Ecological footprint is a multi-dimensional indicator of environmental quality that measures how much the regenerative biological capacity of land and sea areas to maintain a given human demand on food, services, transportation, goods and housing (Wiedmann et al., 2006). Apart from this, the available literature on ecological footprint from the economic perspective is constantly increasing. We present recent studies on ecological footprint in the following sub-sections.
2.1 The environmental Kuznets curve (EKC) hypothesis with ecological footprint
The EKC hypothesis is used extensively to investigate the environmental aspect of economic growth. A majority of current studies is found to consider measures of pollution as proxies for environmental quality. Generally, carbon dioxide (CO2) emission is chosen as one of the most popular pollutants to proxy for environmental degradation in testing the EKC hypothesis (Esteve & Tamarit, 2012; Hamit-Haggar, 2012; Wang, 2012; Chow & Li, 2014; Yii & Geetha, 2017; Lau et al., 2019; Sarkodie & Ozturk, 2020; Ummalla & Goyari, 2021; Go et al., 2021a). In fact, the use of CO2 emissions in the analysis of the EKC hypothesis could produce bias estimates due to inappropriate environmental degradation indicator adopted.
These bias estimates are found in previous EKC studies in the context of different countries. For example, Qatar over the period of 1980–2011(Mrabet & Alsamara, 2017), Malaysia over the period of 1971–2016 (Bello et al., 2018) and 14 European countries over the period of 1990–2014 (Altıntaş & Kassouri, 2020). By using a broader proxy for re-evaluating the hypothesis, countries’ ecological footprint provides a means by which researchers can keep abreast of a more comprehensive measure of environmental degradation. For this reason, several studies opt to validate the EKC hypothesis that explains the relationship between environmental quality and economic development by emphasizing on the role of ecological footprint as an alternative to CO2 emissions (Caviglia-Harris et al., 2009; Al-Mulali et al., 2015; Aşıcı & Acar, 2016; Acar & Aşıcı, 2017; Charfeddine & Mrabet, 2017; Ulucak & Bilgili, 2018; Destek et al., 2018; Mikayilov et al., 2019; Yilanci & Pata, 2020; Dogan et al., 2020; Ansari et al., 2020; Danish et al, 2020; Naqvi et al., 2021; Pata & Caglar, 2021).
The EKC hypothesis with ecological footprint is initially supported by the findings of Al-Mulali et al. (2015) who demonstrate an inverted U-shaped relationship between ecological footprint and economic growth in most of the upper middle- and high-income countries over the period of 1980–2008. However, this relationship does not occur in low-income countries in which technologies are available in improving energy efficiency. Due to high costs, energy saving and renewable energy in such countries are not accessible. Then, several scholars proceed to validate this hypothesis in other countries, wherein they successfully provide clear evidence of an inverted U-shaped for the EKC hypothesis. For instance, Aşıcı and Acar (2016) attempt to investigate whether countries that grow richer tend to reduce their ecological footprint. By analyzing the production and import components of the ecological footprint for the period 2004–2008, they perform the analysis for a panel of 116 countries. Their results indicate the support for EKC hypothesis between income per capita and ecological footprint of production. In terms of imported footprint, they find that it exhibits a monotonic increasing trend with income. When the economy grows further, the countries would export the ecological cost of their consumption to other poorer economies. By studying Turkey over the period of 1961–2008, Acar and Aşıcı (2017) find an inverted U-shaped relationship between footprint production and income, suggesting that the country tends to domestically reduce its outputs from environmentally harmful production through imports.
Additionally, Charfeddine and Mrabet (2017) find that the real economic growth per capita exhibits an inverted U-shaped relationship with ecological footprint in eight oil-exporting countries for the period between 1975 and 2007. Ulucak and Bilgili (2018) apply continuously updated fully modified and continuously updated bias corrected models to reveal that the EKC hypothesis is present among all examined countries’ ecological footprint regardless of income groups from 1961 to 2013. Destek et al. (2018) apply second generation panel data methodologies to take the cross-sectional dependence among countries into account. Their results demonstrate that the real income exhibits U-shaped relationship with ecological footprint in European Union countries from 1980 to 2013. By employing fully modified ordinary least squares and dynamic ordinary least squares long-run estimators for the period from 1992 to 2016, Danish et al. (2020) find that the EKC hypothesis with ecological footprint is validated in individual BRICS countries (Brazil, Russia, India, China and South Africa). Naqvi et al. (2021) reach the similar finding across a panel of 155 countries from different income groups over the period of 1990–2017.
Some studies fail to find evidence for the inverted U-shaped relationship between ecological footprint and economic development. For instance, Caviglia-Harris et al (2009) use an unbalanced panel of 146 countries over the period of 1961–2000 and find that economic growth alone could not lead to sustainable development. Moreover, Mikayilov et al. (2019) investigate the long-run impact of tourism development on ecological footprint in the case of Azerbaijan for the period of 1996–2014. By employing time-varying coefficient and conventional cointegration techniques, their results support time invariant income elasticity of environmental degradation, implying that the EKC hypothesis is not present. In a study on Brazil, Russia, India, China, South Africa and Turkey for the period of 1980–2014, Dogan et al. (2020) take the issues of heterogeneity and cross-section dependence into account. Their results do not support the EKC hypothesis. In addition, they find that energy intensity and energy structure are important determinants of environmental degradation.
With the application of dynamic ordinary least square and fully modified ordinary least square, Ansari et al. (2020) find that an inverted U-shaped relationship between economic growth and ecological footprint does not exist in the case of Gulf Cooperation Council countries (Bahrain, Oman, Qatar, Saudi Arabia and the United Arab Emirates) from 1991–2017. By considering time-varying causality, another study by Yilanci and Pata (2020) on China shows no evidence for the EKC hypothesis over the period of 1965–2016. Their results indicate that the short-term elasticity of economic growth is smaller than the long-term elasticity, implying that economic complexity has an increasing impact on ecological footprint over time. By taking the presence of one structural break in the annual data of China into account, Pata and Caglar (2021) find a U-shaped quadratic relationship between ecological footprint and income level from 1980–2016, revealing that the EKC hypothesis does not hold.
2.2 The environmental Phillips curve (EPC)
Another strand of the literature explores the relationship between environmental degradation and unemployment (Kashem & Rahman, 2020a; Anser et al., 2021). In an effort to provide a new concept in explaining this relationship, Kashem and Rahman (2020a) propose the EPC. They apply a panel data estimation method to validate their concept by looking into 30 industrialized countries for the sample period of 1990–2016. Based on both visual inspection and econometrics, they observe that the invented function shows an inverse relationship between pollution and unemployment. This finding confirms the existence of a negative relationship between pollution and unemployment. In line with this, the authors suggest that the use of any viable technology could curb pollution and maintain or improve the employment level of the economy.
However, Rayhan (2020) queries their justification by stating that the relationship between pollution and unemployment would become vertical when the economy achieves the full employment level of output in the long run. By responding to the query, Kashem and Rahman (2020b) state that the full employment would not exist in any countries in the reality. Their empirical study demonstrates the existing negative relationship between these two variables in most of the countries, provided that a reflection of real situation prevails in the countries. Lastly, Anser et al. (2021) conduct a study using a panel data set that consists of Brazil, Russia, India, China, South Africa and Turkey for the period spanning from 1992 to 2016. Their findings affirm the validity of the EPC by indicating that a significant trade-off exists between unemployment and environmental degradation.
2.3 The impact of clean energy on air pollution and ecological footprint
The use of clean energy is vital for environmental sustainability (Tapaninen et al., 2009). In line with this, many current studies demonstrate that pollution emerges as the key factor behind the significant growth of clean energy sources. For instance, Menyah and Wolde-Rufael (2010) find that consumption of nuclear energy could mitigate CO2 emissions in the United States from 1960 to 2007. Cai et al. (2018) reveal a unidirectional causality running from clean energy consumption to CO2 emissions in the United States for the period from 1965 to 2015. By using a balanced panel dataset from 1995 to 2015, Lau et al. (2019) find that electricity generated by nuclear source could lower CO2 emissions without retarding the long-run growth in a group of 18 OECD countries. Maji (2019) performs the analysis of system generalized method of moments by using annual data of 2010–2017. Their results support the notion that increased renewable energy usage could dampen CO2 emissions in 42 sub-Saharan countries. Anser et al. (2021) find that renewable energy consumption could reduce the growth of CO2 emissions in Brazil, Russia, India, China, South Africa and Turkey from 1992 to 2016. Also, Destek and Aslan (2020) discover that consumption of disaggregated renewable energy (hydroelectricity, wind, solar and biomass) could reduce carbon emissions in the Group of Seven countries between 1991 and 2014. Usman et al. (2020) demonstrate that alternative and nuclear energy asymmetrically affects CO2 emissions in the case of Pakistan for the period from1975-2018.
Using a dataset from 31 Chinese provinces for the period of 2011–2017, Zhu et al. (2020) demonstrate that technological innovations in renewable energy could alleviate concentrations of nitrogen oxides and respirable suspended particles, but not for sulfur dioxide. Ummalla and Goyari (2021) find that clean energy consumption could significantly reduce CO2 emissions in a panel of BRICS countries for the period from 1992–2014. By using Australian annual data from 1980 to 2014, Ahmed et al. (2021) find that a high elasticity of reduction in CO2 emission per capita is due to an increase in the long-run consumption of clean energy.
To shed more light on the clean energy usage, a further empirical investigation is performed to determine whether it is responsible for the increase or decrease of ecological footprint. Based on varied economic structures and environmental regulations across the globe, most of the studies suggest that clean energy usage can improve environmental quality. For instance, by controlling for the effects of financial development and real output, Usman et al. (2020) reveal that the share of renewables in the total primary energy supply exerts a negative pressure on ecological footprint in the long run using quarterly data from 1985 to 2014 for the United States. Meanwhile, renewable energy is positively linked to ecological footprint in the short run. In examining the determinants of ecological footprint in BRICS economies, Danish et al. (2020) find that an increase in the percentage of total renewable energy consumption could reduce ecological footprint over the period from 1992 to 2016. More recently, Sharma et al. (2021) find that the long-run usage of renewable energy could significantly reduce ecological footprint in 8 developing countries of South and Southeast Asia during the period from 1990 to 2015. Based on a sample of top 22 renewable energy countries, Ansari et al. (2021) find that consumption of renewable energy could provide a negative impact on ecological footprint in the long run. Lastly, a study by Naqvi et al. (2021) demonstrates that consumption of biomass energy could negatively contribute to ecological footprint in high- and low-income countries from1990-2017.
2Proposed by Kashem and Rahman (2020).
3It is because people in rich countries demand for more resources than citizens in the poor countries