A two-edged sword: The impact of public debt on economic growth-the case of Ethiopia

Yimer, Addis; Alemayehu Geda Fole Article A two-edged sword: The impact of public debt on economic growth-the case of Ethiopia Journal of Applied Economics Provided in Cooperation with: University of CEMA, Buenos Aires Suggested Citation: Yimer, Addis; Alemayehu Geda Fole (2024) : A two-edged sword: The impact of public debt on economic growth-the case of Ethiopia, Journal of Applied Economics, ISSN 1667-6726, Taylor & Francis, Abingdon, Vol. 27, Iss. 1, pp. 1-43, https://doi.org/10.1080/15140326.2024.2398908 This Version is available at: https://hdl.handle.net/10419/314292 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/ Journal of Applied Economics ISSN: (Print) (Online) Journal homepage: www.tandfonline.com/journals/recs20 A two-edged sword: the impact of public debt on economic growth—the case of Ethiopia Addis Yimer & Alemayehu Geda To cite this article: Addis Yimer & Alemayehu Geda (2024) A two-edged sword: the impact of public debt on economic growth—the case of Ethiopia, Journal of Applied Economics, 27:1, 2398908, DOI: 10.1080/15140326.2024.2398908 To link to this article: https://doi.org/10.1080/15140326.2024.2398908 © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. Published online: 13 Sep 2024. Submit your article to this journal Article views: 2975 View related articles View Crossmark data Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=recs20 RESEARCH ARTICLE A two-edged sword: the impact of public debt on economic growth—the case of Ethiopia Addis Yimer a and Alemayehu Geda b,c,d a Global Research and Evaluation Specialist, Global Research and Evaluation Unit, Save the Children International, Addis Ababa, Ethiopia; b Department of Economics, Addis Ababa University, Addis Ababa, Ethiopia; c Department of Economics, Bahir Dar University, Bahir Dar, Ethiopia; d African Export and Import Bank (Afreximbank), Cairo, Egypt ABSTRACT This study investigates the dynamic effects of public debt on economic growth in Ethiopia using annual data from 1980 to 2021. The results from the Autoregressive Distributed Lag (ARDL) modeling approach reveal that while public debt boosts investment and enhances growth in the short term, it hinders long-term growth. Additionally, debt servicing negatively impacts growth in both the short and long term by diverting vital resources from investment. Thus, public debt acts as a two-edged sword for Ethiopia’s economic growth. On one side, it finances infrastructure and other growth-stimulating projects; on the other, high debt levels can impede growth. To mitigate the adverse impacts of public debt, Ethiopia should implement prudent fiscal discipline, mobilize domestic revenue, manage debt efficiently, address its structural trade deficit, and prioritize needs to prevent misuse and corruption. This approach should also prioritize social spending and public investment while strategically transitioning from debt dependence. ARTICLE HISTORY Received 21 December 2023 Accepted 26 August 2024 KEYWORDS Public debt; Impact; economic growth; Ethiopia Debt is a two-edged sword. Used wisely and in moderation, it clearly improves welfare. But, when it is used imprudently and in excess, the result can be disaster. For a country, too much debt impairs the government’s ability to deliver essential services to its citizens. Cecchetti et al. (2011) 1. Introduction Public debt can have both positive and negative effects on economic growth, depending on how it is used and managed. On the positive side, public debt can be used to finance investments in infrastructure, education, and healthcare, which can contribute to longterm economic growth. For example, investments in transportation infrastructure can enhance the productivity of businesses and reduce transportation costs, while CONTACT Addis Yimer [email protected] Global Research and Evaluation Specialist, Global Research and Evaluation Unit, Save the Children International, Addis Ababa, Ethiopia JOURNAL OF APPLIED ECONOMICS 2024, VOL. 27, NO. 1, 2398908 https://doi.org/10.1080/15140326.2024.2398908 © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/ licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent. investments in education and healthcare can improve the quality of the workforce and lower healthcare costs. However, public debt can also burden the economy, as it requires a significant portion of the government’s revenue to be allocated towards interest payments. This, in turn, can diminish the amount of funding available for other crucial sectors, such as education, healthcare, and infrastructure. Thus, if public debt is not managed properly, it can have negative effects on economic growth. For instance, studies have found that public debt negatively impacts growth by crowding out private investments (see, e.g., Panizza & Presbitero, 2013; Reinhart & Rogoff, 2010; Woo & Kumar, 2015). It can also lead to an increase in the cost of borrowing for private businesses (see, e.g., Cecchetti et al., 2011; Clements et al., 2003; Pattillo et al., 2006; Woo & Kumar, 2015). In addition, high levels of public debt can lead to inflation, currency depreciation (devaluation), and other macroeconomic vulnerabilities, which can have a negative impact on the economy (see, e.g., Woo & Kumar, 2015). Private investment could also be adversely affected by the “debt overhang” problem if economic agents expect high public debt to mean future high taxes (Pattillo et al., 2006). In the case of Ethiopia, the country’s public debt is accumulating in large amounts due to increasing financing needs, both domestic and external shocks, and structural macroeconomic imbalances. In recent years, the debt-to-GDP ratio has reached 50.7% in 2021. This reached as high as 60% in 2018. While some of this debt has been used to finance infrastructure and other vital projects, there are concerns about the sustainability of the debt and its potential negative impact on economic growth. Bad governance, natural disasters, and emergencies such as conflicts, the climate crisis, and the COVID-19 pandemic further exacerbate the increasing public debt and the challenge of servicing it. The growing accumulation of debt could become unsustainable, resulting in difficulties with debt repayment and hindering growth, as well as impeding the achievement of other development goals. Understanding the pathways and nature of the relationship between public debt and economic growth in Ethiopia is more crucial than ever. This is particularly true as the government intensifies its efforts to transform the country into a middle-income nation by 2030. This transformation requires a sustainable method of financing its ambitions. This is because the causal relationship between sovereign debt variables and economic growth has direct policy implications, particularly on tax and investment choices – and consequently on economic growth (see Gómez-Puig & Sosvilla-Rivero, 2015, 2018). Therefore, it is important for policymakers to carefully analyze the relationship between debt and economic growth and take measures to manage the debt in a sustainable manner. This may include implementing fiscal reforms, increasing revenue generation, and improving debt management practices. By doing so, Ethiopia can ensure that public debt is effectively utilized to promote long-term economic growth and development. While numerous studies have examined the impact of public debt on economic growth in general (see, e.g., D’Andrea, 2022; de Soyres et al., 2022; Donayre & Taivan, 2017; Ewaida, 2017; Gómez-Puig et al., 2022; Huang et al., 2018; Mohsin et al., 2021), little has been done, however, to investigate this relationship in Ethiopia. This is consistent with the paucity of literature on the subject in Africa in general. In addition, the relationship between debt and economic growth is specific to each country and time 2A. YIMER AND A. GEDA period. Therefore, it is crucial to analyze the specific impact of public debt on economic growth in every country, including Ethiopia. While the few available country-case studies on Ethiopia provide valuable insights into the relationship between debt and growth in the country, their primary focus is on determining whether debt impacts growth in Ethiopia. However, they fail to address the policy-relevant question of how debt affects growth in the country, specifically the mechanisms through which debt affects growth. They also predominantly focused on the growth impact of the external component of public debt, disregarding the fact that domestic (or internal) debt constitutes approximately half of the total public debt. Furthermore, they also suffer from methodological and data-related problems (see, e.g., Alani, 2020; Gebrekidan, 2023; Getinet & Ersumo, 2020). Thus, this study complements previous research on Ethiopia and aims to address some of the gaps in the existing literature by conducting a comprehensive analysis of the relationship between debt and economic growth. The study examines the shortand long-term impacts of public debt on economic growth using a combination of theoretical approaches. Specifically, it focuses on analyzing the “crowding out” and “debt overhang” hypotheses. Based on this approach, the study aims to answer the following research questions: a) Does Ethiopia’s public debt have any effect on the country’s economic growth? b) If so, is the investment channel important? and c) How does this influence vary in the short run and the long run? Using annual data from 1980 to 2021, the study employs the autoregressive distributive lag (ARDL) modeling approach to address these questions. This study makes three major contributions to the literature on the debtgrowth nexus. First, it comprehensively investigates the dynamic effects of public debt on economic growth in Ethiopia from 1980 to 2021 using the Autoregressive Distributed Lag (ARDL) modeling approach. Unlike previous studies, this research distinguishes between the short-term and long-term impacts of public debt on economic growth, showing that public debt can enhance growth in the short term while hindering it in the long term. Additionally, this study integrates the effects of debt servicing on economic growth, offering a holistic view of public debt dynamics and revealing how debt servicing exacerbates negative growth impacts by diverting resources from critical investment areas. Second, the study contributes a novel policy-oriented analysis, offering tailored recommendations for Ethiopia’s economic framework. Researchers, policymakers, and economic analysts can benefit from these results: researchers gain a detailed case study for comparative analyses with other developing countries, policymakers can use the insights to design better fiscal and debt management policies, and economic analysts can forecast economic trends and advise on sustainable debt practices. For example, the findings highlight the dual role of public debt as both a catalyst for short-term investment-driven growth and a hindrance to long-term economic stability due to debt servicing burdens. By emphasizing the importance of prudent fiscal discipline, domestic revenue mobilization, efficient debt management to prevent misuse and corruption, and improved prioritization of investment needs, along with the critical importance of addressing the country’s structural trade deficit, this research provides actionable insights specifically designed to address Ethiopia’s unique economic challenges. Lastly, the study’s single-country focus on Ethiopia JOURNAL OF APPLIED ECONOMICS 3 allows for an in-depth analysis of local factors influencing public debt and economic growth. This detailed case study is valuable for other researchers as it can be contrasted with results from other nations, helping to build a broader understanding of debt dynamics in emerging economies. This focus enhances the specialized literature by offering a detailed, context-specific study that can inform more generalized theories and models of public debt and economic growth in developing regions. The remainder of the study is organized as follows: Section 2 briefly discusses the general outlook of public debt and economic growth in Ethiopia. Section 3 presents a review of the relevant literature. Section 4 discusses the methodology and data used. Section 5 presents the findings and discusses the results. Section 6concludes the study. 2. The outlook of public debt and economic growth in Ethiopia This section provides a brief overview of the general patterns and evolution of public debt and economic growth in Ethiopia from 1980 to 2021. However, it should be emphasized at the outset that the evolution of public debt and economic performance are closely connected to the dynamics of the political-economic landscape of the period being examined. For instance, political instability, as well as drastic policy changes and reversals, have characterized Ethiopia’s long political history (Geda & Degefe, 2005). Such political processes have a significant impact on the behavior of economic agents, macroeconomic balance and performance, domestic borrowing, and external financial flows to the country (Geda, 2008; Geda & Degefe, 2005). The analysis in this study focuses on two of the most recent regimes that the country has witnessed: the “Derg” (the military regime) and the Ethiopian People’s Revolutionary Democratic Front (EPRDF) regime. The period 1974–1991 corresponds to the Derg (military) regime. The Derg experimented with socialism, in which a centralized command system controlled all spheres of decision-making in the country (Geda, 2008). This period is characterized by the prolonged civil war between the Derg and the thenopposition parties, mainly the EPRDF and Eritrean People’s Liberation Front (EPLF), the war with Somalia, deliberate market and private sector repression policies, nationalization policies, and drought. These factors contributed to highly erratic economic performance during this period (Geda & Yimer, 2016). The second period, from 1991 to the present, began with the Tigray People’s Liberation Front (TPLF)-led Ethiopian People’s Revolutionary Democratic Front (EPRDF) taking power in 1991, militarily ousting the Derg. The regime supported free market policies and implemented market liberalization, as well as various reform programs (Geda, 2008; Geda & Yimer, 2016). However, this period has also been marked by numerous episodes of conflict. These include the war with Eritrea (1998–2000), the countrywide political unrest (2015–2018), sporadic ethnic-based conflicts in various parts of the country (mainly in the post-2018 period), and the Tigray war (November 2020–November 2022). Thus, the analysis in this study needs to be understood in the context of these two regimes and the events that characterize each period (see Yimer, 2024; Geda & Yimer, 2023 for details). 4A. YIMER AND A. GEDA 2.1. Public debt outlook in Ethiopia Figure 1 depicts the evolution of public debt (the sum of external and domestic debt) as a percentage of GDP in Ethiopia over the last four decades. As shown in Figure 1, the country has a high dependency on public debt. During the TPLF-led EPRDF period, there were some of the highest peaks, with an average of 69% of the domestic output. This is a significant increase from the 57% during the Derg regime (Figure 1). As of 2021, the public debt stood at 51% of the country’s GDP. In some years of the TPLF-led EPRDF regime, this rate has reached as high as 110 to 121% of GDP (Figure 1). 22.4 79.3 56.5 120.9 70.0 116.8 116.0 110.4 32.1 30.4 59.9 50.7 -3.0 5.0 13.0 21.0 29.0 37.0 45.0 53.0 61.0 69.0 77.0 85.0 93.0 101.0 109.0 117.0 125.0 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 The Derg regime The EPRDF regime Figure 1. Public debt outlook in Ethiopia (% of GDP), 1980–2021. Source: Authors’ computation based on the Ministry of Finance and Economic Development (MOFED) various years’ annual reports. -16 -14 -12 -10 -8 -6 -4 -2 0 2 4 6 8 10 12 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 Period's average = -0.2% Period's average = 5% The Derg regime The EPRDF regime Figure 2. Real per capita GDP growth in Ethiopia (1980–2021). Source: Authors’ computation based on National Bank of Ethiopia’s (NBE) various years’ annual reports. JOURNAL OF APPLIED ECONOMICS 5 2.2. Economic growth outlook in Ethiopia Figure 2 depicts the pattern of growth, as measured by real per capita GDP growth, over the last four decades. During the study period, i.e., 1980–2021, economic growth in Ethiopia had two distinct features, depending on the regime considered (Figure 2). During the Dreg regime, economic growth was very erratic (see Figure 2). Growth decelerated in 1981 before reaching a negative rate in 1982. The instability induced by the emerging new policies of the Derg, such as the nationalization policy, along with drought, the war with Somalia, and internal civil war, explain a significant portion of this decelerating and negative growth performance. Partly due to relative political stability and favorable weather conditions, a positive growth rate of 5.3% was recorded in 1983. In 1984 and 1985, growth decelerated quickly and reached − 5.2% and − 13.5%, respectively, primarily due to a devastating drought. Growth became positive again in 1986 and 1987, reaching 10.1% in the latter year. Following the intensified civil war and adverse weather conditions, economic growth turned negative again for each of the years between 1988 and 1991. Overall, growth during this period was very erratic and had a negative average of − 0.2%. In May 1991, the TPLF-led EPRDF came into power. Following a period of low economic activity and political uncertainty, growth remained negative in 1992 (−12.3%). Growth regained momentum and increased to 9.4% in 1993. Except for the three years, namely 1997, 1998, and 2003, where growth was negative (primarily due to drought in those years), the growth was hailed as impressive for most of the remaining period under the EPRDF. Other notable episodes of real GDP growth in the country include the deceleration of growth in 2006 and 2009, which occurred as a result of the contested election in 2005 and the global financial crisis in 2008/09. Partly due to the fall in commodity prices in 2011 and thereafter, growth decelerated in the successive years of 2011 and 2012. The political unrest in the country from 2015 through 2018 has also contributed to the slowdown of economic growth during the same period. In 2020, amidst the COVID-19 pandemic and the war in Tigray, economic growth slowed down but remained positive. Overall, growth during the post-Derg period has been quite good, with real GDP per capita growing by an average of 4.5% per year (Figure 2). The availability of internal and external debt financing explains a significant portion of this growth. Notwithstanding the strong economic growth and Ethiopia’s status as one of the fastest-growing economies in Africa, it still remains one of the poorest countries in the world, with a per capita income of US$ 835 in 2021 (World Bank, 2023b). Overall, during the study period, there seems to be a general negative correlation between public debt and economic growth, with a limited episode of positive association (Figure 3). This will be further examined econometrically in Section 3. 3. Review of literature There is no consensus on the effects of public debt on economic growth. The literature has identified various channels through which debt affects economic growth. The discussion in this section focuses on highlighting the theoretical and empirical literature that has broadly shaped the debt-growth literature and the relevant studies that have guided this study. 6A. YIMER AND A. GEDA 3.1. The theory The effects of public debt on economic growth can be broadly examined using three different theoretical growth models: classical and neoclassical growth theories, Keynesian and post-Keynesian growth theories, and endogenous (new) growth theories. Public debt is considered detrimental to long-term growth and economic development by the mainstream classical school (see, e.g., Mill, 1848; Ricardo, 1817; Smith, 1776). Under the principle of “laissez-faire,” in the neoclassical version of classical economics, proponents argue for limiting the role of the state to ensuring the proper operation of economic relations, such as maintaining the rule of law, national security, and diplomatic relations. According to this principle, the government is not permitted to interfere in the economy. They argue that economic resources are managed more inefficiently in the public sector compared to the private sector. Additionally, public debt diverts private capital from its productive function to non-productive uses, which has a negative impact on capital accumulation. This diversion of investment undermines long-term growth (Ricardo, 1817; Smith, 1776). Ricardo (1817), in his concept of Ricardian Equivalence, noted that government borrowing in the present requires future tax rates to be raised above the normal rate in order to repay the borrowed amount (see also Roberts, 1942; Shoup, 1957). This means that efforts to stimulate the economy by increasing public spending through debt financing will be ineffective. Taxpayers are aware that the repayment of the debt will ultimately have to be funded through future taxes. Because taxpayers save in order to pay the anticipated future taxes that will be imposed to finance the repayment of debt, this will offset the macroeconomic benefits of increased aggregate demand resulting from increased public spending (Barro, 1974, 1979, 1989; Churchman, 2001). Thus, in the classical school, public debt is regarded as a societal burden (Elmendorf & Mankiw, 1999; Kumar & Woo, 2010; Woo & Kumar, 2015). -15 -10 -5 0 5 10 15 0.0 20.0 40.0 60.0 80.0 100.0 120.0 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020 Total Public Debt (% of GDP) Real per capita GDP per growth ( %) Linear (Total Public Debt (% of GDP)) Linear (Real per capita GDP per growth ( %)) Real per capita GDP growth (%) Total public debt (% of GDP) Figure 3. Total public debt (% of GDP) and real per capita GDP growth in Ethiopia (1980–2021). Source: Authors’ computation based on growth data from NBE and debt data from MOFED’s various years’ annual reports. JOURNAL OF APPLIED ECONOMICS 7 4.2. The investment equation: the theoretical model and description of variables Taking into account the crucial role of investment in growth, many studies (see, e.g., Akram, 2015) suggest that it is important to analyse the relationship between public debt and investment as well. To do so, we will also estimate the following reduced-form equation of investment. kt¼γþX k j¼1 δjwtj þX p m¼1 θmpdtm þ�t(3) where γ denotes the intercept, kt represents investment at t time wtj is a vector of control variables, δj is a vector of the coefficients of control variables. The vector pdtm represents various public debt indicators, θm represents the vector of the coefficients of public debt indicators, and �t is the usual error term. To analyze the impacts of public debt on investment in Ethiopia, we used time series data from 1980 to 2021 (see Table B1 in Appendix B for the list of variables, their measurement, and the sources of data). Following the literature on the determinants of investment in general and the relationship between public debt and economic growth in particular, the investment equation in this study includes the following variables as regressors: the natural logarithm of per capita real GDP yð Þ, the natural logarithm of trade openness opð Þ, the natural logarithm of interest rate irð Þ, the natural logarithm of inflation infð Þ and two public debt indicators, the natural logarithm of total public debt pdð Þ and the natural logarithm of public debt service. Thus, by substituting the control variables in Equation (3), we can investigate the investment effects of debt using Equation (4) as shown below: kt¼αþβ1ytþβ2optþβ3irtþβ4inftþþβ5pdtþβ6pdstþ�t(4) 4.3. The econometric technique: the autoregressive distributed lag (ARDL) approach A number of cointegration techniques exist in the literature, including the Engle and Granger (1987), Johansen (1988), Johansen and Juselius (1990), Phillips and Hansen (1990), Gregory and Hansen (1996), Saikkonen and Lütkepohl (2000), Pesaran and Shin (1999), Pesaran et al. (1996), and Pesaran et al. (2001) ARDL approach. This study employs the ARDL approach advanced by Pesaran et al. (2001) to empirically examine the effects of debt on economic growth in Ethiopia for the period 1980–2021. The ARDL approach has several advantages over other cointegration techniques. First, it can be used regardless of whether the variables are integrated of order 0 (I(0)) or all integrated of order 1 (I(1)), or have a combination of these integration orders. Traditional approaches require that all series have identical orders of integration (Engle & Granger, 1987; Johansen & Juselius, 1990; Phillips & Hansen, 1990). The ARDL approach, however, will be inefficient in the presence of I(2) or higher-order series. Second, unlike other multivariate cointegration techniques (see, e.g., Johansen & Juselius, 1990), this method is relatively simple and allows for estimating a cointegration relationship using the ordinary least squares (OLS) method. Third, it is comparatively more robust and efficient in small samples comprising 30 to 80 observations (Pesaran et al., 2001). 14 A. YIMER AND A. GEDA In addition, traditional cointegration techniques may also encounter issues of endogeneity, whereas the ARDL technique typically yields unbiased estimates of the long-run model and valid t-statistics, even when the regressors are endogenous (Narayan & Smyth, 2005; Harris & Sollis, 2003; Pattichis, 1999; H. Pesaran & Shin, 1999; Pesaran et al., 1996, 2001). Furthermore, the appropriateness of using an ARDL model lies in the fact that it is based on a single-equation framework. ARDL cointegration estimates shortand longrun relationships simultaneously and provides unbiased and efficient estimates (H. Pesaran & Shin, 1999). An error correction model (ECM) can also be derived from an ARDL model through a simple linear transformation (H. Pesaran & Shin, 1999). As noted by H. Pesaran and Shin (1999), ECM combines short-term adjustments with longterm equilibrium while retaining long-term information. These advantages of the ARDL technique over other standard cointegration techniques justify its application in this study. The estimation procedure in the ARDL framework involves two steps. First, the existence of a long-run relationship between the variables of the model is tested by considering F-statistics, referred to as a “bound test.” If evidence of a long-run relationship is found, the ARDL method is used at the second stage to estimate the short-run and long-run parameters. Following M. Pesaran et al. (2001), the ARDL model in this study can be written as follows: yt¼αX p i¼1 γiytiþX k j¼1X qj i¼0 X0 j;tiβj;iþεt(5) An ARDL is a least squares regression that includes the lags of both the dependent variable (y) and the explanatory variables (the X’s) in Equation 5. ARDL models are typically represented as ARDL (p;q1;...;qh), where p represents the number of lags of the dependent variable, q1 represents the number of lags of the first explanatory variable, and qh represents the number of lags of the k-th explanatory variable. For an ARDL model written as Equation (5), some of the explanatory variables, Xj, may have no lagged terms in the model (qj¼0). These variables are referred to as static or fixed regressors. Explanatory variables with at least one lagged term are called dynamic regressors. To specify an ARDL model, we must first determine the number of lags for each variable to be included (i.e., specify ;q1;. . . ;qh) in the models. In this study, the optimal lag order of the ARDL is determined using the Schwarz Information Criterion (SIC). The SIC is particularly suitable for small sample sizes and offers a more concise specification compared to other information criteria in the literature (H. Pesaran & Pesaran, 2009). 4.3.1. Long-run relationships Since an ARDL model estimates the dynamic relationship between a dependent variable and explanatory variables, it is possible to transform the model into a long-run representation. This representation shows the long-run impact of changes in the explanatory variables, including public debt indicators, on the dependent variable in our models. The calculation of these estimated long-run coefficients, once the estimation is complete, is given by Equation (6) as: JOURNAL OF APPLIED ECONOMICS 15 θj¼αPqj i¼1^ βj;i 1Pp i¼1γi (6) 4.3.2. Cointegrating relationships The cointegrating regression from an ARDL model is obtained by transforming Equation (5) into differences and substituting the long-run coefficients from Equation (6) into the resulting equation, resulting in (7): Δyt¼  X p1 i¼1 γ� iΔytiþX k j¼1X qj1 i¼0 ΔX0 j;tiβ� j;i^ ϕECt1þεt(7) where ECt¼ytαPk j¼1X0 j;t^ θj; ^ ϕ¼1Pp i¼1^ γi; β� j;i¼Pqj j¼1βj;m 4.3.3. Bounds testing Using the cointegrating relationship form in Equation (7), Pesaran et al. (2001) provided a methodology for testing whether the ARDL model contains a level (or long-run) relationship between the dependent variable and the regressors. The Bounds test procedure transforms Equation (7) into the following representation: Δyt¼  X p1 i¼1 γ� iΔytiþX k j¼1X qj1 i¼0 ΔX0 j;tiβ� j;iρyt1αX k j¼1 X0 j;t1δjþεt(8) The test for the existence of level relationships is then simply a test of ρ¼0 δ1¼δ2¼. . . ¼δk¼0 (9) The coefficient estimates used in the test can be obtained from a regression using Equation (5) or can be estimated directly from a regression using Equation (8). The test statistic, based on Equation (9), has a distinct distribution under the null hypothesis (which assumes no level relationships). This distribution varies depending on whether the regressors are all I(0) or all I(1). Further, in both cases, the distribution is non-standard. M. Pesaran et al. (2001) provide critical values for cases where all regressors are I(0) and cases where all regressors are I(1). They suggest using these critical values as upper and lower bounds for the more typical cases where the regressors are a mixture of I(0) and I(1). At this stage, the order of integration of each variable should be determined before any inferences can be made. When the order of integration of all the variables is found to be I (1), the decision is made based on the upper critical bound. On the other hand, if all the series are I(0), then the decision is made based on the lower critical bound. If the F-statistic is higher than the upper bound critical value, we reject the null hypothesis (H_0) of no cointegration and conclude in favor of a long-run relationship. In contrast, if the F-statistic is below the lower critical bound, then we cannot reject the null hypothesis of no cointegration, indicating that there is no long-run relationship. However, if the F-statistic falls between the upper-bound and lower-bound critical values, the inference would be inconclusive. 16 A. YIMER AND A. GEDA The standard ordinary least squares (OLS) model calculates the coefficient covariance matrix assuming that there are no issues of autocorrelation or heteroskedasticity in the error terms (Geda & Yimer, 2016; White, 1980). If these assumptions do not hold, inferences based on the resulting error-correction model (ECM) will be invalid (Roecker, 1991; White, 1980; Wooldridge, 2000). However, heteroskedasticity and autocorrelation are common issues encountered in time series analysis. Thus, in such studies, it is important to estimate the coefficient covariance matrix under the assumption that errors are conditionally heteroskedastic and serially correlated (Newey & West, 1987). The resulting estimator for the coefficient covariance is the Heteroskedasticity and Autocorrelation Consistent Covariance (HAC) or Newey-West estimator. This procedure will only modify the standard errors of the estimated coefficients without altering the coefficients (Newey & West, 1987). This study has followed the procedure. Finally, a series of diagnostic tests are conducted to assess the robustness and reliability of the ARDL model. These tests include assessing the normality of the error term, checking for serial correlation and heteroscedasticity, and verifying the functional form of the empirical model. All of the models that have been reported have passed these tests. The models reported here are, thus, the best models that we came up with after experimenting by estimating various models with different specifications, data points, and a battery of diagnostic tests. In this study, two versions of the growth and investment equations are estimated. The first model uses the total public debt stock variable, while the second model disaggregates the total public debt stock variable into external public debt and domestic public debt in both the growth and investment equations. The ARDL specification of the models used to investigate the effects of public debt on economic growth and the public debtinvestment nexus can be written as follows: Δyt¼αþβ1yt1þβ2popgt1þβ3kt1þβ4opt1þβ5gct1þβ6pdt1þβ7pdst1 þX p1 i¼0 γ1iΔpopgtiþX p2 i¼0 γ2iΔktiþX p3 i¼0 γ3iΔopt1þX p4 i¼0 γ4iΔgcti þX p5 i¼0 γ5iΔpdtiþX p6 i¼0 γ6iΔpdstiþεt (10) Δyt¼αþβ1yt1þβ2popgt1þβ3kt1þβ4opt1þβ5gct1þβ6epdt1 þβ7dpdt1β8pdst1þX p1 i¼0 γ1iΔpopgtiþX p2 i¼0 γ2iΔktiþX p3 i¼0 γ3iΔopt1 þX p4 i¼0 γ4iΔgctiþX p5 i¼0 γ5iΔepdtiX p6 i¼0 γ6iΔdpdtiþX p7 i¼0 γ7iΔpdstiþεt (11) JOURNAL OF APPLIED ECONOMICS 17 Δkt¼αþβ1kt1þβ2yt1þβ3opt1þβ4irt1þβ5inft1þβ6pdt1þβ7pdst1X p1 i¼0 γ1iΔyti þX p2 i¼0 γ2iΔopt1þX p3 i¼0 γ3iΔirtiþX p4 i¼0 γ4iΔinftiþX p5 i¼0 γ5iΔpdti þX p6 i¼0 γ6iΔpdstiþ�t (12) Δkt¼αþβ1kt1þβ2yt1þβ3opt1þβ4irt1þβ5inft1þβ6epdt1þβ7dpdt1 þβ8pdst1X p1 i¼0 γ1iΔytiþX p2 i¼0 γ2iΔopt1þX p3 i¼0 γ3iΔirtiþX p4 i¼0 γ4iΔinfti þX p5 i¼0 γ5iΔepdtiþþX p6 i¼0 γ6iΔdpdtiþX p7 i¼0 γ7iΔpdstiþ�t (13) 5. Discussion of results In this section, we will begin by presenting the pre-estimation tests that were conducted. The estimated model results are then presented, along with a test to assess the robustness of these results. 5.1. The econometric results Before conducting econometric estimation, a test for the stationarity of the variables is performed (Table 1, with reported p-values). The results indicate that most of the variables are I(1), while others are I(0) (Tables 1). Table 1. ADF unit-root test results. Variable Level First difference InferenceIntercept Intercept & trend Intercept Intercept & trend y0.99 0.92 0.00 0.00 I(1) k0.38 0.14 0.00 0.00 I(1) popg 0.00 0.00 0.00 0.00 I(0) h0.82 0.13 0.04 0.08 I(1) op 0.53 0.12 0.00 0.00 I(1) gc 0.47 0.31 0.00 0.00 I(1) ir 0.22 0.46 0.00 0.00 I(1) inf 0.00 0.00 0.00 0.00 I(0) pd 0.10 0.17 0.00 0.00 I(1) epd 0.30 0.30 0.00 0.00 I(1) dpd 0.11 0.17 0.00 0.00 I(1) pds 0.66 0.91 0.06 0.00 I(1) Note: All the variables are as defined previously (see also for Table B1 in the Appendix). 18 A. YIMER AND A. GEDA After determining the order of integration in the variables of our empirical model, as given in Equations (10)–(13), the bounds test for cointegration is conducted using the appropriate lag length. One of the most important issues in applying the ARDL approach is choosing the order of the distributed lag functions. 8 The results from the bounds test for the four models estimated in this study (i.e., two for the growth and two for the investment models) are presented in Tables 2. Based on the bounds test for cointegration shown in Table 2, the null hypothesis of no long-run relationship among the variables in the respective models (i.e., the growth and investment models) is rejected. This is because the computed F-statistic for the test equation is greater than the upper-bound critical value even at the one-percent level of significance for both the growth and the investment models. Table 2. The bound-test to cointegration. Method: ARDL Bounds Test Sample: 1980–2021 Null Hypothesis: No long-run relationships exist Test Statistic Value k Model 1 (Eq. 10) The growth model (Total public debt variable used as a regressor) F-statistic 6.37 7 Significance I0 Bound I1 Bound 10% 2.12 3.23 5% 2.45 3.61 1% 3.15 4.43 Model 2 (Eq. 11) The growth model (External public debt and domestic public debt replace total public debt as regressors.) F-statistic 7.84 7 Significance I0 Bound I1 Bound 10% 2.38 3.45 5% 2.69 3.83 1% 3.31 4.63 Model 3 (Eq. 12) The investment model (Total public debt variable used as a regressor) F-statistic 5.16 6 Significance I0 Bound I1 Bound 10% 2.12 3.23 5% 2.45 3.61 1% 3.15 4.43 Model 4 (Eq. 13) The investment model (External public debt and domestic public debt replace total public debt as regressors.) F-statistic 6.12 7 Significance I0 Bound I1 Bound 10% 2.38 3.45 5% 2.69 3.83 1% 3.31 4.63 Note: In Model 1, the cointegration test equation includes the dependent variable yð Þ and the following regressors: pd, pds, popg, k, op, and gc. In Model 2, pd is replaced by its components, epd and dpd, while keeping all other variables in Model 1 unchanged. In Model 3, the cointegration test equation includes the dependent variable (k) and the following regressors: pd, pds, ir, inf, and op. In Model 4, pd is replaced by its components, epd and dpd, while keeping all other variables in Model 3 unchanged. All the variables are as defined previously and also in Table B1 in Appendix B. Pesaran et al. (2001) critical values for the bounds test are used and reported. 8 Since we have a small data sample (42 annual observations), SIC is the criterion used for choosing lag lengths. M. Pesaran et al. (2001) showed that SIC is preferable to other lag-length selection criteria because it is suitable for small sample sizes. JOURNAL OF APPLIED ECONOMICS 19 5.1.1. The growth effect: the long-run and short-run models results This section aims to answer the question, “Does public debt affect economic growth in Ethiopia?”, and presents the results of the estimated models for this exercise. Specifically, the estimation results for Equations (10) and (11) are discussed (see Tables 3 and 4). Table 3 presents the estimated results of the growth model specified in Eq. (10), in which total public debt and public debt service are used as indicators of the debt variable. The results show that public debt has a significant negative effect on real output per capita in the long run. However, its short-run effect can be both negative and positive, depending on the time lag. Table 3. The short run and long run model result: the growth model (Equation 10.) Model: ARDL Cointegrating and Long Run Form Sample: 1980 2021 The short run model (Error Correction Model (ECM)) result Dependent Variable: Δ ln real GDP per capita Selected Model: ARDL(3, 1, 1, 2, 2, 2, 2) Variable Coefficient Standard error Prob. Δ(ln real GDP per capita(−1)) −0.20** 0.06 0.01 Δ(ln real GDP per capita(−2)) −0.82*** 0.09 0.00 Δ(ln population growth) −0.19*** 0.04 0.00 Δ(ln gross capital formation as % of GDP) 0.16*** 0.04 0.00 Δ(ln government consumption as % of GDP) 0.01 0.04 0.90 Δ(ln government consumption as % of GDP(−1)) −0.07*** 0.04 0.00 Δ(ln openness) 0.09* 0.04 0.07 Δ(ln openness(−1)) −0.08** 0.03 0.03 Δ(ln total public debt as % of GDP) −0.14*** 0.04 0.00 Δ(ln total public debt as % of GDP(−1)) 0.14** 0.05 0.03 Δ(ln public debt service as % of exports) −0.02*** 0.03 0.08 Δ(ln public debt service as % of exports(−1)) −0.02*** 0.02 0.00 Δ(Regime dummy) −0.08*** 0.01 0.00 EC(−1) −0.25*** 0.05 0.00 The long run model result Dependent Variable: ln real GDP per capita ln population growth −1.72** 0.64 0.02 ln gross capital formation as % of GDP 0.88** 0.28 0.01 ln government consumption as % of GDP −0.08 0.15 0.58 ln trade openness 0.69*** 0.14 0.00 ln total public debt as % of GDP −0.93*** 0.19 0.00 ln public debt service as % of exports −0.17*** 0.02 0.00 Regime dummy −0.30*** 0.06 0.00 Constant 6.81*** 0.62 0.00 @trend 0.0004 0.0013 0.77 Model diagnostic tests Test statistic Value R-squared 0.99 Adjusted R-squared 0.99 F-statistic 28.11 Jarque - Berra 2.55 Prob(Jarque - Berra) 0.28 Breusch-Godfrey Serial Correlation LM Test♣0.23 Heteroskedasticity Test: ARCH ♣ 0.82 Ramsey RESET Test ♣ 0.71 Note: Δ denotes change and ***, **, * indicates 1 %, 5% and 10% level of significance respectively. EC is the adjustment coefficient (the error correction term). ♣ in the diagnostic tests indicates that the P-value for the F-Statistics is reported. 20 A. YIMER AND A. GEDA Debt service is found to have a significant negative effect in both the long run and the short run. However, when compared to the short run, the magnitude of the effect is found to be stronger in the long run (Table 3). In Ethiopia, high public debt service payments can have a negative effect on economic growth in both the short run and the long run, especially when the government’s fiscal space is limited. As a result of high debt service payments, the government has less room to maneuver when dealing with economic downturns, which can result in reduced public investment, lower productivity, and slower economic growth. Moreover, the government may sometimes rely on Table 4. The short run and long run model result: the growth model (Equation 11.) Method: ARDL Cointegrating And Long Run Form Sample: 1980 2021 The short run model (Error Correction Model (ECM)) result Dependent Variable: Δ ln real GDP per capita Selected Model: ARDL(3, 2, 1, 1, 2, 0, 2, 2) Variable Coefficient Standard error Prob. Δ(ln real GDP per capita(−1)) −0.02 0.07 0.82 Δ(ln real GDP per capita(−2)) −0.80*** 0.11 0.00 Δ(ln population growth) −0.25*** 0.04 0.00 Δ(ln population growth (−1)) 0.16** 0.05 0.01 Δ(ln gross capital formation as % of GDP) 0.20*** 0.01 0.00 Δ(ln government consumption as % of GDP) 0.04* 0.02 0.06 Δ(ln openness) 0.02 0.01 0.30 Δ(ln openness(−1)) −0.09*** 0.01 0.00 Δ(ln external public debt as % of GDP) −0.13*** 0.01 0.00 Δ(ln domestic public debt as % of GDP) 0.05*** 0.01 0.00 Δ(ln domestic public debt as % of GDP (−1)) 0.20*** 0.02 0.00 Δ(ln public debt service as % of exports) 0.01 0.03 0.74 Δ(ln public debt service as % of exports (−1)) −0.07*** 0.02 0.00 Δ(Regime dummy) −0.05*** 0.01 0.00 EC(−1) −0.31*** 0.02 0.00 The long run model result Dependent Variable: ln real GDP per capita ln population growth −2.30*** 0.32 0.00 ln gross capital formation as % of GDP 0.79*** 0.06 0.00 ln government consumption as % of GDP −0.40*** 0.06 0.00 ln openness 0.44*** 0.10 0.00 ln external public debt as % of GDP −0.42*** 0.02 0.00 ln domestic public debt as % of GDP −0.33** 0.12 0.02 ln public debt service as % of exports −0.25*** 0.01 0.00 Regime dummy −0.17*** 0.03 0.00 Constant 6.18*** 0.34 0.00 @trend 0.007 0.005 0.17 Model diagnostic tests Test statistic Value R-squared 0.99 Adjusted R-squared 0.99 F-statistic 46.22 Prob(F-statistic) 0.39 Jarque - Berra 0.39 Prob(Jarque - Berra) 0.82 Breusch-Godfrey Serial Correlation LM Test ♣ 0.24 Heteroskedasticity Test: ARCH ♣ 0.11 Ramsey RESET Test ♣ 0.72 Note: Δ denotes change and ***, **, * indicates 1 %, 5% and 10% level of significance respectively. EC is the adjustment coefficient (the error correction term). ♣ in the diagnostic tests indicates that the P-value for the F-Statistics is reported. JOURNAL OF APPLIED ECONOMICS 21 increased taxation to service its debt, which can reduce consumer and business confidence, thereby lowering economic growth in both the short run and the long run. Finally, in Ethiopia, high public debt service payments often lead to inflationary pressures. If the government prints more currency to finance its domestic debt service obligations, this can lead to inflation, which can further reduce economic growth in the long run. Table 4 presents the estimated results of the growth model given in Eq. (11), specifically the growth model with a disaggregated public debt variable. The results show that public debt can have both negative and positive effects, depending on the sources of borrowing and the time period considered. As shown in Table 4, the analysis reveals that external debt has a detrimental impact on the real per capita output of the country, both in the short and long run, while domestic debt is found to have a positive effect on economic growth in the short run, but its long-run effect is negative. Similar to our earlier finding in the previous model (Table 3), we find that debt servicing has a significant negative effect on the real per capita output of the country, both in the short run and the long run (Table 4). Based on the results presented in Tables 3 and 4, the estimated coefficient for the error-correction term (EC) is significant in both specifications. This finding suggests that, as noted by Banerjee et al. (1998), a significant negative coefficient for the errorcorrection term provides additional evidence of a stable long-term relationship among the variables used in the model. With regard to the control variables, the results of both models are generally consistent with the findings of previous studies on economic growth. For instance, in the long run, population growth and government consumption have a negative impact on real per capita output. On the other hand, gross capital formation and trade openness have a significant positive impact on the country’s per capita output. These findings on the control variables align with the results of existing literature and are consistent with expectations, as they have extensive empirical support (see, for example, Yimer, 2023a, 2024). In summary, the short-run negative effects of public debt on real per capita output may be due to the necessity of diverting resources away from productive activities in order to service the debt. While the positive results on public debt flows suggest that public debt can help stimulate economic growth through capital formation. A similar result has been found in other studies conducted in different countries (see, e.g., Akram, 2015; Mohamed, 2013). The long-run negative effect of public debt on per capita GDP aligns with the widely held view that public debt has a detrimental impact on economic growth (see, e.g., Table A1 in Appendix A for further details). A battery of model diagnostic tests was applied to assess the robustness of the estimated models. The tests indicate that the estimated models have the desired statistical properties (see Tables 3 and 4). Both models have a good fit. In addition, the models successfully passed a battery of tests, including tests for normality, heteroskedasticity, serial correlation, model specification, and stability. The Jarque-Bera statistic confirms the normality of the residuals, as the null hypothesis that “errors are normally distributed” is not rejected in each of the specifications of the growth model. Based on the results of the Breusch-Godfrey Lagrange Multiplier (LM) test and the Autoregressive Conditional Heteroskedasticity (ARCH) test, we do not have enough evidence to reject 22 A. YIMER AND A. GEDA the null hypotheses of no serial correlation and no heteroscedasticity of the residuals, respectively. Thus, there are no issues of serial correlation or heteroskedasticity in the estimated models. The Ramsey Regression Equation Specification Error Test (RESET) supports the null hypothesis of the correct functional form (Tables 3 and 4). Model parameter stability is one of the requirements for a well-specified and performing ARDL model (Murthy & Okunade, 2016). The stability of the regression coefficients is evaluated through stability tests, which can determine whether the regression equation remains stable over time (H. Pesaran & Pesaran, 2009). To assess the stability of the estimated coefficients, we conducted cumulative sum (CUSUM) and cumulative sum of squares (CUSUMSQ) tests on the recursive residuals derived from the estimated ARDL models for each specification of the growth equation, i.e., Equations 10 and 11. As depicted in Figures 4 and 5, the plots of the CUSUM and CUSUMSQ statistics both fall within the critical bounds at the 5% significance level and do not cross the lower and upper critical limits in any of the estimated models. This indicates that the estimated coefficients exhibit the desired characteristics of parameter stability throughout the entire sample period of the estimated model. With regard to the robustness check, the estimated baseline growth models were examined to assess the robustness of the results. Although the results from such exercises are not reported here, alternative specifications using different sets of control variables of the estimated models have shown that the findings are robust across different Figure 4. Parameter stability tests: the growth model reported in Table 3. Figure 5. Parameter stability tests: the growth model reported in Table 4. JOURNAL OF APPLIED ECONOMICS 23 ORCID Addis Yimer http://orcid.org/0000-0002-9494-2386 Availability of data and materials All data analyzed in this study are available on request from the authors. References Abiad, A., & Mody, A. (2005). Financial reform: What shakes it? what shapes it? The American Economic Review, 95(1), 66–88. https://doi.org/10.1257/0002828053828699 Adamu, I. M., & Rasiah, R. (2016). External debt and growth dynamics in Nigeria. African Development Review, 28(3), 291–303. https://doi.org/10.1111/1467-8268.12206 Adegbite, E. O., Ayadi, F. S., & Felix Ayadi, O. (2008). The impact of Nigeria’s external debt on economic development. International Journal of Emerging Markets, 3(3), 285–301. https://doi. org/10.1108/17468800810883693 Aguiar, M., Amador, M., & Gopinath, G. (2009). Investment cycles and sovereign debt overhang. Review of Economic Studies, 76(1), 1–31. https://doi.org/10.1111/j.1467-937X.2008.00523.x Ahlborn, M., & Schweickert, R. (2018). Public debt and economic growth–economic systems matter. International Economics & Economic Policy, 15, 373–403. https://doi.org/10.1007/ s10368-017-0396-0 Aizenmana, J., Pinto, B., & Radziwill, A. (2007). Sources for financing domestic capital – is foreign saving a viable option for developing countries? Journal of International Money & Finance, 26 (5), 682–702. https://doi.org/10.1016/j.jimonfin.2007.04.009 Akram, N. (2011). Impact of public debt on the economic growth of Pakistan. Pakistan Development Review, 50(4), 599–615. Akram, N. (2015). Is public debt hindering economic growth of the Philippines? International Journal of Social Economics, 42(3), 202–221. https://doi.org/10.1108/IJSE-02-2013-0047 Alani, J. (2020). Intertemporal government budget constraint: Debts and economic growth in Ethiopia, 1990–2018. MPRA Paper 103180. University Library of Munich. Amann, J., & Middleditch, P. (2020). Revisiting Reinhart and Rogoff after the crisis: A time series perspective. Cambridge Journal of Economics, 44(2), 343–370. https://doi.org/10.1093/cje/ bez009 Amin, A. A., & Audu, I. (2006). External debt, investment and economic growth: Evidence from Nigeria. CBN Economic and Financial Review, 44(1), 88–113. Arčabić, V., Tica, J., Lee, J., & Sonora, R. J. (2018). Public debt and economic growth conundrum: nonlinearity and inter-temporal relationship. Studies in Nonlinear Dynamics & Econometrics, 22 (1), 20160086. https://doi.org/10.1515/snde-2016-0086 Asteriou, D., Pilbeam, K., & Pratiwi, C. (2021). Public debt and economic growth: Panel data evidence for Asian countries. Journal of Economics & Finance, 45(2), 270–287. https://doi.org/ 10.1007/s12197-020-09515-7 Augustine, B., & Rafi, O. P. C. M. (2023). Public debt - economic growth nexus in emerging and developing economies: Exploring nonlinearity. Finance Research Letters, 52(103540), 103540. https://doi.org/10.1016/j.frl.2022.103540 Baldacci, E., & Kumar, M. (2010). Fiscal deficits, public debt and sovereign bond yields. IMF Working Paper, WP/10/184. International Monetary Fund. Banerjee, J., Dolado, J., & Mestre, R. (1998). Error-correction mechanism tests for cointegration in single-equation framework. Journal of Time Series Analysis, 19(3), 267–283. https://doi.org/10. 1111/1467-9892.00091 Barik, A., & Sahu, J. P. (2022). The long-run effects of public debt on economic growth: Evidence from India. Journal of Public Affairs, 22(1), e2281. https://doi.org/10.1002/pa.2281 30 A. YIMER AND A. GEDA Barro, R. J. (1974). Are government bonds net wealth? Journal of Political Economy, 82(6), 1095–1117. https://doi.org/10.1086/260266 Barro, R. J. (1979). On the determination of public debt. Journal of Political Economy, 87(5, part 1), 240–271. https://doi.org/10.1086/260807 Barro, R. J. (1989). The Ricardian approach to budget deficits. Journal of Economic Perspectives, 3 (2), 37–54. https://doi.org/10.1257/jep.3.2.37 Barro, R. J. (1990). Government spending in a simple model of endogenous growth. Journal of Political Economics, 98(5/2), 103–125. https://doi.org/10.1086/261726 Barro, R. J., & Sala-I-Martin, X. (1997). Technological diffusion, convergence, and growth. Journal of Economic Growth, 2(1), 1–26. https://doi.org/10.1023/A:1009746629269 Baum, A., Checherita-Westphal, C., & Rother, P. (2013). Debt and growth: New evidence for the euro area. Journal of International Money & Finance, 32, 809–821. https://doi.org/10.1016/j. jimonfin.2012.07.004 Blanchard, O. J. (1985). Debt, deficits, and finite horizons. Journal of Political Economy, 93(2), 223–247. https://doi.org/10.1086/261297 Blanchard, O., & Perotti, R. (2002). An empirical characterization of the dynamic effects of changes in government spending and taxes on output. Quarterly Journal of Economics, 177 (4), 1329–1368. https://doi.org/10.1162/003355302320935043 Bosworth, B., & Collins, S. M. (2003). The empirics of growth: An update. Brookings Papers on Economic Activity, 34(2), 113–206. https://doi.org/10.1353/eca.2004.0002 Brida, J. G., Gómez, D. M., & Seijas, M. N. (2017). Debt and growth: A non-parametric approach. Physica A: Statistical Mechanics and its Applications, 486, 883–894. https://doi.org/10.1016/j. physa.2017.05.060 Butkus, M., & Seputiene, J. (2018). Growth effect of public debt: The role of government effectiveness and trade balance. Economies, 6(4), 62. https://doi.org/10.3390/economies6040062 Calderón, C., & Fuentes, R. J. (2013). Government debt and economic growth. IDB working paper, series, No. IDB-WP-424. Cecchetti, S. G., Mohanty, M. S., & Zampolli, F. (2011). The real effects of debt. Bank for International Settlements (BIS) Working Paper. No. 352. Bank for International Settlements. Chen, C., Yao, S., Hu, P., & Lin, Y. (2017). Optimal government investment and public debt in an economic growth model. China Economic Review, 45, 257–278. https://doi.org/10.1016/j.chieco. 2016.08.005 Chiu, Y. B., & Lee, C. C. (2017). On the impact of public debt on economic growth: does country risk matter?. Contemporary Economic Policy, 35(4), 751–766. https://doi.org/10.1111/coep. 12228 Chowdhury, A. R. (2001). Foreign debt and growth in developing countries. Paper presented at WIDER Conference on Debt Relief, United Nations University, Helsinki. Chudik, A., Mohaddes, K., Pesaran, M. H., & Raissi, M. (2017). Is there a debt-threshold effect on output growth? The Review of Economics and Statistics, 99(1), 135–150. https://doi.org/10.1162/ REST_a_00593 Churchman, N. (2001). David Ricardo on public debt. Palgrave. Clements, B., Bhattacharya, R., & Nguyen, T. Q. (2003). External debt, public investment, and growth in low-income countries. IMF Working Paper No. 03/249. International Monetary Fund. Coccia, M. (2017). Asymmetric paths of public debt and of general government deficits across countries within and outside the European monetary unification and economic policy of debt dissolution. Journal of Economic Asymmetries, 17, 17–31. https://doi.org/10.1016/j.jeca.2016.10.003 D’Andrea, S. (2022). A meta-analysis on the debt-growth relationship. MPRA Paper 114409. University Library of Munich. Davidson, P. (1996). Reality and economic theory. Journal of Post Keynesian Economics, 18(4) (Summer, 1996): 479–508. https://doi.org/10.1080/01603477.1996.11490083 Dell’erba, S., Hausmann, R., & Panizza, U. (2013). Debt levels, debt composition, and sovereign spreads in emerging and advanced economies. Oxford Review of Economic Policy, 29(3), 518–547. https://doi.org/10.1093/oxrep/grt026 JOURNAL OF APPLIED ECONOMICS 31 Deshpande, A. (1990). The debt overhang and the disincentive to invest. Journal of Development Economics, 52(1), 169–187. https://doi.org/10.1016/S0304-3878(96)00435-X de Soyres, C., Kawai, R., & Wang, M. (2022). “Public debt and real GDP: Revisiting the impact. IMF Working Paper WP/22/76. International Monetary Fund. De Vita, G., Trachanas, E., & Luo, Y. (2018). Revisiting the bi-directional causality between debt and growth: Evidence from linear and nonlinear tests. Journal of International Money & Finance, 83, 55–74. https://doi.org/10.1016/j.jimonfin.2018.02.004 Diamond, P. (1965). National debt in a neoclassical growth model. The American Economic Review, 55(5), 1126–1150. Doğan, İ., & Bilgili, F. (2014). The non-linear impact of high and growing government external debt on economic growth: A Markov Regime-switching approach. Economic modelling, 39, 213–220. https://doi.org/10.1016/j.econmod.2014.02.032 Dombi, A., & Dedák, I. (2019). Public debt and economic growth: What do neoclassical growth models teach us? Applied Economics, 51(29), 3104–3121. https://doi.org/10.1080/00036846. 2018.1508869 Donayre, L., & Taivan, A. (2017). Causality between public debt and real growth in the OECD: A country-by-country analysis. Economic Papers, 36(2), 156–170. https://doi.org/10.1111/17593441.12175 Eberhardt, M., & Presbitero, A. F. (2015). Public debt and growth: Heterogeneity and non-linearity. Journal of International Economics, 97(1), 45–58. https://doi.org/10.1016/j.jin teco.2015.04.005 Eisner, R. (1989). Budget deficits: Rhetoric and reality. Journal of Economic Perspectives, 3(2), 73–93. https://doi.org/10.1257/jep.3.2.73 Elbadawi, I., Ndulu, B., & Ndung’u, N. (1997). Debt overhang and economic growth in SubSaharan Africa. In Z. Iqbal & R. Kanbur (Eds.), External finance for low-income countries (pp. 49–76). International Monetary Fund. Elmendorf, D. W., & Mankiw, G. N. (1999). Government debt. In J. B. Taylor & M. Woodford (Eds.), Handbook of macroeconomics, edition 1 (Vol. 1, chapter 25, pp. 1615–1669). Elsevier. Engen, E. M., & Hubbard, R. G. (2005). Federal government debt and interest rates,” NBER chapters. In M. Gertler & K. Rogoff (Eds.), NBER macroeconomics annual 2004 (Vol. 19, pp. 83–160). MIT Press. Engle, R., & Granger, C. (1987). Co-integration and error correction: Representation, estimation and testing. Econometrica, 55(2), 251–276. https://doi.org/10.2307/1913236 Esteve, V., & Tamarit, C. (2018). Public debt and economic growth in Spain, 1851–2013. Cliometrica, 12(2), 219–249. https://doi.org/10.1007/s11698-017-0159-8 Ewaida, H. Y. M. (2017). The impact of sovereign debt on growth: An empirical study on GIIPS versus JUUSD countries. European Research Studies Journal, XX(2A), 607–633. https://doi.org/ 10.35808/ersj/662 Fosu, A. K. (1999). The external debt burden and economic growth in the 1980s: Evidence from Sub-Saharan Africa. Canadian Journal of Development Studies / Revue Canadienne d’études du Développement, 20(2), 307–318. https://doi.org/10.1080/02255189.1999.9669833 Gebrekidan, A. (2023). “The impact of external debt on economic growth in Ethiopia”. Ethiopian Economic Association. Geda, A. (2008). The political economy of growth in Ethiopia. In B. Ndulu, S. A. O’Connell, J. Azam, R. H. Bates, A. K. Fosu, J. W. Gunning, & D. Njinkeu (Eds.), The political economy of growth in Africa: 1960–2000 (pp. 116–142). Cambridge University Press. Geda, A., & Alemu, G. (2023). Institutional aspect of the debt and debt management challenges in Ethiopia. Research Paper. International Development Research Center (IDRC). Geda, A., & Degefe, B. (2005). Conflict, post-conflict and economic performance in Ethiopia. In A. K. Fosu & P. Collier (Eds.), Post-conflict economies in Africa (pp. 125–142). Palgrave Macmillan. Geda, A., & Yimer, A. (2016). Capital flight and its determinants: The case of Ethiopia. African Development Review, 28(S1), 39–49. https://doi.org/10.1111/1467-8268.12180 Geda, A., & Yimer, A. (2023). Fundamental and proximate drivers of public debt in Ethiopia. Research paper. International Development Research Center (IDRC). 32 A. YIMER AND A. GEDA Getinet, B., & Ersumo, F. (2020). The impact of public external debt on economic growth in Ethiopia: The ARDL approach to co-integration. Journal of Economics & Sustainable Development, 11(11), 2020. Gómez-Puig, M., & Sosvilla-Rivero, S. (2015). The causal relationship between public debt and economic growth in EMU countries. Journal of Policy Modelling, 37(6), 974–989. https://doi. org/10.1016/j.jpolmod.2015.09.004 Gómez-Puig, M., & Sosvilla-Rivero, S. (2018). On the time-varying nature of the debt-growth nexus: Evidence from the euro area. Applied Economics Letters, 25(9), 597–600. https://doi.org/ 10.1080/13504851.2017.1349284 Gómez-Puig, M., Sosvilla-Rivero, S., & Martínez-Zarzoso, I. (2022). On the heterogeneous link between public debt and economic growth. Journal of International Financial Markets, Institutions and Money, 77, 101528. https://doi.org/10.1016/j.intfin.2022.101528 Gordon, L. B., & Cosimo, M. (2018). Government debt in EMU countries. Journal of Economic Asymmetries, 18(C), 1–14. https://doi.org/10.1016/j.jeca.2018.e00096 Gregory, A., & Hansen, B. (1996). Residual-based tests for cointegration in models with regime shifts. Journal of Econometrics, 70(1), 99–126. https://doi.org/10.1016/0304-4076(69)41685-7 Harris, R., & Sollis, R. (2003). Applied time series modelling and forecasting. Wiley. Heimberger, P. (2022). Do higher public debt levels reduce economic growth? Journal of Economic Surveys. https://doi.org/10.1111/joes.12536 Herndon, T., Ash, M., & Pollin, R. (2014). Does high public debt consistently stifle economic growth? A critique of Reinhart and Rogoff. Cambridge Journal of Economics, 38(2), 257–279. https://doi.org/10.1093/cje/bet075 Hilton, S. K. (2021). Public debt and economic growth: Contemporary evidence from a developing economy. Asian Journal of Economics and Banking, 5(2), 173–193. https://doi.org/10.1108/ AJEB-11-2020-0096 Huang, Y., Panizza, U., & Varghese, R. (2018). Does public debt crowd out corporate investment? International evidence. Working Paper No. HEIDWP08-2018. The Graduate Institute of International Studies. Iamsiraroj, S. (2016). The foreign direct investment–economic growth nexus. International Review of Economics & Finance, 42(C), 116–133. https://doi.org/10.1016/j.iref.2015.10.044 Imbs, J., & Romain, R. (2005). The overhang hangover. Policy research working paper series 3673. The World Bank. Intartaglia, M., Antoniades, A., & Bhattacharyya, S. (2018). Unbundled debt and economic growth in developed and developing economies: an empirical analysis. World Economy, 41(12), 3345– 3358. https://doi.org/10.1111/twec.12626 Islam, N. (1995). Growth empirics: A panel data approach. Quarterly Journal of Economics, 110(4), 1127–1170. https://doi.org/10.2307/2946651 Jafarov, E., Maino, R., & Pani, M. (2020). Financial repression is knocking at the door, again. should we be concerned?. IMF Working Paper, WP/19/211. International Monetary Fund. Johansen, S. (1988). Statistical analysis of cointegration vectors. Journal of Economic Dynamics and Control, 12(2–3), 231–254. https://doi.org/10.1016/0165-1889(88)90041-3 Johansen, S., & Juselius, K. (1990). Maximum likelihood estimation and inference on cointegration– with applications to the demand for money. Oxford Bulletin of Economics and Statistics, 52 (2), 169–210. https://doi.org/10.1111/j.1468-0084.1990.mp52002003.x Josten, S. D. (2000). Public debt policy in an endogenous growth model of perpetual youth. FinanzArchiv, 57(2), 197–215. Kalecki, M. (1954). Theory of economic dynamics. George Allen & Unwin. Karadam, D. Y. (2018). An investigation of nonlinear effects of debt on growth. Journal of Economic Asymmetries, 18, e00097. https://doi.org/10.1016/j.jeca.2018.e00097 Kempa, B., & Khan, N. S. (2017). Spillover effects of debt and growth in the euro area: Evidence from a GVAR model. International Review of Economics & Finance, 49, 102–111. https://doi. org/10.1016/j.iref.2017.01.024 Kim, E., Ha, Y., & Kim, S. (2017). Public debt, corruption and sustainable economic growth. Sustainability, 9(3), 433. https://doi.org/10.3390/su9030433 JOURNAL OF APPLIED ECONOMICS 33 Kraay, A., & Nehru, V. (2006). When is external debt sustainable? The World Bank Economic Review, 20(3), 341–365. https://doi.org/10.1093/wber/lhl006 Krugman, P. (1988). Financing vs. forgiving a debt overhang. Journal of Development Economics, 29(3), 253–268. https://doi.org/10.1016/0304-3878(88)90044-2 Kumar, M. S., & Woo, J. (2010). Public debt and growth. IMF Working Paper no. WP/10/174. International Monetary Fund. Lavoie, M. (2006). A post-Keynesian amendment to the new consensus on monetary policy. Metroeconomica, 57(2), 165–192. https://doi.org/10.1111/j.1467-999X.2006.00238.x Lee, S., Park, H., Seo, M. H., & Shin, Y. (2017). Testing for a debt‐threshold effect on output growth. Fiscal studies, 38(4), 701–717. https://doi.org/10.1111/1475-5890.12134 Levine, R., & Renelt, D. (1992). A sensitivity analysis of cross-country growth regressions. The American Economic Review, 82(4), 942–963. Liaqat, Z. (2019). Does government debt crowd out capital formation? A dynamic approach using panel VAR. Economics Letters, 178, 86–90. https://doi.org/10.1016/j.econlet.2019.03.002 Lim, J. J. (2019). Growth in the shadow of debt. Journal of Banking and Finance, 103(C), 98–112. https://doi.org/10.1016/j.jbankfin.2019.04.002 Lo, S., & Rogoff, K. S. (2015). Secular stagnation, debt overhang and other rationales for sluggish growth, six years on. BIS Working Papers 482. Bank for International Settlements (BIS). Maitra, B. (2019). Macroeconomic impact of public debt and foreign aid in Sri Lanka. Journal of Policy Modeling, 41(2), 372–394. https://doi.org/10.1016/j.jpolmod.2019.03.002 Makun, K. (2021). External debt and economic growth in pacific island countries: A linear and nonlinear analysis of Fiji Islands. Journal of Economic Asymmetries, 23, e00197. https://doi.org/ 10.1016/j.jeca.2021.e00197 Manassea, P., & Roubinib, N. (2009). Rules of thumb’ for sovereign debt crises. Journal of International Economics, 78(2), 192–205. https://doi.org/10.1016/j.jinteco.2008.12.002 Mankiw, N. G., Romer, D., & Weil, D. (1992). A contribution to the empirics of economic growth. Quarterly Journal of Economics, 107(2), 407–437. https://doi.org/10.2307/2118477 Mill, J. S. (1848). Principles of political economy. Augustus M. Kelley1976. Modigliani, F. (1961). Long-run implications of alternative fiscal policies and the burden of the national debt. The Economic Journal, 71(284), 730–755. https://doi.org/10.2307/2228247 Mohamed, B. M. (2013). Assessing the short‐ and long‐run real effects of public external debt: The case of Tunisia. African Development Review, 25(4), 587–606. https://doi.org/10.1111/1467-8268.12054 Mohsin, M., Ullah, H., Iqbal, N., Iqbal, W., & Taghizadeh-Hesary, F. (2021). How external debt led to economic growth in South Asia: A policy perspective analysis from quantile regression. Economic Analysis & Policy, 72, 423–437. https://doi.org/10.1016/j.eap.2021.09.012 Murthy, V., & Okunade, A. (2016). Determinants of US health expenditure: Evidence from autoregressive distributed lag (ARDL) approach to cointegration. Economic Modelling, 59, 67–73. https://doi.org/10.1016/j.econmod.2016.07.001 Narayan, P., & Smyth, R. (2005). Electricity consumption, employment and real income in Australia evidence from multivariate Granger causality tests. Energy Policy, 33(9), 1109–1116. https://doi.org/10.1016/j.enpol.2003.11.010 Newey, W., & West, K. (1987). A simple positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix. Econometrica, 55(3), 703–708. https://doi.org/10.2307/1913610 Obstfeld, M., & Rogoff, K. (1996). Foundations of international macroeconomics. MIT Press. Owusu-Nantwi, V., & Erickson, C. (2016). Public debt and economic growth in Ghana. African Development Review, 28(1), 116–126. https://doi.org/10.1111/1467-8268.12174 Panizza, U., & Presbitero, A. F. (2013). Public debt and economic growth in advanced economies: A survey. Swiss Journal of Economics and Statistics, 149(2), 175–204. https://doi.org/10.1007/ BF03399388 Pattichis, C. (1999). Price and income elasticities of disaggregated import demand: Results from UECMS and application. Journal of Applied Econometrics, 31(9), 1061–1071. https://doi.org/10. 1080/000368499323544 Pattillo, C., Poirson, H., & Ricci, L. (2006). External debt and growth. IMF Working Paper WP/02/ 69. International Monetary Fund. 34 A. YIMER AND A. GEDA Pegkas, P. (2018). The effect of government debt and other determinants on economic growth: The Greek experience. Economies, 6(1), 10. https://doi.org/10.3390/economies6010010 Pegkas, P. (2019). Government debt and economic growth. A threshold analysis for Greece. Peace Economics Peace Science and Public Policy, 25(1). https://doi.org/10.1515/peps-2018-0003 Perotti, R. (1999). Fiscal policy in good times and bad. Quarterly Journal of Economics, 114(4), 1399–1436. https://doi.org/10.1162/003355399556304 Pesaran, H., & Pesaran, B. (2009). Time series econometrics using microfit 5. Oxford University Press. Pesaran, H., & Shin, Y. (1999). An autoregressive distributed-lag modeling approach to cointegration analysis Chapter 11. Econometrics and economic theory in the 20th century: the ragnar frisch centennial symposium. Econometric Society Monographs (pp. 371–413). Cambridge: Cambridge University Press. Pesaran, M., Shin, Y., & Smith, R. (1996). Testing for the existence of a long run relationship. DAE Working Paper, No. 9622. Pesaran, M., Shin, Y., & Smith, R. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3), 289–326. https://doi.org/10.1002/jae.616 Phillips, P., & Hansen, B. (1990). Statistical inference in instrumental variables regression with I(1) processes. Review of Economic Studies, 57(1), 99–125. https://doi.org/10.2307/2297545 Presbitero, A. F. (2012). Total public debt and growth in developing countries. European Journal of Development Research, 24(4), 606–626. https://doi.org/10.1057/ejdr.2011.62 Ramos-Herrera, M. D. C., & Sosvilla-Rivero, S. (2017). An empirical characterization of the effects of public debt on economic growth. Applied Economics, 49(35), 3495–3508. https://doi.org/10. 1080/00036846.2016.1262522 Reinhart, C. M., Reinhart, V. R., & Rogoff, K. S. (2012). Public debt overhangs: Advanced-economy episodes since 1800. Journal of Economic Perspectives, 26(3), 69–86. https://doi.org/10.1257/jep.26.3.69 Reinhart, C. M., & Rogoff, K. S. (2010). Growth in a time of debt. The American Economic Review, 100(2), 573–578. https://doi.org/10.1257/aer.100.2.573 Reinhart, C. M., Rogoff, K. S., & Savastano, M. (2003). Debt intolerance. Brookings Papers on Economic Activity, 34(1), 1–74. https://doi.org/10.1353/eca.2003.0018 Ricardo, D. (1817). On the principles of political economy and taxation. In P. Sraffa (Ed.), The works and correspondence of David Ricardo (Vol. 1, pp. 1–220). Cambridge University Press, 1951. Roberts, R. O. (1942). Ricardo’s theory of public debts. Economica, 9(35), 257–266. https://doi.org/ 10.2307/2549539 Roecker, E. B. (1991). Prediction error and its estimation for subset-selection models. Technometrics, 33(4), 459–468. https://doi.org/10.1080/00401706.1991.10484873 Romer, P. M. (1994). The origins of endogenous growth. Journal of Economic Perspectives, 8(1), 3–22. https://doi.org/10.1257/jep.8.1.3 Sachs, J. D. (1989). Developing country debt and economic performance, volume 1: The international financial system. National Bureau of Economic Research, Inc. Sachs, J. D. (2002). Resolving the debt crisis of low-income countries. Brooking Papers on Economic Activity, 2002(1), 257–286. https://doi.org/10.1353/eca.2002.0013 Saikkonen, P., & Lütkepohl, H. (2000). Testing for the cointegrating rank of a VAR process with structural shifts. Journal of Business & Economic Statistics, 18(4), 451–464. https://doi.org/10. 1080/07350015.2000.10524884 Saint-Paul, G. (1992). Fiscal policy in an endogenous growth model. Quarterly Journal of Economics, 107(4), 1243–1259. https://doi.org/10.2307/2118387 Sala-I-Martin, X. (1997). I just ran two million regressions. The American Economic Review, 87(2), 178–183. Sala-I-Martin, X., Doppelhofer, G., & Miller, R. I. (2004). “Determinants of long-term growth: A bayesian averaging of classical estimates (BACE) approach. The American Economic Review, 94 (4), 813–835. https://doi.org/10.1257/0002828042002570 Sandow, J. N., Oteng-Abayie, E. F., & Duodu, E. (2022). External debt and economic growth in Sub-Saharan Africa: Does heterogeneity in the quality of public sector management make a difference? Heliyon, 8(9), e10627. https://doi.org/10.1016/j.heliyon.2022.e10627 JOURNAL OF APPLIED ECONOMICS 35 Schclarek, A. (2004). Debt and economic growth in developing and industrial countries. Working Papers. Lund University. Shahor, T. (2018). The impact of public debt on economic growth in the Israeli economy. Israel Affairs, 24(2), 254–264. https://doi.org/10.1080/13537121.2018.1429547 Sharaf, M. F. (2021). The asymmetric and threshold impact of external debt on economic growth: New evidence from Egypt. Journal of Business and Socio-Economic Development, 2(1), 1–18. https://doi.org/10.1108/JBSED-06-2021-0084 Shoup, C. S. (1957). Ricardo and taxation. FinanzArchiv/Public Finance Analysis, 18(1), 13–24. Siddique, A., Selvanathan, E. A., & Selvanathan, S. (2016). The impact of external debt on growth: Evidence from highly indebted poor countries. Journal of Policy Modeling, 38(5), 874–894. https://doi.org/10.1016/j.jpolmod.2016.03.011 Smith, A. (1776). The wealth of nations. Strahan and T. Cadell. Solow, R. M. (1956). A contribution to the theory of economic growth. Quarterly Journal of Economics, 70(1), 65–94. https://doi.org/10.2307/1884513 Solow, R. M. (1957). Technical change and the aggregate production function. The Review of Economics and Statistics, 39(3), 312–320. https://doi.org/10.2307/1926047 Spiro, P. S. (1988). The effects of government debt and deficits on interest rates. Business Economics, 23(4), 39–46. Sutherland, A. (1997). Fiscal crises and aggregate demand: Can high public debt reverse the effects of fiscal policy? Journal of Public Economics, 65(2), 147–162. https://doi.org/10.1016/S00472727(97)00027-3 Tchereni, B. H. M., Sekhampu, T. J., & Ndovi, R. F. (2013). The impact of foreign debt on economic growth in Malawi. African Development Review, 25(1), 85–90. https://doi.org/10. 1111/j.1467-8268.2013.12015.x Todaro, P. M., & Smith, S. C. (2006). Economic development (9th ed.). Pearson Education, Harlow. Villanueva, D. P. (1972). Public debt, ‘efficient’ labour, and growth: Comment. Journal of Money, Credit, and Banking, 4(4), 1016–1018. https://doi.org/10.2307/1991243 Were, M. (2001). The impact of external debt on economic growth in Kenya. UNU-WIDER Research Paper, 116. DP. White, H. (1980). A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroscedasticity. Econometrica, 48(4), 817–838. https://doi.org/10.2307/1912934 Woo, J., & Kumar, M. S. (2015). Public debt and growth. Economica, 82(328), 705–739. https://doi. org/10.1111/ecca.12138 Wooldridge, J. M. (2000). Introductory econometrics: A modern approach. South-Western College Publishing. World Bank. (2023a). International debt statistics. The World Bank Group. World Bank. (2023b). World development indicators. The World Bank Group. Yimer, A. (2023a). The effects of FDI on economic growth in Africa. The Journal of International Trade & Economic Development, 32(1), 2–36. https://doi.org/10.1080/09638199.2022.2079709 Yimer, A. (2023b). When does FDI make a difference for growth? A comparative analysis of resource-rich and resource-scarce African economies. International Finance, 26(1 Spring), 82–110. https://doi.org/10.1111/infi.12423 Yimer, A. (2024). Foreign direct investment, spillovers, and productivity: Firm-level evidence from Ethiopia. Canadian Journal of Development Studies. Yimer, A., & Geda, A. (2023). The impact of public debt on economic growth in Ethiopia. Working paper. Department of Economics, Addis Ababa University. Zouhaier, H., & Fatma, M. (2014). Debt and economic growth. International Journal of Economics and Financial Issues, 4(2), 440–448. 36 A. YIMER AND A. GEDA Appendices Appendix A. An overview of empirical literature on the effects of public debt on economic growth Table A1. An overview of empirical literature on the effects of public debt on economic growth. Author Scope Debt type Method Effect on growth Linear Non-linear (Threshold effect) Developing countries Sandow et al. (2022) 31 sub-Sahara African (SSA) countries (2005–2017) External debt System generalized method of moments (SGMM) and panel smooth transition regression (PSTR) Negative 45% of GDP Mohsin et al. (2021) South Asian countries, (Afghanistan, Bangladesh, Bhutan, India, Pakistan, Sri Lanka, Maldives, and Nepal) (2000–2018) External debt Panel ordinary least square, fixed effect, Quantile regression, and robust output regression were used to analyze the World Bank data from 2000 to 2018. South Asian countries, Negative Maitra (2019) Sri Lanka (1977–2016) External debt ARDL Negative Adamu and Rasiah (2016) Nigeria (1970–2013) External debt ARDL Negative Owusu-Nantwi and Erickson (2016) Ghana (1970–2012) External debt t Johansen cointegration and Vector Error Correction Model (VECM) Positive Siddique et al. (2016) 40 heavily indebted poor countries (HIPCs) (1970-2007) External debt ARDL Negative Doğan and Bilgili (2014) Turkey (1974–2009) External debt Markov Regime-switching approach Negative Zouhaier and Fatma (2014) 19 developing countries (1990-2011) External debt Dynamic panel regression (Arellano‐Bond estimator) Negative Mohamed (2013) Tunisia (1970–2010) External debt Engel and Granger error correction model (ECM) Negative >30% of GDP Tchereni et al. (2013) Malawi (1975–2003) External debt zero Adegbite et al. (2008) Nigeria (1975–2005) External debt OLS and generalized least squares (GLS) Negative Pattillo et al. (2006) 93 developing (1969–1998) External debt OLS; Instrumental variables (IV); FE; and SGMM Negative 35–40% of GDP Clements et al. (2003) 55 low‐income countries (1970–1999) External debt Fixed effects (FE) & SGMM Negative >35% of GDP Fosu (1999) 35 sub-Saharan Africa (SSA) (1980– 1990) External debt OLS Negative (Continued) JOURNAL OF APPLIED ECONOMICS 37 Table A1. (Continued). Author Scope Debt type Method Effect on growth Linear Non-linear (Threshold effect) Elbadawi et al. (1997) 99 developing countries spanning SSA, Latin America, Asia, and the Middle East External debt Cross-section Regression (Fixed and random effect) Negative Developed countries Liaqat (2019) 39 high income countries (1980–2017) Domestic debt Panel VAR Negative Pegkas (2019) Greece (1970–2016) Domestic debt Regression model with multiple thresholds 21%—50% & >90% of GDP De Vita et al., (2018) 10 EMU, US, UK and Japan (1970–2014) Domestic debt Granger causality & ARDL cointegration Negative Esteve and Tamarit (2018) Spain (1851–2013) Domestic debt Dynamic Ordinary Least Square (DOLS) No threshold Gómez-Puig and Sosvilla-Rivero (2018) Euro area countries (1961–2015) Domestic debt Panel ARDL Positive Shahor (2018) Israel (1983–2013) Domestic debt Undefined Pegkas (2018) Greece (1970–2016) Domestic debt ARDL & VAR >90% of GDP Amann and Middleditch (2020) United Kingdom (1995–2013) Domestic debt Granger causality & cointegration tests Negative Kempa and Khan (2017) 11 major Euro zone countries (1991–2014) Domestic debt Panel VAR zero Lee et al. (2017) Advanced economies (1946–2009) Domestic debt Median regression 21%—50% of GDP Panizzaa and Presbitero (2014) 17 developed OECD countries Public debt (Domestic debt & external debt) IV zero No threshold Reinhart and Rogoff (2010) (Continued) 38 A. YIMER AND A. GEDA Table A1. (Continued). Author Scope Debt type Method Effect on growth Linear Non-linear (Threshold effect) Mixed countries (Developing and Developed) Asteriou et al. (2021) 14 countries in Asia (1980–2012) Public debt (Domestic debt & external debt) Pooled mean group (PMG), mean group (MG), dynamic fixed effects (DFE) allowing for common correlated, and asymmetric panel Autoregressive Distributed Lag Model (ARDL) method Negative Lim (2019) 41 advanced & emerging economies (1952–2016) Total Debt (private & public debt) Panel VAR Negative Intartaglia et al. (2018) 48 developing & developed countries (1961–2015) Domestic debt Panel VAR Negative Arčabić et al. (2018) OECD & non-OECD countries (1960–2009) Domestic debt Panel VAR, FE, FE with IV, SGMM zero No threshold Butkus and Seputiene (2018) 152 countries (1996–2016) Domestic debt SGMM, Pooled OLS (POLS) & LSDV <20% & >90% of GDP Karadam (2018) 135 countries (1970–2012) Domestic debt PSTR 71%—90% & >90% of GDP Ramos-Herrera and Sosvilla-Rivero (2017) 115 developed & developing economies (1970–2013) Public debt (Domestic & external debt) Mean, median, winsorized mean & trimmed mean Negative Chudik et al. (2017) 40 countries (1965–2010) Domestic debt Panel ARDL Negative Ewaida (2017) Highly indebted countries in Euro & non-Euro zone (1993–2013) Domestic debt POLS Negative Kim et al. (2017) 77 countries (1990–2014) Domestic debt POLS, FE & SGMM No threshold Chiu and Lee (2017) 61 countries (1985–2009) Domestic debt PSTR Positive & Negative Brida et al. (2017) 16 countries in Euro & non-Euro (1977–2015) Domestic debt Minimal spanning tree & hierarchical tree 71%—90% of GDP Ahlborn & Schweickert (2018) 111 developing & developed economies (1971–2010) Domestic debt FE & 2SLS 51%—70% of GDP Chen et al. (2017) 65 developing & developed economies (1991–2014) Domestic debt PSTR 21%—50% of GDP (Continued) JOURNAL OF APPLIED ECONOMICS 39