Assessment of Global Sustainable Development, Environmental Sustainability, Economic Development and Social Development Index in Selected Economies

Deforestation has a negative impact on global climate and ecological system [1, 2]. Thus, it has a negative impact on livelihood security and human well-being. Deforestation increased due to high population growth, overwhelming urbanization, agricultural expansion, industrialization, infrastructural development and over pressure of population on natural resources at global level. Most economies are implementing polices to achieve high economic growth in term of gross domestic product (GDP) [3, 4]. Thus, these economies are using surplus natural resources and ecosystem services (i.e., forestry, water, land, air, soil) to produce goods and services to satisfy the needs of present and growing population. As environmental development is an essential component of sustainable development (SD) [4]. However, the concept of SD is very old and that is emerged in 1972. It has more than 100 different definitions and interaction with numerous indicators and socio-economic activities in a country [5]. Hence, it is projected that SD cannot be achieved without environmental development [3, 4]. Furthermore, quality and quantity of natural resources are adversely affected due to overwhelming deforestation in most countries. Thus, extensive deforestation created a complication to maintain SD especially in developing economies. SD pursues to satisfy the demands of current generations without decline the ability of next generations to achieve their own necessities [4-6]. In above perspectives, theoretical review has shown that SD is an integration of economic, human, social, technological and environmental development [3, 4, 7-12]. Thus, it creates an appropriate bridge between economic, social and environmental development [13, 14]. A group of studies have claimed that protection of environmental factors and ecosystem services, and economic and social development are the crucial determinants of SD [5, 15-18]. Basiago [19] reviewed that economic, social and environmental sustainability are the main dimensions of SD. Guijarro and Poyatos [20] noticed that SD includes income inequality, environmental sustainability, innovation, justice and sustainable consumption of available resources. Sathaye et al. [21] claimed that environmental and economic dimensions are the main determinants of SD. Furthermore, it is also reported that economic growth and economic development directly depend upon environment and natural resources conservation in a country [1, 4]. Howes et al. [22]; Dong and Hauschild [23] explained the factors of environmental sustainability which are also significantly associated with SD. Therefore, to achieve the different goals of SD must be a prime agenda of global economies.

Moreover, recycling, minimization of waste material, substitution of materials, pollution controls, efficient use and protection of natural resources through applications of technologies in production activities are conducive to achieve sustainable development (SD) [1, 3, 5, 7, 14, 24]. Conversely, most economies are framing their policies to attain high development in economic, social and technological sectors [4] as paying low attention towards environmental development and ecological security. As forest area preserves the quality of environmental system and ecological services in term of water conservation and purification, air purification, nutrient cycling, atmospheric environmental purification, soil protection, erosion control, flood protection, carbon fixation, oxygen release and reduce solar radiation impact on human health [3, 23]. Thus, forest area protects the quality and quantity of environmental and natural resources [2, 4]. However, forest area is diminishing continuously due to overwhelming urbanization, high population growth, heavy industrialization, excessive infrastructure development and migration of population from rural to urban area and expansion in cultivated area [3]. Hence, there would be a difficult task to achieve SD without maintaining the environmental development at world-wide.  

Also, there is urged to scientific research community, existing researchers and international development organizations to discover more environmental and Appropriate Technologies (AT) that must be useful to mitigate the adverse effects of deforestation on sustainable development (SD). Though, the movement of AT started in 1970, while it was an attempt to discover and design various types of technologies [7]. That time the main goals of AT was to solve the social and environmental problems efficiently [7]. Another aim of AT was to increase additional use of renewable resources and technologies in production activities to increase economic and social development [7]. Thus, use of AT in production activities work as a key driver to maintain economic, social and environmental development at micro level [25]. Hence, the necessary role of AT is to maintain environmental development and consequently is helpful to attain SD. At present environmental scientists and researchers are working to discover environmental and green technologies, and scientific process which can be used to produce goods and services. Environmental technologies are useful to reduce pollution that is generated due to production activities and provide new material, energy and resource-efficient production process [24]. As environmental technologies create a bridge between economic, social and environmental development [24]. Most researchers and scientists, therefore, claimed that environmental and green technologies are essential for environmental sustainability. Thus, applications of environmental and green technologies are helpful to decouple environmental pollution and resources, thus, both may be useful to achieve SD [5, 16, 24-27]. Gavin [28] also argued that extensive applications of environmental technologies will be conducive to reduce risk for environmental degradation. Matin et al. [29] have noticed that environmental and social development cannot be separated form sustainability. Shafiei and Abadi [30] have also mentioned that environmental and ecosystem friendly technologies would be supportive for SD. Nevertheless, a group of researchers claimed that technologies may be harmful for environment and ecosystem services, if it does not reduce or mitigates the negative consequences of production activities on environmental and natural resources [7]. Urban [31] have conceptually proved that innovation in the environmental field is beneficial to increase SD. Anadon et al. [32] have perceived that SD is positively associated with science & technological development. Armenanu et al. [6] have also highlighted the significance of technologies in SD.

Furthermore, several studies provided a hypothetical aspect on prominence of environmental and green technologies in sustainable development (SD) [20, 27, 30-33]. However, limited research could provide a scientific and empirical evidence on association of environmental and green technologies with SD [31]. Furthermore, existing researchers and research academia could not develop a scientific and universally acceptable method and indicators for measurement of SD. For this, previous studies have created global sustainable development index as an integration of economic, social and environmental development, sustainable development goal index and national sustainable development index using different methods [4, 14, 20, 25, 34, 35]. Based on estimated sustainable development index, most studies claimed that performance of a country in SD depend upon chosen method and undertaken indicators [25, 34, 36]. However, these studies could not assess the interconnection of SD with indicators of economic, social and environmental development. Also, existing researchers such as Singh et al. [3], Singh et al. [4], Armenanu et al. [6], Beder [7] Phimphanthavong [15], Kongoli [17], Singh and Issac [24], Miola and Schiltz [34], Nagy et al. [36] have addressed the answer on various research questions with regards to selection of appropriate indicators for assessment of sustainable development (SD) that are presented here: 

• What must be the appropriate measurement of SD?
• What is interconnection of SD with its components?   
• How environmental technologies are associated with SD? 
• How global economies can achieve SD using environmental technologies in production of goods and services?
• What is the relative performance of economies in SD and its components as compared to others?

Based on aforesaid research question, the present study is accomplished following objectives:

• To estimate the Global Sustainable Development Index (GSDI) as an integration of environmental sustainability index (ESI), economic development index (EDI), and social development index (SDI) for selected 39 global economies. For this, Composite Z-score technique is used to create country-wise GSDI, ESI, EDI and SDI.
• To provide the relative performance of selected economies in SD as compared to others based on estimated values of GSDI.
• To explore the influence of environmental technologies, deforestation and other socio-economic indicators on estimated GSDI using linear, non-linear and log-linear regression models.

3.1 Descriptive results

Figure 1 shows the average values of GSDI for two periods i.e., 2000-2007 and 2008-2016 for selected economies. Accordingly, the ranking of undertaken countries in sustainable development, environmental sustainability, economic development and social development based on mean values (during 2000-2016) of GSDI, ESI, EDI and SDI respectively is presented in Table 5. As the estimated values of GSDI lie between 0.413-0.609 during 2008-2016, thus it infers that there is an existence of high variation in sustainable development (SD) across economies. Sweden, Norway and Switzerland, Finland, New Zealand, Canada, Austria, Australia, Denmark, France, Germany, Japan, Portugal, Estonia, USA, Luxembourg, Netherlands, Belgium, Lithuania, United Kingdom, South Korea, Latvia, Brazil, Croatia, Spain, Czech Republic, Greece, Romania and Hungry have the value of GSDI more than 0.5 during 2008-2016. Thus, these economies have a better position in SD as compared to other economies. These economies could create an effective ecosystem to maintain SD due to their consistent contribution to prevent the environmental and natural resources factors.

India, South Africa and Tunisia have 39^th, 38^th and 37^th ranks respectively as per the estimated values of GSDI during 2000-2007. Thus, these economies have deprived position in SD among the 39 economies. High population growth, overwhelming urbanization, excessive industrialization, extensive dependency of population on agriculture sector, overwhelming deforestation, low applications of green technologies in production activities, extreme poverty, low per capita income, income inequality, low R&D expenditure, low literacy rate, low quality of education, ineffective mechanism of government policies, poor health and sanitation facilities and high gender discrimination are the crucial reasons for these economies to make their poor position in SD. Moreover, extreme poverty, low jobs opportunities, high income inequality, extreme corruption, high illiteracy and political instability are creating obstacles to achieve the goals of SD in these economies. Thus, these economies are required to implement an effective and conducive policy to increase the SD. Mexico, Poland, Slovak Republic, Moldova and China have better position in SD as compared to South Africa, India and Tunisia. Most developed economies like Sweden, Norway, Switzerland, Finland, New Zealand, Canada, Australia, Denmark, Austria, Portugal, France, USA, Germany, Estonia, Japan, Luxembourg, Netherlands, United Kingdom, and Belgium adopted effective and conducive social and economic policies to make their clean environment.

Accordingly, these economies have better position in SD as compared to developing and largely agrarian economies. These economies could provide electricity to all population; thus, these are able to improve the quality and quantity of environmental and natural resources. Mainali et al. [50] suggested that more applications of electricity would be beneficial to maintain clean environment in developing economies. Moreover, these economies have a low population growth, urbanization and industrialization. Therefore, these countries are also able to maintain the balance in natural resources due to migration of population from rural to urban areas. Consequently, these economies could mitigate the adverse impact of urbanization, population growth and industrialization on natural resources. Accordingly, these economies could create an effective platform for SD.

Sweden, Finland and Norway have 1^st, 2^nd and 3^rd position in environmental sustainability among the 39 economies, thus, these economies have better infrastructure to increase environmental development. South Africa, India and Luxembourg have 39^th, 38^th and 37^th position respectively in environmental sustainability. Thus, there is essential for these economies to improve their position in environmental sustainability though implementing conducive policies such as water management and conservation, and protection of ecosystem services. Furthermore, the values of ESI lie between 0.623-0.418 for across countries. Therefore, it infers that there is high variation in environmental sustainability in the 39 countries. It is also seemed that Switzerland, Luxembourg and Australia have a better performance in economic development as compared to other economies. It is concluded that economic development is varied across countries due to diversity in social and economic development associated factors. As per the values of SDI, it is also found that most countries such as Sweden, Denmark, Norway, France, Switzerland, United Kingdom, New Zealand, Finland, Germany, Canada, USA, Lithuania, Australia, Belgium, Netherlands, Luxembourg, Portugal, Estonia, Latvia, Croatia, Hungry, Moldova, South Korea, Spain, Argentina and Czech Republic have better position in social development. India, Tunisia and South Africa have 39^th, 38^th and 37^th position respectively in social development. These countries, therefore, need to increase their situation in social development. Moreover, it is observed that there exist is high variation in values of GSDI, ESI, EDI and SDI for all countries (except Sweden).

3.2 Viability and credibility of estimated indexes

Credibility of estimated index is an important task in academic research. It increases the unanimity among the existing researchers about estimated indexes [3, 4, 12, 24, 51, 52, 53]. Singh et al. [3], Singh et al. [4], Singh et al. [12], Singh and Issac [24], Kumar et al. [51], Kumar et al. [52], Ashraf and Singh [53] also argued that an index has viability or credibility when it has positive or negative but statistically significant correlation with its internal or external indicators. While, the internal and external indicators can be selected based on exiting literature review and theories. Thus, correlation coefficients of GSDI with ESI, EDI, SDI, percentage share of patent applications files in environmental technology and forest area (FA) are estimated to check credibility and viability of aforesaid indexes. Table 6 provides the results for Karl-Pearson correlation coefficient of GSDI with ESI, EDI, SDI, percentage share of patent applications files in environmental technology (ET) and forest area (FA). The estimates infer that the association of GSDI with ESI, EDI, SDI and FA are positive and statistically significant. Thus, estimated indexes have credibility and these indexes also can be used to make a rational prediction. It also indicates that above-mentioned indexes may be used for further empirical investigations. Singh et al. [3], Singh et al. [4], Singh et al. [12], Singh and Issac [24], Kumar et al. [51], Kumar et al. [52], Ashraf and Singh [53] also used afore-mentioned technique to check the validity of estimated indexes. Additionally, the results recommend that SD to be improved as increase in environmental, economic and social development, and forest area at world-wide.

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Source: Author’s Estimation

Figure 1. Performance of selected economies in sustainable development

Table 5. Values of GSDI, ESI, EDI and SDI for selected countries during 2000-2016

Source: Author’s estimation.

Table 6. Linkages of GSDI with ESI, EDI, SDI and other indicators

Source: Author’s estimation. Note- **: Correlation coefficient is significant at the 0.01 level and *: Correlation coefficient is significant at the 0.05 level. GSDI: Global sustainable development index; ESI: Environmental sustainability index; EDI: Economic development index; SDI: Social development index; PPAFET: Percentage of patent applications files in environmental technology; FA: Forest area as a % of land area.

3.3 Influence of ESI, EDI, ET and forest area on GSDI

Table 7 shows the empirical results which examine the influence of ESI, EDI, SDI, ET and forest area on GSDI. Regression coefficients of explanatory variables are estimated using linear, log-linear and non-linear regression models. As log-linear regression model produce lowest values of AIC and BIC as compared to linear and non-linear regression models. Thus, this model provides consistent regression coefficients of explanatory variables. Accordingly, it explains the statistical interpretation of results based on log-linear regression model. The estimates imply that GFSI has a positive and statistically significant association with ESI, EDI, SDI, PPAFET and GFA. Here, it is argued that sustainable development (SD) will improve as increase in environmental, economic and social development. Earlier studies have also claimed that SD in an integration of above-mentioned developmental related indicators [3, 4, 7-9, 12]. These results are also supported by R-squared value i.e., 1.00 and it shows that 100% variation in sustainable development can be captured through environmental, economic and social development related factors.

Table 7. Impact of ET, SDEI, EDI and forest area on GSDI

Source: Author’s Estimation.

Environmental and green technology (ET) would be effective to maintain the path of SD. Furthermore, ESI, EDI, SDI are the integrated index of associated several variables. Hence, it is concluded that SD is an integrated component of economic, social and environmental development, and technological development. Singh et al. [4] also found similar results across countries. ESI is integration of various factors such as access to electricity, CO₂ emissions from various sources, air pollution, electric power consumption, electricity production form different sources, renewable energy consumption, forest area, infant mortality rate, irrigated area, agricultural land, fertilizer consumption, population growth, population density, urbanization, fresh water resources, basic drinking water and sanitation facilities. Therefore, there is requirement to abate CO₂ emissions from various sources using green and environmental technologies in production activities and adoption of best environmental practices to maintain the environmental sustainability in global economies [5]. Use of electricity in production activities is effective to reduce the CO₂ emissions in atmosphere. Therefore, access to electricity for all communities and production of electricity form water, solar and other renewable sources will be favorable to increase environmental sustainability. Renewable energy consumption is also a vital factor to preserve the quality of available resources. Furthermore, sustainable use of water in agriculture will enhance the water sustainability in near future. Forest area is found a significant factor to absorb CO₂ emissions from various sources and it is useful to increase the clean environment [3, 4]. Therefore, it is recommended that global economies are required to adopt an effective policy to ensure the forest area. It is also apparent that forest area preserves the quality and quantity of available natural resources. For this, global economies should control deforestation to protect the reserves forest area. Extensive use of fertilizer and pesticide in cultivation is also caused to increase environmental degradation. There are many demographical factors like overwhelming population growth, population density, urbanization and industrialization also have negative impact on environment and ecosystem services [4]. Therefore, aforesaid issues must be included to formulate a policy towards sustainable development at world-wide. 

Economic development index (EDI) is a combination of GDP per capita, GDP per person employed, total vulnerable employment, total wage and salaried workers, total self-employed, foreign direct investment net inflow, price stability, exports of goods and services, gross capital formation, gross fixed capital formation and consumption expenditure. Thus, aforesaid factors have a greater contribution to maintain the economic development of a nation [4]. Countries like India, South Africa, Tunisia, Moldova, Argentina, Mexico, Hungry, Czech Republic and Greece needs to focus on aforementioned activities to increase their performance and success in economic development.

Social development index (SDI) is a combination of sex ratio, contribution of females in economic activities, female infant mortality rate, total life expectancy rate at birth, education expenditure, age dependency ratio and fixed telephone subscriptions. As sex ratio and female’s contribution in economic activities are useful to maintain the social equality and development. Furthermore, literacy rate is observed a vital factor to increase social equality and social development. Hence, extensive education expenditure will be useful to increase literacy rate and social development as well. Social communication increases as increase in fixed telephone subscriptions. Thus, it a crucial determinant to increase social development. In brief, countries such as South Africa, India, Tunisia, China should include aforementioned activities in further policy formulation to improve their position in social development in global economies. Also, environmental technology (ET) has a positive influence on GSDI, thus, it would be useful to achieve SD in future. Therefore, it is requested for global economies to discover more environmental and green technologies for production of goods and services. Environmental and green technologies will be developed through strengthening the science & technological development, increasing the involvement of researchers and scientists in R&D activities and extensive R&D expenditure in environmental and natural resources sciences. Thereafter, applications of environmental and green technologies in production activities would be helpful to mitigate the negative consequences of deforestation, natural disasters, climate change, other socio-economic activities and demographical change on SD [1, 4]. Furthermore, the empirical results based on non-linear regression model, indicate that sustainable development has a linear association with economic development, social development, and forest area. While, environmental sustainability and environmental technology have non-linear association with sustainable development.

Table 8. Correlation coefficient of error-term with its lags

Source: Author’s Estimation. Note: * indicates the coefficient is significant at 5% level.

3.4 Viability and credibility of regression coefficients

This study used three different models to estimate the regression coefficients of explanatory variables. Hence, it is compulsory to check the credibility of regression coefficients to make the rationality in the prediction of results. For this, existing researchers like Singh et al. [54], Jyoti and Singh [55], Singh and Jyoti [56] estimated the correlation coefficients of error-term with its various lags under a well-defined regression model to check the credibility of regression coefficients. Further, above-mentioned studies claimed that if the correlation coefficients of error-term with its at least first two lags are statistically significant then the regression coefficient may be valid and have credibility as well. Accordingly, regression coefficients may be used to make the future prediction about the output. Therefore, the Auto-correlation coefficient and Partial Auto-correlation coefficients of error-term and its various lags for linear, log-linear and non-linear regression models is given in Table 8. Auto-correlation coefficient among the error-term and its various lags under log-linear regression model is found statistically significant. Thus, regression coefficients of explanatory variables under this model have credibility.

In this study, ESI is as an integration of several factors that is given as:

(i) Air Quality and Pollution: There is essential to abate CO₂ emissions from various production activities. Hence, it is urged to scientific community to discover a carbon sink which can be absorbed the CO₂ emissions from various activities [51]. It would be imperative to preserve the quality and quantity of natural resources, subsequently it may be helpful to achieve SD [14, 21]. Air quality also would improve as use of electricity in production activities. Thus, it is indispensable to provide the electricity to all community to increase environmental quality.

(ii) Energy Management: Appropriate energy management practices like use of electric power consumption, renewable electricity output from various sources such as natural gas, coal, hydroelectric, nuclear and renewable sources would be effective to increase environmental sustainability [3, 4, 16, 17, 50, 59, 60]. Also, renewable energy practices and clean fuel energy consumption would be useful to increase economic development with sustainable economic growth [33].

(iii) Forest and Bio-diversity: Forrest area is an ecosystem-adaption based technique which can be used to reduce the negative impact of carbon emission on natural resources [61-63]. Forest area mitigates the negative impact of climate change in agricultural production activities. It is also useful to increase the water level in ground and reduce the possibilities of natural disasters such as floods, hurricanes, drought, tornadoes, volcanic eruptions, hailstorms, earthquakes, tsunamis and other natural calamities. 

(iv) Human Health and Disaster: There is also essential to maintain human health to control the infant mortality rate through providing better food security and livelihood security. It would be positive to achieve SD. Infant mortality rate can be reduced through providing basic sanitation and better health facilities to rural and urban dweller [3, 64]. 

(v) Land Use Pattern and Agriculture: Applications of fertilizer and pesticides in farming is a significant contributor of GHGs emissions. Thus, there is requirement to adopt organic farming practices to abate GHGs emissions from agriculture and allied sectors. Then, it would be beneficial to preserve the quality and quantity of natural and ecological resources [4, 14, 24, 65].

(vi) Population Pressures on Ecosystem Services: Natural resources and ecosystem services are diminishing due to over population growth and higher urbanization at global level [4]. Thus, it must be mandatory for policy makers to formulate a policy to control population and urbanization to maintain the balance of population pressure on ecosystem services. 

(vii) Water Generation Management: Water resources is scare in nature and it is continuously decreasing due to population growth, urbanization, and extensive use of water in farming, industrial and other sectors [66]. Therefore, it is necessary to adopt water management and conservation policies to maintain water sustainability.

Population growth, urbanization, population density, access to electricity, deforestation, forest area, renewable source of energy, water conservation and fertilizer consumption in cultivation, and science & technological development are seemed most influencing factors of environmental sustainability index [67, 68].

Economic development index (EDI) is an integration of GDP per capita, GDP per person employed, vulnerable employment, wage and salaried workers, total self-employed, foreign direct investment net inflows, inflation GDP deflator, exports of goods and services, gross capital formation, labor force participation rate, gross fixed capital formation, total employers, final consumption expenditure and total unemployment rate [12, 53]. As per capita GDP and labor participation rate generate a conducive path for economic development [14]. Foreign investment net inflow is useful to increase financial stability, create physical asset and it generates more jobs in a country. Consumption expenditure is also useful to increase the demand of goods and services. Accordingly, it provides incentive to manufacturing sector to produce additional goods and creates more jobs for skilled and unskilled labors in a nation. Hence, per capita GDP, labor participation rate, foreign direct investment net inflow, inflation and consumption expenditure are observed most influencing factors of economic development index. Furthermore, R&D expenditure is also significant driver to increase economic development [69].

Social development index (SDI) is a combination of sex ratio at birth, ratio of female to male labor force participation rate, female labor force, female unemployment, and female infant mortality rate, life expectancy at birth, education expenditure and fixed telephone subscriptions [6, 12]. It is found that education expenditure, female labor force, fixed telephone subscriptions, age dependency ratio, female labor force and employment opportunity for female will be useful to increase social development. Gender equity and female’s participation in economic activities are useful to maintain social equity [4, 70]. Education expenditure is effective to increase the literacy rate. Thus, gender equity, female’s participation and education expenditure are found most influencing factors of social development index (SDI). Also, the benefits of social and economic development must be effective for poverty eradication and abating inequality in the society to achieve SD [15].