Does Governance Affect Economic Growth? Evidence from SANE Countries

1. Introduction

The discussion on the relationship between governance and economic growth has captured the interest of academics, activists, development economists, international practitioners, development partners, development policy practitioners, civil society groups, political institutions, and policymakers. Poor governance is largely to blame for the economic and developmental issues of the SANE (South Africa, Algeria, Nigeria, and Egypt) economies. Lawbreaking, insecurity, corruption, nepotism, unemployment, abduction for ransom, religious extremism, and the rising level of poverty are all symptoms of bad government. According to the 2022 Transparency International corruption perceptions report, South Africa, Algeria, Nigeria, and Egypt (SANE) rank 72nd, 116th, 150th, and 130th out of 180 countries, respectively, due to their poor governance, which prevents them from prospering and luring investors. Their scores are 43, 33, 24, and 30, respectively. It makes sense that the World Bank (1994) and Perkins, Radelet, and Lindauer (2006) introduced the idea of governance and its significance to economic advancement at the start of the 1990s.

In addition to sustaining and boosting growth, governance is crucial for establishing peace and reviving economies that have been ravaged by war (Brinkerhoff, 2005). It makes sense why development and aid professionals highlighted governance reforms as a requirement for maintaining the economy. The development and growth of a state's economy depend greatly on its governance indices. It is understandable why economists agree that one of the key factors explaining the performance gap between developing and developed countries is governance (Nducho, 2022). Data from the World Bank's Governance Indicators indicate that majority of African economies have struggled with corruption, political unrest, violent crime, and weak governance over the years (African Capacity Building Foundation [ACBF], 2017).

Implementing wise policies, delivering public services, and fostering economic growth and development all benefit from good governance. At both the regional and national levels in Africa over the past 20 years, there has been an increase in interest in governance (ACBF, 2017). In both developing and developed economies around the world, good governance can establish the framework for reducing abuse of power, poverty, legal infractions, insecurity, corruption, unrestrained military spending, and inequality. The findings of this study will be important for policymakers who have emphasized the importance of good governance in SANE countries. Through the adoption of ideas for the enhancement of governance in SANE economies, this study will lead to the implementation of people-oriented policies. Once more, the results of this study may help establish policies that promote development and sustainable growth to raise living standards in emerging economies. Additionally, policymakers in SANE economies and other nations might use the study's findings as a benchmark for assessing their governance practices and enacting the necessary changes to promote economic growth. The results would ensure that development policies in SANE economies mainstream good governance.

Despite having a wealth of mineral resources, some SANE countries have remained among the most indebted economies with a low per capita income. For instance, Hanson-Agumbah (2019) asserted that since Nigeria's independence in 1960, the military has deposed its democratically elected government eight times. Along with the coup d'état, other issues include terrorism, social unrest, self-determination movements, nepotism, militants in the Niger Delta's calls for resource control, and an alarming rate of poverty. These precursors are primarily the product of poor governance, which has led to erratic economic growth. Furthermore, despite the significant resources invested in economic growth, policy reforms, and their implementation for the enhancement of governance in SANE economies, there have been no discernible changes in the standard of living of the citizens of some of these countries. This is further supported by the fact that South Africa, Algeria, Nigeria, and Egypt are ranked 116th, 168th, 124th, and 151st on the 2023 Index for Economic Freedom, respectively, with scores of 55.7, 43.2, 53.9, and 49.6.

Poor governance may be to blame for the ineffective use of external debt in some SANE countries, and the reason they have continued to struggle with issues. In the contention of Easterly (2002), wars and external shocks were not the main causes of how highly indebted poor countries (HIPCs) came to be. Instead, it was bad governance and the policies that went along with it. SANE economies have to use governance to enhance policymaking, achieve sustainable economic growth, and properly integrate into the global economy as key actors, according to Rodrik's (2008) argument that it is a crucial tool for development.

The governance-economic growth literature's empirical findings are rife with flaws. Some of the existing literature suggested a negative relationship between the two (Evrensel, 2010; Assiotis & Sylwester, 2012; Goldsmith, 1995; Salawu, Yusuff, Salman, Ogunniyi & Rufa, 2018)), while others suggested a positive relationship between the two (Adams & Mengistu, 2008; Anwar & Cooray, 2012; Alonso, 2010; Busse & Groizard, 2008; Khamfula, 2007; Mauro, 1995; Seldadyo, Nugroho & Haan, 2007; Law & Habibullah, 2006; Han, Khan & Zhuang, 2014; Emara & Jhonsa, 2014; Emara & Chiu, 2016; Alam, Kitenge & Bedane, 2017; Epaphra & Kombe, 2017; Lahouji, 2017; Kraipornsak, 2018; Salawu, Yusuff, Salman, Ogunniyi & Rufa, 2018), some studies suggested that it could be positive if it interacted with the money supply (Anwar & Cooray, 2012), some showed that it could be positive depending on the situation (Butkiewicz & Yanikkaya, 2011), or insignificant (Feeny & Mcgillivary, 2010; Ekanayake & Chatma, 2010; Commander & Nikoloski, 2010; Pere, 2015; Emara & Chiu, 2016; Mira & Hammadache, 2017; Almohammed & Ekşi, 2021).

Despite its significance in developing nations around the world, the literature has not completely explored the empirical relationship between governance and economic growth. There are many previous studies (Olson, Sarna, & Swamy, 2000; Kurtz, & Schrank, 2007; Younis, Lin, Sharahili, & Selvarathinam, 2008; Hamadi, Rihab, & Lotfi, 2009; Huynh, & Jacho-Chávez, 2009; Mehanna, Yazbeck, & Sarieddine, 2010; Zhuang, de Dios, & Martin, 2010; Gani, 2011; Haggard, & Tiede, 2011; Chowdhury, & Sundaram, 2012; Akpan, & Effiong, 2012; Abdelbaky, 2012; Fayissa, & Nsiah, 2013; Han, Khan, & Zhuang, 2014; Asuquo, 2014; AIBassam, 2013; Omoteso, & Ishola, 2014; Sen, 2014; Emara, & Jhonsa, 2014; Asuquo, 2014; Emara, & Jhonsa, 2014;. Manyinsa, 2014; Pere, 2015; Yerrabati, & Hawkes, 2015; Emara & I-Ming, 2016; Emara & Chiu, 2016; Adefeso & Abioro, 2016; Lahouij, 2017; Rachid & Ahmed, 2017; Tharanga, 2018; Kim, Wu, & Lin, 2018; AIAdlani, 2019; Anoy, 2021; Almohammed & Eksi, 2021; Nducho, 2022) that examine the relationship between governance and economic growth.

Nonetheless, a number of these research focused on the economies of the Middle East and North Africa (MENA) (Mehanna, Yazbeck, & Sarieddine, 2010; Abdelbaky, 2012; Emara & Jhonsa, 2014; Emara, & I-Ming, 2016; Rachid & Ahmed, 2017). Once more, the South and East Asia and Pacific region, Africa, developing countries, selected economies of sub-Saharan African region, transition economies, sub-Saharan Africa, Western Balkan economies, developing Asia, East African Community Countries and  Morgan Stanley Capital International (MSCI) economies were the focus of some (Yerrabati, & Hawkes, 2015), (Fayissa, & Nsiah, 2013), (Gani, 2011), (Asuquo, 2014), (Hamadi, Rihab, & Lotfi, 2009), (Akpan & Effiong, 2012; Omoteso & Ishola, 2014), (Pere, 2015), (Zhuang, de Dios, & Martin, 2010), (Manyinsa, 2014) and (Almohammed & Eksi, 2021). Moreover, a few (Younis, Lin, Sharahili, & Selvarathinam, 2008; Haggard, & Tiede, 2011), focused on the broken-down components of governance and economic growth. The remaining research was both country-specific and cross-country analyses.

Thus, there is a lack of research on how governance affects economic growth in SANE countries. Additionally, a large portion of the research on governance (Adefeso & Abioro, 2016; Salawu, Yusuff, Salman, Ogunniyi & Rufa, 2018; Adenuga & Evbuomwan, 2014) focused on governance as an aggregate (single aggregate score for governance). From the best that we can tell, the disaggregated governance elements (the six aspects of governance) have not received any attention in SANE countries. Because it has not piqued the broad attention of many academics, it is necessary to research how these governance metrics affect economic growth in SANE countries. Finally, there aren't many studies that aim to examine all or even most aspects of governance simultaneously. Therefore, the purpose of this study is to determine whether the economic growth of SANE countries is influenced by the governance indices of Government Effectiveness (GE), Rule of Law (RL), Control of Corruption (CC), Regulatory Quality (RQ), Voice and Accountability (VA), and Political Stability and Absence of Violence (PS). The question to be addressed in this study is does economic growth in SANE economies depend on the six governance indicators?

This study will add to the governance-economic growth nexus from four different directions. First, based on what we know, the effect of governance on economic growth in SANE economies will be investigated for the first time. In the second case, the Gross Domestic Product (GDP) per capita, Purchasing Power Parity (PPP) was used as the dependent variable to examine price differences among the SANE countries, in contrast to other research that used GDP per capita. In the third case, analysis was conducted using Principal Component Analysis (PCA) and the Heterogeneous Dynamic Panel Data estimation Approach. The variables were subjected to a PCA to resolve the multicollinearity induced by the significant correlation between some pairs of governance indices, and to identify the linear combination that accounts for the most variability. Lastly, it will identify the aspect of governance that has a greater bearing on the explanation of economic expansion in the SANE economies. The schedule for the rest of this research is as follows: A summary of the SANE economies' economic growth rates and governance developments is presented in Section 2; the literature review and theoretical framework are presented in Section 3; the methodology is presented in Section 4; the results are analysed in Section 5; the limitation of the study is presented in Section 6 and the conclusion and recommendations are presented in Section 7.

2. Overview of SANE Countries

2.1. Overview of Economic Growth Rate of SANE Countries

Source: Authors’ Compilation using data from WB WDI Database

In terms of revealing Africa's potential for economic development, the SANE (South Africa, Algeria, Nigeria, and Egypt) countries, or Africa's G4, have been dubbed the continent's growth poles. According to Michele and Michael (2010), of the 54 countries in Africa, the G4 is considered to have the continent's most likely opportunity of creating an economic bloc whose function in Africa will be similar to that of the BRIC (Brazil, Russia, India, and China) rising markets. Numerous issues that have had an impact on these economies' rates of economic growth have plagued them throughout their histories. For instance, insufficient electricity supply has repeatedly constrained South Africa's Gross Domestic Product (GDP) growth rate; Algeria's GDP per capita has decreased due to ineffective reforms; Nigeria's GDP growth rate has been impacted by the Boko Haram insurgency; and Egypt's GDP growth rate has been negatively impacted by the Arab Spring. These nations were also impacted by the COVID-19 epidemic. Figure I illustrates the GDP growth rate performance of SANE economies. For the period under consideration, SANE economies' economic performance was inconsistent. Nigeria had the highest average growth rate over the examined period, at 4.7 percent, followed by Egypt, Algeria, and South Africa, at 4.5, 3.1, and 2.3 percent, respectively.

The rapidity of structural reforms and the implementation of Vision 2030 were responsible for Egypt's economic performance (Asharq Al-Awsat, 2021). The poorest record, though, was held by South Africa. The South African economy's growth rate throughout the review period must have been constrained by a lack of electricity supplies (The World Bank Group, 2023). According to trend data, Nigeria had the highest growth rate in the years 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2013, and 2014, with percentages of 11.6, 5.6, 7.1, 4.9, 4.6, 5, 5.2, 6.1, 6.1, 5.1 and 4.8. Egypt was the only nation to post a positive GDP growth rate of 3.6 per cent during the COVID-19 pandemic in 2020. Nigeria, Algeria, and South Africa all experienced negative growth rates, with respective figures of -1.8, -5, and -6.1. Additionally, in 2009 and 2016, respectively, both South Africa and Nigeria saw negative growth rates. South Africa's negative growth rate in 2009 was caused by the worldwide financial crisis of 2008–2009 (Maral, 2009). Nigeria’s own was caused by the severe economic downturn endured as a result of the sharp decline in oil prices. Additionally, Egypt experienced the highest growth rate in 1997, 1998, 1999, 2000, 2006, 2007, 2008, 2010, 2018, 2019 and 2022 respectively among SANE economies. Furthermore, Egypt was also the only SANE economy to experience positive GDP growth over the study period.

2.2. Governance Developments in SANE Countries

The data on the six indices of governance for the SANE countries were not available in 1997, 1999 and 2001 respectively. Thus, our analysis was from 2002 to 2023. An overview of the six indices of governance – Control of Corruption, Political Stability and Absence of Violence/Terrorism, Rule of Law, Regulatory Quality, Government Effectiveness, and Voice and Accountability for the period under review in SANE economies indicated that the South African economy performed very well. South Africa has improved considerably compared to other SANE countries. The governance index is appraised on a scale of -2.5 considered as poor quality of governance to 2.5 believed to be high quality of governance. The governance trends in SANE countries are depicted in Figures 2, 3, 4, 5, 6 and 7 respectively.

The voice and accountability indicators are the degree to which a nation's residents can choose their government, as well as their right to free speech, association, and the press. For this metric during the period under review, South Africa was ranked best. Nigeria and Algeria were in second and third positions respectively. However, the worst-ranked SANE country was Egypt. Among the SANE economies, Egypt was the worst ranked in 2002 at -1.10. South Africa was the highest-ranked country at 0.66. Algeria and Nigeria are at -1.04 and -0.63 followed by Egypt respectively. South Africa sustained its highest ranking from 2002 to 2023. In addition, Nigeria maintained its position as the second-ranked SANE economy. This is depicted in Figure 2.

Source: Authors’ compilation using data from the WB WDI Database

The political stability and absence of violence metric is based on the probability that a government may be overthrown by violent or unconstitutional means, including terrorism. For this indicator, Figure 3 showed that South Africa was the most politically stable SANE country for the period under investigation. However, their performance declined from 2021 to 2023. Unlike the voice and accountability metric, Nigeria was ranked as the most politically unstable SANE country. In 2002, Algeria and Nigeria were the lowest-ranked SANE economies at -1.63 respectively. On the other hand, South Africa and Egypt were ranked first and second at -0.25 and -0.41 individually. In 2011, Egypt deteriorated in terms of political stability and absence of violence and it continued till 2020. However, at the same time, Algeria improved in terms of political stability and absence of violence and it continued till 2023. The Arab Spring that started on 17^th December 2010 was responsible for this situation. While Egypt suffered as a result of the Arab Spring, Algeria was not affected.

Source: Authors’ compilation using data from the WB WDI Database

Figure 4 depicts the government effectiveness metrics of SANE countries. This indicator is evaluated in terms of the effectiveness of public services, the capability of the civil service, its independence from political influence, and the standard of policymaking. South African government was the most effective government in SANE countries. On the other hand, the Nigerian government was the least efficient. This indicator is critical for the advancement of private undertakings, reduction of bureaucracy and stimulation of economic activities (Manyinsa, 2014). From -1.20 in 2009, Nigeria improved to -0.10 in 2013. The efficiency of governance in Algeria and Egypt was uneven and unpredictable most of the time.

Source: Authors’ compilation using data from the WB WDI Database

The metric of regulatory quality is gauged by a government's capacity to implement wise laws and rules that support and encourage the growth of the private sector. For this metric, South Africa was the highest-ranked SANE country. South Africa had the best regulatory framework at 0.73 in 2002. Nigeria had the worst regulatory framework in 2002 at -1.18. However, Algeria and Egypt were ranked -0.57 and -0.46 respectively in 2002.  This is indicated in Figure 5.

Source: Authors’ compilation using data from the WB WDI Database

The rule of law index is gauged by how much agents respect and uphold social norms, such as the standard of property rights, the effectiveness of the police and courts, and the likelihood of crime. This metric is shown in Figure 6. For this metric, South Africa just like in the last four indicators had consistently maintained the best-ranked position. Thus, South Africa was the highest-ranked SANE country in terms of adherence to the rule of law. However, Nigeria was the worst-ranked SANE country from this angle. This governance index is vital for the attraction of foreign direct investment and the development of the private sector. In 2002, South Africa had the best adherence to the rule of law at 0.03. This was followed by Egypt, Algeria and Nigeria at -0.01, -0.64 and -1.50 respectively.

Source: Authors’ compilation using data from the WB WDI Database

The control of corruption is the degree to which public authority is used for personal advantage, including both small-scale and large-scale corruption as well as elite "capture" of the state. This indicator is revealed in Figure 7. For this metric, South Africa was again ranked as the least corrupt economy in SANE countries. However, Nigeria was ranked as the most corrupt country in SANE economies. In 2002, South Africa was ranked the least corrupt economy at 0.33. The SANE economies of Algeria, Nigeria and Egypt were ranked at -0.93, -1.50 and -0.44 respectively. South Africa sustained positive rankings from 2002 to 2010. However, with the exception of 2016, negative rankings were recorded for the remaining years under investigation. Furthermore, from 2016 to 2021, South Africa was volatile with inconsistent oscillations.

Source: Authors’ compilation using data from the WB WDI Database

3. Theoretical and Empirical Issues

3.1. Theoretical Framework

In order to investigate the connection between economic growth and its underlying causes, economists have used a variety of hypotheses. Prior until today, it was not thought to be significant because the role of the government in promoting economic growth "lies outside the boundary of economics" (Kong, 2007, p. 7). The endogenous and neoclassical theories of economic growth put forth various perspectives on the role of the government in the economy. The neoclassical academics opposed the government's creation of an atmosphere that encouraged investment. However, it was backed by proponents of the new growth theories. Numerous studies have demonstrated the value of institutions for economic growth since they serve as incentives for luring in foreign investment (Acemoglu, Johnson & Robinson, 2004; North, 1990).

Government and governance historically were interchangeable terms before the 1970s. However, its significance increased as a result of the implementation of a revolutionary governance paradigm.  The concepts of governance, as well as their extensive use by many organizations and practitioners, are described below. The early philosophers accepted the state's functions in economic growth through the governors. As Smith (1776) put it, proponents of the "mercantile system" or "system of commerce" believed that accumulating wealth was the source of economic progress and that it was a tool for enhancing state sovereignty (McDermott, 1999). Mercantilists understood that a country's worth depended on how much gold and currency it had acquired. As a result, they were in favour of the "favourable trade balance" strategy, which states that "a country must export more than it imports, which would lead to a net inflow of bullion" (Magnusson, 2015, p. 217). This served as justification for government interference in the economy to increase the state's riches and authority.

According to Wood (2002), this was accomplished by limiting wages, controlling the sea, giving traders monopolies, emphasizing the export of finished goods, safeguarding the home industry, and regulating the export of raw materials. Following the Mercantilists, Physiocrats believed that agriculture or production was the source of prosperity through their theory of Physiocracy, which was considered the antithesis of mercantilism. Instead of using business and industrial models, they believed that land development was the primary force behind economic growth. Classical growth thinkers continued this discussion by criticizing the economic theories of mercantilists and Physiocrats.

The classicists, led by Adam Smith, had a different viewpoint, though. Less government involvement in the economy was advocated, but they backed the construction of an environment that allowed people to pursue their development through the "invisible" forces of supply and demand. Therefore, these philosophers consistently saw the need for a well-run state that would protect the populace, uphold law and order, provide ways of trade, etc., to realize progress (AlAdlani, 2019). John Maynard Keynes established the need for the state to actively participate in economic activities by engaging in productive economic activity as well as creating and maintaining an environment that is conducive to economic players while keeping an eye on the contributions of classical thinkers. According to Sharipov (2015), the Keynesian model emphasized the expansion of aggregate demand and investment as the key drivers of economic growth.

This leads to a variety of opinions on the relationship between the state's responsibility and economic growth because the state's responsibility is thus understood not only from the perspective of the significance of the state's machinery but also exceedingly in the employment of such machinery by those in authority. In this way, the institutional and structural constraints on economic growth in developing economies are seen by the structuralist theory of the late 1960s and early 1970s. This is predicated on the idea that, in the eyes of structuralists, Less Developed Economies (LDCs) are characterized by rigidities that restrict economic adjustments and suffer significant constraints or structural difficulties. This model emphasized the impact of institutional constraints that are both internal and external on a state's ability to build its economy.

As a result, structural reasons are what cause the governance phenomena in global emerging economies. The complexity of the SANE countries' experience is explained by this. The economic development of nations is influenced by rules and units because they are arranged by fundamental structures that the human mind has built into important systems. Accordingly, Jhingan (1997) said that nowadays, it is widely accepted that the state must play a constructive role in order to overcome the rigidities that characterize less developed countries (LDCs). Jhingan (1997) further emphasized that the state's primary duty in such economies is to close social disparities and promote the psychological, ideological, social, and political circumstances necessary for economic growth and development. Government reformers and the World Bank both agree that "good governance" is a prerequisite for sustainable development and an environment that is conducive to investment (Nducho, 2022).

3.2. Review of Empirical Studies

The relationship between governance and economic growth has been extensively studied in literature from around the world, with varying outcomes and interpretations. In the first instance, AlBassam (2013) utilized an exploratory method of analysis to investigate whether the strong association between governance and economic growth occurs in eras of economic crises or merely in non-crisis times. The findings revealed that the global economic crisis exerted an invisible effect on the association between governance and economic growth. Nevertheless, the study unearthed that the association between governance and growth in crisis periods is influenced in innumerable aspects by the diverse levels of the country’s development. Hence, the volatility in the association between governance and economic growth throughout the economic crisis is underlined by the findings of this study.

Manyinsa (2014) explored the impact of World Governance Indicators (WGI) of Voice and Accountability, Political Stability, Government Effectiveness, Regulatory Quality, Rule of Law, and Control of Corruption on economic growth in East Africa Community (EAC) countries from 1999 to 2012. Panel data methodology was utilized in the study. The five economies were Burundi, Tanzania, Rwanda, Kenya and Uganda. The findings showed that Regulatory Quality and Political Stability had a negative impact on economic growth. On the other hand, Control of Corruption exerted a positive impact on economic growth. Furthermore, the growth rate of the population and rates of inflation exerted negative impacts on economic growth in EAC economies.

Sen (2014) studied the connection between governance and outcomes of development in Asia with an emphasis on the developing economies of Asia. They utilized the disaggregated indicators of governance – administrative capacity, state accountability and legal infrastructure in their practical analysis. The findings showed that governance affected most development indicators apart from the levels of schooling. This result is remarkably obvious for the administrative capacity of the state and legal infrastructure. However, it was less obvious for state accountability. Nevertheless, our findings depicted that the association between governance and development was weaker for economies of Asia for numerous indices of development employed. In addition, the results revealed that increment in domestic resources mobilization and strengthening of the mechanism for spending these resources on social sectors were the main means through which governance affects development.

Adenuga and Evbuomwan (2014) looked into the dynamics of governance, investment, and economic growth in Nigeria from 1999Q1 to 2010Q4 using cointegration and the Vector Error Correction Mechanism (VECM). Estimating the short-run dynamics and error-correction mechanisms of governance, investment ratio, price level, prime lending rate, openness, and financial sector development on economic growth were the specific goals. The findings supported the theory that investment and good governance encourage economic growth in Nigeria. Yerrabati and Hawkes (2015) in another study, meta-synthesised the practical proof of the nexus between governance and economic growth in South and East Asia Pacific economies from 1980 to 2012 building on 29 papers with 554 estimates. The findings demonstrated that even as corruption had a negative and significant impact on economic growth, government effectiveness and regulation exerted a positive and significant impact. In addition, law and political stability exerted no significant influence on economic growth. Furthermore, the empirical literature on governance and economic growth was unsuccessful in presenting proof of the real influence of voice and accountability on economic growth. Conclusively, the results revealed that total governance was vital for economic growth.

Emara and Chiu (2016) used a cluster of 188 economies to analyse the relationship between governance and economic growth. They used the Principal Components Analysis (PCA) technique to create a "Composite Governance Index" (CGI) that condensed the present six elements of governance in the WGI into a single overall score for governance. The results demonstrated that governance has a beneficial effect on economic growth in nine MENA economies. This includes economies that had seen a fall accompanied by a decline and economies that had experienced an improvement accompanied by, respectively, an improvement in the index of governance and economic growth. Additionally, the results showed that a one-unit increase in CGI would increase GDP per capita by around 2%. The results further demonstrated that a simple five-unit increase in CGI would result in a seven-year GDP per capita gain twice based on the Rule of 70. They emphasized that they focused primarily on the 21 MENA economies, but that their findings are also relevant to other economies.

Adefeso and Abioro (2016) examined the relationship between governance administration and economic development in Nigeria from 1970 to 2014 using the Error Correction Methodology (ECM). The results demonstrated that the governance administration index had a favourable effect on economic growth. Tax income also had a detrimental effect on the growth of the economy. Using Panel data methodology, Lahouij (2017) examined the link between governance and economic growth in developing economies from 2002 to 2014 intending to carry out a comparative analysis. The results showed that governance had a positive relationship with economic development in developing economies irrespective of their income level. Additionally, the findings revealed that political stability, voice and accountability and the rule of law exerted a positive and significant impact on the economic development of low-income economies. Furthermore, it indicated that regulatory quality, voice and accountability, rule of law and government effectiveness had a positive link with the economic growth of upper-middle-income economies.

Tharanga (2018) used the Pooled Ordinary Least Square Methodology, Fixed Effects (FE) Methodology and Random Effects Methodology (RE) to examine the impact of control of corruption, political stability and absence of violence and voice and accountability on economic growth utilizing data from 145 economies from 2002 to 2014. The results showed that control of corruption was a vital ingredient for economic growth. However, the study stressed the significance of joint and effective management of control of corruption and political stability and absence of violence for the realization of higher economic growth. In addition, it emphasized that when the rate of economic growth is compared to those of European Union (EU) economies and the North American economies, other economies recorded considerably lower rates except for the MENA regions. Furthermore, the results revealed that the rate of economic growth in high-income economies was greater than that of middle-income economies by 20%. Conversely, the economic growth rate in low-income economies was 23.5% lower than that of middle-income economies.

AlAdlani (2019) used descriptive analysis and panel data techniques to investigate the association between governance and economic growth in the Arab World from 1996 to 2017. The WGI six dimensions of governance - Voice and Accountability (VA), Government Effectiveness (GE), Political Stability and Absence of Violence (PS), Regulatory Quality (RQ), Control of Corruption (CC) and Rule of Law (RL) were utilized in the study. The findings showed that there is no significant association between governance and economic growth in the Arab World. However, the findings showed that governance may be related to economic growth in some specific groups of economies once the Arab World was disintegrated into several political, regional and economic groups. The results further showed that some indices of governance exerted more impact when compared to others. For instance, government effectiveness, political stability and absence of violence, and voice and accountability had a significant link with economic growth in Low- Income Countries. On the other hand, voice and accountability and control of corruption had a significant association with economic growth in the region of Greater Maghreb. Moreover, voice and accountability had a significant link with economic growth in Republics while government effectiveness had a significant association with economic growth in Monarchies. Furthermore, the results revealed that variation in the function of governance was caused by regime, the distribution of income and region.

In another study, Anoy (2021) employed regression methodology to investigate the impact of WGI of voice and accountability, political stability and absence of violence, government effectiveness, regulatory quality, rule of law and control of corruption on the growth rate of the GDP of Bangladesh from 1996-2018. The findings revealed that control of corruption was the most significant index of governance and exerted a positive impact on economic growth. Equally, there was a positive and significant relationship between rule of law and economic growth. Granting that the parameter estimate for voice and accountability was significant, the negative sign of the parameter does not suggest the anticipated influence on GDP growth possibly as a result of the small sample size utilized for the study. However, government effectiveness, regulatory quality and political stability and absence of violence were not statistically significant and had no impact on the economic growth of Bangladesh. Almohammed and Ekşi (2021) studied the impact of governance on economic development in emerging economies from 2002-2018. The study employed countries based on MSCI classification as a sample owing to their growing significance. The study used the PCA and Generalized Method of Moments (GMM) for empirical analysis. The findings revealed that governance had no significant effect on economic development.

Nducho (2022) evaluated the effect of governance on economic growth in Cameroon in relation to Finland by employing the qualitative methodology. The case study model was used for data analysis. The case models used were Yaoundé and Helsinki. The findings revealed that the economic growth level caused by good governance was comparatively higher in Finland than in Cameroon. Evidence from the evaluated literature suggested that research on the connection between governance and economic growth in SANE countries was scarce. Much of the research was conducted about other pronounced economic blocs of the world. Many findings emerged from the empirical literature on the relationship between governance and economic growth. These investigations employed various methods for analysis. The WGI dataset was used in most research as a stand-in for governance. A portion of these research was conducted in MSCI economies, East African Community countries, and developing economies in Asia. The Pooled Mean Group (PMG) Panel Autoregressive Distributed Lag (ARDL) approach was not employed in any of the studies analyses. Once more, none of these researches were conducted in economies of SANE. However, this study was influenced by the dearth of empirical research on the relationship between six indicators of governance and economic growth in SANE economies.

4. Methodology

4.1. Data

The data used in this study ranged from 1996 to 2023. The choice of this period was influenced by the data's accessibility. Only the years 1996 to 2023 were covered by the World Bank's (WB) WGI statistics. However, data on the six indices of governance for the SANE countries were not available in 1997, 1999 and 2001 respectively. We used extrapolation to fill the gaps. Even though there were other indices for assessing governance in the literature, this study utilized the six WB WGI governance indicators. The WGIs are more dependable than other indices because they combine individual indicators from a wide range of corporate and nonprofit organizations, as well as experts, to create a composite index that can be used to compare the quality of governance across nations and even within particular regional countries over time. They have also been extensively employed in research investigations and development projects. Indicators that cover all facets or dimensions of the governing process, such as political, economic, and institutional, are also included in the WGIs, which is extremely important for the goals of this study. Six separate metrics, each representing a different aspect of governance quality, are available in the database.

These factors include political stability, government effectiveness, regulatory quality, the rule of law, voice and accountability and corruption control. The indicators are presented in two different ways: first, as conventional normal units with a range of around -2.5 to 2.5, and second, as percentile ranks with a range of 0 to 100, where higher values indicate better results. The six indicators were first proposed and used by Kaufmann, Kraay, and Zoido-Lobaton (1999), and they have since been used by academic researchers and international organizations to assess government performance and investigate the link between governance and growth (Arndt & Oman, 2006; Huynh & Jacho-Chávez, 2009; Emara & I-Ming, 2016; Zhu, 2013). A World Bank team published the data for these indicators.

Kauffman, Kraay, and Mastruzzi (2009) provided the approach for the production of these indicators, which are thought to have a significant ability to improve the business environment. The WB’s WGI database served as the source of information for the six governance indices, which include voice and accountability, political stability, government effectiveness, regulatory quality, rule of law and corruption control. The WB World Development Indicators (WDI) database was used to acquire information on the GDP per capita, PPP, domestic credit to the private sector and foreign direct investment. The GDP per capita, PPP was utilized as the dependent variable to check the price differentials among the SANE economies. Table I displays the variable's name and definition.

Table 1: Variable’s Name and definition

Source: Authors’ Compilation

Table 2: Correlation matrix for the six indicators of governance for SANE Countries

Source: Authors’ Compilation

         Table 2 shows the correlation matrix of the six dimensions of governance. Outside of the brackets are the variables' correlation coefficients. The likelihood values, though, are in parenthesis. There was a multicollinearity issue. This was due to several pairs of starred regressors having pairwise correlations of more than 0.8. It would be difficult to separate the impact of CC and GE, CC and RQ, GE and RQ, GE and RQ, and RL and RQ separately on GDP per capita, PPP, in this scenario. 

In our study, a high correlation between the explanatory factors may be problematic. For the purpose of tackling multicollinearity problems in datasets, the Principal Component Analysis (PCA) has been extensively used (Jolliffe, 2002; Johnson & Wichern, 2007; Hair, Black, Babin, & Anderson, 2010). Furthermore, improving interpretation is one advantage of employing PCA for multicollinearity (Browne, 2001; Shlens, 2014; Ding et al., 2018). Thus, it makes analysis and interpretation easier as a result. Hence, to find the linear combination that explains the most variability, the variables were submitted to a PCA to resolve the multicollinearity caused by the significant correlation between some pairs of governance indices resulting in the emergence of a sole composite index termed the Index of Good Governance (IGG). The linear combination of the original variables that makes up the first PCA component explains the most variation in the original data. Following the PCA, CC emerged as the sole factor that accounted for 74% of the variability in the initial data. Only this governance indicator had an eigenvalue greater than one. The eigenvalue of it is 4.4628. As a result, it was kept. This element of the governance indicator is thus regarded as the IGG. Hence, to investigate the relationship between governance and economic growth, IGG was chosen as the primary governance indicator. The variables also met the minimal criterion of 0.4 and had loadings between 42% and 96%. Our data were subjected to PCA because Kaiser's Measure of Sampling Adequacy value of 0.8097 indicated that it was appropriate. The findings of the factor analysis are shown in Table 3.

Table 3: Factor analysis results of the governance construct

Source: Authors’ Compilation

Table 4: Correlation Matrix of Variables

The correlation matrix between the dependent and independent variables is displayed in Table 4. The highest coefficient in this result that was reported was 0.7704, which was below the 0.8 benchmark. Based on this premise, no independent variable pairs had a strong correlation, and multicollinearity was not an issue.

4.2. Model Specification

For this investigation, the model used by Manyinsa (2014) will be modified. A general empirical model connecting governance and economic growth in the SANE countries can be stated as follows, based on the intuitions provided by this author regarding the anticipated link between economic growth and some causative variables:

           Each of the variables had a country (i) and period (t) index. The dependent variable was logged, and its logarithm sign was represented by L. The time-series features of the data were examined using the Levin, Lin and Chu panel unit root tests before the estimation of the equation of economic growth. Additionally, we tested for multicollinearity to establish if the explanatory variables were highly correlated with one another. We used the Pooled Mean Group (PMG) Panel Autoregressive Distributed Lag (ARDL) procedure introduced by Pesaran, Shin and Smith (1999) for analysis. In addition to the predicted long-run coefficients, this technique also displays short-run dynamics. The panel ARDL statistical process was calculated using E-Views version 9 of the econometric program.

Equation 3.2 depicts the ARDL (p,q) model, which is established from the work of Pesaran and Shin (1996).

The re-parameterised panel-ARDL model of equation 3.2 is specified to account for the long-run and short-run dynamic panel model. Hence, to account for the adjustment coefficient and the long run dynamics, equation 3.2 is reparametrized as follows:

To estimate equation 3.3, the PMG developed by Pesaran et al. (1999) was employed. Thus, the panel-ARDL model of the relationship between governance and economic growth is:

The dependent and independent variables are defined in model form in Equation 3.5.

5. Results and Discussions

Table 5: Results of Panel Unit Root Test

Note: ***indicate statistical significance at the 1% level of significance

Source: Authors’ Compilation

The series was tested for stationarity using the panel unit root test developed by Levin, Lin, and Chu in 2002. Results for the unit root are shown in Table 5. The outcomes showed that the variables had either an integration order of I(0) or I(1). The adoption of the panel ARDL approach was supported by the various degrees of integration among the series.

Table 6: Results of Long-run Coefficients

Note: ** and * indicate statistical significance at the 5% and 10% levels of significance, respectively.

Source: Authors’ Compilation

Note: Probability Values are in bracket - ( ).

t-statistics are in []

Table 6 displays the outcomes of the long-run coefficients. The results showed that the index of good governance had a negative and insignificant effect on economic expansion. The findings of Anoy (2021), Manyinsa (2014), Assiotis and Sylwester (2012), Haggard and Tiede (2011), Khamfula (2007), Hakimi and Hamdi (2017), Lahouij (2017), AlAdlani (2019) and Mauro (1995) are opposed to this outcome. It, however, agrees with what Evrensel (2010) and Gani (2011) found. Hence, it has a greater bearing on the explanation of economic expansion in the SANE economies. Additionally, domestic credit to the private sector had a positive and effect on economic expansion. This suggests that, over time, domestic financing of the private sector promotes economic growth in SANE economies. Additionally, foreign direct investment had a positive impact on economic expansion. This finding agrees with AlAdlani’s (2019) and Lahouij’s (2017) submissions. However, it violates Duru and Ezenwe's (2020) submission.

Table 7: Results of Short-run Coefficients

Note: *** and ** indicate statistical significance at the 1% and 5% levels of significance, respectively

Source: Authors’ Compilation

Table 7 displays the outcomes of the short-run dynamics. The results demonstrated that there was no significant correlation between economic growth in SANE economies and changes in the index of good governance, domestic loans to the private sector, or foreign direct investment from the previous year. The results showed that the Error Correction Terms (ECT) were negative and statistically significant. The coefficient value of the  ECT suggests that about 7.63 per cent of divergences from long-run equilibrium are adjusted in 13 years. This implies that there are long-term correlations between the variables. Additionally, in the long run, IGG, DOMCREP, and FDI do mutually propagate to produce RGDPPCPPP. However, the short-run coefficients per country data revealed that South Africa, Algeria, Nigeria and Egypt had ECT coefficients of -0.0623, -0.0530, -0.1525 and -0.0374, respectively. They were statistically significant and negative. For South Africa, Algeria, Nigeria and Egypt, respectively, the coefficients of -0.0623, -0.0530, -0.1525 and -0.0374 indicate that 0.06%, 0.05%, 0.15% and 0.04% of divergences from long-run equilibrium were rectified in 16 years, 19 years, 7 years and 27 years respectively. We may also conclude that the variables were cointegrated and that IGG, DOMCREP, and FDI collectively generate RGDPPCPPP in the long term because the ECT was negative and significant. Table 8 displays the short-run coefficient results by country. The finding from the short-run coefficients by country results showed that the ECT coefficient was negative and significant in line with the short-run dynamics group findings.

Table 8: Short-run Coefficients Results of Panel ARDL Estimations by Country

Note: ***, ** and * indicate statistical significance at the 1%, 5% and 10% levels of significance, respectively.

Source: Authors’ Compilation

5. Limitations of the Study

         The study's data set covered the years 1996 through 2023. The availability of the data had an impact on the selection of this time frame. The WB's WGI data only covered the period from 1996 to 2023. However, in 1997, 1999, and 2001, respectively, statistics on the six indices of governance for the SANE countries were not available. To close the gaps, extrapolation was applied. This did not allow us to extend the study to 2024. Moreover, the WB’s WDI database did not provide the yearly percentage of GDP per capita increase in PPP. It was anticipated that this indicator would enable comparisons of GDP per capita growth across SANE economies. In its absence, however, the PPP of GDP per capita growth was used as the dependent variable to verify the pricing differences among the SANE economies. Furthermore, in 2023, the data on domestic credit to the private sector was not available for Nigeria. Once again, extrapolation was applied to fill the gap.

6. Conclusion and Recommendations

The relationship between governance and economic growth in SANE economies from 1996 to 2023 was examined in this study. The analysis used the PCA and the PMG Panel ARDL approach. According to the findings, the index of good governance had a negative and insignificant impact on economic growth in SANE economies. As a result, the management of the index of good governance can be partly responsible for the SANE economies' economic adversity. Furthermore, the economic growth of SANE economies depends mostly on the index of good governance element of the governance indexes. It has a negative and insignificant influence on economic growth in SANE economies. Hence, it has not really influenced economic expansion in SANE countries. However, foreign direct investment had a positive and significant effect on economic growth in SANE economies. Furthermore, domestic loans to the private sector had a positive impact on economic growth in SANE countries. Based on the findings of this study, the following were recommended: The governments of the SANE nations should sustain the current policies on foreign direct investment since it is yielding the desired outcome. Furthermore, since the index of good governance hasn't had much of an impact on SANE countries' economic growth, those policies meant to address it should be revisited. Furthermore, in order to achieve economic progress, the government agencies tasked with combating corruption in SANE economies should make sure that corruption is reduced through measures that support the rule of law. Policies for guaranteeing the growth of the private sector through domestic financing must also be sustained. In a similar vein, sensible measures for ensuring political stability among others ought to be sustained to encourage the growth of the private sector. 

Authors’ Contributions: Conceptualization, U.I.D., A.M.E., O.P.E; Methodology, software and formal analysis, U.I.D, C.C.E., O.P.E; Validation, A.M.E., K.P.U., T.F.O; Investigation, A.M.E., C.F.O., E.E.O., O.P.E; Data Curation, U.I.D, C.C.E., O.P.E; Writing – Original Draft, U.I.D; Writing – Review & Editing, A.M.E., U.I.D., C.F.O, K.P.U; Visualization, C.F.O., T.F.O., E.E.O; Supervision, O.P.E., A.M.E., C.F.O., E.E.O. 

Funding: Not applicable. 

Conflict of Interest: The authors declare no conflict of interest. 

Informed Consent Statement/Ethics Approval: Not applicable.

Data availability: The datasets used are available at the World Bank's World Development Indicators Database.

Declaration of Generative AI and AI-assisted Technologies: This study has not used any generative AI tools or technologies in the preparation of this manuscript.