Abstract
At the present time, information and communication technology (ICT) has played a vital role in socio-economic development such as economic growth, literacy, life expectancy, and employment levels in societies, however, such development has come with various environmental damages perspectives. This study scrutinizes the impact of ICT, economic growth, and foreign direct investment (FDI) on carbon dioxide (CO2) emissions in the 44 One Belt and Road Initiative (OBRI) countries split into sub-region from 1991 to 2019. This study applied various econometrics approaches such as cross-sectional dependence, second-generation unit root, and Westerlund panel cointegration techniques are executed to analyze the panel data set. The full modified ordinary lease square and dynamic ordinary lease square estimators are applied to investigate the long–term influence of ICT development, GDP (economic growth), and FDI on CO2 emissions. The empirical analysis was performed at a disaggregated level to assess the possible environmental influences across the OBRI countries. Overall, the results reported that broadband and mobile development have an adverse effect on CO2 emissions. The finding further reveals that the broadband indicator negatively affects CO2 emissions in all OBRI regions except South Asia. Similarly, the mobile use indicator protects the environmental quality in all OBRI regions except MENA (Middle East and North Africa) and Central Asia. Regarding country-wise analysis, broadband has alleviated the pollution level in 21 countries, while mobile has alleviated it in 15 countries. Moreover, economic growth is responsible to increase pollution levels in all panels and regions except Europe. Besides, the results highlight that higher FDI reduces environmental pollution whereby, the pollution halo hypothesis is supported to hold for all OBRI panels and regions except MENA countries. Based on the empirical findings, the policymakers and governments of these economies should design policies to grow smarter cities, transportation systems, electrical grids, industrial processes, and energy-saving production through ICT development on a macro level.
Keywords
Introduction
The significant impact of information and communication technology (ICT) on the socioeconomic development of society has been an extensively debated topic over the last couple of decades. In the current era of economic integration, a rapid increase in ICT sector development contributes to all divisions of an economy, however, its environmental penalties cannot be overlooked. Moreover, ICT is a vital indicator in the development of the industrialization process through a significant upsurge in the utilization of energy resources which negatively damages the environment (Dogan & Turkekul, 2016). In spite of being causative to gross domestic product (GDP), the quick alteration to the industrialization has carried environmental contamination and sternly influence the health and morals of human beings. It is the foundation for assessing climate variation, adapting and mitigating its impacts, and helping in the conversion to an eco-friendly nation (Zhang & Liu, 2015; Faisal et al., 2020; Mirza et al., 2020). Irrespective of the effective applications of ICT development in a country very slight devotion has been given to the upcoming environmental penalties of ICT for instance, the internet, mobile phones, satellites, etc. All these technologies play a vital part in handling the main challenges of Sustainable Development Goals (SDGs) regarding climate variation and global warming. The 17 United Nation Sustainable Development Goals (SDGs) seek to mobilize worldwide efforts around a common set of goals and targets and establish the priorities and aspirations for global sustainable development for the year 2030. Within the constraints of the planet, the SDGs encourage governments, businesses, and members of civil society all over the world to act to eradicate poverty, create a life of dignity and opportunity for all people, and ensure environmental sustainability (Mirza et al., 2020). Additionally, in the modern era of digitalization, it is important to recognize the carbon inferences of ICT while addressing the challenges of climate change (Jiang et al., 2022; Wang et al., 2015; Lu, 2018).
The linkages between environmental quality and ICT are very complicated (Danish, 2019; Asongu, 2018). A series of related literature postulates that ICT development affects environmental quality through three different channels. First, the “use effect” means that during the ICT equipment production, distribution, processing, and installation waste considerably contributes to environmental pollution. Likewise, hazardous ICT equipment and e-waste output, for instance, mobile data traffic use and large global data centers pose a risk to environmental quality (Ibrahim & Waziri, 2020). It is observed that approximately 2–3% of global carbon dioxide (CO2) emission is generated by the production of ICT equipment (Danish, 2019). Second, the “substitution effect” depicts that ICT sector development influences the environmental quality through reorganization of the production process including, dematerialization, demobilization, decarbonization reducing outdoor activities, smart transport systems, quick traffic control structure using closed-circuit television (CCTV) cameras, replacement of physical goods with e-books, teleconferences, and post mail with email (Ozcan & Apergis, 2018; Park et al., 2018; Salahuddin et al., 2016; Usman & Radulescu, 2022). Likewise, online distribution and dematerialization, management and monitoring applications, travel and transport substitution, recycling, and product stewardship together diminish energy consumption and carbon dioxide emissions. Third, the “cost-effective” explores that ICT development increases demand other goods due to a reduction in prices consequently increasing environmental pollution. In the meantime, ICT development increase trade flow and other economic activities, enabling new communication networks and this may affect environmental quality. In this context, OBRI CO2 emissions (metric tons per capita) increased from 476.5 to 497.4 from 1991 to 2019 (Figure 1). CO2 emissions (metric tons per capita) in OBRI over the tested period.
It is observed that the impact of ICT sector development on environmental excellence is not only vague and indefinite but multifaceted in nature for both developed and developing nations is also unclear how the decisions about the implementation and deployment of ICT will affect the excellence of the environment which leads to distinction in the economic development sustainability. For that reason, exploring the impact of ICT sector development on environmental excellence is a hot issue that needs to be addressed on urgent bases. Additionally, global warming and climate variations have now a universal challenge that interrupts the economies and people’s health severely. Some other global environmental challenges should be addressed on early bases such as upgrading in energy efficiency, loss of natural habitat, waste management, biodiversity, water superiority, and CO2 emissions. The fundamental objective of this current paper is to scrutinize the impacts of ICT development on environmental excellence from the viewpoint of belt and road initiative (OBRI) economies. It links ICT and environmental quality while considering GDP, and foreign direct investment (FDI) as control variables. Sketchily, this study will try to explore how the internet and mobile use are useful in tackling the environmental quality issue in the OBRI economies.
The importance of including FDI is that along with the quick upsurge in FDI and trade actions, the tendency of ICT sector growth has enlarged speedily across the world. So, there is a necessity to discover the answer to the question; does ICT recover or worsen environmental excellence? Moreover, there are several reasons behind the selection of OBRI economies for this study. First, these economies interact with each other based on FDI, GDP growth, and trade openness. The Belt and Road project is started by China for validating the association of trade among 60 economies beyond Europe, Africa, and Asia continents. Moreover, ICT plays a vital role in economic integrations from side to side of FDI and helps in promoting trade collaboration. Hence, ICT has a significant and constructive influence on communication channels for infrastructure development, trade transport, investment flows, global connectivity, and socio-economic partnership among companies, firms, people, and economies along Belt and Road corridors (Oliveira et al., 2020; Qiang et al., 2022). Second, the maintenance of infrastructure, operation, and large-scale construction, especially roads that consume a big amount of steel, cement, power plants, bridges, and dams, need a big volume of fossil energy utilization that leads to higher environmental pollution levels (Danish, 2019). As a result, abating environmental pollution is crucial and it is very complicated to protect environmental quality during the execution of the “Belt and Road” project. Other distinctive features of this study include the use of a large sample of OBRIcountries for the available dataset, the introduction of some important indicators related to economic development like GDP growth, and FDI, and the use of a full modified ordinary least-square (FMOLS), and dynamic ordinary least-square (DOLS) models for the empirical estimation.
The rest of the paper is planned as follows. The bellow sections provide the litrature review, data and empirical framework, econometric strategy, results and discussion, and finally concludes the study with suitable policy recommendations.
Literature Review
The nexus between ICT development and environmental quality has been documented in a plethora of studies. In order to explain the nexus between numerous variables of this study, the literature has been divided into different categories. There are a plethora of studies available in the literature which explores the association between ICT development, GDP, and environmental dilapidation. In this regard, many researchers applied different econometric approaches to discover the long-term and short-term nexus between these variables (Ibrahim & Waziri, 2020). According to Higón et al. (2017), GDP directs that an economy produces more products and services, mostly with the use of ICT, and economic growth leads to an increase in ICT goods and services which enhances the utilization of electricity and ultimately CO2 emissions. Furthermore, Asongu (2018) examined the link between ICT, carbon emissions, and trade openness in the case of Africa. This study determined that ICT growth can help in lowering the possible negative impact of the globalization process on the environment. Another research conducted by Zhang and Liu (2015) revealed that ICT industries diminished environmental contamination in China for the period of 2000–2010. For OECD economies, Salahuddin et al. (2016) analyzed the influence of ICT development on environmental contamination using the pool mean group (PMG) approach. The conclusions approve the long-term association among the candidate variables. Also, this study postulated that GDP, financial development, and trade significantly diminish the environmental contamination in the panel of OECD nations. Similarly, Shahiduzzaman and Alam (2014) explored the nexuses between GDP growth, and ICT development and extend the empirical scrutiny with the association between GDP and non-ICT products for the Australian economy. The empirical evidence confirmed the causalities discover from ICT development to GDP growth and non-ICT products to GDP growth. Moreover, Binuyo (2015) found similar results and confirmed the positive impact of ICT development on GDP growth in the long run.
In addition, Batool et al., (2022) explored the linkages between ICT development and CO2 emissions in selected developing countries of East and South Asia over the period from 1985 to 2020. The PMG estimator findings suggest that ICT and financial development (FD) positively contribute to the dilapidation of environment excellence in the long term, while their influence on environmental contamination is insignificant in the short term. Khan et al., (2022) conclusions recommend that ICT and effective governance are the crucial indicators to reduce environmental contamination. Danish (2019) described that the introduction of innovative industrial processes, transportation systems, smart cities, and energy-saving output on a universal scale is predictable to alleviate environmental contamination. Similarly, Lennerfors et al. (2015) claimed that ICT is a crucial factor for CO2 emissions mitigation in many sectors of an economy like finance, industrial, transport, energy, and agriculture sectors. Instead of using workers on a large scale in different sectors, the usage of labor-saving machines can be supportive in improving environmental quality. Furthermore, Nchofoung & Asongu, 2022 noted that ICT sector development has a positive and significant effect on sustainable development in the case of a global sample. Moreover, (Zafar et al., 2022) conclusions recommend that ICT and financial development upsurge environmental excellence.
Some researchers divided the association between ICT and environmental excellence into two different strands. First-strand of the literature concluded that ICT development alleviates environmental pollution (Zhang & Liu, 2015; Wang et al., 2015; Lu, 2018). Consistent with this argument, Ozcan and Apergis (2018) analyzed the influence of internet use on environmental contamination and determined that the use of the internet plays a key role in the reduction of pollution levels in developing countries. Similarly, Al-Mulali et al., (2015) reported that online shopping (a proxy for ICT) has a positive inspiration on environmental excellence because internet usage lowers outdoor actions that decrease energy utilization. In contrast, the second strand of literature highlights the adverse influences of ICT development on environmental excellence. In this regard, Lee et al. (2016) described that ICT usage stimulates environmental contamination. However, Lee and Brahmasrene (2014) confirmed that ICT contributes to both CO2 emissions and GDP growth in ASEAN economies. Similarly, Asongu (2018) studied the African nations and verified the positive association between ICT and environmental contamination. Likewise, in Europe, Park et al., (2018) confirmed that ICT contributes to environmental pollution through a significant increase in CO2 emissions levels in the long run.
For the economic growth and environmental degradation relationship, it is observed in many studies that this relationship is nonlinear in nature. In this regard, a well-known theory Environmental Kuznets curve (EKC) developed by Grossman & Kruger (1995) exists in the literature. The EKC hypothesis postulates that initially, environmental quality effects are initially low at the lower economic growth levels. However, pollution increases as economic growth proceed in an economy. Further, at higher economic growth levels, economies are able through structural transformation to substitute towards agricultural and industrial technologies that are less damaging to the environmental quality. Literature reports that GDP growth affects the environmental quality through three different channels. First, income through “scale effect” depicts that the environmental damages, compromising technological change and economic structure. Second, the “composition effect” lower down the hazardous impacts of income through the structural change in a country. Third, the “technique effect” that shows the significant deficiency in pollution levels due to the implication of stringent environmental standards and adaptation of eco-friendly technologies. Danish (2019) described that the domination of technique and composition effect over scale effect leads to the establishment of an inverted U-shaped connection between environmental degradation and per capita income.
A seminal contribution is made by Dogan and Turkekul (2016) who examined the legitimacy of EKC for the US economy. Using data from 1960 to 2010, this study concluded that the findings are not supporting the inverted U-shaped relationship between economic growth and environmental damage. Additionally, this study established bidirectional causal linkages between GDP and environmental quality via using Granger causality. On the other hand, Dogan et al. (2017) study explored the linkages between GDP growth and CO2 for OECD economies and confirmed the long-term association between understudy variables under the EKC framework. Massagony and Budiono (2022) study explored the linkages between GDP and CO2 emissions for Indonesia’s economy and found that the EKC hypothesis is not valid for CO2 emissions in Indonesia. However, the EKC is valid in the PIIGS region (Balsalobre-Lorente et al., 2022).
It is observed that there are still many deficiencies that prevail in the existing literature. First of all, earlier studies are mainly based on individually developed economies like Australia, the EU, the UK, and the USA or disaggregated developing economies using cross-sectional or time-series datasets. Other than the environmental quality challenges are faced by all economies together with developed and developing as well. For that reason, the authors need a panel data analysis as it can capture more accurate information and reduce estimation bias. Second, the majority of the earlier studies emphasized the influence of ICT development on electricity consumption or energy efficiency, and less emphasis on the direct impact of ICT sector development on environmental quality. Furthermore, most of the earlier studies have applied conventional/traditional regression techniques to analyze the impact of ICT development on environmental pollution. Therefore, the findings based on this study are vulnerable.
A review of previous literature points out that there is no clear consensus related to the impact of ICT development on environmental quality. Numerous researchers used various sets of variables and different kinds of econometrical models to explore the ICT-environment nexus. However, the authors observed that the study on the ICT-environment nexus is limited for developed and developing economies. In this pursuit, there is no serious attempt has been made yet with the perspective of countries along with the Belt and Road project. This study is an attempt to seal these gaps in the literature. The inconclusive relation between ICT and CO2 emissions and no empirical study on Belt and Road economies motivated us to re-investigate this relationship with an effective set of series and appropriate econometrical techniques.
Data, Empirical Framework, and Methods
Data Specifications
List of a Selected Panel of OBRI Countries.
OBRI = One belt and road initiative.
Description of Variables.
Empirical Framework
This study investigates the relationship between ICT development and environmental quality while, considering GDP growth, and FDI as control variables. CO2 emission is a dependent variable, and fixed broadband and mobile cellular are independent variables for empirical analysis. However, GDP and FDI are used as control variables to avoid model specification bias. The empirical model specification of this study is followed by Asongu (2018) and Danish (2019). To capture the impact of ICT development on environmental quality, the econometric model of this study is presented as follows
Methods
Cross-Sectional Dependency
The possible cross-sectional dependency (CSD) across panel countries is an essential assumption considered in panel data models. The CSD emanates due to ICT development, GDP growth, and FDI, GLOB, economic integration, externalities (spatial or spillover), unknown common shocks, and undefined residual dependency. The presence of CSD support in the error term is acquired from the model analyzed by Pesaran (2007). The CSD equation is given as
Panel Unit Root Test
To investigate the panel data’s stationarity properties in the presence of CSD, a unit root test that can control for CSD can generate reliable results. The first-generation unit root tests lack this property, as these tests assume the panel cross-sections to be homogeneous and independent, leading to biased and misleading results (Chandio et al., 2022). The unit root tests of the second-generation kind are thus selected to capture the order of integration for the study variables. Pesaran (2007) recommended two tests, the cross-section augmented Dickey-Fuller (CADF) and the cross-section Im-Pesaran and Shin (CIPS) to check series stationarity. Based on the assumption of heterogeneity, both CADF and CIPS can generate more robust and consistent results in CSD presence. The equation for the CADF is written as
Panel Cointegration Test
The panel cointegration tests are applied when the variables are not level stationery. Hence, the present study employs the panel cointegration technique of Westerlund (2007) to explore the variables’ long-run interactions based on error correction. There are no common factor limitations imposed by the four simple structural-based Westerlund panel cointegration tests and are robust against the panel’s CSD. The appearance of the Westerlund cointegration approach is as follows
Long-Run Cointegration Test
This study uses FMOLS and DOLS estimation tactics to estimate the impact of ICT, GDP, and FDI on CO2 emissions. The variables under consideration are primarily macroeconomic variables and they have a normal relationship between regressors and error terms. In this way, the ordinary least-square (OLS) approach gives unreliable and biased estimates. Regarding the regression model, when there is a certain degree of association between regressors and error terms, the FMOLS is a suitable method for empirical analysis (Faisal et al., 2020). Further, panel data has the problems of endogenous variables, which disturbs their decision and estimates. If these effects are ignored in the model, the omitted variables problem would arise and estimates would be inconsistent. To confirm the findings of the FMOLS method, Also, FMOLS and DOLS estimators have eliminated the possible effects of serial correlation in the error term and endogeneity, which can increase the accuracy of the panel econometric model. The mathematical procedure of FMOLS evaluations is stated in equation (6) as follows
OBRI Countries Descriptive Statistics and Correlation Matrix.
Notes. *represents 1% level of significance. CO2 = Carbon dioxide; FDI = Foreign direct investment.
Empirical Results and Discussion
Cross-Sectional Dependency Test
CSD Test Results.
Note. Null hypothesis: no cross-sectional dependence, and ***p < .01, **p < .05, *p < .1 denote the level of significance. CSD = Cross-sectional dependency; OBRI = One belt and road initiative.
Panel Unit Root Tests
Panel Unit Root Statistics.
CO2 = Carbon dioxide; FDI = Foreign direct investment; OBRI = One belt and road initiative.
Panel Cointegration Test
Results of Westerlund Cointegration Test.
Note. Null hypothesis: no co-integration, level of significance is ***p < .01, **p < .05, *p < .1. OBRI = One belt and road initiative.
Regional Long-Run Elasticity/Coefficients
Results of FMOLS and DOLS Estimates (Region-wise).
Note. t-statistics are in presented in parentheses, and ***p < 0.01, **p < 0.05, *p < 0.1. FMOLS = Full modified ordinary lease square; FDI = Foreign direct investment; OBRI = One belt and road initiative; DOLS = Dynamic ordinary lease square.
However, mobile cellular has a negative impact on CO2 emissions in OBRI panel, South Asia, East and South East Asia, Europe, and Central Asia. This means that with the high usage of internet services along with mobile networks, these nations are producing energy-efficient ICT equipment, which furthermore improves energy utilization and eventually improves environmental excellence. This negative effect of mobile in this study is consistent with the findings of Lu (2018) for Asian countries. In this respect, mobile and internet have continued to improve the environment in the Asia region, because China, Japan, South Korea, and India are the new centers of eco-friendly manufacturing in the Asia region. In short, all ICT-related alterations in daily life outcome in less energy consumption and then very fewer carbon emissions. Although mobile has a positive influence on environmental contamination in the MENA region, it infers that mobile is not used in positive activities for the environment. They create environmental pollution through mobile information. Though, it can be understood that the coefficient of broadband is greater as compared to mobile, which specifies that the role of mobile in declining environmental excellence still needs public awareness in order to make it eco-friendly. Overall, FMOLS and DOLS have similar findings in direction but different in magnitude.
Additionally, GDP has an adverse impact on environmental contamination only in the Europe continent. This proposes that a 1% upsurge in GDP can lessen environmental contamination by 0.13% in FMOLS and 0.17% in DOLS. Although Salahuddin et al. (2016) also described the same conclusions for OECD nations. This outcome is similar to fast-emerging economies (Faisal et al., 2020) as it helps in producing more domestic output without hindering the environment. However, the domestic production of South Asia, East and South East Asia, MENA, and Central Asia are not environmentally clean, they produce more pollution for these economies. Similarly, the coefficient of FDI is a positive and statistically significant effect on environmental contamination only in the MENA region. The possible reason is that FDI leads to a further upsurge in energy utilization, which is the main reason for environmental contamination in MENA countries. This depicts that the pollution haven hypothesis prevails in this region. However, all other regions of OBRI have negative effects of FDI on pollution in South Asia, East and South East Asia, Europe, and Central Asia. This shows that the pollution halo hypothesis exists in these regions. Furthermore, the robustness of our empirical estimations has been verified by using the DOLS. The signs of Broadband, Mobile, GDP, and FDI remain robust in DOLS maintaining a similar level of significance.
Country-Wise Analysis
FMOLS Estimates (Country-wise).
Note. t-stats are in parentheses ***p < .01, **p < .05, *p < .1. FDI = Foreign direct investment.
However, on the other hand, mobile subscription has a negative impact on CO2 emissions for Bangladesh, Sri Lanka, China, Singapore, Thailand, Azerbaijan, Korea, Israel, Armenia, Azerbaijan, Georgia, Hungary, Latvia, Lithuania, Moldova, and Slovenia. The coefficient estimate of mobile subscription with CO2 emissions is positive for countries like India, Pakistan, Mongolia, Indonesia, Malaysia, Vietnam, Russia, Egypt, Iraq, Jordan, Saudi Arabia, Yemen, Morocco, Tunisia, Belarus, Bulgaria, Croatia, Czech Republic, Slovak Republic, Ukraine, Kazakhstan, and Uzbekistan. Regarding control variables, GDP has a positive significant effect on CO2 emissions for 30 out of 45 economies, this suggests every economy still consumes large amounts of fossil fuel to accelerate a country’s economic growth, in adverse, it enhances the CO2 emissions. This also indicates that GDP increases the economic size and dirty economic activities, which creates more pollution in an economy while GDP has a negative significant effect on carbon emissions in 7 economies. Similarly, a positive and significant impact of FDI on CO2 emissions is observed in 19 economies and also proved the “Pollution haven hypothesis” but a negative impact of FDI on CO2 emissions has been observed in 17 economies. These findings confirm the “Pollution halo hypothesis.” These economies allow only green FDI that is a more positive effect on environmental quality. Another channel of FDI is mainly improving the level of technological innovation by inducing social, human, and physical capital, thus affecting environmental pollution. The detailed empirical findings are reported in Table 8.
Conclusion and Policy Implications
This study examines the impact of ICT development, and CO2 emissions in OBRI countries, over the period from 1991 to 2019. The CSD tests, CIPS, CADF unit root tests, Westerlund panel cointegration test, and the FMOLS, and DOLS are applied for empirical analysis. For robustness check, this study divides the OBRI countries' data into regional sub-samples. This study uses broadband and mobile as proxies of ICT development. The findings of this study show that broadband and mobile have a negative effect on carbon emissions in OBRI panel economies. Furthermore, broadband and mobile subscription negatively affect the carbon emissions in sub-regions of OBRI countries such as, East and South East Asia and Europe continents. Besides, broadband (mobile) has a positive (negative) effect on CO2 emissions in MENA and Central Asia countries. Although the adverse result is found in South Asia, mobile subscription alleviates the level of carbon emissions but broadband enhances environmental pollution. Regarding country-wise analysis, broadband has a negative significant impact on carbon emissions in 21 countries while broadband has a positive significant impact on carbon emissions in 16 countries. However, mobile subscription has a negative impact on carbon emissions in 16 countries. The coefficient estimate of mobile with CO2 emissions is positive for 22 countries.
The study results call for a suggestion for some crucial policies. Energy-saving ICT devices (i.e., mobile, broadband, and smart application) are necessarily required in OBRI countries to alleviate CO2 emissions. Clean energy projects, with the assistance of ICT, authorities can decrease dependence on fossil fuel consumption in OBRI. The major findings suggest that ICT equipment utilization should be stimulated in all sectors of the economy. The ICT equipment that can be transferred in the course of FDI is beneficial. Moreover, OBRI countries can upgrade their industrial structure and increase green productivity through ICT development. The policymakers and governments of these economies should design policies to grow smarter cities, transportation systems, electrical grids, industrial processes, and energy-saving production through ICT development on a macro level. Government authorities and policymakers should inspire firms, individuals, and industries to move into the registration of brand names when they have been competent to invent climate alleviation processes, products, and services, as well as technology. The industrial sector would be stimulated by environmental-related technologies, and better production methods, among others which could earn more from the trademark. Moreover, the foreign trade strategies might be redesigned to accommodate revolutionizes in the energy strategies, and the foreign trade policies will be intended for increasing ecological excellence, such as the countries will be pitiful towards cleaner and green trade strategies. This calls for the bloc to make use of sustainable energy sources such as wind and solar. The study also recommends that the government sets an emission cap and strictly implements them and one exceed the cap, the government may put a heavy fine. Furthermore, the OBRI nations should also consider improving rural areas to avoid the urbanization problem that increases carbon emissions. All these initiatives can help the countries to speed up the achievement of SDGs.
One of the important limitations of this study is that this study could not find the composite (interaction) effect of globalization and ICT on environmental pollution. The authors of this study left this question for future research. In the future, a similar study can be designed to analyze a single-country analysis for the OBRI economies by performing the advanced nonlinear and dynamic ARDL time series methods.
Footnotes
Declaration of conflicting interests
The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Funding
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Hainan Provincial Social Science Project 2022 (HNSK (QN) 22-60).
