The role of environmental quality, financial development and institutional quality in sustainable economic growth: Evidence from China

Cai, Yuqing; Ur Rahman, Habib; Khan, Ali Burhan; Fareed, Muhammad Article The role of environmental quality, financial development and institutional quality in sustainable economic growth: Evidence from China Contemporary Economics Provided in Cooperation with: VIZJA University, Warsaw Suggested Citation: Cai, Yuqing; Ur Rahman, Habib; Khan, Ali Burhan; Fareed, Muhammad (2025) : The role of environmental quality, financial development and institutional quality in sustainable economic growth: Evidence from China, Contemporary Economics, ISSN 2300-8814, VIZJA University, Warsaw, Vol. 19, Iss. 3, pp. 312-328, https://doi.org/10.5709/ce.1897-9254.568 This Version is available at: https://hdl.handle.net/10419/330345 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/ www.ce.vizja.pl 312 This work is licensed under a Creative Commons Attribution 4.0 International License. China's robust economic growth serves as a key driver propelling the global economy forward. As such, understanding the factors influencing its sustainable economic growth remains a critical concern for stakeholders. In this context, this study aims to investigate the key determinants of China's sustainable economic growth. Specifically, it examines the effect of environmental quality, institutional quality and financial development on sustainability in the Chinese context. To achieve this, the study employs a range of econometric analyses, including Ordinary Least Square (OLS), Generalized Method of Moments (GMM), and Quantile Regression (QR), using data spanning 2002 to 2019. The empirical findings reveal that environmental quality, institutional quality and financial development significantly contribute to China's sustainable economic growth. Additionally, the interaction effects of the institutional environment provide nuanced insights into the relationship. This study offers valuable implications for policymakers, highlighting the need to prioritize impactful financial inclusion over mere financial sector expansion, alongside focusing on other growth-enhancing initiatives. This study contributes to the body of knowledge by providing empirical evidence of the interaction effect of the institutional environment within this framework. 1. Introduction1. Introduction Sustainable economic growth is fundamental for improving and maintaining real GDP, as it helps balance a country's income generation and expenditures. This study examines the critical role of environmental quality (measured by CO2 emissions), institutional quality and financial development in influencing economic growth in China. According to Michieka et al. (2013), China and other emerging countries have achieved substantial social and economic advancements through trade liberalization and economic reforms over recent decades. However, this growth has significantly increased energy demand, leading to challenges related to environmental degradation and sustainability (Ozturk & Al-Mulali, 2015). China remains one of the largest producers of carbon dioxide emissions globThe Role of Environmental Quality, Financial Development and Institutional Quality in Sustainable Economic Growth: Evidence from China ABSTRACT F36, G28, O43, Q56. KEY WORDS: JEL Classification: sustainable economic growth, China, financial development, Quantile Regression, global indicators. 1 Nanyang Centre for Public Administration, Nanyang Technological University, Singapore 2 Faculty of Higher Education (Accounting and Finance), Holmes Institute, Australia 3 Department of Management Sciences, National University of Modern Languages, Pakistan 4 School of Business, VIZJA University, Poland 5 Faculty of Economics and Business, Universitas Brawijaya, Indonesia Correspondence concerning this article should be addressed to: Muhammad Fareed, School of Business, VIZJA University, ul. Okopowa 59, Warsaw, Poland. E-mail: [email protected] Yuqing Cai1 , Habib Ur Rahman2 , Ali Burhan Khan3 , and Muhammad Fareed4,5 Primary submission: 08.12.2024 | Final acceptance: 03.02.2025 313 Cai, Rahman, Fareed, and Khan 10.5709/ce.1897-9254.568DOI: CONTEMPORARY ECONOMICS Vol. 19 Issue 3 312-3282025 ally (EPA, 2014). While the relationship between environmental pollution and economic growth has been widely researched (Azam et al., 2016; Baek, 2015; Burnett et al., 2013; Feng et al., 2020; Onafowora & Owoye, 2014; Wang et al., 2016; Wang et al., 2024; Zhang & Zhao, 2024; Zou et al., 2016), further investigation is needed to understand how these factors interact in the context of emerging economies like China (Dogan & Seker, 2016). China is actively exploring new avenues to expand its trade. The Silk Road Economic Belt, initiated by the Government of China, is a key component of their latest trade expansion agenda. Consequently, this initiative is expected to increase energy demand, potentially exacerbating environmental pollution. However, trade expansion also provides opportunities to mitigate environmental pollution. Through trade, countries can exchange advanced technology and capital, enabling the transformation of traditional manufacturing methods into modern, sustainable practices. Moreover, adopting environment-friendly strategies will foster sustainable economic growth and contribute to building a resilient economy. While examining the association between economic growth and environmental quality, assessing whether this relationship is compatible is essential. If compatibility exists, measures must be taken to control the CO2 emissions relative to Gross Domestic Product (GDP). Achieving this goal requires large-scale deployment of energy-efficient technologies to meet energy demand while reducing CO2 emission intensity (Medlock III & Soligo, 2001). For a country like China to maintain CO2efficient production units, a robust financial system is essential to ensure adequate financing, risk management and market liquidity (Eren et al., 2019). According to the figures provided by the National Bureau of Statistics of China, savings deposits reached up to 28.7 trillion dollars in 2019, with an increase of 2.3 trillion dollars by year-end. Total saving deposits amounted to 28 trillion dollars, while foreign currency loans across all financial intuitions totalled 23 trillion. Consequently, an adequate credit supply is vital for fostering a supportive financial environment that drives economic development to higher levels. Moreover, a sound economic environment facilitates energy development. In addition, the role of financial development is particularly significant. Early work, such as Schumpeter (1934), highlighted the relationship between finance and growth, emphasizing that expanding the financial sector is a crucial prerequisite for growth in the real economy. Later studies support this concept (Beck et al., 2000; Beck & Levine, 2004; Demirgüç-Kunt & Levine, 1996; and Levine & Zervos, 1998). Although this relationship has a solid theoretical foundation, empirical research has often overlooked the impact of financial development on economic growth. According to Andersen and Tarp (2003), the connection between financial development and economic growth is more nuanced and less conventional than other economic theories. Some researchers argued that "too much finance" can hinder economic growth by diverting resources from the real economy and creating instability (Arcand et al., 2015; Cecchetti & Kharroubi, 2012; Dabla-Norris & Srivisal, 2013). The essence of these studies is that an excessively developed financial sector may divert human capital from the real sector, leading to macroeconomic and financial fragility, which can undermine the broader economy instead of an economic boost. As economic growth drives financial development and energy consumption, it might be relevant to note that the financial development and energy consumption are crucial for enhancing social productivity (Khan et al., 2019; Rafindadi & Ozturk, 2016; Shahbaz et al., 2013, 2017). In the context of China's revolutionary strategy, economic growth influenced by financial development is critical, as it helps optimize the energy ecosystem and facilitate coordinated development in a multi-agent economy, thereby ensuring sustainable economic growth. Moreover, non-economic factors, particularly institutional factors, are increasingly recognized for their role in economic growth. Traditionally, most researchers focused exclusively on the nexus between economic factors and growth. According to Maruta et al. (2020), institutional factors are critical to economic growth and highlight the importance of governance in maintaining proper checks and balances on institutional quality. Institutional or governance quality is measured through the www.ce.vizja.pl 314 The Role of Environmental Quality, Financial Development and Institutional Quality in Sustainable Economic Growth: Evidence from China This work is licensed under a Creative Commons Attribution 4.0 International License. Worldwide Governance Indicators (WGIs) provided by the World Bank, which are widely relied upon by policymakers and academics. The WGIs have six dimensions for institutional quality: voice and accountability, political stability, government effectiveness, regulatory quality, the rule of law, and control of corruption. Generally, a robust governance system is advantageous for a country' 's economic growth. However, its impact varies significantly in regions or nations with weak institutional performance. For instance, freedom of speech, combined with freedom of the press and democratic accountability, plays a pivotal role in enhancing economic development. Democracy is also an essential condition for the efficient functioning of a market economy and fostering economic growth. According to the Asian Development Bank (ADB), while the economic performance of Asian countries is relatively strong compared to other regions, their poor institutional quality remains a significant obstacle to attracting foreign investment, promoting trade, and achieving sustainable economic development. Previous studies have also established a significant association between economic growth and direct and indirect governance (Adams & Mengistu, 2008; Ndulu & O'Connell, 1999; Pradhan, 2011). To the authors' knowledge, the combined roles of environmental quality, institutional quality, and financial development have not been examined exclusively and empirically in previous research. Therefore, this study aims to empirically explore the relationship between environmental quality, financial development and institutional quality in relation to economic performance in China. Furthermore, the findings of this study offer countryspecific insights that can guide global economies in addressing developmental diversity, particularly in the context of infrastructure development.This study also contributes to the literature by providing theoretical guidance on the interplay between these factors and their collective impact on economic performance. Previous studies have lacked a multivariate framework, resulting in insufficient models for capturing the complexities of economic performance. By incorporating environmental quality, financial development, and institutional quality, this study seeks to develop a comprehensive model to understand better and improve economic growth. Many existing studies rely on direct regression analysis between two variables, which risks producing spurious results. To address this limitation, the present study employs advanced econometric techniques, including quantile regression, to identify the critical determinants of China's economic growth. This study further examines the moderating impact of institutional quality on the relationship between environmental quality, financial development, and economic performance within China's economy. By assessing these linkages across different economic development levels, this research addresses key deficiencies in the existing literature and provides actionable insights for policymakers and academics. The remainder of the study is structured as follows: Section 2 synthesizes the relevant literature, Section 3 outlines the methodology, and the results are presented and discussed in Section 4. The final section concludes the study with recommendations and directions for future research. 2. Literature Review2. Literature Review This section reviews the previous research on the subject matter, which is organized into three main segments. The first segment focuses on environmental quality and economic growth. The second segment examines financial development and economic growth, while the final segment discusses institutional quality and economic growth. 2.1. Environmental Quality and Economic Growth The Environmental Kuznets Curve (EKC) is a widely recognized theory for understanding the link between environmental quality and economic growth. According to the theory, an increase in income growth initially leads to higher environmental pollution. However, as income levels continue to rise, a threshold is reached where further income growth results in a reduction in environmental pollution. This creates an inverted U-shaped curve, suggesting that economic growth initially contributes to pollution, but eventually leads to its decline. The EKC connection is influenced by 315 Cai, Rahman, Fareed, and Khan 10.5709/ce.1897-9254.568DOI: CONTEMPORARY ECONOMICS Vol. 19 Issue 3 312-3282025 a variety of interconnected factors, including the composition of production and consumption, the size of the economy, the vintage of technology, the structure of economic activity, income inequalities, forms of energy use, environmental priorities, and the effectiveness of regulations. Along similar lines, a strand of recent literature (Zhang & Zhao, 2024; Wang et al., 2024) highlights how green finance and renewable energy intersect with economic growth and environmental quality within the framework of the EKC hypothesis. In the past three decades, the Chinese economy has experienced exponential growth. In the 1970s, the government of China introduced market reforms, and since then, China has maintained the growth rate of approximately 9.70% per annum (BP, 2010). This rapid economic expansion has allowed China to lift itself out of extreme poverty. With the increase in economic growth, the demand for fossil fuels has also risen, making China one of the largest producers of CO2 emission. In addition to fossil fuels, China is the world's largest consumer of crude oil, accounting for 46.9% of global consumption (BP, 2010). According to Crompton and Wu (2005), China consumed 31%, 10.7%, 7.6%, and 1.2% of the world's coal, hydroelectricity, crude oil, and gas, respectively, in 2003. Furthermore, in 2009, consumption increased by 46.9% for coal, 18.8% for hydroelectricity, 10.4% for crude oil, and 3.0% for gas. This trend of rising fuel consumption continues each year. While energy consumption brings benefits, it also poses significant drawbacks. For instance, it has a strong negative impacts on the environment (Soytas & Sari, 2003). Environmentalists have found that as energy consumption increaes, pollutant emission also rise, contributing to global warming (Si et al., 2021; Rahman, 2024). The government should support private firms in investing in innovation and production of renewable energy sources like solar, hydro, and wind. This shift would reduce the region's resilience on fossil fuels, which are an expensive environmentally harmful option (Aziz et al., 2020). Green growth is one of the essential elements for achieving sustainable development. Like many other South Asian countries, China relies on natural resource exploitation to meet its growth objectives. Therefore, effective policies are crucial for ensuring both sustainability and economic growth (Ahmed et al., 2022). Incremental increases in energy use to achieve higher growth result in higher CO2 emissions, leading to environmental degradation. Financial development, however, can mitigate these effects by promoting investments in energy-efficient technologies, as demonstrated in the case of Portugal (Shahbaz et al., 2015). This highlights the challenge many countries face in achieving coordinated economic development while addressing environmental concerns (Wang et al., 2021). Global warming is a primary concern related to economic growth and current energy sources. Therefore, minimizing carbon emissions, particularly CO2, is crucial to mitigating global warming. Mardani et al. (2019) emphasize that CO2 emissions are a major greenhouse gas (GHG), playing a central role in maintaining the planet’s habitablility. CO2 emissions, which result from human activities and fossil fuel consumption, are the primary driver of global warming. Furthermore, fossil fuels account for approximately 80% of GHG emissions (Soytas & Sari, 2003). Further, the Stanford Woods Institute for the Environment (2019) reports that controlling carbon emissions could reduce them by 50% by 2030. It is also worth noting that carbon emissions could be reduced to zero if the proposed practices are implemented by 2050. Using the Long-range Integrated Development Analysis (LINDA) model, Luukkanen et al. (2015) demonstrate that CO2 emissions could reduce to one-third of their current level by 2030. However, Mladenović et al. (2016) argued that carbon emissions in relation to economic growth and population, could be predicted by employing techniques such as Support Vector Machine (SVM), genetic programming (GP), and Artificial Neural Network (ANN). According to Mardani et al. (2019), CO2 emissions and economic growth remain critical issues that require immediate attention. To address the carbon emission problem and predict future emissions, Sun et al. (2017) used Particle Swarm Optimization (PSO) and the Extreme Learning Machine (ELM) method. Their study demonstrates that the www.ce.vizja.pl 316 The Role of Environmental Quality, Financial Development and Institutional Quality in Sustainable Economic Growth: Evidence from China This work is licensed under a Creative Commons Attribution 4.0 International License. proposed method is accurate and suitable for future applications. Based on previous literature and the above discussion, it is concluded that creating a carbon-efficient economy is a global challenge that demands immediate attention from researchers and policymakers, along with a solid strategy to address this issue. According to recent studies, the financial sector must assess the ecological viability of projects before providing funding for their completion (Kihombo et al., 2021). 2.2. Financial Development and Economic Growth In the current context, the ongoing issue regarding financial development theory is the complex relationship between financial development and economic growth. According to King and Levine (1993), numerous studies have addressed the link between financial development and economic growth, yet their findings remain inconclusive. Countries focusing on financial development to boost economic growth can achieve this by efficiently allocating resources (Shahbaz et al., 2022). While financial development influences economic growth, the significance and magnitude of this effect vary depending on the specific context (Boikos et al., 2022). Therefore, the existing literature can be divided into three segments. The first segment asserts that financial development significantly influences economic growth (Nyasha, 2015; Yang, 2019). According to the growth model outlined by Diallo & Al-Titi (2017), financial development positively affects local-level economic growth. Similarly, using data from China's Beijing– Tianjin–Hebei region, Wang et al. (2019) found similar results to those of Diallo and Al-Titi (2017). The second segment of the literature suggests a negative association between financial development and economic growth (Ouyang & Li, 2018; Sassi & Gasmi, 2014). Sassi and Gasmi (2014) used data from 27 European countries from January 1995 to December 2012 and found a negative relationship between financial development and economic growth. They attributed this negative relationship to the heterogeneity of financial development across the 27 European countries. In contrast, several studies (Liu & Zhang, 2020; Luukkanen et al., 2015; S. Wang et al., 2016; Yang, 2014) highlight the non-linearity between financial development and economic growth. For instance, Liu and Zhang (2020) examined the financial structure mechanism and economic growth across 29 provinces in China from 1996 to 2013. The study found an inverse U-shaped relationship between financial structure and economic growth. Additionally, Law and Singh (2014) used data from 87 countries to provide evidence of a nonlinear relationship between financial development and economic growth. Their study revealed threshold effects, suggesting that economic growth is primarily influenced by the lack of financial development. Similarly, the non-linear impact of financial development on economic growth is also observed in the context of China (Chen et al., 2013; Guender, 2018). However, despite extensive empirical analysis and theoretical support, the literature on the relationahip between financial development and economic growth remain inconclusive. 2 .3. Institutional Quality and Economic Growth Institutions play a crucial role in promoting economic development and driving economic progress. Poor institutional quality undermines capital accumulation and income distribution (Qamruzzaman, 2022). The significant role of institutions is emphasized in existing literature, highlighting factors such as governmental efficiency, government mechanism, democracy and freedom, and property protection for fostering economic growth (Acemoglu et al., 2005; Rodrik, 2018; Ploeg & Poelhekke, 2010). Institutional quality positively influences a country's economic development (Singh & Pradhan, 2022). Economic growth depends on how people adapt themselves to the existing institutional context and institutional change (Urbano, Audretsch, Aparicio, & Noguera, 2020). In theory, institutional quality has a critical macroeconomic role. Its relationship with economic growth is optimal in ensuring economic development (Mehmood, Mohy Ul Din, Aman‐ Ullah, Khan, & Fareed, 2023). These studies argue that a single index cannot adequately capture the performance of institutional quality over time at the country level. They also contend that investment, 317 Cai, Rahman, Fareed, and Khan 10.5709/ce.1897-9254.568DOI: CONTEMPORARY ECONOMICS Vol. 19 Issue 3 312-3282025 financial development, and institutional quality variables can be further explored within the context of economic development dynamics, which are essestial to understanding the growth processes (Brunnschweiler & Bulte, 2008; Rodrik, 2018). Lastly, the studies mentioned above did not address how institutional quality influences economic growth with varying effects at different stages. Previous literature shows both negative and positive significant associations between institutional quality and economic growth (Acemoglu & Robinson, 2008; Sarmidi et al., 2014). Similarly, improvements in institutional quality may reduce trade barriers in the international market and promote economic growth (Kurtz & Brooks, 2011; Lederman & Maloney, 2006). Economists and policy experts worldwide agree that institutional quality is crucial in determining growth differentials. Kilishi et al. (2013) used the GMM system approach to test the role of institutional quality in determining the economic performance of Sub-Saharan Africa (SSA). Their empirical evidence showed that regulatory quality is critical for the economic performance of SSA. This finding underscores the importance of regulatory quality in improving SSA's performance. Similarly, Vianna and Mollick (2018) conducted a similar study on 192 countries, specifically focusing on Latin America between 1996 and 2015. They found that every 0.1% improvement in institutional quality results in a 3.9% increase in per capita income and 2.6% increase in world development. These findings also highlight the limited opportunities and the weak rule of law in Latin America. Similarly, Butkiewicz and Yanikkaya (2006) emphasized that certain characteristics, such as the rule of law, significantly affect growth performance. They suggested that effectively implementing the rule of law can help improve a country's economic growth. Using data from 20 countries in a comparative study, Gurvich (2016) argued that most developmental programs failed in Russia between 2000 and 2010 due to a rigid institutional framework. They also suggested that economic growth is unattainable without proper institutional reforms. Institutions play a crucial role in enhancing various sectors of the economy. To the best of the author's knowledge, a gap exists in the existing literature regarding the combined effect of environmental quality, financial development, and institutional quality on economic growth, particularly in the context of the Chinese market. Therefore, country-specific implications can guide the region in formulating strategies that take into account its unique challenges and reforming its developmental approaches to foster economic growth. The next section of this paper presents the research methodoy used to conduct this research. Table 1 Description of Study Variables Variable Notation Measurement Sustainable Economic Growth SEG GDP growth (Annual %) Environmental Quality ENV CO2 Emission Per Capita Financial Development FND Domestic credit to the private sector by banks (% of GDP) Institutional Quality INQ The index is created using Principal Component Analysis (PCA) of six governance indicators: (1) Control of Corruption, (2) Government Effectiveness, (3) Political Stability and Absence of Violence or Terrorism, (4) Regulatory Quality, and (5) Rule of Law, and (6) Voice and Accountability. The percentile rank is used as a reference. Debt DTE External debt stocks, public and publicly guaranteed (PPG) Global Index GEI S&P Global Equity Indices (annual % change) Note. The SEG, FND, INQ, DTE and GEI data is collected from the World Development Indicators (WDI, 2019). The data for the ENV is collected from the Knoema Data Base. For brevity, we do not include the PCA. However, the results of the PCA are available on request. www.ce.vizja.pl 318 The Role of Environmental Quality, Financial Development and Institutional Quality in Sustainable Economic Growth: Evidence from China This work is licensed under a Creative Commons Attribution 4.0 International License. 3. Research Methodology3. Research Methodology 3.1. Data Sources and Study Variables This study used quarterly data from 2002 to 2019 to examine 'China's sustainable economic growth determinants. The dependent variable is measured by the Gross Domestic Product (GDP) growth rate, following the approach suggested by Sala-i-Martin and Barro (1995), who argued that economic growth in developing countries is often low and is better assessed through growth per capita. The study incorporates three critical independent variables: (1) environmental quality, (2) financial development, and (3) institutional quality. Carbon dioxide (CO2) emission per capita was used to measure environmental quality, reflecting the environmental impact of economic activities. The proxy aligns with the Environmental Kuznets Curve (EKC) hypothesis, which posits a relationship between economic growth and environmental quality. The role of banks in economic development is well-documented, with bank credit serving as a critical indicator of financial development and a primary source of enterprise financing and growth. Considering the structure of China's financial market, this study uses the balance of credit funds for financial institutions as a proxy for financial development (Obeng-Amponsah et al., 2019). This measure is consistent with the Finance-Growth Nexus, which underscores the importance of financial systems in fostering economic growth. Institutional quality (IQ) is also included as a critical variable based on the framework developed by Acemoglu and Robinson (2008), who emphasized the role of institutions in addressing economic inequalities and promoting growth. While previous studies often used the democracy or polity index to measure institutional quality (Brunnschweiler & Bulte, 2008; Sachs & Warner, 2001), this study employs six governance indicators from the World Bank to capture a broader perspective of institutional quality. These indicators include voice and accountability, control of corruption, the rule of law, political stability, regulatory quality, and government effectiveness. These dimensions align with theories linking governance quality to economic performance, particularly in emerging economies. In addition to these core variables, the study incorporates two control variables: public debt and global index performance. The relationship between public debt and economic growth has been widely discussed in the literature, with numerous studies exploring their interdependence (Reinhart & Rogoff, 2010; Josten, 2002; Easterly, 2001). Global index performance, representing the stock market's overall performance, is included to account for the impact of international trade and financial flows on China' 's economy (Arslanalp et al., 2016). This variable reflects China' 's interconnectedness with global economic systems and its vulnerability to external shocks. A conceptual framework links these variables to the theoretical models underpinning this. These include the EKC hypothesis for environmental quality, the Finance-Growth Nexus for financial development, and governance theories for institutional quality. This framework ensures theoretical grounding for the empirical analysis. The notations, measurements and sources of selected variables are provided in Table I. 3.2. Empirical Model This study aims to investigate the relationship between economic growth (GDP) and its key determinants, such as environment quality (ENV), financial development (FnD), institutional quality (INQ), Debt (DTE) and global index performance (GEI). The analysis of these factors aims to provide a comprehensive understanding of how each influences economic growth. The relationship using a simple regression framework, as outlined below. (1) All the variables are defined in Table I. We also include the squared term of ENV in model 1 to examine the Environmental Kuznets Curve (EKC) suggested by Rahman et al. (2020). The independent variables are expected to be correlated, possibly leading to multicollinearity issues. To address this, we apply instrumental variable analysis to isolate the effect of each independent variable from potential group effects. In this study, institutional quality is treated as a moderating variable, measured using a composite index of six indicators: voice and accountability, political stability, absence of violence, government effectiveness, regulatory quality, the rule of law, and control of corruption. The interaction terms between institutional quality and the other independent variables are presented in equations 2 to 5. 319 Cai, Rahman, Fareed, and Khan 10.5709/ce.1897-9254.568DOI: CONTEMPORARY ECONOMICS Vol. 19 Issue 3 312-3282025 (2) (3) (4) (5) Moreover, we employed quantile regression to enhance the robustness of the empirical model. Quantile regression was conducted at the 50th, 75th, and 90th percentiles to examine the impact of predictor variables across different dependent variable levels. The coefficients at these percentiles also change with each unit change in the predictor variable. Quantile regression provides more reliable coefficient estimates by minimizing the influence of outlines compared to traditional least squares regression. (6) (7) (8) (9) Quantile regression is considered a suitable tool for addressing variables with distributional characteristics and handling time series data (Angrist & Pischke, 2008). According to Andriansyah and Messinis (2016), quantile regression is particularly well-suited for analyzing economic growth due to its ability to account for distributional characteristics. It also provides the added advantage of explaining the relationship between variables beyond just the mean. This technique helps uncover non-normal and non-linear relationships between variables. Table 2 Descriptive Statistics SEG ENV FND INQ DTE GEI Mean 9.0900 6.3717 130.7655 0.0000 138.5081 15.8165 Median 9.2662 7.0720 126.0474 -0.6178 108.4710 7.0895 Maximum 14.2309 8.2319 164.6643 3.5135 318.0652 80.7194 Minimum 6.1101 3.0294 101.9897 -1.8396 83.7359 -52.7044 Std. Dev. 2.1764 1.5473 19.0577 1.6339 64.1347 36.6699 Skewness 0.6832 -0.7023 0.3193 0.9990 1.4788 0.3700 Kurtosis 2.7857 2.1547 1.8771 2.7652 4.4436 2.3200 Jarque-Bera 5.7386 8.0619 5.0058 12.1404 32.4932 3.0300 Probability 0.0567 0.0178 0.0818 0.0023 0.0000 0.2198 VIF 3.201 4.021 3.958 2.936 4.025 3.162 Sum 654.4825 458.7600 9415.1130 0.0000 9972.5850 1138.7890 Sum Sq. Dev. 336.3111 169.9847 25786.9000 189.5451 292041.8000 95472.5600 Observations 72 72 72 72 72 72 Note. SEG, ENV, FND, INQ, DTE and GEI indicate sustainable economic growth, environmental quality, institutional quality, external debt stock and global equity index. For further details, see Table 1. www.ce.vizja.pl 326 The Role of Environmental Quality, Financial Development and Institutional Quality in Sustainable Economic Growth: Evidence from China This work is licensed under a Creative Commons Attribution 4.0 International License. ports on CO2 emissions. Applied Energy, 104, 258–267. 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