The effects of financial development and technological progress on environmental sustainability: novel evidence from Asian countries

This research is an endeavor to improve the literature on information and communication technology (ICT)-financial development-environmental sustainability nexus by conducting an aggregated and disaggregated analysis on the role of financial development and technological progress in attaining a sustainable environment. By employing a unique and comprehensive set of financial development and ICT indicators, this study offers an in-depth analysis of the role of financial development, ICT, and especially their interactions in maintaining environmental sustainability in 30 Asian economies from 2006 to 2020. Results from the two-step system generalized method of moments indicate that separately, both financial development and ICT are detrimental but together, their joint effects are beneficial to the environment. Several policy implications and recommendations are made to help policymakers to craft, design, and implement appropriate policies to improve environmental quality.


Introduction
The issue of sustainability has come to prominence over the past several decades. As a result, the United Nations (UN) adopts 17 so-called Sustainable Development Goals (SDGs) after years of negotiation. As these SDGs are endorsed by all 194 members of UN, it appears that global sustainability is ensured. Among these 17 goals, SDG 6, SDG 7, SDG 13, SDG 14, and SDG 15 focus on environmental goals, while the rest are divided into economic and social goals.
These sustainable goals are interconnected in a manner that achievement of goals of one dimension can facilitate the attainment of other goals. Regarding global sustainability, the realization of environmental goals is the most imperative issue. In the literature, environmental sustainability usually refers to persistent improvements in quality and possible protection of environmental resources (Kasayanond 2019;Murshed and Dao 2020). In view of the importance of environmental sustainability and security of global energy, the UN is committed to taking adequate measures to ensure greater accessibility and availability to affordable and clean energy supplies. SDG 7 specifically aims to substantially raise the share of renewable energy in total global energy consumption and dramatically enhance energy efficiency. A sustainable environment is expected to contribute to ensuring food security, facilitating good health of human capital, providing efficient renewable energy resources, and thus boosting economic growth. In addition to economic growth, a sustainable environment is confirmed to play a significant role in achieving other macroeconomic objectives for numerous countries (Hysa et al. 2020). Therefore, it is not unreasonable to expect that environmental sustainability has a crucial role to play in Asia.
Asia is a home to 59.8% of the world population with two major growing economies and also major carbon emitters: India and China. In 2021, the Asia Pacific region alone emitted about 17.74 billion metric tons of carbon dioxide (CO 2 ), accounting for 52% of the world total emissions. Among top ten global contributors of carbon emission, seven countries 1 are Asian nations (EU JRC 2020). Most of Asian countries still utilize non-renewable energy sources such as coal and petroleum products to fulfill their energy requirements which, in turn, can inflict devastating consequences on the environment. Carbon emissions along with other greenhouse gases are considered the main culprits causing worldwide climatic change. Among different sub-regions in Asia, South Asia is also regarded as the most vulnerable region as it possesses the largest number of non-polar glaciers. Himalayan glaciers are receding ever-faster, causing downstream flooding with dramatic average temperature rise every decade since the 1960s. Compared to 1990, about 30% decline in crop productivity is expected until 2050 with lack of water availability accelerating every year. All notions suggest a serious threat to sustainability in general and the attainment of SDGs in particular.
According to the UN (2022), the progress of achieving SDGs in Asian region is stagnated or even heading in the wrong direction mainly due to the high costs of obtaining these goals. Among potential solutions to the high cost of achieving SDGs, financial sector development is the need of hour as it can help to meet sustainable goals by ensuring the smooth functioning of various sectors of the economy. Regarding its definitions, financial development is a multidimensional concept and can be studied under different dimensions like financial inclusion, depth, efficiency, and stability of financial system. The impact of each dimension of financial development on environmental sustainability makes up a separate debate. Therefore, in addition to the aggregate analysis of the impact of financial development, this study will explore the effects of each of them on environmental sustainability.
It is estimated by the World Bank (WDR 2021) that "Climate change will drive 68 million to 132 million people into poverty by 2030." The attainment of development goals is confronted with several limitations. Among them, technological redundancies within developing countries are believed to exert unfavorable effects on bottlenecking fulfillment of environmentally sustainable goals (Mirza et al. 2009;Simsek et al. 2020). To overcome these barriers, developing economies are looking forward to information and communication technology (hereafter, ICT). In recent years, ICT has revolutionized the financial sector (Cheng et al. 2020). According to the International Telecommunication Union (ITU), total mobile subscribers are approximately 8 billion, whereas household with internet access in Asia are 70% in urban areas and 36% in rural areas, showing a fair adoption of modern technology.
Usually regarded as innovations in the financial sector facilitated and accelerated by advanced ICT (Wan et al. 2022), digital finance has transformed the phenomenon of financial inclusion and led to financial development. It has the potential to boost financial inclusion and ensure financial stability in emerging economies (Ozili 2018). Financial institutions equipped with state-of-the-art technology like e-banking may make them consumer-friendly, increase geographical coverage, reduce bank visits, enhance transparency, and make information available all the time, resulting in fewer emissions. ICT-adopting countries have witnessed significant escalation in their financial inclusion. Therefore, ICT usage is considered a gateway of financial development and internet usage is imperative to foster financial inclusion in Asia (Le et al. 2019).
This study aims to empirically examine the role of ICT and financial development in achieving environmental sustainability in Asia. It also adds significantly to the literature in the following points. First, it takes into account the interactions of ICT and financial development. To the authors' best knowledge, the literature on the joint effect of ICT and financial development on environmental sustainability is scant. Prior studies mostly focus on either the financial development-environmental sustainability nexus (Ben Youssef et al. 2020), ICT-financial development nexus (Shamim 2007;Boateng et al. 2018;Abeka et al. 2021), or ICT-sustainable development nexus (Tyagi et al. 2020;Jayaprakash and Radhakrishna Pillai 2021;N'dri et al. 2021). Second, unlike previous studies that only use individual proxies for environmental sustainability, this paper takes into account different aspects of environmental sustainability by generating an index using scores of environment-related SDGs. Third, we also investigate the separate effects of different financial development dimensions on the environment.
The remainder of the paper is structured as follows: the "Review of literature" section focuses on literature review; the "Data, model specification, and estimation method" section discusses data, estimation methods, and model specification; the "Empirical findings" section is result discussions, while the "Conclusion and policy implications" section concludes the paper.

ICT and environmental sustainability
The crucial role of ICT and its related benefits is wellestablished in the literature with its effects being felt in almost all sectors . ICT is also believed to bring about profound structural transformation of firms, economies, and even societies (Zhao et al. 2022), and the environment in general and CO 2 in particular should not be the exception. Therefore, it is not surprising that the literature on the ICT-CO 2 emissions nexus is voluminous and grabs special attention thanks to its crucial importance.
ICT tools are expected to be able to break through technological barriers and, therefore, make significant contributions to improving energy efficiency and mitigating CO 2 emissions. However, the effects of ICT on CO 2 emissions remain controversial with the existing literature on environment sustainability and ICT diffusion being classified under three different approaches. In the first approach, ICT developments and adoption are likely to elevate efficiency in energy uses through better management of their consumption (Kramers et al. 2014). It is also predicted that ICT diffusion in the global energy sector can curb energy demand by 3.5-6.3% without compromising economic growth (Rodríguez Casal et al. 2005). As a result, ICT-based solutions are expected to aid in reducing greenhouse gas emission (Webb 2008). In contrast to the first approach, the second approach views ICT as environmentally unfriendly as the ICT industry has become a power drainer and contributes 2% of global carbon emissions. Disposal of e-waste is also a source of environmental degradation. Finally, according to the third school of thought, the links between ICT and environment are unclear due to "rebounds effects" which means that positive effects of ICT in short run can be offset with negative effects in long run.
Similar to the theoretical arguments on the ICT-CO 2 emissions nexus, empirical results concerning ICT-CO 2 emissions remain inconclusive. Some authors confirm the positive impact of ICT in mitigating CO 2 emissions nexus (Park et al. 2018;Ozcan and Apergis 2018;Lu 2018;Khan et al. 2019). Conversely, other authors counter-argue that ICT usage may even do more harm than good to the environment, and therefore, higher use of ICT applications may lead to more pollution (Lee and Brahmasrene 2014;Asongu 2018). Few studies even propose that the effects of ICT on CO 2 emissions nexus bear close similarities to the environmental Kuznets curve (EKC): environmental dilapidation at first increases with adoption of ICT, and then environmental quality starts to improve after a certain threshold of ICT adoption, suggesting that ICT adoption has a positive impact on environmental quality in the long run. Zhang and Liu (2015) explore the nexus between ICT industries on CO 2 emissions by applying STIRPAT model to Chinese provincial data from 2000 to 2010. Their findings indicate that the impact of ICT is more profound in central region than in eastern region of China and insignificant in western region. Majeed (2018) conducts a comprehensive analysis of 132 developing and developed countries from 1980 to 2016 to investigate the impact of ICT on environment using pooled ordinary least square (POLS) and generalized method of moments (GMM). Their results establish that ICT is only beneficial to the environment in developed countries, while ICT could be counter-productive in developing nations. Ozcan and Apergis (2018) find that increased internet access helps in reducing air pollution in emerging countries from 1990 to 2015 with panel causality test suggesting unidirectional causality from internet usage to reduction in CO 2 emissions. Avom et al. (2020) investigate the effects of ICT on CO 2 emissions and document a negative relationship between ICT adoption and CO 2 emissions in Sub-Saharan African (SSA) countries. In the light of review of literature, there is a conflict in findings, and new research aiming the role of ICT on quality of environment in Asian economies is required.  examine impacts of ICT on CO 2 emissions in 9 Asian countries over the period 1990-2018. By employing ARDL and NARDL models, their study confirms the existence of asymmetric responses of CO 2 emissions to ICT shocks in 6 out of 9 economies. In most of the selected economies, ICT is found to increase CO 2 emissions, but lowering CO 2 emissions by reducing the use of ICT may hinder progress in other sectors. Using time-series data over the period 1996 to 2018, Raihan and Tuspekova (2022) find that increase in technological innovation significantly lowers CO 2 emissions in Kazakhstan. In a recent study, Ahmad et al. (2023) study results estimated by applying ARDL show that technological innovation adds to economic growth without harmful effects on the environment in China.
Based on the above literature review, we propose the following hypothesis regarding the ICT-environmental sustainability nexus.

Financial development and environmental sustainability
Despite the fact that the literature on determinants of environmental quality is huge, the link between finance and environmental quality in developed and developing economies remains unclear. Numerous studies suggest that at early stages of financial development, the priority is economic growth through industrialization over environmental sustainability, but later financial development will improve the quality of environment through the facilitation of clean energy use and investments in environmental projects (Al-Mulali et al. 2015). In literature, we find three ways by which financial development affects the environment (i) household effect channel (Sadorsky 2011); (ii) business influence; and (iii) wealth effect channels (Acheampong 2019). Frankel and Romer (1999) propose that the development of financial sector stimulates the investment which encourages research and development (R&D) activities and therefore leads to better environmental conditions. Tamazian et al. (2009) maintain that the allocation of funds and credit at low cost facilitates the purchasing of energy efficient technologies that reduce carbon emission. Consequently, development in financial sector reduces the harmful effects of greenhouse gases because of adequate financing for acquisition of ecofriendly equipment (Charfeddine and Kahia 2019). However, the empirical literature appears to be divided into three schools in terms of the impact of financial development on CO 2 emissions. The first group of studies suggest developed financial structure escalates the quality of the environment (Shahbaz et al. 2015;Nasir et al. 2019;Zaidi et al. 2019). The second group of study reveals that financial development worsens the environment through different channels (Abid 2017;Ali et al. 2017 andBaloch et al. 2019). The third group argues that there is no significant relationship between financial development and CO 2 emissions (Ozturk and Acaravci 2010;Omri et al. 2015). By applying different econometric techniques like DOLS, 2 FMOLS, 3 and DFE 4 model to a group of GCC 5 nations, Salahuddin et al. (2015) affirms that financial development reduces CO 2 emissions. By generating a composite financial index through stock market and bank-based financial development indicators for Pakistan from 1980 to 2014, Shahbaz et al. (2016) conclude that financial development is harmful to environment quality. Hence, it is suggested that policies that encourage lenders to allocate financial resources in environment friendly projects should be promoted. Seetanah et al. (2019) confirm the insignificant impact of financial development on environmental degradation in 12 developing islands. Nasir et al. (2019) also shed light on the effects of foreign direct investment (FDI), economic growth, and financial development on environment quality in five ASEAN countries from 1982 to 2014. Their study asserts that financial development has damaging effect on environment as the former tends to increase harmful pollution.
The study by Zaidi et al. (2019) determines the dynamic linkages between financial development and pollution in APEC 6 economies for the period 1990 to 2016. The study employs Westerlund cointegration test to find long-term relationships between variables. Empirical results of the study suggest that financial development significantly decreases carbon emission. Aluko et al. (2020) established that there is bidirectional causality between capital market development and CO 2 emission from 1985 to 2014 in 35 SSA countries. Unlike prior studies, novel composite index was used in the study and also consider the technology aspect of financial development on environment. The outcomes of the study revealed that financial market is a positive driver of environmental quality and the technology effect of financial development has a deteriorating impact on environmental quality.
Sharma and Kautish (2020) employ a CS-ARDL technique on eight South Asian countries and document that financial market has moderating impact on nexus of energy and environment footprints. In another study, Manta et al. (2020) examine the association between CO 2 emissions, economic growth, energy use, and financial development for 10 CEE 7 countries from 2000 to 2017. By utilizing VECM, 8 Granger causality, and FMOLS estimations, results from Manta et al. (2020) suggest that developed financial sector increases CO 2 emission. By using POLS, fixed effects model, random effects model, and quantile regression, Nyarkoa and Kaya (2021) investigate the financial development-environmental quality nexus in 36 countries from 1996 to 2012 by applying fixed and random effects models. Their empirical analysis reveals that financial development has a negative effect on environmental quality while the effect is insignificant in quantile regression model. Khan et al. (2021) employ dynamic ARDL from 1980 to 2019 in Malaysia to discover the relationship of economic growth and financial development on ecological footprints. It is deduced that 10% or less boost in financial development causes a negative impact on environment in short run. However, the effect is positive in the long run. More than 10% financial development positively affects environment as more financial resources are used to invest in environmental friendly projects. Usman and Makhdum (2021) estimate the dynamic relationship between renewable and non-renewable energy, ecological footprints, agriculture value added, forest area, and financial development and found no causality between financial development and forest area. Based on the abovementioned analysis, we suggest the following hypothesis: H2: The effect of financial development on environmental sustainability in Asian economies likely to be negative.

Financial development-ICT interactions and environmental sustainability
Empirical evidence depicts that ICT diffusion has significant positive impact on developing financial sector in general and on increasing financial inclusion in particular. Andrianaivo and Kpodar (2011) assert that ICT tools are associated with higher economic growth through financial sector channel as these tools provide and energize financial services more conveniently. By using quasi-ARDL approach, Godil et al. (2020) uncover that joint effect of ICT and financial development may prove useful in reducing CO 2 emissions in Pakistan. Saleem et al. (2020) find similar findings for Asian economies using FMOLS technique. Raheem et al. (2020) document that ICT and financial development has positive effects on growth in the short run and negative effect in the long run. Furthermore, ICT magnifies the role of financial development on CO 2 emissions. By employing FE model, and GMM to solve endogeneity problem, Alshubiri et al.  Chien et al. (2021) explore the nexus between ICT and financial development and carbon emissions using GMM and quantile regression techniques. Their findings indicate that financial development significantly contributes to raising carbon emission across all quantiles, while ICT significantly mitigates carbon emissions only at lower emission quantiles in BRICKS countries from 1995 to 2018. From the review of extensive literature, it is evident that ICT and financial development are interlinked, interdependent, and likely to magnify the role of each other and have a significant impact on environmental sustainability. Therefore, we propose the 3rd hypothesis as follows: H3: ICT improves financial sector development in Asian countries for achieving environmental sustainability.

Other control variables
In order to deal with the problem of potential endogeneity and omission variable bias, we also include other control variables in the model. The first control is GDP (proxied by GDP per capita growth). In Asia's developing economies, GDP growth is primarily supported by industrialization which, in turn, implies a certain relationship between GDP growth and CO 2 emissions. However, similar to the ICT-CO 2 emissions and financial development-CO 2 emissions nexuses, the GDP-CO 2 emissions nexus remains debatable. While Beckerman (1992) and Tamazian et al. (2009) opine that higher growth is beneficial to the environment, Rothman (1998) argues that higher growth can do more harm than good to the environment. This paper aims to clarify the link between GDP growth and CO 2 emissions for Asian countries in the sample. In addition to GDP growth, inflation, foreign direct investment (FDI), and rule of law are also included.

Data and model specification
In this study, we use a panel of 30 Asian economies 9 for the time span of 2006 to 2020. SDG 6, SDG 7, SDG 13, SDG 14, and SDG 15 are considered as environmental dimensions of SDGs. The dependent variable of this study is environmental sustainability. Therefore, we used the various indicators to measure these SDGs. The description and detail of indicators is provided in Table 1. By using the principal component analysis (PCA) method, we develop an index (ENV) for environmental quality. It should be noted that a higher value of ENV indicates better environmental quality and vice versa. ICT is measured by mobile phone penetration (MOB), fixed broadband subscription (BRB), and internet usage (INTRN).
For aggregate analysis, a composite index (ICT) is used. High value of composite ICT index represents deeper ICT penetration. This paper takes into account four dimensions of financial development: financial depth, inclusion, efficiency, and stability, respectively. Financial development (FIN_D) is a composite index for financial development for aggregate analysis. Similar to the aggregate/composite environmental and ICT indices, greater value of the aggregate index indicates higher level of financial development. The technique of making financial development index is employed in many studies (see, e.g., Lenka 2015; Svirydzenka 2016; Asongu & Odhiambo 2020). We follow Kassi et al. (2020) and construct composite index of financial sector development through PCA. Other control variables include GDP per capita growth (GDPG), inflation (INF), foreign direct investment (FDI), and rule of law (ROL). The description of variable is given in Table 1.
Following Aluko and Obalade (2020) and Lu (2018), the model used to estimate the joint effect of financial development and ICT on environmental sustainability is as follows: where ENV it is the environmental sustainability; FIN_D it is the financial development and measured by indicators related to financial depth, efficiency, inclusion, and stability; information and communication technology ( ICT it ) representing by mobile phone, internet, broadband subscription and mobile phone subscription; ICT it + FIN_D it is the interaction between ICT and financial development; X ′ jit is the vector of regressors used as control variables (i.e., FDI, inflation, GDP, and rule of law); and i is the country-specific effect.

Estimation method
We apply the system GMM estimator approach by Blundell and Bond (1998) to examine the effect of various dimensions of financial sector development and ICT on environmental sustainability in Asian economies. We apply the system GMM estimator approach by Blundell and Bond (1998) to examine the effect of various dimensions of financial sector development and ICT on (1) environmental sustainability in Asian economies. Three are three principal reasons to employ this technique for present analysis: First, the number of countries (N) is higher than the number of time period (T) (Roodman 2009), and this condition is satisfied in present case (N = 30 > T = 15). Second, system GMM estimators suggested by Blundell and Bond (1998) are used for present analysis because difference GMM estimator proposed by Arellano and Bover (1995) produced biased estimates in the case of small sample (Baltagi 2008). First difference and in level equations are combined in system GMM in which the variables are econometrically instrumented by their first differences. Third, it addresses the endogeneity issues produced by reserve causality among the considered variables. For instance, the two-ways causation may exist between CO 2 and financial sector development (Xu et al. 2018;Shahbaz et al. 2020), CO 2 and ICT (Shehzad et al. 2020), and ICT and financial sector development (see. e.g., Pradhan et al. 2015). For this reason, system GMM is suggested to deal with these problems and ensure the reliability of our estimate.
Suppose the dynamic specification of the dependent variable and a single covariate is modeled as follows: where i is the unobserved individual-specific effect and it is the error term. Often nonzero correlation is expected between i and covariate y it . Moreover, it is expected that Furthermore, y it may exhibit a nonzero correlation with error term, i.e.,E( it | | y it ) ≠ 0 . In the presence of these endogeneity issues, the application of OLS may yield inconsistent estimates. To this end, an alternative estimation technique such as difference GMM which proposes differencing equations to eliminate the country-specific effects is most commonly used. Blundell and Bond (1998) suggested the use of moment conditions that are based on the stationarity restrictions of time-series properties of the data. For model (2), the proposition is which indicate that original series have constant correlation over time with the country-specific effects. Blundell and Bond (1998) explain that system GMM perform better than difference GMM because instruments in the level model are good predictors for the endogenous variable even in the presence of highly persistent series. Table 2 provides the descriptive analysis of all variables which helps to understand the basic features of data under consideration.

Findings of pre-estimation tests
(2) Table 3 presents the results of aggregated analysis that explain the moderating effect of ICT index on the nexus between financial sector development and environmental sustainability in Asian countries. The coefficients of FIN_D is negative, explaining the detrimental effect on environmental sustainability. In terms of control variables, economic growth and rule of law are adversely affecting environment, but the role of inflation and FDI in preserving environment is positive. On in-depth analysis, we find that financial depth and inclusion have negative effect, but financial efficiency and stability have a significant positive effect on environmental sustainability. Furthermore, the joint effect of financial development and ICT is also found to be significant in all models. The study also calculates the individual effect of ICT indicators (MOB, BRB, and INTRN) on environment (see Tables 4, 5, and 6). It is observed that environmental sustainability decreases by 0.01%, 0.26%, and 0.02% for 1 percentage point increase in MOB, BRB, and INTRN, respectively. The positive and significant coefficients of financial efficiency (BNIM) and financial stability (BZS) in all models suggest that efficiency and stability in financial sector have a strong influence on environment. Financial inclusion (ATM) coefficients also shown to be negative and significant, no matter at which proxy is used for ICT. The coefficients of control variables are also in consensus with literature.

Findings of GMM
The p-value of Hansen test in all the models is insignificant suggesting validity of results. In addition, the AR (2) p-value is also insignificant in all models which validate the absence of 2nd-order autocorrelation.

Discussion of results
Estimation results in Tables 3, 4, 5, and 6 are interesting and revealing. First, we document that coefficients of financial development index are negative and significant in all models indicating that a sound and well-functioning financial system provides an opportunity to access capital and facilitates investment. This fosters economic activities and energy usage triggers environmental degradation. The aggregated and disaggregated effect of ICT on environmental sustainability are negative explaining that the expansion of the ICT sector causes high energy demand and increases CO 2 emissions. These results are supportive of the existing literature. Previous studies Avom et al. (2020), Ali et al. (2019), and Baloch et al. (2019) also confirm the negative effect of ICT and financial development on environmental sustainability. However, ICT and financial development together are beneficial to the environment as the interaction between them is found to positive and significant, meaning that in combination, ICT and financial development can help boost environmental quality. This could probably be attributed to the fact that ICT helps to develop financial system, mitigate the problem of asymmetric information, and enhance financial integration, thus leading to economies of scale in industries, higher energy efficiency, energy consumption, and less carbon emissions. The direct negative effect of ICT may be due to e-waste and indirect effect is due to trade. The estimated coefficient of FDI is negative suggesting the presence of pollution haven hypothesis which means FDI likely to improve environment sustainability in Asian economies. Researchers often argue that developing countries are less sensitive to the environment sustainability and foreign companies often use poor management practices and technologies that account for more environment degradation (Zhu et al. (2016). Furthermore, this study find that inflation exerts significant and positive impact on environmental quality This phenomenon can be attributed to the fact that higher inflation represents macroeconomic instability that discourages investors, slows down activities, and thus relaxes the pressure on environment. This finding is consistent with Setyadharma et al. (2021) and Ahmad et al. (2021). The economic growth effect is found to be negative, suggesting more growth leads to more industrialization and more carbon emission and, therefore, lower environmental quality.
Regarding the in-depth analysis of effect of financial development on environmental sustainability, it is documented that financial efficiency and financial stability have a positive association with environmental sustainability, whereas the effects of financial depth and financial inclusion are significant and negative, suggesting that in developing   countries a financial inclusion has deteriorating effect on environmental health. Financial and capital market expansion accelerate purchases of large-scale machinery and new production lines, which further enhances energy demand and consumption and causes environmental worsening (Nasir et al. 2019). As financial stability and financial efficiency have a positive and significant effect on environmental sustainability, it is implied that a stable and efficient financial system may help improve environmental health by providing funds for the purchase of advanced technologies and facilitate the adoption of energy-saving production processes. These findings are in line with Nasreen et al. (2017). When proxied by mobile phone subscription, ICT is found to exert a significant and harmful effect on the environment. This could be explained by the emission laden process of smartphone and consumption of precious mineral resources in production which has a detrimental effect on environmental sustainability. The consumerist society upgrading their smartphones frequently due to advancement in technology and fashion whims also aggravates by creating an incredible amount of e-waste. E-waste radiates contaminants like arsenic, mercury, and zinc which not only pollute atmosphere but also a threat for life on land and below water. The interaction term between financial development and mobile phone subscription is found to be positive and statistically significant. This suggests that while these variables may do more harm than good to the environment, the joint effect of ICT and financial development may reverse these negative impacts and boost environmental quality. When represented by broadband network and internet penetration, the effects of ICT on environment are similar.

Conclusion and policy implications
This study is aimed at exploring the effects of financial sector development and ICT on environmental sustainability in Asian economies. This paper goes one step further and makes a novel contribution to the literature by examining the joint effect of financial development and ICT on environmental sustainability. In the current study, we generated aggregate indices for ICT and environmental sustainability through the use of PCA. We also focus on the environmental effects of different dimensions of financial development to derive specific individual financial indicators, namely financial depth, financial efficiency, financial inclusion, and financial stability effects. The thorough analysis using aggregate and disaggregate indices also provides deeper insights for policymakers. Results from GMM estimations reveal that financial development and ICT are detrimental to   environmental sustainability in Asian economies. The joint effect of the aggregate financial development index and aggregate ICT index is also enhancing the positive effect on environmental sustainability. ICT by reducing information asymmetries promotes carbon emission. The increasing drift of mobile phone subscription is consuming natural resources and also producing e-waste. Financial development if used in fuel efficient eco-friendly projects can help in achieving sustainability.
In terms of disaggregate (individual) financial development indicators, it is found that the encouragement of financial depth and financial inclusion is likely to compromise environmental sustainability. On the contrary, financial efficiency and stability tend to have a positive impact on environmental health in all models. The outcomes of the study also suggest that FDI have positive influence, and economic growth implies a negative effect on environmental sustainability.
The study strongly endorses on the importance of efficient and stable financial systems that can invest in environmental friendly projects. An extensive range of policy initiatives should be explored that can encourage financial sectors to curb unchecked financial deepening. There must be a department comprising of environmental engineers or environmental health officers in financial markets to ensure environmental sustainability is not compromised. For developing financial sector, financial depth should not be targeted on the cost of environment; rather, it is suggested to invest in fuel-efficient eco-friendly projects that will help in achieving sustainability.
In order to address the negative consequences of ICT and financial development in Asian economies, policymakers should adopt green technologies and raise people's awareness about the environmental cost of trendy mobile phones. Finally, as digital finance, e-commerce, and mobile banking all mitigate carbon emissions, these services should be encouraged and facilitated. Asian economies should now maintain a balance between growth and environmental degradation. Economic growth should be accompanied with cleaner energy, green technologies, and investment in environmentally friendly projects.
Future research may devote more attention to other panels with diverse ICT and financial development measures. The time frame of this study is 2006 to 2020; therefore, future research may focus on longitudinal data for their research. The outcome would be more interesting if quantitative and qualitative approaches are used simultaneously in future research. Table 5 GMM estimation (using BRB as a proxy for ICT) ***, **, and * imply level coefficient significance at 1%, 5%, and 10% level, respectively. The values in standard errors are in parenthesis; p-values are in square brackets