Measuring economic, social and environmental wellbeing of Asian economies

This study aims to address the economic, social, and environmental wellbeing issues simultaneously by measuring the carbon intensity of wellbeing (CIWB) of Asian economies employing Prais-Winsten and pooled OLS estimator. The measure of CIWB is made taking into account a ratio of the two indicators—CO2 emissions per capita and life expectancy at birth. There is a paucity of studies that concentrate on human and social wellbeing indicators (i.e., water, sanitation, life expectancy) together applying the Environmental Kuznets Curve (EKC) hypothesis. Therefore, we have also investigated the EKC hypothesis as this theory hypothesizes the link involving human and environmental wellbeing and development. The findings utilizing the two econometric techniques indicate that in both the estimation models urban population access to an improved water source and total population access to improved water source has consistently negative and significant effects on CIWB. The fertility rate and prevalence of HIV pose no threat to CIWB. These findings demonstrate that social and human wellbeing indicators of the Asian economies are sustainable to this moment as they are lowering CIWB which is desirable. Contrary, GDP per capita, exports as a percent of GDP, and urban population have a significant and positive impact on CIWB which poses a challenge for the sustainability issue. We also have found the existence of the EKC hypothesis indicating environmental quality will increase past a turning point. The findings of the paper are well matched with the view of the “Economic and ecological modernization” theory and “human ecology” theory.


Introduction
Over the last few decades, wellbeing study has acknowledged greater attention as a source of good or quality life . Wellbeing indicators are over and over again related to economic and social policies, and environmental development issues are lagging behind addressing the wellbeing indices even though the environment plays a crucial role in the sustainability and quality of wellbeing (Smith et al. 2013;Wainger & Price 2004). Measuring environmental issues on sustainability and their influence on economic, social, and human wellbeing becomes clear, particularly while considering both economic growth and quality life together (Jordan et al. 2010). Quality of life-wellbeing could be compromised due to some socioeconomic and environmental factors, i.e., inequality, poverty, and environmental change, etc. At present, the growth scenario has failed to address environmental pollution and income inequality issues that hamper the sustainability of the environment (Zhao et al. 2021). However, wellbeing has multidimensional aspects and can be seen as subjective and objective wellbeing. Subjective wellbeing is often defined based on human perception, therefore, not directly measurable (Sirgy 2012). Conversely, objective wellbeing takes account of fundamental economic, social, and environmental essentials, therefore, directly measurable (Parris & Kates 2003;Talberth et al. 2007). This study aims to incorporate the economic, social, and environmental indicators to measure wellbeing in the sustainable development perspective in an Asian context. How to ensure the human wellbeing exclusive of environmental degradation remains, an essential inquiry for sustainability? Particularly for environmental sustainability, a healthier socio-economic growth is essential (Yin et al. 2021). Sustainable development is termed as satisfying human needs without compromising natural and social capital. Therefore, the goal of sustainability is to achieve wellbeing by preserving the natural environment. There are different schools of thought in environmental sociology regarding the interactions between economic growth, degradation of the environment, and wellbeing. Modernization theories, including "economic and ecological modernization," are in favor of the positive role of economic growth in achieving sustainability and wellbeing (Knight & Rosa 2011;York et al. 2003). On the other hand, the "treadmills of production" theory postulates that rapid economic development and growth led to a huge demand for energy consumption, which negatively impacted the environment (Knight & Rosa 2011;York et al. 2003). The "human ecology" theory encompasses a wider perspective and views of wellbeing, including health and climate conditions (Bubolz & Sontag 2008;Dietz et al. 2009). This study addresses which of the prevailing theories are appropriate for the Asian economy as a whole, taking some indicators of choice that proxy for the economic, social, and environmental wellbeing that ultimately ensures human wellbeing. Besides, the Environmental Kuznets Curve (EKC) hypothesis is receiving prominence among academics in well-being studies. If an economy is energy efficient, utilizes more renewable energy, and has environmental cognizance, an inverted U-shape relationship between income and pollution is visible (Ozturk et al. 2016).
As a wellbeing indicator, life expectancy is an inclusive evidence of individual wellbeing and happiness that embraces the usual standard of livelihood, physical state, mental contour, societal ambiance, ecological atmosphere, and even the political structure (D'Albis & Bonnet 2018;Hill & Jorgenson 2018). Therefore, it is crucial to investigate the improvement of countrywide indices while measuring economic, social, and human wellbeing. These measurements are interrelated, predominantly as civilization progress towards the postindustrial knowledge and information era where economic achievement greatly relies on investment in human competency improvement. Urbanization is a universal phenomenon though it has a diverse impact in different contexts as a social wellbeing indicator. Urban development focused on human and environmental concerns is an essential sustainable development issue and Sustainable Development Goals (SDGs) have a specific goal regarding the sustainability of cities (Sachs 2015). It is also an integral element of human-induced land-use transformation, and therefore, this issue needed to be reflected while modeling regional climate issues (Hu et al. 2015), and the reduction of urbanization levels might help decrease the environmental damage  with policies to manage sewage, solid waste, and industrial waste produced by urban residents .
The studies related to CO 2 emissions, development, and wellbeing could be biased if the analysis is done by overlooking the regional disparities, combining all nations of the world in a common sample (Jorgenson et al. 2012;Jorgenson & Clark 2013). In this context, we examine the relationships between environmental, economic, and social wellbeing indicators for all Asian countries to eliminate regional bias addressing the key issues of sustainable environmental development. In this study, a ratio term between per capita CO 2 emission and average life expectancy at birth as a wellbeing indicator is used. GDP per capita and export to capture the economic development aspect is incorporated. Urbanization, along with other urban and human wellbeing attributes (i.e., water, sanitation, fertility rate, prevalence of HIV), are factored into the analysis to represent social indicators. All these mentioned indicators are incorporated to analyze the impact of economic, social, and environmetal wellbeing focusing on the sustainable environment development issue of Asian economies.
This study focused on Asian economies for some specific reasons. Firstly, there is a paucity of studies that give attention to human and social wellbeing factors (i.e., water, sanitation, life expectancy, fertility rate), simultaneously considering the EKC hypothesis in the context of Asian economies. Therefore, we have investigated the EKC hypothesis as this theory hypothesizes the link involving human and environmental wellbeing and development. To the best of authors' knowledge, in the context of Asian economies, this is the first study in this regard. Secondly, there has been an unanticipated growing demand for energy in low-and middle-income countries since the last two decades (Culver 2017). Most of the Asian economies fall within this group, with few exceptions. This phenomenon requires more significant investigation as more energy consumption leads to greater emissions (Alam et al. 2011;Baek & Kim 2013;Pao et al. 2011;Sharma 2011;Sadorsky 2014) and that will risk human wellbeing. Therefore, for the sustainability of the environment, CO 2 emission and wellbeing studies need special attention for the Asian economies. Against the above circumstances, the study focuses on measuring the wellbeing of Asian economies with other predictors. Thirdly, as the findings are responsive to the methodology employed, we have used both Prais-Winsten regression model with panel-corrected standard errors (PCSEs) and the pooled OLS (Driscoll-Kraay) standard errors to get robust results. Finally, this particular study contributes to the existing literature in another way and that is, the findings might have implications in regional policymaking concerning wellbeing issues. As no previous study is found contemplating solely on this region, the findings might influence regional policy decisions and help in deepening environmental integration.
The organization of the paper is structured as follows: Section 1 is designed for introduction, and in Section 2, the dynamism of Asian economies is portrayed. It is followed by Section 3, a succinct review of literature. Section 4 illustrates data sources and econometric methodology. Empirical results and their interpretations are analyzed in Section 5. In the final section, the conclusion and policy implications are drawn.

Dynamism of Asian economies
The World Bank defines economy for the current fiscal year 2021 based on per capita GNI; < $1035 to low-income, $1036-$4045 to lower-middle-income, $4046-$12,535 to upper-middle-income, and > $12,535 to high-income economies (World Bank 2019). As Asian upper and lower middle income and lower-income economies if taken separately, enclose a small number of countries, we have organized these three income categories as developing economies following World Bank definition. Therefore, most of the economies of Asia are developing economies with few exceptions. The country by GDP scenario provided in Appendix 1 also demonstrates that other than China, Japan, India, South Korea, Indonesia, Saudi Arabia, Turkey, Taiwan, Thailand, and Iran, the countries follow the comparable GDP scenario.
The dynamism of Asian economies (economies considered for this study is listed in Appendix 2 Table 8) lies within the fact that most of the economies can be portrayed as developing, albeit there is disparity amongst them (Campbell 2019). On the one hand, the continent contains one of the most economically developed nations of the world, Japan. On the other hand, it includes the poorest countries like Afghanistan, Cambodia, and Nepal. There are also regional varieties among Asian economies. According to the World Bank category 2019, the largest part of Southwest Asia clubs in one of the middle-income categories, including high-income economies, i.e., Israel, Kuwait, Qatar, and the United Arab Emirates. Economies of North and Central Asia are predominantly low-income economies apart from Russia (World Bank 2019). The South Asia region mainly falls in the lower-middle-income economic category. The most affluent side of the continent is East Asia.
The region is not only the world's most heavily populated area but also familiar with an array of climate change impacts. The major environmental glitches that confront Asia are air pollution, deforestation, water and sanitation management, land degradation, loss of biodiversity, health, and climate change (Shrestha et al. 2020). The region is attributed as having ineffective domestic environmental regulation and absence of solid regional environmental principles with transboundary pollution problems (Campbell 2019). Given the perils of environmental issues with other socio-economic concerns, this region opts for a distinct research.
Furthermore, countries in Asia are following the trends of rapid urbanization (Zhang 2016) and industrialization compared to the rest of the world; however, a bulk of the populace is still occupied in agricultural activities. The trade-related interdependence of economies grew considerably during the late twentieth century. Energy consumption (per capita) in Asia is lower than the world standard except for the oil-producing economies that has a significant impact on health and wellbeing (Spagnoletti & O'Callaghan 2013). China is the largest producer of energy and the largest CO 2 emitter, simultaneously the leading investor in renewable energy as well (BP 2020). As emission-related issues have a transboundary/cross-boundary effect, we have taken the whole Asian sample to measure wellbeing so that it might contribute to regional policy decisions related to wellbeing indicators as well as help deepening regional environmental integration.

Carbon intensity of wellbeing (CIWB) and economic development
The scholars termed the link between CO 2 emissions and human wellbeing as the carbon intensity of wellbeing (CIWB) or ecological intensity of human wellbeing (EIWB) that measures environmental and human wellbeing simultaneously (Dietz et al. 2012;Jorgenson 2014). There are nascent literature that concentrates on the assumption that a larger value of CIWB refers to a higher level of CO 2 emission, whereas a lesser value denotes a lower level of CO 2 emission (Jorgenson 2014;Jorgenson & Dietz 2015). Studies of Dietz et al. (2009), Dietz & Jorgenson (2013, and Jorgenson & Dietz (2015) concentrate on the wide-ranging ecological intensity of the wellbeing context. In their opinion, it is a ratio of environmental pressure to human wellbeing which is operationalized taking the ratio between per capita CO 2 emission and average life expectancy indicators. The CIWB concentrates on sustainable development issues by dissolving the environmental and human wellbeing indicators into one indicator.
The study on the link between CO 2 emission and economic development receives substantial consideration; however, a very limited degree of attention has been paid to the relationship between CO 2 emissions and wellbeing indicators by emphasizing economic development (Knight & Rosa 2011). Moreover, most studies concentrate on single or broad indicators, i.e., life expectancy, human development index, and life satisfaction, apart from few exceptions (O'Neill et al. 2018). Some studies that have concentrated on fundamental socio-technical changes that convey a message to keep economic development, energy use, and emissions within the boundary of ecological wellbeing (Lamb 2016;Sulkowski & White 2016).
The relationship between economic development (growth) and environmental wellbeing is elucidated utilizing the EKC theory of Grossman and Krueger in 1995 (Press & Journal 2010). There are innumerable studies that deal with the EKC hypothesis (Al-Mulali et al. 2015a, 2015bFriedl & Getzner 2003;Hamit-Haggar 2012;Sharmin & Tareque 2020). These studies have postulated that each economy is unique in terms of underlying aspects that impels the link involving human and environmental wellbeing and development. The study of Raza & Shah (2018) has found the existence of the ECK hypothesis for G7 countries where renewable energy has a negative impact on CO 2 emission. Likewise, the study of Raza et al. (2020) postulates that renewable energy reduces emission with the presence of the EKC hypothesis in Next-11 and BRICS countries. Similarly, Ali et al. (2020) have supported the EKC for 33 European countries, with GDP being the main contributor to environmental degradation. There are no known studies that concentrate on social wellbeing indicators (i.e., water, sanitation, life expectancy issues) applying the EKC hypothesis on Asian economies. Rosa et al. (2010) establish that the impact of economic development on CIWB is a sustainability issue concerning the links among environmental, social, and economic growth. Givens (2015) has identified that levels of economic development and urbanization are linked with higher CIWB. This study also finds that a healthy urban development could lower the carbon intensity of wellbeing. Dietz & Jorgenson (2013) investigate population dynamics with affluence as a stimulator of environmental impacts to show human-environment connections. Another study (Sadorsky, 2015) examined the effect of urbanization on CO 2 emissions in 7 emerging economies. The study of Sharmin & Tareque (2018) investigated that growth exploits energy consumption which is the reason behind the increase of CO 2 emissions that hinders the quality of the environment in Bangladesh. Sharif & Ali Raza (2016) found that energy consumption and urbanization with other indicators have a substantial impact on CO 2 emission in Pakistan. A kind of similar findings is seen from a study on Bangladesh that growth, energy consumption, and urbanization have a positive impact on CO 2 emissions (Islam et al. 2021).

Economic development, urbanization, energy consumption, and CIWB
Urbanization is increasing energy consumption as found from the study of A. K. Jorgenson et al. (2010), and their findings suggest that energy consumption is indispensable for the quality of life improvement. In this respect, CIWB has a direct relationship with CO 2 emissions and quality of life. Corresponding to that, it positively correlates with CO 2 emissions (Jorgenson et al. 2014). In connection with environmental and other human wellbeing issues, Liu et al. (2010) found that most arable land is transformed to urbanization and it is harmful to those countries that have a high depletion rate but a low potential for sustainable development. The study of Mazur (2011) has found that increased energy and electricity use is vital for poor nations to improve wellbeing and is not associated with improved wellbeing of industrialized nations.
Some studies are in favor of using renewable energy instead of non-renewable energy to sustain environmental and human wellbeing (e.g., Al-Mulali 2014; Baek & Kim 2013;Sharif et al. 2019;Sharmin 2021). In their view, more use of renewable energy might have a positive impact on overall wellbeing indicators and could reduce the ecological footprint.
From the abovementioned empirical evidence, it is discernible that a large amount of literature investigates the connection linking economic activities and their impact on the environment. But there is a paucity of studies that concentrate on social and human wellbeing indicators (i.e., water, sanitation, life expectancy, health issues) along with environmental issues applying the EKC hypothesis and in exclusively concentrating on Asian economies this type of study is absent. This study aims to contribute to the abovementioned less explored areas of literature.

Data
The scales of analysis of this study are country level. The study uses data on 47 Asian countries for the period 1990-2019 for panel analyses. Annual data of all study variables are collected from the World Development Indicators (WDI) database (World Bank 2019). The list of Asian countries is available in Appendix 1. China and Hong Kong are treated as separate nations in this study as the World Bank provides separate datasets for them. The description of the included variables can be found in Table 1.
All variables included in this study are transformed into natural logarithms. Log transformation would help to measure the elasticity of estimated coefficients that would represent the percentage change in the dependent variable (CIWB) for a percentage in the independent variable (York et al. 2003).

Dependent variable
The measure of the carbon intensity of wellbeing (CIWB) is a ratio between CO 2 emissions per capita and life expectancy at birth which is consistent with others (e.g., Dietz et al. 2012;Jorgenson 2014;Jorgenson & Givens 2015). But one complication arises with a ratio as a measure when the range and variability differ substantially and creates the problem of the numerator or denominator dominance. In our dataset, the coefficient of variation of CO 2 emissions per capita is 0.903, and the range is 0.097-5.46. The coefficient of variation of life expectancy is 0.092, and the range is 50.33-84.93. To solve the issue of dominance, a constant is added to the numerator, which shifts the mean with changing the variance, thereby helping to balance the coefficient of variation of our numerator and denominator (e.g., Dietz et al. 2012;Givens 2015). For this study, the coefficient of variation of life expectancy and CO 2 emissions per capita has been made equivalent by adding 7.915466 to CO 2 emissions per capita. Further, it was multiplied by 100 to scale the ratio. The carbon intensity of wellbeing (CIWB) is measured as: CIWB = ((CO2 emissions per capita + 7.915466)∕life expectancy) × 100 Therefore, the CIWB measures the human wellbeing obtained for each unit of CO 2 emitted; a lower CIWB is more likely expected than a high CIWB for making the economic development and other social indicators sustainable.

Independent variable
The independent variables of interest are the real GDP per capita, exports as a percentage of GDP, and percentage of the urban population. Following (Givens 2015), the percent of the urban population with access to an improved water source and improved sanitation facilities as well as a percent of the total population with access to an improved water source and improved sanitation facilities are taken in this study to address further urban social attributes. Another two variables are incorporated; the expectation to have a considerable impact on overall health and CO 2 emissions. And those are the total fertility rate and the prevalence of HIV (Jorgenson & Rice 2016).

Model specification
The purpose of our study is to measure the economic, social, and environmental wellbeing of Asian economies. We have incorporated carbon intensity of wellbeing (CIWB) as a dependent variable. The measure of the CIWB is inspired by the works of Dietz et al. (2012), Jorgenson (2014), Jorgenson & Givens (2015), and Givens (2015). We have followed the theoretical background of the EKC hypothesis (M. Ali et al. 2020;Raza et al. 2020) as well as taking the squared GDP per capita.
Following Givens (2015), the functional form of the tested model is given as follows:

Model estimation technique
The study uses the time-series cross-sectional Prais-Winsten regression model with panel-corrected standard errors (PCSEs). The Prais-Winsten regression model is suggested by Beck & Katz (1995) because the Feasible Generalized Least Squares (FGLS) method 1 produces incorrect standard errors. In STATA 14, PCSEs assume by default that the disturbances are heteroskedastic and contemporaneously correlated across panels. First-order autocorrelation, AR(1), within panels is corrected for estimation (Sweidan & Alwaked 2016), and a two-way fixed-effect technique is employed to control for country-specific and time-specific disturbances. To check the robustness of the estimation, the pooled OLS (Driscoll-Kraay standard errors, which are more robust in the presence of heteroscedasticity and autocorrelation up to some lags in the error term) method is also applied.

Descriptive statistics
It is fundamental to understand the underlying characteristics of studied variables before any adoption of estimation techniques in econometric analysis. Table 2 presents the descriptive analysis of the studied variables from 1990 to 2019 under investigation. The mean carbon intensity of wellbeing (CIWB) of the panel is 2.519, and the mean GDP per capita of the samples is 8.3 US$. The average percentage of people living in urban areas is 3.882, and the mean exports percentage is 3.523. The mean percentage of services (water and sanitation) of the urban and total population is almost the same and all those are around 4.45. The mean fertility rate of the panel is below one, and the mean prevalence of HIV among people of the reproductive age group is − 1.849.
The correlation matrix of the studied variables is reported in Table 3. The table shows that GDP per capita and urbanization are negatively correlated with CIWB. Urbanization is positively correlated with GDP per capita, where the fertility rate is negatively correlated with GDP per capita. Basic citizen services, e.g., drinking water and sanitation, are also positively correlated with GDP per capita and urbanization. But those services are negatively correlated with CIWB.

Panel unit root test
Two-panel unit root tests with and without trend were conducted to check the stationary property of the datasets and presented in Table 4. Both ADF-Fisher and PP-Fisher tests confirmed that all variables become stationary at levels except GDP per capita. The GDP per capita becomes stationary after first differencing. Therefore, the order of the integration of GDP per capita is I(1) and all other variables are I(0).

Panel cointegration
To test the long-run relationship of the studied variables, the study has conducted a Kao test for testing panel cointegration (Table 5). Out of the five, three statistics of the Kao test have rejected the null hypothesis of no cointegration. This outcome leads us to conclude that the variables have a longrun relationship. Table 6 presents the detailed findings for the estimated models using Prais-Winsten estimator and pooled OLS estimator. Both models contain all 47 countries included in the analyses and controls for the following: GDP per capita, exports as a percent of GDP, urban population as a percent of the total population, the percent of the urban population with access to an improved water source, the percent of the urban population with access to improved sanitation facilities, the percent of the total population with access to an improved water source, and the percent of the total population with access to improved sanitation facilities. Regression outputs report the regression coefficients, significance level, panel-corrected standard errors, R-squared statistic, and the number of observations. In the Prais-Winsten and pooled OLS estimator models, GDP per capita is positive and statistically significant in the total sample of countries. This finding is compatible with some earlier works of (Al-Mulali et al. 2015a, 2015b; Aslam et al. 2021;Farhani & Ozturk 2015;Islam et al. 2021) who postulates the growth is emission enhancing. To be specific, a 1% increase in GDP per capita will increase CIWB by 0.27% which is detrimental. As most of the Asian countries are developing economies, they are using more energy for sustaining their growth process and as a cost of development process emitting more CO 2 emission. This result indicates that there is a necessity of choosing cleaner energies for cleaner production to sustain the growth process. Both estimator models exhibit the same coefficient for GDP per capita, confirming the robustness of the model. In both estimation techniques, the environmental Kuznets hypothesis is sustained that describes the overall relationship between GDP per capita and CIWB. This finding is not compatible with the findings of (Farhani & Ozturk 2015) as they have not found the existence of EKC in their study, but a number of recent works have found the existence of the EKC hypothesis (Ali et al. 2020;Raza et al. 2020;Sharmin & Tareque 2020). One reason for divergence might be we have taken CIWB as our dependent variable instead of CO 2 emission with panel specification. Since GDP per capita is the indicator for the level of development of an economy for the linear term, having a positive and significant association between GDP per capita and CIWB is undesirable. If the CIWB Table 3 Correlation matrix *p < 0.05, **p < 0.01, ***p < 0.001. increases with the increase of per capita GDP, then it may threaten economic sustainability in the long run as lower CIWB is desirable and is an attribute of human wellbeing. On the other hand, a negative coefficient for the square of the GDP per capita resulting an inverted U-shaped pattern which is envisaged by the Kuznets theory. It postulates that a boost up in economic affluence from the lowest levels to a mid-level tends to increase the CIWB, but past a turning point, carbon intensity per unit wellbeing decreases which is desirable. Exports as a percent of GDP correspond to the connection to the world economy and are significant as long as the urban population is positive and significant for the sample of countries. These findings are consistent with the outcomes of Ali et al. (2019), Givens (2015), and Ullah et al. (2020) where the later study incorporated industrialization as an indicator of emission. Both urbanization and export require more energy consumption and amenities like electricity and transportation, which in turn is emission-conducive. In terms of the findings of specific interest, urban population access  Table 6 Effects of studied variables on the carbon intensity of wellbeing Standard errors in parentheses. * P < 0.05, ** P < 0.01, *** P < 0.001. to an improved water source and total population access to an improved water source have consistently negative and significant effects on both estimation models. But the urban population access to improved sanitation and total population access to improved sanitation is negative and insignificant in models. These findings are somewhat contrary to the findings of Givens (2015). If we consider the whole Asian economy, the outcomes of water and sanitation scenarios seem to be sustainable as of now. But as the development process is continuing, if not considered carefully, the scenario might change or become unsustainable as the development process is generally associated with any type of consumption, i.e., water and energy. The conventional form of energy utilization to meet the basic needs is harmful to the environment as CO 2 emission occurs more from those sources. Two additional control variables were taken in the estimation procedure with the expectation that they might have an impact on the overall wellbeing of humans and the environment, and those are total fertility rate and the prevalence of HIV in the population of 15-49 year olds (Table 7). The total fertility rate is incorporated to address the population dynamics along with physical health and way of life, and the prevalence of HIV is indicative of health and epidemiological factors. Both of these features are directly linked with life expectancy. This table shows the findings for the estimated models using Prais-Winsten estimator and pooled OLS estimator. Both models contain all 47 countries included in the analyses and control variables are the same as Table 6. Regression outputs report the regression coefficients, significance level, panel corrected standard errors, R-squared statistic, and the number of observations. The outputs of Table 7 are not so different from the obtained findings of the previous table (Table 6). Here, the results also support the environmental Kuznets hypothesis.

Prais-Winsten estimator
Exports as a percent of GDP are significant as long as the urban population is positive and significant for the sample countries. Specifically, urban population access to an improved water source and total population access to an improved water source has consistently negative and significant effects on both estimation models. But the urban population access to improved sanitation and total population access to improved sanitation is negative and insignificant in models. These findings indicate that human requirements are not always a threat to sustainability. Both the fertility rate and the prevalence of HIV are interlinked with a decrease of the CIWB in the case of Asian countries showing no harmful impact. The findings are also desirable to lower CIWB. These two aspects are linked with urban growth also. Therefore, to ensure human wellbeing, sustainability issues require much rigorous attention and consideration so that those issues could help to lessen the overall CIWB.

Discussions
If we further go deeper into the findings we have got from the two models, the results are consistent and follow theoretical explanation. The assumption of the EKC hypothesis is straightforward that an increase in per capita GDP (affluence) will decrease environmental stress and enhance sustainability therefore wellbeing. Our findings support the EKC hypothesis. The findings of this study for Asian economies as a whole are supporting "economic and ecological modernization" theory and opposing the "treadmills of production" theory which is different from the findings of Dietz et al. (2012) and Knight & Rosa (2011). The reason might be unlike their studies, we have incorporated issues like social wellbeing indicators (i.e., water, sanitation, fertility rate, the  prevalence of HIV) while applying the EKC hypothesis. The factors other than per capita GDP could play a substantial role in wellbeing and sustainability, as suggested by both the abovementioned studies are working here. The study of Rice (2008) put forward that in comparison to developed economies, developing economies have a higher level of marginal utility of environmental utilization. Figure 1 in Appendix 1 shows the GDP of Asian economies are mostly developing economies other than few developed economies. This could be another reason that the findings supporting the "economic and ecological modernization" theory and "human ecology" theory for Asian economies. The findings of this study are also compatible with the findings of Jorgenson (2014) as long as the African economies are concerned though, in present decades, their growth-CIWB relationship is becoming slightly unsustainable. However, considering Asian economies, the study found that with the increase in GDP per capita CIWB increases. This finding diverges from our finding that with the increase in growth, CIWB decreases as established by EKC theory. The rationale might be that the study of Jorgenson did not incorporate all the Asian economies and only concentrates on GDP per capita and CIWB whereas, our study includes other indicators also to see the relationship. The growth-CIWB association for North America, Europe, and Oceania is positive because this region is generally pooled to the high-income economies, and they may be burning more fossil fuels to ensure economic growth. Steinberger et al. (2012) have found that high-income countries are responsible for more carbon emissions, and Fang et al. (2019) also address that G-20 countries are also following an unsustainable path for growth. These findings resonate with the study of Akenji et al. (2016), and they have found that the richest economies should reduce their expenditure, whereas the poorest economies could increase their growth to reduce the ecological pressure.
Moreover, Asia is constantly urbanizing, with many people shifting to urban vicinities (UN DESA 2018) with greater needs for energy. Therefore, the need for industrial activities is also increasing which is indicative of the positive impact of export and urbanization on CIWB as found from the study. This rural-urban transition is telling us of massive urban growth with the enormous scale of energy need that poses a fundamental challenge to economic opportunity, social cohesion, and the continuation of healthy environments (Moore et al. 2003). Contrary, the significant connection involving economic development and urbanization is well-known. As suggested from the study outcomes, urban places are unable to provide better facilities due to a lack of efficient services with the provision of economic activity and healthy environments, therefore increasing CIWB. The findings also indicate that the urban transition is becoming unsustainable as it is increasing CIWB using energy-intensive technologies in urban transportation and non-renewable energies in urban facilities. Export is another reason for increasing CIWB as it is important for sustaining growth. It seems that growth and industrialization are following an unsustainable path. Urban facilities are sustainable as found from the results though urbanization hampering the overall wellbeing. In this respect, some issues are pertinent. The water and sanitation scenario, fertility rate, and prevalence of HIV to this moment give the impression that it is following a sustainable course but more use of conventional energy in ensuring urban facilities could blight the otherwise pleasant scenario by increasing CIWB.
Due to limitations in data availability, the study uses unbalanced data on 47 Asian countries for the period 1990-2019 for panel analyses. Moreover, the inclusion and exclusion of different variables might show dissimilar outcomes.

Conclusion and policy implications
This study investigates the economic, social, and environmental wellbeing issues by measuring the carbon intensity of wellbeing (CIWB) of Asian economies. "Economic and ecological modernization" theory is of the opinion that for sustainability, economic development is fundamental and "human ecology" theory encompasses a wider perspective and views of wellbeing considering human development and sustainable climate conditions. On the other hand, the "treadmills of production" theory and political economy theory negates the necessity of economic development for sustainability. The findings of the paper are well matched with the view of the economic and ecological modernization theory that postulates that with the increase in economic growth environmental quality will be restored as well as with the human ecology perspective that is in favor of wellbeing including health and climate conditions. It is evident from the findings of this study that a negative coefficient for the square of the GDP per capita resulting in an inverted U-shaped pattern and also from the other social indicators.
Employing Prais-Winsten and pooled OLS estimator, in both the estimation models urban population access to an improved water source and total population access to the improved water source has consistently negative and significant effects on CIWB. The fertility rate and prevalence of HIV also pose no threat to CIWB. These findings as a whole demonstrate that social and human wellbeing indicators of the Asian economies are sustainable to this moment as they are lowering CIWB. These results confirm and relate to the study of Givens (2015). On the other hand, GDP per capita, exports as a percent of GDP, and urban population are significant and positive for CIWB in the case of Asian countries, which pose a challenge for the sustainability issue as they are increasing CIWB. Supporting these findings, Asian economies should choose better urbanization and economic growth policies that ensure the sustainability of the human and environmental factors and reduces the impact on CIWB. To be specific, growth, urbanization, and export require necessary utilization of energy. Excessive consumption of traditional fossil fuel in this regard is harmful. Therefore, a required amount of energy, i.e., both renewable and nonrenewable is indispensable in the total energy mix so that it does not harm the overall wellbeing.
Needless to say that decarburization is arduous to achieve overnight but the incorporation of low carbon measures in national and regional policies may support to realize a range of development priorities including employment opportunities, better health outcomes, social inclusion, less congestion, poverty alleviation, reduce inequality, and so on. Moreover, the economic benefits of low carbon measures are quite substantial in the monetary unit as well to give a second thought rather to think of decarburization exclusively. Although the economic gain of low carbon measures is necessary, but not a sufficient condition for wide decarburization. More specifically, the use of clean energy and renewable energy for the decarburization of a country's economy is crucial with environmental governance and better institutional quality for ensuring sustainable CIWB as it corresponds to the geographical and political phenomenon. In addition, regional policy decision related to wellbeing indicators as well as a deepening regional environmental integration is necessary to safeguard CIWB. Future studies should take into account the feminization of environmental issues in wellbeing research.