While some theorists see liberal globalization as an opportunity for global economic leveling, others view it as a cause of social injustice and deprivation across vast parts of the globe. The reduction of transportation and communication costs in the latter part of the twentieth century accelerated the process of globalization, resulting in the dissemination of knowledge, trade, and financial transactions, but also in the worsening of inequalities, population migration, and climate change. Among the plethora of consequences of capitalism-based globalization, a renewed economic geography emerged, carved on the ruins of inequality and economic meaninglessness experienced by millions of human beings who live in a constant struggle for change and the quest for their own identity. This scenario, which gives rise to new spatial hierarchies, has already led to the observation of the global system through the eyes of central regions (rather than States), i.e., regions that are highly economically integrated and have financial and informational supremacy. They are followed by other peripheral or semi-peripheral regions, which are suppliers to central regions and exhibit low initiative, scarce technology, low investment, and limited decisional power (Taylor 2000). Even if this new order is recognized, the scenario of global regions replacing the mosaic of States remains unfulfilled. For now, globalization seems to be a unifying force, viewing every space as having the potential for production and trade, whereas the international division of labor acts Economies 2024,12, 42. https://doi.org/10.3390/economies12020042 https://www.mdpi.com/journal/economies Economies 2024,12, 42 2 of 26 as a dividing force, establishing dominating locations that stimulate activity elsewhere. The expression of this global hierarchy of spaces requires the affirmation of “the subaltern in counter-hegemonic globalization” (Evans 2000;Santos and Rodríguez-Garavito 2005), in light of the significant impacts produced on human life (and the planet), as measured by dual spatial relationships: benefits–costs, access to–exclusion, participation–isolation, hegemony–marginalization, North–South. This divide is neither defined by geographical boundaries nor statistically fixed; it is not restricted to a “community of victims” either (Dussel 1998). The South refers to a region that is not defined by specific geographic locations. Instead, it reflects the impacts of an unfavorable exchange ratio vis-à-vis the advanced economies in the developed North, as reflected in human development indicators outlined in the United Nations Human Development Reports. These regions are referred to as “emerging and low-income economies” (Mignolo 2011). The forms of economic subordination produced by market logic are more pronounced in the South, which has led to extensive discussions about the trajectory of growth in the South across various fields of knowledge, including economics. These discussions aim to determine the most appropriate explanation for its impoverishment, which could be attributed primarily to a direct relationship with colonialism and imperialism, as posited by dependency theories, or to a set of internal impediments hindering its growth and development processes, as suggested by obstacle theories and neoclassical counterrevolution. Regardless of which theoretical contribution one chooses, the long-standing tension between growth in the North and poverty in the South is evident. Recently, the COVID-19 pandemic has accentuated this divide, particularly in terms of access to preventive and prophylactic healthcare and the varying economic capacities of different regions to support their economies and citizens, thereby impacting economic hardships and social injustices. It is true that the impacts felt in the South did not result in the devastation predicted in terms of fatalities and disease rates (UNCTAD 2020), likely due to a longer period of preparation, a faster response, a low testing rate, a lower average age of the population, and a favorable climate (Okonji et al. 2021). Nonetheless, though not as overwhelmingly as initially expected, there have been devastating effects resulting from uncertainties regarding access to essential goods and services, including healthcare, a decrease in trade volume, and potential long-term economic and financial consequences. Following the closing of borders to Southern economies, ( Agualusa and Couto 2021, p. 1 ) eloquently recalled that there was only one pandemic, not two: “( . . . ) Borders are not closed, people are closed. Economies, societies, and paths to progress are closed. [ . . . ] Once again, politics held science hostage. ( . . . ) There may be two feelings of justice. But there are no two pandemics” [our translation]. While this is true in terms of (one global) infection, the economic repercussions and amount of damage caused to emerging and low-income economies differed significantly from those of the developed world. The pandemic affected the whole world economy and caused the worst recession since 1929 (Sachs et al. 2021), but its impact varied across different parts of the world, widening the North–South divide. Debt, either external or sovereign, is a significant issue for many countries in the South. This does not diminish the significance of debt sustainability in AE, as evidenced by a substantial body of studies on the Euro Area sovereign debt crisis (e.g., De Grauwe and Ji 2013;Greenwood-Nimmo et al. 2023) and the sustainability of fiscal debt in the United States (Aldama and Creel 2019). However, Southern countries frequently find themselves needing to borrow for development projects, and due to factors, such as lower credit ratings, unstable political environments, and sometimes unfavorable terms of trade, they may end up paying higher interest rates. This situation can lead to a cycle of debt, where countries borrow additional funds to pay off existing debts, further exacerbating their financial challenges. The relationship between the North–South divide and debt is complex and multifaceted (Raffer and Singer 2002). On one hand, high levels of debt can exacerbate the economic challenges faced by countries in the South, hindering development and per- Economies 2024,12, 42 3 of 26 petuating the divide. On the other hand, countries in the North largely influence the global financial system, which determines the terms and availability of credit for Southern countries, thus impacting their debt levels. Given the presence of unique vulnerabilities on a global scale, this analysis aims to evaluate the effects of COVID-19 on the North and South divide, specifically by examining the interconnection between external and public debt and countries’ capacity to address the pandemic. Considering the global natural experiment triggered by the COVID-19 outbreak, which functions as an exogeneous shock to borrowing needs (Zheng 2023), two questions are addressed: (a) How has the indebtedness of emerging markets and developing economies changed during the COVID-19 pandemic when compared to advanced economies? (b) Does this trajectory show the existence of a growing North–South divide? The study categorizes global economies based on the IMF’s classification: Advanced economies (AE) and emerging markets and developing economies (EMDE). Covering the timeframe from 2015 to 2022, we estimate several panel data regressions, analyzing three debt ratios (external debt to GDP, external debt to exports, and public debt to GDP) against various indicators of the pandemic, along with several control variables. Our measures of the pandemic vary, including post-COVID dummy variables and variables indicating the severity of the pandemic. Limitations to our study include, firstly, the availability and quality of data, especially for EMDE, which may affect the precision of our findings; variations in data reporting and accuracy across countries could impact the robustness of the analysis. Secondly, the study’s focus on the aftermath of the COVID-19 pandemic within a specific time frame (2015–2022) may not capture the full extent of the pandemic’s long-term effects on global debt trends. First, we demonstrate that EMDE faced escalated external and public debt burdens, while AE primarily encountered amplified public debt due to fiscal stimuli in response to the crisis. Despite initial concerns, EMDE managed to navigate a potential rollover crisis while maintaining elevated debt levels. Second, we argue that the observed trend in debt dynamics during the COVID-19 pandemic does suggest the widening of a North–South divide. AE, primarily located in the Global North, have handled debt challenges differently compared to EMDE, mostly situated in the Global South. The divergent impact of the pandemic on debt levels could exacerbate the existing gap between these economic segments. To address these vulnerabilities, we outline several financial policy measures conducive to debt reduction. These measures range from orthodox to heterodox policies for debt reduction, as outlined by Kose et al. (2022). Orthodox policies include strategies such as promoting economic growth, fiscal consolidation, privatization of public assets, and implementing wealth taxation. Heterodox policies involve alternative approaches to debt reduction, including inducing higher inflation through fiscal and monetary measures, implementing financial repression through capital controls and financial sector regulations, and considering debt default and restructuring as a last resort. We also emphasize that international assistance and initiatives are crucial for supporting countries burdened by high levels of debt, underscoring the importance of debt relief programs. The paper is organized as follows: The next section gives an overview of the problem by preliminarily evaluating the main COVID-19 repercussions on AE and EMDE, introducing the relevant debt ratios for the study, and presenting the determinants of debt changes. Section 3describes the methodology of the analysis. Section 4then presents the results and offers a preliminary analysis of the debt trajectory during COVID-19. The research further discusses the results in Section 5, comparing developing and developed economies and identifying a few paths for unburdening the economies of the South. Finally, the concluding section summarizes the primary findings and points to the possibility of a fundamental shift in the current economic paradigm largely accountable for the North–South divide. Economies 2024,12, 42 4 of 26 2. Background and Literature Review 2.1. Comparative Major COVID-19 Impacts in AE and EMDE According to the World Economic Outlook (IMF 2020), the pandemic crisis triggered by COVID-19 hindered two decades of average growth of 4.1% in EMDE (one percentage point higher than in 1980–1999), a period during which important advances were made in poverty reduction and income distribution. In terms of economic growth, global GDP slowed by 2.8% as a result of the pandemic in 2020, with a rebound of 6.3% in the subsequent year (IMF 2023d). However, Figure 1shows that neither the downturn nor the burst happened in the same way in all world economies. Economies 2024, 12, x FOR PEER REVIEW 4 of 28 research further discusses the results in Section 5, comparing developing and developed economies and identifying a few paths for unburdening the economies of the South. Finally, the concluding section summarizes the primary findings and points to the possibility of a fundamental shift in the current economic paradigm largely accountable for the North–South divide. 2. Background and Literature Review 2.1. Comparative Major COVID-19 Impacts in AE and EMDE According to the World Economic Outlook (IMF 2020), the pandemic crisis triggered by COVID-19 hindered two decades of average growth of 4.1% in EMDE (one percentage point higher than in 1980–1999), a period during which important advances were made in poverty reduction and income distribution. In terms of economic growth, global GDP slowed by 2.8% as a result of the pandemic in 2020, with a rebound of 6.3% in the subsequent year (IMF 2023d). However, Figure 1 shows that neither the downturn nor the burst happened in the same way in all world economies. Figure 1. GDP growth rates (2015–2022). Source: IMF (2023d). The pandemic had the greatest impact on AE, while EMDE experienced relatively less severe contractions, with notable disparities in the size of the shock. Latin America and the Caribbean experienced the greatest impact (−7.0%), while Asia performed better (−0.5%), primarily due to China’s performance (+2.2% in 2020). Over the first year of the pandemic, the decline in economic growth as well as the number of casualties aligned with the income inequality levels in each country, with nations more reliant on the service sector and those that enforced stricter measures, such as lockdowns, facing greater reductions in GDP growth (Ghecham 2022). Notwithstanding, over the course of 2020 and 2021, in AE, COVID-19 fatalities had a somewhat larger, though not statistically significant, negative impact on GDP. Conversely, lockdown restrictions had a more detrimental effect on the economic activities in EMDE. Furthermore, global trade served as a significant channel for the economic repercussions of the pandemic to spill over national borders (Gagnon et al. 2023). This contraction in the global economy plunged more people into poverty. Indeed, the International Food Policy Research Institute estimated that in the absence of social and economic mitigation measures in the Global South, the number of poor would increase by 20% (almost 150 million people) with respect to the situation in the absence of COVID-19 (Laborde et al. 2021). For the first time since 1990, estimates predicted worldwide poverty to increase, reversing over a decade of global progress toward poverty reduction (Sumner et al. 2020). In fact, the 2020 global Multidimensional Poverty Index (MPI) noted that the pandemic would set back progress in poverty reduction by 3–10 years. By 2022, estimates from the Figure 1. GDP growth rates (2015–2022). Source: IMF (2023d). The pandemic had the greatest impact on AE, while EMDE experienced relatively less severe contractions, with notable disparities in the size of the shock. Latin America and the Caribbean experienced the greatest impact ( − 7.0%), while Asia performed better ( − 0.5%), primarily due to China’s performance (+2.2% in 2020). Over the first year of the pandemic, the decline in economic growth as well as the number of casualties aligned with the income inequality levels in each country, with nations more reliant on the service sector and those that enforced stricter measures, such as lockdowns, facing greater reductions in GDP growth (Ghecham 2022). Notwithstanding, over the course of 2020 and 2021, in AE, COVID-19 fatalities had a somewhat larger, though not statistically significant, negative impact on GDP. Conversely, lockdown restrictions had a more detrimental effect on the economic activities in EMDE. Furthermore, global trade served as a significant channel for the economic repercussions of the pandemic to spill over national borders (Gagnon et al. 2023). This contraction in the global economy plunged more people into poverty. Indeed, the International Food Policy Research Institute estimated that in the absence of social and economic mitigation measures in the Global South, the number of poor would increase by 20% (almost 150 million people) with respect to the situation in the absence of COVID-19 (Laborde et al. 2021). For the first time since 1990, estimates predicted worldwide poverty to increase, reversing over a decade of global progress toward poverty reduction (Sumner et al. 2020). In fact, the 2020 global Multidimensional Poverty Index (MPI) noted that the pandemic would set back progress in poverty reduction by 3–10 years. By 2022, estimates from the United Nations Development Programme, and the Oxford Poverty and Human Development Initiative suggested that the most pessimistic scenarios were then plausible (UNDP 2022). These scenarios were associated with lost schooling, slower learning processes, or even abandonment attributed to the pandemic. Furthermore, data on food insecurity indicated that the number of people living in food crises or worse increased to 193 million in 2021. By then, due to large disparities in vaccine access and policy support, AE were expected to regain the pre-pandemic trend path faster than most emerging economies groups, with the exception of the Asian developing economies (IMF 2021c). The Gini Economies 2024,12, 42 5 of 26 coefficient (which quantifies inequality within a population—a value of zero shows perfect equality, while 100 implies maximum inequality) declined by only three points over the two preceding decades (from 44 to 41, on average), but this was associated with an increase in income disparity in one-third of low-income developing countries (IMF 2020). There was a significant divide between AE and EMDE. The threat, even to modest gains, was significant. Indeed, although prior pandemics elevated the Gini coefficient, research suggested that the COVID-19 impacts were worse than the earlier crisis (Furceri et al. 2022). Aside from income inequality, research revealed other severe discrepancies in the COVID19 pandemic between AE and EMDE, particularly in terms of mortality ( Ahmed et al. 2020 ) and vaccination (Arellano et al. 2023;Tatar et al. 2021), which seemed to widen the gap between them. Nonetheless, wealthy nations had lost more life years per capita than poorer countries, owing to the population’s older age structure in richer countries and a disease with a highly age-selective lethality (Ferreira 2021). Regarding gender equality, despite improvements, gender disparities in labor force participation remained high, especially in low-income countries (IMF 2020). However, even in AE, the COVID-19 shock deepened gender inequality by disproportionately affecting women (Flor et al. 2022;Yerkes et al. 2020). Other indicators of slow growth or reversal included increased inequality due to higher unemployment (Petrakos et al. 2023), unequal access to technological resources (Korkmaz et al. 2022), which determined the conditions necessary to provide distance education exacerbated the inequity in education ( Ferreira 2021 ), and mental health, to name a few. The pandemic’s unequal impact on vulnerable workers also jeopardized the progress made before the crisis and potentially exacerbated the imbalances between AE and EMDE (Bottan et al. 2020;Furceri et al. 2022). More comprehensive measures of well-being than the GDP, such as the Human Development Index (HDI), which combines factors such as health, education, and the economy, indicated a steep and unprecedented decline in 90% of countries in 2020 or 2021 ( UNDP 2022 ). An alternative measure proposed by Jones and Klenow (Jones and Klenow 2016 cit. in IMF 2020, p. 37), which considers factors such as real consumption per capita, life expectancy, leisure time, and consumption inequality, indicated a drop in well-being as high as 8%, owing in large part to a surge in inequality (IMF 2020). Policies of redistribution and measures to support afflicted individuals and businesses were critical for mitigating adverse effects on inequality, education, and overall well-being. When comparing the economic impact of the COVID-19 pandemic with past shocks, such as the oil shocks or the 2007–2008 Global Financial Crisis (GFC), it reveals distinct characteristics and implications for each event. Firstly, the total economic impact of the COVID-19 pandemic is expected to exceed that of the GFC, both in size and scope. The pandemic lockdowns resulted in severe declines in oil prices (Rose 2020) and had an impact on currency volatility about eight times greater compared to the GFC ( Gunay 2021 ), highlighting its global reach. The distributive consequences of the pandemic may surpass those arising from historical pandemics and exceed the effects observed in typical recessions and financial crises (Furceri et al. 2022). Secondly, the COVID-19 pandemic had significant consequences on government debts, requiring extensive debt relief measures. This differs from past sovereign debt crises, where the focus was more on austerity and restructuring (Becchetti and Scaramozzino 2021). Thirdly, the pandemic created both a demand and supply shock in the oil industry, leading to high levels of oil price volatility. This is different from traditional oil shocks, which were typically driven by supply-side factors ( Bourghelle et al. 2021 ). Fourthly, the borrowing during the COVID-19 pandemic did not adequately account for the impact of climate change on countries’ ability to repay debt, a concern that was less prominent in past financial crises (Dibley et al. 2021). Finally, although COVID-19 had a significant impact on financial markets, marked by substantial declines in stock market indexes and heightened volatility, the literature reports mixed results when comparing it to the GFC. On the one hand, El-Khatib and Samet (2021) suggest that the effects of the pandemic on stock markets did not reach the magnitudes observed during the GFC, with the most pronounced effects being observed in Asian Economies 2024,12, 42 6 of 26 emerging markets and the least in European emerging markets (Topcu and Gulal 2020). Accordingly, De La Peña and García(2023) found that financial shocks accounted for half of the contraction of the GDP cycle in the GFC, while during COVID-19, the contraction was mainly due to a demand shock. Contrarily, Muzindutsi et al. (2022) found that the impact of the COVID-19 pandemic on financial markets was more severe than that of the GFC, with contagion effects being more pronounced in EMDE than in AE during both crises. 2.2. Debt Ratios to Respond to Crises and Shocks Countries must (either save or) borrow in order to fund recovery and development programs, which are jeopardized in the presence of large debt loads and default risks. This is especially important in a world following COVID-19 (Elkhishin and Mohieldin 2021) and facing the likelihood of other infectious disease outbreaks that are anticipated to become more prevalent and difficult to control (UNOCHA 2021). The more indebted a country is and the greater the burden of debt repayment, the less able it is to fund a health crisis response and accomplish development objectives. As such, it is reasonable to anticipate a deepening of inequality in such countries. Among the vast array of current debt metrics, this research focuses its examination on debt solvency, that is, the capacity of a country to respond to long-term obligations, and analyzes debt burden ratios, in particular stock-based indicators—external debt-to-GDP, external debt-to-exports, and government debt-to-GDP. External debt refers to debt liabilities owed by (both public and private) residents of an economy to nonresidents. External debt is very important, particularly for developing countries, since it provides resources that supplement local savings and fund investment. Nonetheless, a high level of external debt may also disrupt growth and the efficient performance of capital markets. As such, debt ratios and the trajectory of external debt must be examined in order to reduce future risks and recognize (challenges to) economic policy choices. The external debt-to-GDP ratio measures the total outstanding external debt at the end of the year in relation to gross domestic product. i.e., it indicates the potential to repay foreign debt if resources were to be redirected from the production of domestic goods to generating exports (IMF 2000). Supplementarily, the external debt-to-exports ratio expresses the relationship between the total outstanding debt at the close of the year and the economy’s exports of goods and services in that year (IMF 2000). This ratio is used as a measure of sustainability since, at a given interest rate, a rising debt-to-exports ratio signals that the country may have difficulty servicing its debt obligations in the future, as it indicates that overall debt is growing faster than exports, i.e., than the country’s primary source of external revenue. The government debt-to-GDP ratio is another relevant debt metric. National governments issue sovereign debt, which is considered a unique asset in the financial system due to its perceived safety and liquidity compared to private debt, thanks to the government’s ability to tax future income. It aids economic agents in managing liquidity, smoothing consumption, and seizing investment opportunities. However, there is a contrasting view highlighting the challenges in enforcing sovereign debt contracts, especially with foreign investors. Enforcement is difficult not due to a lack of legal framework but because foreign courts cannot compel sovereigns to relinquish assets, most of which are within their borders. In advanced countries, where sovereign debt is largely held domestically, default is politically unviable, while in emerging markets, with weaker political institutions and segmented debt markets, the focus is on the sovereign’s control over its territory and assets. Both perspectives underscore the sovereign’s extraordinary powers: the ability to tax and to control territory and assets (Martinez et al. 2022). It is also vital to pay close attention to the probability of adverse effects on these indicators. The trajectories of growing debt, stagnation of the output level, inflation, and increasing interest rates are all factors that may heighten the risks of failing to meet financial obligations, with consequences in the form of higher interest rates and the aggravation of payment terms. Indeed, a paradox emerges in that, in the context of rising interest rates, Economies 2024,12, 42 7 of 26 the indebtedness capacity drops exactly when it is most required. Arellano et al. (2020) demonstrate that in EMDE, pandemic shocks heighten the risks of sovereign defaults, consequently limiting their capacity to borrow, while Zheng (2023) finds that in AE, where governments can issue more bonds to address unexpected fiscal shocks, there is no evidence to suggest that pandemic shocks lead to an increase in sovereign bond spreads. For the purposes of this study, the observation of the aforementioned ratios is deemed adequate and sufficient, although additional indicators could be presented, such as liquidity indicators and solvency flow-based indicators. Examples of the former could include international reserves to short-term debt (which assesses future vulnerability to liquidity crises) and short-term debt to total outstanding debt (which measures reliance on shortterm financing). Examples of the latter could include debt service to exports or debt service to GDP. Note that debt service is the amount of money necessary to repay the interest and principal on a loan over a certain term. As a result, debt-service-related metrics inform about the resources a country must allocate to repay its debts and the burden on the system due to crowding out alternative uses of financial resources. In general, it is useful to monitor debt service in relation to exports and (government) revenues (IMF 2022a,2014). One should note, in particular, that since the subprime mortgage crisis of 2007–2008, the growing trend of national (public) debt levels has been evident, but it escalated swiftly in reaction to the COVID-19 epidemic, which became related to the repeated financing demands of economic activity. Compared to 2008, almost 90% of advanced countries have greater national debt-to-GDP ratios in 2019. Meanwhile, in this same year, approximately two-fifths of low-income developing countries were at high risk of or experiencing debt distress (UNCTAD 2019). Yet, the evaluation of national debt ratios for AE and EMDE is significantly different. For the former, low-interest monetary policies coupled with debt practices in their own currency have enabled them to maintain large debt ratios. In these economies, changing these practices is expected to slow down economic growth, decrease tax revenues, increase the need to invest in economic recovery, increase the costs of debt service, and increase the risk of having a high debt ratio. Nevertheless, increasing interest rates have more severe and sustained effects for developing economies since the majority of these nations have funded at least a portion of their debt by external borrowing, which increases the likelihood of debt distress and debt crises. Faced with this increased risk, some governments have to choose between cutting public spending or preserving it. The first choice makes growth, health, and social vulnerability more unequal, while the second one increases borrowing costs, debt burdens, and the risk of debt defaults. Following the pandemic’s outbreak, all economies were affected, but the impact was particularly acute in EMDE, where deteriorating financial capacity for external indebtedness jeopardized the implementation of anti-pandemic policies and significantly limited the continuation of external funding for long-term development programs. In contrast, AE continued, to a greater or lesser extent, to be capable of implementing fiscal stimulus packages in addition to expansionary monetary policy measures without major repercussions on their financial conditions or exchange rates. Indeed, there is a clear difference in how the national debt ratios changed in AE and EMDC. Figure 2illustrates the annual percentage change in debt indicators’, with distinct representations for both groups of economies. Beginning in 2010, EMDE were already experiencing a rapid accumulation of debt, often referred to as the “fourth wave” of debt (Kose et al. 2020). This trend was exacerbated during the pandemic-induced global recession of 2020, transforming the fourth wave into a more perilous “tsunami” due to the sharp increase in debt (Kose et al. 2021). As such, it is not surprising that the economies that responded best to external pressures were those that “exhibit a balanced integration, rather than an asymmetric integration, and those that promote a conscious external allocation of savings to productive projects” (Dornbusch and Helmers 1991, p. 234). As a result, those authors argue that “an efficient indebtedness strategy is an integral aspect of a broader development strategy.” [Our translation]. Economies 2024,12, 42 8 of 26 Economies 2024, 12, x FOR PEER REVIEW 8 of 28 stimulus packages in addition to expansionary monetary policy measures without major repercussions on their financial conditions or exchange rates. Indeed, there is a clear difference in how the national debt ratios changed in AE and EMDC. Figure 2 illustrates the annual percentage change in debt indicators’, with distinct representations for both groups of economies. Figure 2. Year-on-year percentage changes in average debt ratios. (a) External debt to GDP; (b) external debt to export; (c) public debt to GDP. Source: Authors’ calculations based on the data sources included in Appendix A Table A1. Beginning in 2010, EMDE were already experiencing a rapid accumulation of debt, often referred to as the “fourth wave” of debt (Kose et al. 2020). This trend was exacerbated during the pandemic-induced global recession of 2020, transforming the fourth wave into a more perilous “tsunami” due to the sharp increase in debt (Kose et al. 2021). As such, it is not surprising that the economies that responded best to external pressures were those that “exhibit a balanced integration, rather than an asymmetric integration, and those that promote a conscious external allocation of savings to productive projects” (Dornbusch and Helmers 1991, p. 234). As a result, those authors argue that “an efficient indebtedness strategy is an integral aspect of a broader development strategy.” [Our translation]. 2.3. Determinants of Debt Indicators As mentioned earlier, this analysis explores the trajectory of debt indicators in AE and EMDE, as these indicators demonstrate the countries’ ability to finance COVID-19 response strategies, whether externally or domestically. The specific debt indicators examined in this analysis include the ratios of external debt to GDP, external debt to exports, and government debt to GDP. The choice of these major indicators relates to their significance in assessing a country’s ability to undertake an accommodating political economy as a response to the pandemic. This is not to diminish the relevance of all the many other indicators, economic or otherwise, to such an extent that an analysis of major social-economic impacts has been included in Section 2.1. Figure 2. Year-on-year percentage changes in average debt ratios. (a) External debt to GDP; (b) external debt to export; (c) public debt to GDP. Source: Authors’ calculations based on the data sources included in Appendix ATable A1. 2.3. Determinants of Debt Indicators As mentioned earlier, this analysis explores the trajectory of debt indicators in AE and EMDE, as these indicators demonstrate the countries’ ability to finance COVID-19 response strategies, whether externally or domestically. The specific debt indicators examined in this analysis include the ratios of external debt to GDP,external debt to exports, and government debt to GDP. The choice of these major indicators relates to their significance in assessing a country’s ability to undertake an accommodating political economy as a response to the pandemic. This is not to diminish the relevance of all the many other indicators, economic or otherwise, to such an extent that an analysis of major social-economic impacts has been included in Section 2.1. To determine the factors influencing the debt trajectory in our model, we rely on insights from previous research. Table 1lists the key variables most commonly identified in these studies. Additional determinants, such as debt architecture and the dominance of various forms of debt, as discussed by Elkhishin and Mohieldin (2021), could be considered. However, the aim of our study is not to dissect the influence of these determinants on debt indicators but to examine the impact of the pandemic. Therefore, we include control variables in a parsimonious manner rather than assessing the impact of explanatory variables. Table 1. Description of control variables. Group Variable References Fiscal indicators Gov. net lending/borrowing to GDP (Awan et al. 2015;Mahara and Dhakal 2020; Omar and Ibrahim 2021) Gov. revenue to GDP (Mensah et al. 2017;Waheed 2017) Economies 2024,12, 42 15 of 26 spreads increased more in emerging economies than AE, though the former borrowed less during the pandemic. Despite the heightened necessity for fiscal expansion in these countries, surpassing the urgency seen in AE, this limitation persisted. Low-income nations required increased financial support to tackle the pandemic-induced economic crisis and make strides towards achieving the Sustainable Development Goals (SDGs). The pandemic is likely to delay the SDGs by at least a decade, which puts low-income developing countries (LIDC) at risk. To successfully achieve the SDGs, these countries should be able to borrow at the same scale relative to GDP and at approximately the same interest rate as the rich countries, which will require new forms of international policy support that promote increased fiscal space (Sachs et al. 2021). Although recognizing the need to ensure the ability of these economies to continue to undertake essential public expenditure while managing to maintain their international financial obligations (IMF 2021c), higher debt levels and large government financing needs in many countries are also a source of vulnerability. In fact, EMDE are considerably more susceptible than they were at the outset of the global financial crisis, indicating that the effect of the present shock might be more severe and recovery more distant (Elkhishin and Mohieldin 2021). Moreover, one may argue that the resilience of the North not only coexists with the worsening (debt) situation of the South but is sometimes to the detriment of the South’s financial detriment, whether directly or indirectly. E.g., vaccine availability and distribution were inconsistent and unevenly distributed, with only 2.3% of the COVID-19 vaccinations delivered globally being administered in the 30 countries with a humanitarian response plan; total humanitarian assistance, comprising contributions from both public and private donors, experienced only modest growth in 2021; in 2022, despite a 40% increase in funding to appeals, the marginal progress in meeting overall requirements led to a record-high funding shortfall (Development Initiatives 2023, p. 33). This raises the question of whether, had the North played a more significant role in assisting the South, it would have achieved such a rapid recovery (Balfour et al. 2022). With this uncertainty in mind, requiring future investigation, the following section reviews policy measures associated with reducing the external vulnerability of EMDE. 5.2. Tackling the COVID-19 Debt Hike The pandemic’s expansionist fiscal support prevented more severe economic contractions and larger job losses. However, many nations are currently grappling with elevated debt levels, increasing interest rates, and dimming growth forecasts. According to the IMF (2023a), the debt to GDP ratios worldwide are projected to grow by 1 percentage point (p.p.) annually from 2023 to 2028, surpassing the previous expectations prior to the pandemic (IMF 2023b). Debt crises in the EMDE were already a potential issue well before the pandemic and the onset of the polycrisis. The risk of a debt crisis is intensified by the constrained fiscal space in these countries, which is inadequate to support increased government spending during crises (Adarov et al. 2022). Additionally, the combined inability to attract private investment and the current tighter monetary policy measures aggravate the risk of recessions in developed countries, which could worsen the threat of debt crises (UNCTAD 2023). Drawing on historical precedent, Kose et al. (2022) divide debt reduction efforts into two distinct policy options: orthodox policies based on increased growth, fiscal consolidation, privatization, and wealth taxation; and heterodox options based on financial repression, inflation, and default, as well as debt restructuring. According to the orthodox view, the policy of promoting a level of growth greater than the rise in interest rates has aided several economies in reducing their debt stock in proportion to GDP. This has been occurring in several AE. However, relying solely on growth to decrease debt is risky because periods of strong development have historically been followed by rapid debt expansion in response to one-off shocks. Implementing fiscal consolidation as a policy approach, through expenditure cutbacks or revenue increases, can generate primary fiscal surpluses that countries use to repay Economies 2024,12, 42 16 of 26 debt. Nonetheless, given the magnitude of the required public finance interventions, fiscal consolidation may prove to be rather recessive since it would require countries that started the pandemic with already limited budgetary capacity to further strain their budgets. Furthermore, Menguy (2024) shows that a contractionary fiscal policy is more appropriate to ensure the sustainability of the long-term public debt, when the sensitivity of government expenditure to the public debt is high, and long-term labor and consumption taxation rates are high. Even though fiscal consolidation is considered a policy option to achieve the SDGs, Sachs et al. (2021) and Kose et al. (2022) caution about the trade-off between fiscal consolidation and the cost of slower growth. If one focuses the intervention on one-off measures, it must be recalled that in the past, revenues from the privatization of public assets have been used to reduce public debt. However, some of the necessary preconditions for realizing the privatization potential have not yet been implemented, despite the benefits it can bring to some EMDE, including debt reduction. Policy instruments such as wealth taxes, also known as capital taxes or equity taxes (taxes levied on an entity’s ownership of assets), can address concerns about unequal wealth distribution among countries, within individuals, and across generations. EMDE, however, suffer from major implementation hurdles when it comes to increasing revenues via wealth taxes (Kose et al. 2021), since they diminish the return on investment, discourage savings, and thus slow growth. As for heterodox policies, these include inflation, financial repression, default, and debt restructuring. While unanticipated inflation decreases the actual debt burden, it also has disadvantages as a debt reduction strategy since it would raise foreign currencydenominated external debt if coupled with exchange rate depreciation. Additionally, the high rate of inflation puts into question the credibility of the EMDE’s central banks’ achievements during the previous three decades. Moreover, under the current price pressure, “Relying on repeated inflation surprises to reduce public debt is not a viable strategy and will lead to spending pressures (for example, wages and cost of services).” (IMF 2022b). On the other hand, financial repression is a costly method of debt reduction since it discourages saving for productive purposes. Default and debt restructuring may be a country’s sole choices when confronted with foreign currency-denominated external debts. However, even a timely and orderly prepared debt restructuring, aimed at avoiding the higher costs associated with protracted debt crises (IMF 2021c), is a scenario that entails long-term consequences as well. Protracted negotiations prolong the loss of market access and may weaken the balance sheets of institutions, jeopardizing financial stability (Kose et al. 2022). In cases where sovereign debt is unsustainable or financing requirements are significant, it may be necessary to alleviate financial constraints in order to address debt vulnerabilities, for instance, through the assistance of initiatives that boost countries’ reserve assets via the General Allocation of Special Drawing Rights (IMF 2021c). All of the aforementioned debt-reduction strategies present several drawbacks: Inflation, financial repression, and debt restructuring all impose significant economic and social costs, while wealth taxes or growth-enhancing measures might confront technological, logistical, and political obstacles. Thus, the precise mix of possible choices will vary according to each country’s unique circumstances and the kind of debt involved. As long as debt difficulties in EMDE remain more severe than in AE and there is no quick road to debt relief, the danger of a growing disparity between AE and EMDE exists. The problems inherent in debt relief pose some concerns about global governance, namely how AE can effectively assist EMDE in overcoming debt burdens (Kose et al. 2021). Debt relief mechanisms must carefully consider the risk of creating expectations for future relief; moreover, addressing sovereign debt problems requires a sustained investment and economic growth strategy, alongside with responsible debt management policies and institutions (Ahiadorme 2023). Economies 2024,12, 42 17 of 26 Note that following the pandemic’s outbreak, several initiatives were put into practice to tackle these countries’ crisis repercussions. E.g., from April 2020 through the end of fiscal 2021, the World Bank provided more than USD 157 million to over 100 developing countries to fight the impacts of the pandemic (World Bank 2022); the G20 announced the Debt Service Suspension Initiative in April 2020; and the IMF also launched programs to channel resources from economically stronger members to countries where needs are greatest, such as the Poverty Reduction and Growth Trust and the Resilience and Sustainability Trust (IMF 2021c). But this may not be enough to handle sovereign debt overhangs in a post-pandemic economy, an exercise that will be particularly demanding for EMDE that hold high debt burdens, high interest rates, and tight margins for revenue and spending initiatives (IMF 2021c, p. 22). Nonetheless, as previously said, the international community must take a more proactive role in aiding these countries, including through debt restructuring and reclassification whenever necessary. Recent literature highlights the necessity for rich countries and creditor organizations to provide relief to heavily indebted nations, aiding them in fulfilling their debt repayment responsibilities during and after the pandemic (Ozili 2023). Complementing this perspective, Arellano et al. (2020) find strong evidence in favor of the implementation of debt relief programs. They find that these programs offer significant social benefits, enhancing health and economic conditions in the indebted country without incurring costs for international lenders or financial institutions. With regards to debt relief, SDG-17.4 identifies the special needs of promoting debt financing, debt relief, and debt restructuring, where appropriate, and assists Heavily Indebted Poor Countries (HIPC) in reducing financial distress. However, it is crucial to address the high likelihood of many HIPC defaulting due to the depreciation of their currencies, their substantial level of indebtedness, and their significant budget deficits, even if debt is suspended or postponed. Finally, delineating North–South cooperation initiatives does not diminish the relevance of South–South cooperation in terms of trade and development, which offers an opportunity for these countries to explore different paths to development that are more aligned with their unique contexts and challenges. This cooperation includes various forms of collaboration such as trade agreements, joint ventures, technology transfers, and shared development initiatives, as those related to education (Jules et al. 2023), health (de Moraes Achcar 2022) or agriculture (Shankland and Gonçalves 2016). This form of cooperation does not replace North–South relations but rather serves as a complementary approach that diversifies and enriches the global landscape of development and economic growth. 6. Conclusions This paper has delineated the context and consequences of heightened indebtedness arising from the pandemic, shedding light on potential divergences in debt dynamics between developed and developing economies. The findings highlight the necessity of implementing multifaceted measures to alleviate debt vulnerability. Two questions were addressed: (a) How has the indebtedness of emerging markets and developing economies changed during the COVID-19 pandemic when compared to advanced economies? The COVID-19 pandemic triggered significant shifts in global indebtedness, setting record highs due to the dire need for fiscal support, notably impacting EMDE compared to AE. The global economic landscape portrayed varying vulnerabilities during the pandemic. EMDE faced escalated external and public debt burdens, while AE primarily encountered amplified public debt due to fiscal stimuli in response to the crisis. Despite initial concerns, EMDE managed to navigate a potential rollover crisis while maintaining elevated debt levels. Firstly, in the AE, the response to the pandemic crisis caused an increase in public indebtedness by strengthening an already expansionist monetary policy and compelling central banks to ostensibly intervene to prevent interest rates from rising. Even so, the rapid growth in monetary aggregates associated with factors such as supply chain disruptions, rising energy prices, and ongoing global economic recovery efforts raised concerns about Economies 2024,12, 42 18 of 26 inflation, potentially leading to higher interest rates in the medium term, especially in light of the closing of the output gap. Secondly, according to the perspective of inflation, the macroeconomic manuals determine the increase in interest rates, thereby slowing down growth and pressing for an increase in the cost of debt service, both of which are capable of precipitating a financial crisis marked by high inflation and low growth (stagflation) for an extended period (considering the deflationary policies). Although generalized, this impact primarily affects the economies that are most vulnerable to their high levels of debt, including a few AE. Thirdly, the EMDE were already heavily indebted before the epidemic, and their debt load has continued to grow considerably. In contrast to the AE, the EMDE, and particularly the LIDC, lack the financial means to sustain reaction measures to COVID19’s consequences, and hence their development trajectory is likely to be delayed by at least a decade. Developing economies lack the budgetary flexibility necessary to support emergency actions and responses to COVID-19’s impacts, including the development of investment-led recovery plans aligned with the SDGs. Similarly, these countries have a restricted ability to finance themselves in the international market in comparison to highincome nations due to their poor credit quality in the market (measures to debt reduction). (b) Does this trajectory show the existence of a growing North–South divide? The economic North–South divide highlights a global economic system that increasingly favors the economically developed North over the South. The observed pattern in debt dynamics during the COVID-19 pandemic does suggest the widening of a North–South divide. AE, predominantly located in the Global North, managed to handle debt issues differently compared to EMDE, primarily situated in the Global South. The different impact of the pandemic on debt levels may further accentuate the pre-existing divide between these economic segments. It is imperative to take a comprehensive approach to understand the disparities between AE and EMDE debt dynamics. The observed differences, while they might be unfortunately anticipated, highlight the impact of the prevailing global capitalist socioeconomic system. To transform this model, it is necessary to examine alternative paradigms for economic organization, thus enhancing our overall comprehension of global dynamics. Addressing those debt vulnerabilities necessitates a tailored mix of measures, considering each country’s unique circumstances. Our work outlined orthodox and heterodox policies to debt reduction, emphasizing the challenges and drawbacks associated with each. The orthodox suggestions include growth-enhancing measures, fiscal consolidation, privatization of public assets, and wealth taxation. The heterodox policies to reduce debt consider engineering high inflation through fiscal and monetary policy; financial repression, involving capital controls and regulations within the financial sector, aiming to establish discrepancies between real interest rates and growth rates that significantly exceed what would be justified by risk considerations in market-based scenarios; and debt default and restructuring, once governments run out of other options. The research also touched on the need for international assistance and initiatives to support heavily indebted countries, highlighting the significance of debt relief programs. Regardless of the North–South connection, South–South cooperation in terms of trade and development remains extremely significant in terms of growth potential and the possibility for different development paths in the long run. Future research could extend the time frame of the study beyond 2015–2022 to assess the lasting impacts of the pandemic on global debt trends; explore alternative country classifications beyond the traditional AE and EMDE segmentation that only partially captures the diversity of contexts; and investigate the effectiveness of specific policy measures directed at debt reduction and economic recovery in the South. This essay examined the widening disparity between the economies of AE and EMDE in terms of indebtedness and debt sustainability, which has major economic consequences and, from there, a devastating effect on the human community. Within the heterodox perspective of economics and finance, there persists a dominant influence of market forces, Economies 2024,12, 42 19 of 26 accentuating competitive advantage, resource exploitation through capital migration, the diminishing practical value of labor, and the prevalence of strict rationalities within financial frameworks. Addressing this seemingly irreversible dominance of market forces necessitates proactive efforts from academics, politicians, professionals, and activists seeking a paradigm shift. This shift would not necessarily be antagonistic to the market but would explore corrective measures within the market. Author Contributions: Conceptualization: S.B. and M.L.V.; investigation: S.B., M.L.V. and F.R.; methodology: S.B. and M.L.V.; formal analysis: S.B.; writing—original draft: M.L.V.; writing—review and editing: S.B., M.L.V. and F.R. All authors have read and agreed to the published version of the manuscript. Funding: This research received no external funding. Data Availability Statement: The data sources are listed in Table A1. Conflicts of Interest: The authors declare no conflicts of interest. Appendix A Table A1. Data sources of dependent and control variables. Variable Description Source External debt to GDP (%) International Debt Statistics (World Bank 2023): External debt stocks, total (current USD) [DT.DOD.DECT.CD] & GDP (current USD) [NY.GDP.MKTP.CD] External debt (current USD) [supplementary when World Bank data is not available] Balance of Payments and International Investment Position (IMF 2023a): External debt (a) = Liabilities, Direct Investment, Debt Instruments [ILDD_BP6_USD] + Liabilities, Portfolio Investment, Debt Securities [ILPD_BP6_USD] + (Liabilities, Other Investment [ILO_BP6_USD] −Other Investment, Other Equity [ILOE_BP6_USD] Federal Reserve of St. Louis (supplementary where WB & IMF data n/a) https://fred.stlouisfed.org/ (accessed on 13 December 2023) Gross domestic product (current USD) World Economic Outlook (IMF 2023c): Gross domestic product, current prices (USD) [NGDPD] External debt to exports (%) International Debt Statistics (World Bank 2023): External debt stocks (% of exports of goods, services and primary income) [DT.DOD.DECT.EX.ZS] Exports (in current USD) [supplementary when World Bank data is not available] Balance of Payments and International Investment Position (IMF 2023a): Balance of Payments, Current Account, Goods and Services, Credit [BXGS_BP6_USD] + Primary Income, Credit [BXIP_BP6_USD] (current USD) Government debt to GDP (%) World Economic Outlook (IMF 2023c): General government gross debt (% of GDP) [GGXWDG_NGDP] General government net lending/borrowing (% of GDP) World Economic Outlook (IMF 2023c): General government net lending/borrowing (% of GDP) [GGXCNL_NGDP] General government primary net lending/borrowing (% of GDP) World Economic Outlook (IMF 2023c): Primary net lending/borrowing is net lending (+)/borrowing (−) plus net interest payable/paid (interest expense minus interest revenue) (% of GDP) [GGXONLB_NGDP] General government total revenue (% of GDP) World Economic Outlook (IMF 2023c): General government revenue (% of GDP) [GGR_NGDP] Total investment (% of GDP) World Economic Outlook (IMF 2023c): Total investment (% of GDP) [NID_NGDP] GDP per capita World Economic Outlook (IMF 2023c): Gross domestic product per capita, constant prices (Purchasing power parity; 2017 international dollar) [NGDPRPPPPC] Real GDP growth World Economic Outlook (IMF 2023c): Gross domestic product, constant prices (% year-on-year change) [NGDP_RPCH] Inflation World Economic Outlook (IMF 2023c): Inflation, average consumer prices (% year-on-year change) [PCPIPCH] Economies 2024,12, 42 20 of 26 Table A1. Cont. Variable Description Source Real effective exchange rate REER (CPI-based) with 170 trading partners (Darvas 2023) Trade openness = (exports + imports) to GDP Balance of Payments and International Investment Position (IMF 2023a): Current Account, Goods and Services, Debit, US Dollars [BXGS_BP6_USD) & Current Account, Goods and Services, Credit, US Dollars [BMGS_BP6_USD] Legend: (a) “External debt is not a separate component of the IIP but can be derived by summing the liability positions other than (1) financial derivatives (other than reserves) and ESOs [employee stock options], (2) equity and investment fund shares, and (3) other equity. These three liabilities are not debt instruments according to international statistical standards.” (IMF 2022a, p. 8). Table A2. Summary statistics for the control variables in AE. Variable Mean Median Std. Dev Max Min Observ. Fiscal indicators Gov. net lending/borrowing to GDP −1.75 −1.24 5.49 25.35 −41.99 312 Gov. primary net lending/borrowing −0.69 −0.15 4.86 23.88 −36.64 285 Gov. revenue to GDP 38.18 38.65 10.45 63.86 15.25 312 Macro Indicators Investment to GDP 22.18 22.62 5.90 54.77 −1.13 312 GDP per capita 50,149.58 47,653.76 16,926.40 125,279.30 26,526.08 312 GDP growth 2.14 2.46 5.55 24.48 −54.24 312 REER 102.21 98.10 13.45 134.15 78.05 280 Inflation rate 2.07 1.34 2.91 19.45 −1.54 312 Trade openness to GDP 125.01 104.01 80.29 402.46 23.61 298 Table A3. Summary statistics for the control variables in EMDE. Mean Median Std. Dev Max Min Observ. Fiscal indicators Gov. net lending/borrowing to GDP −3.36 −3.23 6.46 47.83 −55.41 1239 Gov. primary net lending/borrowing −1.95 −1.62 5.86 47.98 −55.41 1199 Gov. revenue to GDP 27.34 24.12 18.84 164.17 2.06 1236 Macro indicators Investment to GDP 24.50 23.46 9.16 79.40 −3.95 1065 GDP per capita 12,990.81 9988.47 13,478.07 101,000.90 386.49 1239 GDP growth 2.42 3.25 6.24 62.29 −33.36 1235 REER 125.84 108.55 197.45 6242.25 48.46 1116 Inflation rate 80.79 3.52 1945.63 65374.08 −44.36 1235 Trade openness to GDP 80.71 75.68 39.32 320.92 0.19 1145 Table A4. Correlation matrix for the control variables in AE. Gov. Net Balance Gov. Primary Net Gov. Revenue GDP Growth GDP per Capita Invest. Inflation REER Trade Open Gov. net lending/ borrowing to GDP 1.000 —— — — — — — — — Gov. primary net lending/borrowing 0.947 *** (0.000) 1.000 —— — — — — — — Gov. revenue to GDP 0.156 ** (0.011) 0.203 *** (0.001) 1.000 —— — — — — — GDP growth 0.329 *** (0.000) 0.381 *** (0.000) −0.145 ** (0.018) 1.000 —— — — — — GDP per capita 0.217 *** (0.000) 0.119 * (0.055) −0.132 ** (0.033) 0.195 *** (0.002) 1.000 —— — — — Investment to GDP 0.120 * (0.052) −0.013 (0.837) −0.182 *** (0.003) 0.137 ** (0.025) 0.373 *** (0.000) 1.000 —— — — Inflation rate 0.052 (0.400) 0.017 (0.782) 0.041 (0.506) 0.160 *** (0.009) 0.048 (0.436) 0.170 *** (0.006) 1.000 —— — Economies 2024,12, 42 21 of 26 Table A4. Cont. Gov. Net Balance Gov. Primary Net Gov. Revenue GDP Growth GDP per Capita Invest. Inflation REER Trade Open REER −0.083 (0.182) −0.141 ** (0.022) −0.375 *** (0.000) −0.051 (0.413) −0.105 * (0.088) 0.012 (0.843) 0.137 ** (0.026) 1.000 —— Trade openness 0.153 ** (0.013) 0.075 (0.223) −0.354 *** (0.000) 0.201 *** (0.001) 0.194 *** (0.002) 0.072 (0.246) 0.105 * (0.089) 0.262 *** (0.000) 1.000 — Notes: The p-values are in parenthesis. *, **, and *** indicate significance at the 10%, 5%, and 1% levels, respectively. Balanced sample (listwise missing value deletion) with 263 observations. Table A5. Correlation matrix for the control variables in EMDE. Gov. Net Balance Gov. Primary Net Gov. Revenue GDP Growth GDP per Capita Invest. Inflation REER Trade Open Gov. net lending/ borrowing to GDP 1.000 —— — — — — — — — Gov. primary net lending/borrowing 0.878 *** (0.000) 1.000 —— — — — — — — Gov. revenue to GDP 0.213 *** (0.000) 0.096 *** (0.003) 1.000 —— — — — — — GDP growth 0.211 *** (0.000) 0.200 *** (0.000) −0.103 *** (0.002) 1.000 —— — — — — GDP per capita −0.056 * (0.089) −0.164 *** (0.000) 0.344 *** (0.000) −0.030 (0.353) 1.000 —— — — — Investment to GDP −0.057 * (0.083) −0.106 *** (0.001) 0.072 ** (0.028) 0.099 *** (0.002) 0.115 *** (0.000) 1.000 —— — — Inflation rate −0.102 *** (0.002) −0.092 ** (0.005) −0.116 *** (0.000) −0.153 *** (0.000) −0.035 (0.277) −0.104 *** (0.001) 1.000 —— — REER −0.080 ** (0.014) −0.102 *** (0.002) −0.090 *** (0.006) −0.131 *** (0.000) −0.019 (0.566) −0.010 *** (0.002) 0.841 *** (0.000) 1.000 —— Trade openness 0.113 *** (0.001) 0.066 ** (0.044) 0.379 *** (0.000) 0.083 ** (0.011) 0.323 *** (0.000) 0.048 (0.144) −0.101 *** (0.002) −0.040 (0.217) 1.000 — Notes: The p-values are in parenthesis. *, **, and *** indicate significance at the 10%, 5%, and 1% levels, respectively. Balanced sample (listwise missing value deletion) with 263 observations. Table A6. Cross-section dependence test (null hypothesis: no cross-section dependence) and unit root tests (null hypothesis: panel contains unit root) for EMDE (p-values). Cross-Section Dependence Panel Unit Root Test Common Unit Root Individual Unit Root n/a Pesaran CD LLC Breitung IPS F-ADF F-PP Hadri Debt External debt to GDP (ln) 0.000 *** 0.000 *** 1.000 0.949 0.991 0.000 *** 0.000 *** External debt to exports (ln) 0.000 *** 0.000 *** 1.000 0.957 0.999 0.019 *** 0.000 *** Gov. debt to GDP (ln) 0.000 *** 0.000 *** 1.000 0.973 0.999 0.000 *** 0.000 *** Fiscal Gov. net budget to GDP 0.000 *** 0.000 *** 0.125 0.556 0.374 0.000 *** 0.000 *** Gov. revenue to GDP (ln) 0.000 *** 0.000 *** 1.000 0.451 0.040 ** 0.000 *** 0.000 *** Macro Investment to GDP (ln) 0.000 *** 1.000 0.500 0.724 0.718 0.000 *** 0.000 *** GDP per capita (ln) 0.000 *** 0.000 *** 1.000 0.975 1.000 0.021 ** 0.000 *** GDP growth 0.000 *** 0.000 *** 0.000 *** 0.055 * 0.000 *** 0.000 *** 0.000 *** REER 0.000 *** 0.000 *** 1.000 0.861 0.272 0.000 *** 0.000 *** Inflation rate 0.000 *** 0.000 *** 1.000 0.999 1.000 0.915 0.000 *** Trade openness to GDP (ln) 0.000 *** 0.000 *** 1.000 0.920 0.997 0.001 *** 0.000 *** Notes: Pesaran cross-section dependence test ***, **, and * show cross-section dependence at 1%, 5%, and 10% significance levels, respectively, implying that 2nd generation unit root tests are more appropriate. Panel unit root tests ***, **, and * show stationarity at 1%, 5%, and 10% significance levels, respectively; tests for unit root in level; individual intercept and trend included in the test equation; automatic lag length selection based on Schwarz information criteria. Economies 2024,12, 42 22 of 26 Table A7. Cross-section dependence test (null hypothesis: no cross-section dependence) and unit root tests (null hypothesis: panel contains unit root) for AE (p-values). Cross-Section Dependence Panel Unit Root Test Common Unit Root Individual Unit Root n/a Pesaran CD LLC Breitung IPS F-ADF F-PP Hadri Debt External debt to GDP (ln) 0.000 *** 0.000 *** 0.105 0.568 0.589 0.000 *** 0.000 *** External debt to exports (ln) 0.000 *** 1.000 0.500 0.838 0.997 0.991 0.000 *** Gov. debt to GDP (ln) 0.000 *** 0.000 *** 0.441 0.894 0.999 0.985 0.000 *** Fiscal Gov. net budget to GDP 0.000 *** 0.000 *** 0.014 ** 0.651 0.801 0.040 * 0.000 *** Gov. revenue to GDP (ln) 0.008 *** 0.000 *** 1.000 0.435 0.081 * 0.000 *** 0.000 *** Macro Investment to GDP (ln) 0.000 *** 0.000 *** 0.984 0.865 0.978 0.114 0.000 *** GDP per capita (ln) 0.000 *** 0.000 *** 0.000 *** 0.718 0.952 0.431 0.000 *** GDP growth 0.000 *** 0.000 *** 0.000 *** 0.091 0.001 0.000 *** 0.000 *** REER 0.000 *** 0.000 *** 1.000 0.873 0.979 0.122 0.000 *** Inflation rate 0.000 *** 1.000 1.000 1.000 1.000 1.000 1.000 Trade openness to GDP (ln) 0.000 *** 0.000 *** 1.000 0.974 1.000 1.000 0.000 *** Notes: Pesaran cross-section dependence test ***, **, and * show cross-section dependence at 1%, 5%, and 10% significance levels, respectively, implying that 2nd generation unit root tests are more appropriate. Panel unit root tests ***, **, and * show stationarity at 1%, 5%, and 10% significance levels, respectively; tests for unit root in level; individual intercept and trend included in the test equation; automatic lag length selection based on Schwarz information criteria. Table A8. Results for the effect of the COVID-19 pandemic on debt indicators using GMM. Variable External Debt to GDP (ln) External Debt to Exp.(ln) Govt. Debt to GDP (ln) EMDE (1) AE (2) EMDE (3) AE (4) EMDE (5) AE (6) Post_covid (dummy) 0.171 *** (0.000) 0.042 *** (0.003) 0.322 *** (0.000) 0.023 (0.213) 0.284 *** (0.000) 0.121 *** (0.000) LN_DEBT (−1) 0.155 *** (0.000) 0.161 (0.162) 0.012 (0.919) 0.186 (0.113) −0.096 * (0.085) 0.279 *** (0.003) Instrumental variables Yes Yes Yes Yes Yes Yes Country FE Yes Yes Yes Yes Yes Yes Adjusted R-squared 0.988 0.998 0.902 0.964 0.977 0.991 Panel observations 787 u249 u736 u244 u804 u249 u Cross-sections included 123 35 115 35 125 36 Note: Estimation method: Panel GMM EGLS (cross-section weights). The p-values in parenthesis are based on cross-section weights (PCSE) standard errors and covariance (d.f. corrected). Legend: *, **, and *** indicate significance at the 10%, 5%, and 1% levels, respectively. The superscripts b and u in the number of observations stand for balanced and unbalanced panel observations. Table A9. Results of the effect of the post-COVID-19 period on debt indicators with countries categorized by debt ratios: Below the 2019 median (BM) and above the 2019 median (AM) countries. External Debt to GDP (ln) External Debt to Exp.(ln) Govt. Debt to GDP (ln) BM (1) AM (2) BM (3) AM (4) BM (5) AE (6) Constant 7.313 *** (0.000) 10.066 *** (0.000) 11.464 *** (0.000) 13.136 *** (0.000) 6.992 *** (0.000) 9.663 *** (0.000) Post_covid (dummy) 0.202 *** (0.000) 0.037 *** (0.000) 0.181 *** (0.000) 0.078 *** (0.000) 0.221 *** (0.000) 0.124 *** (0.000) Gov. net balance −0.002 (0.330) −0.007 *** (0.000) −0.012 *** (0.001) −0.007 *** (0.000) −0.016 *** (0.000) −0.009 *** (0.000) Gov. revenue (ln) 0.088 * (0.056) 0.059 (0.220) 0.284 ** (0.029) 0.084 * (0.082) 0.318 *** (0.000) 0.051 (0.242) Economies 2024,12, 42 23 of 26 Table A9. Cont. External Debt to GDP (ln) External Debt to Exp.(ln) Govt. Debt to GDP (ln) BM (1) AM (2) BM (3) AM (4) BM (5) AE (6) Investment (ln) 0.153 *** (0.000) −0.039 ** (0.025) 0.099 ** (0.016) 0.129 *** (0.000) −0.016 (0.519) −0.110 *** (0.000) GDP per capita (ln) −0.448 *** (0.000) −0.501 *** (0.000) −0.370 ** (0.023) −0.333 *** (0.000) −0.479 *** (0.000) −0.574 *** (0.000) GDP growth (%) −−0.000 (0.934) −0.004 *** (0.000) −0.002 (0.406) −0.005 *** (0.000) 0.001 * (0.074) 0.001 * (0.054) REER (index) −0.006 *** (0.000) −0.006 *** (0.000) −0.009 *** (0.000) −0.007 *** (0.000) −0.004 *** (0.000) −0.000 *** (0.000) Inflation (index) −0.002 * (0.067) −0.001 * (0.096) −0.002 (0.461) −0.002 ** (0.021) −0.001 * (0.076) 0.001 ** (0.017) Trade openness (ln) −0.024 (0.573) 0.056 (0.215) −0.848 *** (0.000) −1.013 *** (0.000) 0.066 * (0.069) 0.055 ** (0.034) Country FE Yes Yes Yes Yes Yes Yes Adjusted R-squared 0.967 0.991 0.913 0.978 0.953 0.983 Median 2019 56.817 165.164 48.954 Cross-sections included 77 81 72 78 76 85 Panel observations 563 u627 u534 u594 u575 u637 u Notes: Estimation method: Panel EGLS (cross-section weights). 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