of FDI capital, financial development, the urgent situation of the environment, the strong development of the Industrial Revolution 4.0, and the need for development policies suitable to
INTRODUCE
Reason
The study of economic growth has evolved significantly from the early theories of Adam Smith and Malthus, highlighting its essential role in the development of nations and the global economy (Boldeanu & Constantinescu, 2015) As economic conditions change over time, various theories have emerged, addressing different factors that influence growth It is crucial to identify these impactful factors and explore strategies to ensure sustainable economic development while addressing real-world challenges.
When talking about issues affecting economic growth, Athukorala (2003), Falki
Research by Hlavacek & Bal-Domanska (2016), Kunie et al (2014), and others has examined the influence of foreign direct investment (FDI) on the economic growth of various nations, including Sri Lanka, Pakistan, Nigeria, and several countries in Central and Eastern Europe.
Recent research highlights the significant role of foreign direct investment (FDI) in financing and fostering economic growth, alongside the development of the financial sector While FDI has been shown to have both positive and negative impacts on economic growth, a consistent relationship between FDI and financial development has been established through studies from Schumpeter (1911) to Hong (2015) and Kieu et al (2016) To harness the potential of FDI and financial development for economic advancement, it is essential to conduct broader and more recent studies with a regional focus, providing empirical evidence on their effects on global economic growth In an ever-changing economic landscape, up-to-date research is vital for informed decision-making.
In the context of the Industrial Revolution 4.0, technology and digital infrastructure are crucial driving forces behind economic growth Economists and policymakers are increasingly focused on the impact of digital technology on the economy, with debates surrounding its potential to create jobs or lead to unemployment While concerns about disruptions to traditional industries exist, there is also optimism about new opportunities The role of Information and Communication Technology (ICT) in transforming manufacturing processes across various sectors has garnered significant attention, yet empirical evidence on its contribution to economic growth remains limited Understanding the relationship between ICT and economic growth is essential for APEC countries to develop effective solutions that foster economic advancement, making it vital to recognize both the opportunities and challenges presented by ICT for optimal economic development.
The overexploitation of natural resources to support economic growth has led to significant environmental degradation and pollution, particularly through the rise of CO2 emissions driven by trade, industrialization, urbanization, and deforestation over the past thirty years (Sarwar et al., 2019) Fossil fuel energy is a major contributor to these environmental issues, releasing harmful pollutants and posing a serious threat to climate stability in both developing and developed nations (Muhammad & Khan, 2019) This situation highlights the urgent need for environmental protection to mitigate negative impacts on human health while promoting sustainable development Consequently, researchers and policymakers are increasingly focusing on environmental reforms aimed at addressing climate challenges linked to fossil fuel consumption and non-renewable energy sources, with a particular emphasis on reducing energy demand through innovative products and processes (Shahzad, 2020; Shahzad et al.).
Efforts to combat global warming and lower CO2 emissions are now central to climate policies worldwide Vietnam's rapid industrialization has severely impacted its ecosystem and natural resources, highlighting the critical need for environmental protection As a result, maintaining green development is essential for the future Understanding the relationship between CO2 emissions and economic growth remains a key focus for researchers, as this knowledge can help identify strategies to reduce emissions while promoting economic growth.
In contemporary discussions on economic growth, the focus has expanded beyond foreign direct investment (FDI) and financial development to include critical issues such as CO2 emissions and digital infrastructure Understanding the effects of CO2 emissions on both the environment and economic growth is essential, as is recognizing the significance of digital infrastructure in achieving CO2 reduction goals This research will explore the varying impacts of FDI, financial development, information and communication technology (ICT), and CO2 emissions on economic growth, comparing developed and developing countries.
Recent studies exploring the combined effects of foreign direct investment (FDI), financial development, digital infrastructure, and CO2 emissions on economic growth are still emerging, with limited existing literature This research aims to enhance the understanding of how CO2 emissions, information and communication technology (ICT), FDI, and financial development influence economic growth within the APEC region, particularly among developed and developing nations As the 2030 Sustainable Development Goals approach, it is crucial for policymakers, governments, and researchers to seek solutions that harmonize ecological balance with economic progress, prompting this investigation into the topic.
This study investigates the impact of foreign direct investment (FDI), financial development, CO2 emissions, and digital infrastructure on the economic growth of APEC countries It aims to provide policy recommendations that promote sustainable economic development by enhancing industrial structures within these nations.
Particular objectives
This research aims to provide empirical evidence and analysis on the interplay between financial development (FDL), digital infrastructure, CO2 emissions, and economic growth, while also examining the interactions among these variables.
• Firstly, determine whether foreign direct investment (FDI) and financial development promote economic growth.
The study examines the interaction between foreign direct investment (FDI) and financial development to determine if domestic financial development acts as a catalyst for economic growth It aims to provide evidence on whether FDI contributes to economic growth within the host country.
This study investigates the influence of digital infrastructure on economic growth and aims to propose policies that enhance efficiency and overall economic development, while also offering solutions tailored for the economies of APEC countries.
• Fourth, this study aims to understand the impact of CO2 emissions on economic growth, thereby providing policy suggestions for sustainable economic growth and development.
• Finally, the study aims to understand the impact of FDI, financial development, ICT and CO2 emissions on economic growth in both developed and developing country groups.
Research subjects and scope of study
Between 2000 and 2020, the Asia-Pacific Economic Cooperation (APEC) region, excluding Taiwan, experienced significant economic growth influenced by various factors Foreign direct investment (FDI) played a crucial role in enhancing economic performance, while financial development contributed to more robust financial systems Additionally, the relationship between CO2 emissions and economic growth highlighted the need for sustainable practices, and the advancement of digital infrastructure facilitated increased connectivity and innovation Together, these elements shaped the economic landscape of APEC countries and territories during this period.
About content: research focusing on issues such as economic growth, foreign direct investment (FDI), financial development, digital infrastructure (ICT - Information and Communication Technology), and CO2 emissions.
The analysis focused on 20 countries and territories within the Asia-Pacific Economic Cooperation (APEC), excluding Taiwan The countries examined include Australia, Brunei Darussalam, Canada, Chile, China, Hong Kong, Indonesia, Japan, South Korea, Malaysia, Mexico, New Zealand, Papua New Guinea, Peru, the Philippines, Russia, Singapore, Thailand, the United States, and Vietnam.
About time: Research data was collected in the period from 2000-2020.
LITERATURE REVIEW
FD1
2.1.1 The impact of FDI on economic growth
Foreign direct investment (FDI) involves the transfer of capital or assets between countries and is recognized as a crucial driver of economic growth Various economic growth theories, including classical, exogenous, and endogenous growth theories, highlight the significant positive effects of FDI on economic development Over time, economists have produced diverse findings regarding the relationship between FDI and economic growth This analysis will explore these theories and clarify the essential role of FDI in fostering economic advancement.
Classical economists like Adam Smith, Thomas Malthus, and David Ricardo have extensively analyzed economic growth, focusing on production factors such as labor, capital, and land Smith's theory, established in 1776, emphasized the significance of land and population in economic expansion, positing that population growth is linked to food supply availability He argued that investment, determined by the savings rate, is crucial for growth, with income distribution being a key factor Conversely, Ricardo highlighted the necessity of increasing inputs for output growth, noting that limited land resources lead to higher production costs and reduced profits for landowners This dynamic results in increased prices and lower laborer profits, ultimately constraining investment and hindering economic growth.
Karl Marx (1818-1883) expanded on the factors influencing economic growth, including land, labor, capital, and technological progress, unlike Adam Smith and Ricardo He contended that labor supply is not a determinant of wages, as bargaining and declining profit rates do not hinder capital accumulation but instead lead to wage reductions, exacerbating workers' suffering Marx asserted that capitalists could enhance their profit margins by incorporating machinery into production, yet he also noted that technological advancements, such as mechanization and labor division, do not necessarily yield entirely positive effects on growth.
In addition, Keynesian analysis with the Harrod-Domar model (Harrod, 1939; Domar,
In 1947, it was posited that an increase in savings rates could drive higher economic growth, as a country's income is derived from both savings for investment and consumption This theory suggests that a higher savings rate correlates with accelerated growth Subsequently, Kaldor (1957) argued that savings levels could fluctuate, ultimately stabilizing to ensure that the real growth rate aligns with its expected trajectory.
The exogenous growth theory, exemplified by Solow's neoclassical growth model from 1957, effectively captured global economic growth trends between 1950 and 1970 Unlike Keynesian models, the Solow model allows for flexible substitution between capital and labor while treating land as a fixed resource, which is substituted by physical capital This distinction is significant as capital can be produced and accumulated, leading to enhanced production capacity and improved labor productivity Consequently, the Solow model addresses the law of diminishing returns by demonstrating that increased capital investment can mitigate its negative effects.
The Solow model highlights the significance of capital and savings in production, suggesting that countries with higher saving rates or lower population growth tend to achieve greater long-term per capita income However, it fails to explain the consistent upward trend in average incomes globally over time.
Average income growth is not solely driven by increased savings, as evidenced by the lack of a corresponding decline in real interest rates This observation prompts a new research direction, suggesting that advancements in technology can lead to increases in both average capital and income over time The extended Solow model incorporates technological progress, highlighting that under conditions of perfect technology spillover, technology functions as a public good Consequently, no individual is incentivized to produce new technology, as the outputs are fully utilized by inputs, leaving no rewards for technological contributions Thus, the model assumes that technological growth occurs exogenously, due to the absence of incentives for innovation.
The exogenous growth theory has limitations in explaining long-term growth determinants, leading to the development of subsequent economic growth theories (Barro, 1990) Nonetheless, it suggests that foreign direct investment (FDI) enhances capital in the host country, promoting economic growth through capital accumulation and influencing total domestic investment (Herzer et al., 2008).
The endogenous growth model posits that technology is an endogenous variable influenced by knowledge capital, which includes knowledge spillovers, human capital, and R&D activities This relationship suggests that output is linked to capital, labor, and knowledge, with a focus on how their interaction fosters economic growth According to Romer (1986), economic growth results from technological progress driven by capital accumulation, where increased capital leads to enhanced knowledge through knowledge spillovers The non-conflict nature of pervasive knowledge allows for returns to scale, supporting sustained long-term economic growth Endogenous growth theory indicates that returns to scale can differ between countries, suggesting that nations with lower capital stocks will not necessarily grow faster than those with higher reserves Investment is crucial for promoting economic growth, as emphasized by Lucas (1988), and de Mello (1999) argues that FDI is more effective than domestic investment due to its long-term benefits on technology transfer and human capital development Ultimately, through technology diffusion, labor mobility, and management training, FDI positively influences economic growth.
Foreign investment significantly enhances the productivity of the host country, aligning with the principles of endogenous growth theory This theory, rooted in neoclassical growth concepts, emphasizes that capital investment is a crucial factor influencing economic growth.
Research indicates that foreign direct investment (FDI) has the potential to boost economic growth, as suggested by various growth models and analyses However, empirical studies and real-world observations reveal mixed outcomes regarding the relationship between FDI and the economic development of host countries.
Research indicates that foreign direct investment (FDI) significantly contributes to economic growth in both direct and indirect manners FDI serves as a crucial source of capital for host countries, fostering economic acceleration Studies highlight that FDI can enhance growth through spillover effects, including the introduction of new technologies, capital formation, human resource development, job creation, and the expansion of international trade Notably, de Mello's 1997 analysis of FDI's impact on economic growth across 32 countries from 1970 to 1990 supports these findings.
A comprehensive analysis involving 17 OECD and 15 non-OECD countries reveals that Foreign Direct Investment (FDI) significantly enhances economic growth, primarily through the infusion of capital, technology, and skilled human resources Supporting this, De Gregorio (1992) found a positive correlation between FDI and economic growth in 12 Latin American countries, indicating that FDI outperforms domestic investment in productivity Similar findings emerged from Yao (2006) in 28 Chinese provinces (1978-2000), Upadhyaya et al (2007) in Eastern Europe, and Pegkas (2015) in Eurozone countries (2002-2012), all confirming the robust positive impact of FDI on economic growth Borensztein et al (1998) further emphasized that FDI contributes to growth through industrial transmission channels However, the effectiveness of FDI is influenced by the quality of human resources in the host country, along with factors such as low costs, minimal tariff barriers, and a favorable investment climate, which collectively enhance the benefits of FDI for developing economies.
Several studies indicate a negative relationship between foreign direct investment (FDI) and economic growth For example, Hong (2015) utilized differential GMM estimation on data from 45 countries, including those in the ASEAN region, from 1995 to 2013, revealing that FDI adversely affects economic growth in host countries Additionally, FDI appears to foster economic growth more effectively in developed nations compared to developing ones The author attributes this discrepancy to various factors, including political, economic, legal, and cultural influences, as well as per capita income and political risks Similarly, Falki (2009) examined FDI's impact on Pakistan's economic growth from 1980 to 2006, finding a negative and statistically insignificant relationship Other studies, such as those by Bende-Nabende et al (2001), Li & Liu (2005), and Chaudhury et al (2020), corroborate these findings across different countries and time frames.
Financial development
2.2.1 The impact of financial development on economic growth
The financial system is crucial for economic growth, as it generates investment information, monitors corporate investments and risks, mobilizes savings, and facilitates beneficial transactions (Levine, 2005) Schumpeter's early research (1911) emphasized that financial development is essential for economic progress, asserting that innovation in financial intermediaries enables businesses to access credit necessary for implementing technological advancements and enhancing business operations This perspective aligns with the views of Levine (2005), Goldsmith (1969), and Vanags (1971), highlighting the interconnectedness of financial innovation and economic development.
The development of financial systems is crucial for promoting economic growth, as established by Shaw (1955) and supported by McKinnon (2010) and Shaw (1973) In countries with advanced financial markets, economic growth is enhanced through increased savings and improved investment efficiency Financial markets are essential for providing liquidity to investors, as noted by Diamond and Dybvig (1983) Furthermore, financial intermediaries play a vital role in minimizing unproductive liquid asset holdings and preventing capital misallocation due to liquidity constraints, as highlighted by Bencivenga and Smith (1991).
& Stiglitz (1980) also show that the stock market stimulates the production of information about firms and with the growing liquid financial markets, agents easily gather information and seek profits.
Many researchers have chosen topics related to financial development and economic growth as a guideline for their research work These can be mentioned as the study by King
A study by Levine (1993) involving 80 countries from 1960 to 1989 revealed a positive correlation between economic growth and financial development, attributed to financial development enhancing profits through innovative service provision Supporting this, additional research by Rioja & Valev (2004) and Rousseau & Wachtel (2001) also found that financial development positively impacts economic growth.
Several studies suggest that financial development may negatively impact economic growth For instance, Lan & Trung (2019) found an inverted U-shaped relationship between bank credit and economic growth using panel data from over 135 countries between 1961 and 2015, indicating that exceeding a credit-to-GDP ratio of 103% can hinder growth Similarly, Kieu et al (2016) reported a negative relationship between financial development and economic growth in eight Southeast Asian countries from 1995 to 2014 Hong (2015) also highlighted this negative impact across 45 countries, including those in the ASEAN region, during 1995-2013, revealing that the effects vary among developed, developing, and underdeveloped nations Specifically, financial development positively influences growth in developed countries, while it adversely affects the other two groups due to the greater stability of their financial systems This pattern is supported by findings from Chee & Nair (2010) and Loayza & Rancière (2006), which attribute the negative impact to the instability and fragility of financial systems in developing and underdeveloped countries.
CO2 Emission
2.3.1 The relationship between CO2 emission and economic growth
Carbon dioxide (CO2) is a colorless, odorless gas produced from carbon combustion and respiration, recognized as a significant greenhouse gas that traps heat in the Earth's atmosphere, leading to climate change and global warming High levels of CO2 emissions contribute to rising global temperatures, with projections indicating an increase of 5 to 6°C by the century's end if current trends continue The Glasgow Climate Accord (COP26) emphasizes the urgent need for commitments to reduce greenhouse gas emissions and transition to low-carbon energy systems to achieve net-zero emissions by 2050 As climate change concerns escalate, countries are rapidly shifting towards low-carbon economic development and implementing strategies to limit carbon emissions in line with the Paris Agreement However, this transition presents challenges, particularly for nations like China, where rapid economic growth has been accompanied by increased energy consumption and greenhouse gas emissions.
To develop effective policies for sustainable development goals, it is essential to understand the complex relationship between CO2 emissions and economic growth across different regions While existing literature offers valuable insights, there remains a lack of consensus on this relationship, which can vary significantly; it may be non-existent, bidirectional, or solely influenced by CO2 emissions affecting economic growth Specifically, the dynamics of CO2 emissions and economic growth in APEC countries are not yet fully understood This study aims to investigate the impact of CO2 emissions on economic growth within APEC countries and to explore the variations among different groups within the region.
Numerous studies support the existence of the Kuznets curve, including Maddison's (2008) analysis of the causal relationship between economic growth and CO2 emissions through Granger tests on panel data from 134 countries between 1990 and 2005, revealing a two-way relationship between GDP and CO2 emissions across various income groups Esteve & Tamarit (2012) also demonstrated a connection between CO2 emissions and per capita income in Spain from 1857 to 2007, confirming the presence of the Kuznets curve Additionally, Mamun et al (2014) examined 136 countries from 1980 to 2009, categorizing them into five income groups, and found that the Kuznets curve is prevalent globally, except among high-income countries.
Research indicates an N-shaped relationship between CO2 emissions and economic growth A study by Akpan & Chuku (2011) focused on Nigeria from 1960 to 2008, revealing that economic growth is significantly linked to heightened environmental degradation in both the short and long term.
Similarly, Adebayo et al, (2020) also found that the relationship between CO2 emissions and economic growth is N-shaped.
Numerous experimental studies challenge the validity of the Environmental Kuznets Curve (EKC) theory For instance, Galeotti et al (2006) examined panel data from 24 OECD countries between 1960 and 2002, revealing that the EKC remains a fragile concept Similarly, research by Chebbi & Boujelbene (2008) in Tunisia (1971-2004) and Saboori et al (2011) in Iran (1971-2007) utilized the ARDL distributed lag regression method and also found no support for the EKC, indicating that rising pollution levels accompany economic growth.
Digital infrastructure
2.4.1 Impact of digital infrastructure (ICT - Information and Communication
Digital infrastructure, particularly through information and communication technology (ICT), has emerged as a dynamic investment area over the past decade, significantly influencing economic and industrial structures since the 1990s The COVID-19 pandemic highlighted the critical role of ICT in facilitating the "new normal," demonstrating its capacity to drive technical innovation and enhance productivity Romer (1986) argues that long-term economic growth is linked to improvements in production quality, which are increasingly evident in larger countries Furthermore, ICT fosters idea dissemination among institutions and enhances competition, leading to the development of innovative products and effective macroeconomic activities Classical endogenous theory supports the notion that ICT contributes to economic prosperity by introducing new processes, products, and business models.
Information and Communication Technology (ICT) significantly boosts business revenue by reducing costs, creating new job opportunities, and enhancing market efficiency, particularly in lower-middle-income and low-income countries (Zeng, 2023; Abid et al., 2023; Karaman Aksentijevic et al., 2021) While the benefits of ICT-induced productivity gains are evident in these economies, their impact is less pronounced in high- and middle-income nations Innovations driven by ICT foster economic change and competitiveness across all sectors, with research indicating that a 1% increase in Internet users can reduce inflation's impact by 40% (Chowdhury, 2006) Despite the transformative effects of ICT on manufacturing and the overall market expansion, macroeconomic data often fails to capture its growth impact, leading to a decline in growth rates over decades, a phenomenon known as the Solow paradox (Maurseth, 2018).
Numerous researchers have explored the link between Information and Communication Technology (ICT) and economic growth, with many studies highlighting ICT as a key driver of economic development (Thong et al., 2020; Zhang et al., 2022) Notably, Choi & Yi (2009) conducted a study using cross-country panel data from 1990 to 2015, revealing that while ICT spurred economic growth from 1990 to 2000, it exhibited significant negative effects on economic growth during the 1990-2015 period.
A study by Mahyideen & Ismail (2012) examined the relationship between Information and Communication Technology (ICT) and economic growth in several ASEAN countries from 1980 to 2009 Utilizing the OLS regression method, the findings indicated a positive correlation between ICT and economic growth Similarly, research conducted by Toader et al supports these results.
(2018) (European Union for the period of 18 years from 2000-2017) and research by Nam
Research from 2006 to 2020 indicates that digital infrastructure, or ICT, positively influences economic growth in Vietnam, although some studies, such as Kenny (2003) and Pohjola (2002), suggest a negligible impact due to outdated technology in developing nations Kallal et al (2021) found that while ICT positively affects long-term growth in Tunisia, it may have short-term negative effects Papaioannou & Dimelis (2007) concluded that ICT investment primarily fosters growth in developed countries, whereas Appiah-Otoo & Song (2021) revealed that ICT boosts economic growth in both rich and poor countries, with greater gains observed in poorer nations Niebel (2018) highlighted a significant positive link between ICT and economic development across 59 countries, though differences in output elasticities between developing and developed countries were minimal Additionally, Yousefi (2011) noted that the impact of ICT is more pronounced in middle-income countries, underscoring the influence of a country's income level on the benefits derived from telecommunications advancements.
The relationship between variables FDI, financial development, and
The impact of Foreign Direct Investment (FDI) on economic growth through financial sector development has garnered significant research interest Studies indicate that a robust financial system is vital for fostering a market economy, prompting countries to attract FDI Financial development enhances the ability of FDI recipient nations to fully leverage capital inflows, ultimately leading to positive economic growth outcomes However, research by Hermes & Lensink (2003) reveals that only 37 of 67 countries in Latin America and Asia possess sufficiently developed financial systems to enable FDI's positive contribution to growth Their findings suggest that while FDI initially shows a negative regression coefficient, the interaction between FDI and financial development yields a statistically significant positive effect Conversely, many Sub-Saharan African countries exhibit weak financial systems, hindering FDI's benefits Additionally, Hong (2015) found no significant impact of financial development on the FDI-economic growth relationship in ASEAN countries during the 1995 period.
In 2013, the author highlighted that the financial system's instability in the ASEAN region may lead to a non-statistically significant interaction between foreign direct investment (FDI) and financial development The findings indicate that this interaction variable positively influences developing and underdeveloped countries, with the highest regression coefficient observed in underdeveloped nations This suggests that financial development plays a crucial role in enhancing the relationship between FDI and economic growth, particularly in underdeveloped countries FDI is shown to stimulate economic growth primarily when the financial development index is sufficiently high, indicating that the host country's economy can only fully leverage FDI benefits when its domestic financial market reaches a certain level of maturity (Azman-Saini et al., 2010).
DATA AND RESEARCH METHODOLOGY
Data
The study analyzes data from 20 APEC countries collected from 2000 to 2020, focusing on the growing interdependence of Asia-Pacific economies and the rise of regional trade blocs Established to strengthen economic and political ties, APEC's data primarily comes from the World Bank and the International Monetary Fund (IMF), with detailed sources for each variable listed in Table 3.2.
Asia-Pacific Economic Cooperation (APEC)
Regression model and variables
Building on Hong's (2015) research that explores the effects of foreign direct investment (FDI) and financial development on economic growth, this study further investigates how CO2 emissions and digital infrastructure also influence this relationship.
Previous studies on CO2 emissions and climate change-related issues have prompted countries to transition to low-carbon economic development (Stern, 2007; Zhou and Li,
In 2019, we developed a model to explore the causal relationship between CO2 emissions and economic growth, specifically analyzing how CO2 emissions influence the examined variable.
In today's technology-driven world, developing robust digital infrastructure is crucial for countries aiming for sustainable economic growth According to Romer's (1986) research, long-term economic growth is fueled by increasing returns to scale, which are primarily achieved through technological advancements This phenomenon is more pronounced in developed nations than in their developing counterparts Therefore, our regression model will incorporate digital infrastructure to analyze its impact on economic growth and to investigate the disparities in growth between developed and developing countries in relation to technological differences.
From all of the above, we have the regression model below:
GROWTH = p„ + p,FDI + p FINDEV + p,(FDI X FINDEV ) + p4CO2 + p TECH +
Where the variables are defined as follows:
Economic growth can be effectively measured using various indicators, with real GDP per capita being a prominent choice According to Boldeanu & Constantinescu (2015) and Hong (2015), this approach accurately reflects economic growth In this study, the GROWTH variable is defined as real GDP per capita and is calculated using annual data sourced from the World Bank.
Foreign direct investment (FDI) plays a crucial role in driving economic growth in countries, offering a range of advantages to the host nation Economic theories highlight FDI as a key determinant of growth, measured by the ratio of net FDI inflows to real GDP, with data sourced from the World Bank Research by Khan et al (2023) indicates that FDI positively influences economic growth Therefore, we anticipate that our study will reveal a positive regression coefficient for the FDI variable.
Hypothesis 1: FDI positively influences economic growth
There is no single proxy variable that accurately represents a country's financial development index, leading to ongoing debates about the connection between financial development and economic growth Numerous measurable variables exist, each assessed through various indicators to evaluate financial development For this study, we have selected specific metrics to analyze financial development effectively.
Value ofcredits to private sectorallocated by financial intermediaries (PRỈCRE):
One of the metrics used in this study to measure financial development is the variable
The percentage of "credits to the private sector" relative to real GDP, sourced from the World Bank, is a key indicator of financial development Calderon & Liu (2003) argue that this metric effectively highlights the credit provided by financial intermediaries to the private sector, intentionally excluding public sector credit and central bank-affiliated sectors This focus offers a clearer understanding of the investment-growth relationship, as increased credit to the private sector indicates higher market liquidity, ultimately fostering economic growth.
Liquidity index of the financial system (LỈQLỈA):
The M2 money supply, which encompasses the total money issued by the central bank, includes currency in circulation and commercial bank deposits, as well as savings accounts, demand deposits, and term deposits at credit institutions This measure is calculated based on real GDP and is crucial for assessing financial viability, as a country's ability to generate money reflects the strength of its capital markets Consequently, nations with a higher capacity to generate money tend to experience positive economic growth, driving them towards achieving their growth objectives.
A robust financial system plays a crucial role in promoting economic growth by enabling the efficient transfer of capital from underdeveloped areas to regions where it can be used more effectively, as highlighted by Schumpeter (1911) This process not only optimizes resource allocation but also fosters overall economic development, a concept supported by Calderon & Liu.
In 2023, research shows that financial development plays a crucial role in fostering economic growth by facilitating the efficient and optimal use of accumulated capital As a result, we expect that the indicators of financial development will positively influence economic growth.
Hypothesis 2: FINDEV in both representative variables positively influences economic growth.
Interaction variable (FDI and Financial development - FDIX FINDEV)
This study explores the relationship between foreign direct investment (FDI) and financial development, highlighting the importance of FDI in economic growth, particularly within the financial sector Previous research by Lee and Chang (2009) and Hong (2015) indicates that the interaction between FDI and financial development (FDI X FINDEV) positively impacts economic growth Therefore, we expect to find a positive regression coefficient for the FDI X FINDEV variable, suggesting a beneficial effect on economic growth in our analysis.
Hypothesis 3: The interaction between FDI and Financial development positively influences economic growth.
The rising levels of CO2 emissions present a significant challenge for both developing and developed nations, as they are closely linked to economic growth Efficient energy utilization often leads to increased emissions, raising environmental concerns (Muhammad & Khan, 2019) Research by Lee & Brahmasrene (2014) indicates that rapid economic growth correlates with higher CO2 emissions This study investigates the causal relationship between CO2 emissions and economic growth rates, particularly in countries reliant on natural resources, suggesting that higher per capita CO2 emissions may positively influence economic growth.
Hypothesis 4: CO2 emissions positively influences economic growth
Digital infrastructure is assessed by the percentage of the population accessing the Internet Numerous studies have shown that enhancing digital infrastructure, especially through the expansion of telecommunications networks, can lead to substantial increases in real GDP per capita Research conducted by Liao & Zeng further supports these findings, highlighting the positive impact of such investments on economic growth.
In 2023, research indicates that digital infrastructure significantly boosts economic growth by optimizing energy use in production, distribution, and operations It also enhances productivity by creating social networks, encouraging technology spillovers, and lowering transaction costs Therefore, we expect digital infrastructure to positively influence economic growth.
Hypothesis 5: Digital infrastructure positively influences economic growth
For our study, we include several control variables that have been commonly used in previous research due to their significant impact on economic growth These variables are as follows:
This study measures trade openness by calculating the total import and export volume relative to real GDP, following the methodology of Ibrahim et al (2021) Recognized as a crucial indicator of economic growth in a globalized world, trade openness enhances resource allocation and facilitates the transfer of technology and knowledge through international exchanges Research by Kong et al (2021) provides empirical evidence of the significant positive impact of trade openness on economic growth Therefore, we anticipate that trade openness will positively influence economic growth in our analysis, resulting in a favorable regression coefficient.
Research methodology
3a Liquidity of the financial system
PRICRE Credits to private sector/real GDP (%)
4 CO2 emissions CO2 Metric tons per capita
TECH Percentage of population using the Internet (%)
6 Trade openness TRAOPE Total import and export/real GDP (%)
7 Population growth POPGO Population growth rate (%) —
GOVEXP Total government expenditure/real GDP (%)
GCF Gross capital formation/real GDP (%)
Before starting the research process, it is essential to test for stationarity in datasets with large sample sizes and numerous observations over time, as non-stationary data can result in inaccurate estimations and forecasts A data series is deemed stationary when its variance remains constant To assess stationarity, the authors employed the Fisher-type test by I Choi (2001) Stationary variables were incorporated into the research model, while non-stationary data underwent differencing to achieve stationarity Furthermore, a correlation analysis was performed using a correlation coefficient matrix, and the Variance Inflation Factor (VIF) was used to investigate multicollinearity among variables.
In panel data analysis, three primary methods are utilized: pooled ordinary least squares (OLS), fixed effects model (FEM), and random effects model (REM) The authors implemented these models and conducted quantitative tests to identify the most suitable option The F test was employed to differentiate between FEM and pooled OLS, with the null hypothesis positing that pooled OLS is appropriate Additionally, the Breusch-Pagan test assessed the choice between REM and OLS, assuming pooled OLS is a superior fit Finally, the Hausman test was applied to compare FEM and REM, with the hypothesis suggesting that REM is more efficient than FEM.
After selecting the appropriate model, the authors conducted tests for heteroscedasticity and autocorrelation, addressing any potential model misspecifications They utilized the Wooldridge test to identify autocorrelation, as its presence can render model results unreliable To ensure efficient estimates, the authors selected estimation methods that account for autocorrelation, comparing the p-value with significance levels of 1%, 5%, and 10% Additionally, they employed the Breusch and Pagan Lagrangian test to assess heteroscedasticity, noting that its presence can lead to biased and less effective model estimates.
In regression analysis, it is crucial to account for the seasonality of data and prior issues To enhance data stability, the authors developed a model that incorporates a dummy variable for the year, allowing for a thorough evaluation of the model's reliability.
To ensure the accuracy and reliability of the study, the authors employ Feasible Generalized Least Squares (FGLS) estimation after identifying the optimal model This method effectively addresses any existing misspecifications, thereby improving the robustness of the analysis and enhancing the credibility of the findings.
Implementation process
Step /: Select the factors affecting the economic growth of a country
Step 3: Check the data previously for regression analysis
Step 4: Determine the correlation relationship between the variables by calculating the correlation coefficient.
Purpose: Determine the degree of correlation between variables to select the independent variables that have a linear relationship with the dependent variables and eliminate multicollinearity between the independent variables.
Step 5: Determining the factors affecting the economic growth of a country can be done through the debt ratio criterion by analyzing simple linear regression, multiple linear regression and constructing a regression model.
Step 6: Check for violations of the model's assumptions and present research findings on these topics.
Step 7: Compare and analyze the differences between developed countries and developing countries.
RESULTS AND DISCUSSION
Unit root test
The initial step in conducting a regression analysis is to perform a unit root test to check for stationarity in the variables, excluding dummy variables This is crucial because most economic and financial data series are non-stationary, which can lead to unreliable model estimates To ensure the validity of the analysis, the author utilizes the widely recognized Phillips-Perron (PP) unit root test to evaluate the stationarity of the model's variables.
Table 4.1 Results of unit root tests on panel data
PP-statistic z(p-vakie) PP-stalistic z(p-value)
The symbols *** ** * represent statistical significance at I%, 5%, /0%, respectively
Source: Extracted results from EViews
The initial analysis indicates that the variables GROWTH, FDI, TECH, TRAOPE, and GCF are stable, while PRICRE, LiQLIA, CO2, POPGO, and GOVEXP remain non-stationary To address this issue, the author calculates the first difference of the non-stationary variables, leading to a stabilized series Following tests to ensure the stationarity of all research variables, the author integrates them into the model for further investigation.
Descriptive Statistics
Table 4.2 Descriptive statistics of the variables in the research model
Variables Observations Mean Standard Deviation Min Max
Source: Compilation of the author team from Stata 17.0
Table 4.2 provides descriptive statistics for the research model focusing on 20 Asia-Pacific Economic Cooperation (APEC) countries and territories, excluding Taiwan, with a total of 420 observations based on annual data The economic growth rate (GROWTH) of country i in year t serves as the dependent variable in both study models Key independent variables include net capital inflows (FDI), credit to the private sector (PRICRE), financial system liquidity index (LIQLIA), CO2 emissions (CO2), and digital infrastructure (TECH) Additionally, control variables such as trade openness (TRAOPE), population growth (POPGO), government spending (GOVEXP), and total capital (GCF) are incorporated into the analysis.
In 2020, Peru experienced the lowest economic growth rate among APEC countries at -12.15%, largely due to the severe impact of the COVID-19 pandemic, which adversely affected life safety, social welfare, and the commercial economy In contrast, China's growth rate peaked at 13.63% in 2007 The average growth rate for APEC countries and territories stands at 2.41% Additionally, foreign direct investment (FDI) data reveals that New Zealand had the lowest net capital inflow ratio at -3.81% in 2003, while Hong Kong recorded the highest.
(China) 58,51837 (2015) when this territory is always ranked among the freest economies in the world, simple tax system, good infrastructure, etc., the average net capital inflow of
APEC's private sector credit (PRICRE) averages 55.8888, with Mexico recording the lowest rate at 12.8777 in 2001 In contrast, Hong Kong, one of the world's leading financial centers, boasts the highest PRICRE rates.
In 2020, Hong Kong (China) recorded the highest value in the financial development index (LIQLIA) at 258.9028 In terms of CO2 emissions, Brunei led with the highest emissions at 21.7058, while Papua New Guinea had the lowest at just 0.5129 Additionally, digital infrastructure (TECH) reached a notable value of 96.5051.
(2020) in South Korea and the lowest is Vietnam with 0.2542 (2000), reaching an average value of 29,5680.
Correlation analysis of variables
The symbols ***, **, * represent statistical significance at I %, 5%, 10%, respectively
Source: Compiled by the author's team
Table 4.3 displays the correlation coefficients and VIF (Variance Inflation Factor) for the variables in the two research models The analysis reveals a significant relationship between the economic growth rate (GROWTH) at year t and the other independent variables, indicating a high level of statistical significance for the model, with the exception of trade openness (TRAOPE).
The analysis reveals a significant negative correlation between the first difference of the liquidity index of the financial system (DLIQLI A) and digital infrastructure (TECH) with the dependent variable (GROWTH), contradicting the author's initial expectations This suggests that advancements in financial development and digital infrastructure may hinder economic growth However, relying solely on the correlation coefficient matrix for conclusions can lead to biased results To accurately determine the impact of TRAOPE on GROWTH, it is essential to employ specific quantitative models that address model deficiencies, ensuring the research findings are robust, effective, and highly reliable.
The correlation coefficient between the independent variables serves as an important indicator of potential multicollinearity within the research model As indicated in Table 4.3, the correlation coefficient between the independent variables TRAOPE and FDI is 0.8056, exceeding the critical threshold of 0.8, which raises concerns about serious multicollinearity issues Nonetheless, subsequent regression analysis using the least squares method (OLS) revealed that the variance inflation factor (VIF) indices for all independent variables remained below the acceptable limit, suggesting that multicollinearity may not significantly impact the model.
10, from which it can be concluded that the multivariate phenomenon of collinearity does not significantly affect the results of the regression model.
Results and discussion
Table 4.4 Regression results with DLIQLIA
The symbols ***, ** * represent statistical significance al J %, 5%, 10%, respectively
Source: Compiled by the author's team
The regression analysis utilizing the REM method indicates that FDL DLIQLIA, DCO2, and TECH are statistically significant across the entire sample data In contrast, the interaction variable (FDI X FINDEV) does not demonstrate statistical significance Furthermore, statistical evidence from segmented samples, encompassing both developed and developing countries, reveals consistent results with high levels of statistical significance.
Foreign Direct Investment (FDI) significantly boosts economic growth, as evidenced by a 1% increase in inflows, supporting the group's hypothesis Particularly in 12 out of 20 developing APEC countries, FDI serves as a vital financial source, facilitating investments across various sectors and addressing employment challenges This shift contributes to industrialization and modernization, enhancing workers' income and expanding international trade Consistent with de Mello's (1997) findings, FDI positively influences economic growth by providing capital, technology, and skilled human resources Moreover, it enables developing nations to access advanced technologies and management practices, leading to higher productivity compared to domestic investments, aligning with De Gregorio's (1992) analysis of 12 Latin American countries Additionally, research by Borensztein et al (1998) indicates that FDI fosters economic growth through industrial transmission channels However, the impact of FDI is contingent on the quality of human resources in the host country, along with factors such as low costs, minimal tariff barriers, and a conducive investment environment In contrast, APEC-developed countries show no significant benefits from FDI, likely due to inadequate economic absorption capacity and unattractive tax and regulatory policies.
Foreign direct investment (FDI) significantly boosts economic growth, with a notable impact at the 1% level, particularly in 13 out of 20 APEC developing countries FDI serves as a vital source of capital that enhances employment, increases worker income, and facilitates labor restructuring towards industrialization and modernization It enables developing nations to access advanced technologies and management skills, fostering a competitive environment that compels domestic enterprises to innovate and improve their offerings This aligns with findings from various studies, including de Mello (1997), which demonstrated FDI's positive influence on the economic growth of 17 OECD countries, and De Gregorio (1992), who confirmed similar results in 12 Latin American countries Research by Upadhyaya et al (2007) and Pegkas (2015) highlighted FDI's strong impact on Eurozone economies from 2002 to 2012, while Yao (2006) found a positive effect in 28 Chinese provinces between 1978 and 2000 Additionally, Borenszlein et al (1998) concluded that FDI positively impacts economic growth in developing APEC countries, although this effect is moderated by the quality of human resources in the host country In contrast, developed APEC nations show no significant benefits from FDI, likely due to limited economic absorptive capacity and unattractive tax and regulatory policies.
Financial development, indicated by the liquidity of the financial system (DLIQLIA), is found to negatively impact economic growth at a 10% statistical significance level, which contradicts previous expectations This may stem from the fragility of financial systems in APEC countries, where participants often enter contracts to exchange a certain amount of money today for a larger future return, leading to inflated asset values Such dynamics can create economic bubbles driven by speculative "herd" behavior, resulting in significant sell-offs and subsequent recessions when investor interest wanes Historical crises, such as the 1997 Asian crisis and the 2007-2008 financial crisis, have underscored these vulnerabilities in APEC economies Supporting this, studies by Kieu et al (2016) and Hong (2015) reveal an inverse relationship between financial development and economic growth in several ASEAN countries, while research by Lan & Trung (2019) indicates that exceeding a credit-to-GDP ratio of 103% can adversely affect growth by increasing financial risks While developed APEC nations remain insulated from these effects, developing countries within the region experience significant negative impacts due to their unstable financial systems.
The study indicates that the interaction between foreign direct investment (FDI) and financial development (FINDEV) does not significantly influence economic growth, likely due to the instability and fragility of financial systems in APEC countries and territories.
The interaction between foreign direct investment (FDI) and financial development in APEC countries shows no significant impact on economic growth, largely due to the fragility of their financial systems This fragility, exacerbated by global market variability, makes these export-dependent economies particularly vulnerable to fluctuations in international markets, such as changes in export demand and commodity prices Additionally, unforeseen financial crises, rising global interest rates, and political instability further contribute to uncertainty in the relationship between FDI and financial development Cultural and local factors also play a role, creating a complex business environment across the region These findings align with Hong's (2015) study, which indicated that the instability of financial systems in ASEAN countries led to a lack of impact on the FDI-economic growth relationship from 1995 to 2013 Notably, while the interaction variable is positive for developing countries, it is negative for developed nations, highlighting the crucial role of financial development in fostering economic growth through FDI in developing contexts.
CO2 emissions (DCO2) significantly contribute to economic growth, with a statistical significance at the 1% level As highlighted by Muhammad & Khan (2019), the effective utilization of energy resources is essential for economic development in countries, which consequently leads to increased emissions that adversely affect the environment.
Faster economic growth is linked to higher CO2 emissions, as supported by recent research findings This correlation aligns with previous studies, highlighting that economic expansion typically results in increased energy production and consumption Developing countries, in particular, face significant energy demands to sustain their production levels and support their communities.
The combustion of fossil fuels like coal, oil, and natural gas significantly increases CO2 emissions, particularly as energy demand rises during economic development This is exacerbated by reliance on outdated, inefficient energy industries that consume large amounts of energy while producing excessive CO2 compared to cleaner sources Economic growth also elevates living standards and consumption, further straining energy resources and contributing to CO2 emissions The rapid rise in atmospheric CO2 poses serious environmental challenges, leading to global warming and extreme weather events that threaten agricultural production, biodiversity, and the livelihoods of billions Additionally, CO2 absorption by oceans results in ocean acidification, harming marine ecosystems and fishing industries Research indicates that CO2 emissions have a more pronounced impact on economic growth in developed countries compared to developing nations, highlighting the significant correlation between pollution levels and economic expansion.
Digital infrastructure significantly impacts economic growth, exhibiting a negative correlation due to ineffective implementation of digital projects stemming from limited skills and knowledge High costs associated with information and communication technology (ICT) further exacerbate this issue, as many countries lack the necessary financial resources Low productivity hampers trade in goods and services, while inadequate infrastructure fails to leverage ICT opportunities effectively However, the COVID-19 pandemic has sparked a notable interest in digital development, transforming global habits and positioning ICT as a key growth driver in many countries This aligns with findings from Kallal et al (2021), which highlighted similar trends in Tunisia during the period from 1997.
Research indicates that while Information and Communication Technology (ICT) positively influences long-term economic growth, it can have a negative effect in the short term This finding aligns with studies on the relationship between ICT and economic growth in developing nations, which represent 12 out of 20 APEC countries Conversely, the impact of ICT on economic growth in developed countries remains ambiguous, likely due to insufficient research data and a lack of universal applicability, which diminishes the overall credibility of the findings.
The analysis revealed that government expenditure (DGOVEXP) negatively impacts economic growth, while gross capital formation (GCF) positively influences it, aligning with the findings of Afonso & Furceri (2010) and Barro (1990) In contrast, trade openness (TRAOPE) and population growth (DPOPGO) showed no significant relationship with economic growth The lack of competitive advantage of private investment over government spending, along with issues like ineffective government investment, wastefulness, and corruption, may explain the negative effects on growth Additionally, GCF supports increased investment, enhances production capacity, fosters infrastructure development, boosts consumption, creates jobs, and attracts foreign investment, consistent with Fauzel's (2016) research.
4.4.2 Check the robustness of the research model by using the DPRICRE variable
The authors further tested the robustness of the research model by incorporating the DPRICRE variable, which demonstrated that the independent variables significantly influence the GROWTH variable, aligning with the findings from the DLIQLIA model The research results confirmed that the authors successfully achieved their initial objectives, as the use of DPRICRE yielded comparable outcomes, reinforcing the reliability of the regression findings.
Table 4.5 Regression results with DPRICRE
The symbols ***, **, * represent statistical significance at I %, 5%, 10%, respectively
Source: Compiled by the author's team
4.4.3 Check the robustness of the research model by using the seasonal adjustment
A key challenge in regression analysis is the seasonality of data, which can impact its stability Research by Zaremba et al (2021) and Bakry et al (2022) suggests that to mitigate seasonality effects, incorporating year dummy variables into the research model is an effective approach.
GROWTH = p„ + p.FDI + p.FINDEV., + p.(FDI X FINDEV) + p,CO2 + p,TECH, + p,CONTROLS, + s&YS TlMDUM,k + £,,
The regression analysis indicates that TIMDƯM1 through TIMDUM2 represent binary variables for the years 2000 to 2020, with TIMDƯM1 equal to 1 for 2000 and 0 for other years, and so forth for subsequent years After seasonal adjustment, the dataset remains statistically significant, with regression coefficients closely mirroring those without adjustment The impact of FDL DCO2 and TECH retains its directionality and significance at the 1% level, enhancing the reliability of the study's findings Conversely, DLIQLIA lacks statistical significance, while the interaction variable achieves significance at the 10% level, prompting further investigation using the FGLS method.
Table 4.6 Regression results by seasonal adjustment
The symbols *** ** * represent statistical significance at Ỉ%, 5%, 10%, respectively
Source: Compiled by the author's team
4.4.4 Check the robustness of the research model by using the FGLS method