Introduction

Since the British industrial revolution in the 18th century until now, countries have used various natural resources, especially fossil fuels, to advance the goals of industrialization and urban development. Due to these human activities, the planet’s natural resources have been significantly reduced and witnessed climate problems such as deforestation, desertification, drought, and global warming. This is mainly because the consumption of fossil fuels has had a negative impact on the sustainable development of the country (Shang et al., 2023a). Despite the environmental concerns expressed by various countries, economic prosperity (production, employment, development, poverty alleviation, electricity production, transportation) still depends on fossil fuels. Therefore, countries cannot sacrifice their economic growth for the environment. According to IEA (2021), fossil fuels are the dominant energy resource (nearly 84% to total world energy consumption). Therefore, the rapid change in using a type of energy resource cannot happen. The discourse of sustainable development proposed at the Rio de Janeiro conference (Earth Summit, 14 January 1992) and green growth mentioned at the Rio +20 are two multi-dimensional and gradual targets to combat the climate change threat and make the Earth a better place for the life of posterity.

ADB (2012) defines green growth as a significant theme of Rio+20 (United Nations Conference on Sustainable Development held in Rio de Janeiro, Brazil, in June 2012) and a way to promote economic flourishing while preventing environmental impacts and degradation. Rahman and Alam (2021) express that green growth is a gradual process based on sustainable drivers and environmental protection. By creating green economic prosperity, countries can replace fossil fuels with clean energy, and a bright future awaits the planet’s natural resources. Countries can achieve their desired green economic growth, but it requires comprehensive planning and commitment to the goal of green or sustainable economic growth. Rasoulinezhad and Mostaghimi Ghomi (2022) discuss that sustainable growth depends on various factors and is not a simply accessible target for countries. Releasing countries from consuming non-renewable natural resources and spending on environmentally friendly projects is time-consuming, has unknown angles, and needs global coordination. Xu et al. (2022) state that the green dilemma has arisen due to the conflict between economic interests and environmental concerns. Despite global concerns about a threat such as climate change, economic interests do not allow the acceleration of sustainable development goals such as green economic growth.

There are numerous challenges to realizing the targets of sustainable growth and development. Some scholars (e.g., Chien et al., 2021; Maiti, 2022; Wang and Fan, 2023; Jiakui et al., 2023; Dutta et al., 2023) have emphasized that economic challenges like insufficient capital to make sustainable investments, inflation rate, technological transfer, tax and subsidy, and natural resource rent. However, many earlier studies (e.g., Lee et al., 2022; Purnamawati et al., 2023) have expressed the importance of cultural and social factors to enhance sustainable growth in a country. Education has a meaningful place among different social factors since it directly impacts social literacy and policymaking. In other words, education is a requirement for human development and is a process to make awareness and improve skills for economic activities. Even quality education is one of the defined sustainable development goals by the United Nations. Nousheen et al. (2020) argue that education plays a tremendous role in making social awareness of environmental concerns.

UNESCO (The United Nations Educational, Scientific and Cultural Organization) has defined education for sustainable development (ESD) as an efficient social instrument that can prepare countries to face global challenges like climate change. In the last decade, one of the obstacles to implementing the goal of green economic growth has been the lack of awareness and understanding of society about the critical need to change the way of life and consumption of natural resources in the face of climate change and environmental pollution. Education at different levels can familiarize society with the issues of environmental impacts and natural resource deterioration and prepare for sustainable literacy in different communities, which will positively affect the realization of sustainable economic growth. Zguir et al. (2021) and Yadav et al. (2022) state that education is the primary driver of reaching sustainable development goals in societies, especially in over-populated and developing economies, where social literacy on sustainability can amplify the green economic drivers.

The main impetus of this paper is to measure the impacts of investment in quality language education on green economic growth. The case study of this research is in 23 Chinese provinces. Two primary facts construct the motivations for selecting the case of China for this research. First, realizing green growth is vital for China as the country is a primary global center for carbon emissions, and its contribution to global carbon emissions is more significant than other economies worldwide (27% of global CO2 and 33% of global greenhouse gases in 2021). China’s decision to peak carbon emissions by 2030 and reach carbon neutrality before 2060 is a clear target for the country to obtain sustainable growth and development shortly. Furthermore, China is among the leading countries in the world in terms of sustainable education. Since 1992, the Chinese government has implemented various sustainable educational programs (Min and Dongying, 2007), like the one in the high school affiliated with Fudan University and the green campus of Zhejiang University (Zhu et al., 2021). Exploring the association between quality language education and the country’s green flourishing for Chinese provincial data is scientifically helpful.

The main paper’s contributions to the earlier studies are: First, the green growth index for Chinese provinces is calculated based on the weighting TOPSIS (The Technique for Order of Preference by Similarity to Ideal Solution) method proposed by Lin and Zhou (2022). Second, for the first time, the paper collects the quality of language education from the Chinese General Social Survey data to evaluate the panel data approach. The main challenge in doing this research is to calculate the green growth and quality of language education for the provinces of China due to the need for more access to data.

In continuing, the section “Literature review” provides a literature review. The following Section expresses the theoretical background. Data description and estimation procedure are reported in the section “Data and estimation procedure”. The following Section discusses empirical findings. The last Section summarizes the findings, representing policy implications and recommending points for future research prospects.

Literature review

The related studies to the central theme of the research can be represented in two aspects of research focuses. A strand is to monitor the previous studies focusing on green flourishing in countries. Another strand contains the literature about the impacts of education on green development.

In this first group of studies, scholars emphasized the green growth aspects in different countries. Pelinescu (2015) described the positive impacts of sustainable growth on human capital. They confirmed that sustainable growth improves knowledge-based economic structure by managing natural resources leading to less pollution and more significant outputs. Sandberg et al. (2019) used a critical social theory to discover the social aspects of green growth. The significant findings revealed that environmental sustainability policy through green growth enhances social prosperity and well-being through balancing ecosystems and improving renewable deployment. Xu et al. (2022) studied the green flourishing in BRICS from 1991 to 2014. Employing the quantile regression, they confirmed that green growth depends on various factors that make achieving sustainable growth complex and multi-dimensional. In another study, Fabozzi et al. (2022) declared that green growth is a base of the county’s environmental restoration and conservation. The primary point of green growth is the environment rather than economic flourishing and welfare. Maiti (2022) expressed that green growth improves technological progress in a country, leading to poverty alleviation and less energy gap. Mahmood et al. (2022) argued that energy transformation is the primary factor of economic growth, and countries should try to boost renewable resources deployment instead of burning fossil fuels. Lehmann et al. (2022) studied the German economy. They explained that greening economic sectors aims to decarbonize economic activities by lowering fossil fuel consumption and widening the use of clean energy resources. Zhao et al. (2022) employed the DEA model for Chinese cities to explore the factors influencing green growth. The finding depicted technology and investment’s important role in promoting sustainable economic flourishing. Ge et al. (2023) focused on 285 Chinese cities and evaluated the impact of green growth on geographical neighbors from 2005 to 2018. The results of the particular Durbin model confirmed that ICT diffusion, sustainable innovation, and resource trade influence sustainable growth. Shang et al. (2023b)’s research found that electronic exhibitions are an important factor in achieving a green economy recovery.

Another strand of literature discusses the relationship between education and a sustainable economy. Al-Lian et al. (2019) studied the efficiency of the PERCCOM master’s program on sustainability targets. They concluded that the green ICT diffusion could foster positive impacts of PERCCOM education masters on sustainable literacy of the society. Lee et al. (2022) highlighted the cultural aspect of the green economy. They expressed that educational policies are efficient in improving sustainable culture in a society, changing households’ perception from natural resource deployment to efficient utilization of resources. Ngo et al. (2022) discovered the role of education in improving sustainable human capital in a country, amplifying the green growth drivers. Garcia-Gonzalez et al. (2020) investigated the students’ perceptions of sustainable learning. The findings denoted that sustainable learning causes knowledge and understanding of students about environmental pollution, resource limitations, and climate change threats. Greenland et al. (2022) proposed a five-pillar approach to sustainability in education programs by employing a survey method. They argued that different perceptions of sustainability among respondents are confirmed, which can be addressed as a significant obstacle to realizing sustainable development goals. Dong et al. (2023) did a cross-country study (China, Japan, and India) to determine the primary factor influencing sustainable education. They depicted that sustainable education increases the potential of a country to reach faster to sustainable targets. Educated people are more aware of environmental concerns and the solutions to mitigate carbon emissions.

The review of the last two groups of the literature shows that green economic growth is considered one of the essential discourses of countries. On the other hand, education significantly affects sustainable literacy and skill training in the green economy, changing society’s understanding of development concepts. However, a detailed study has yet to be done on the effect of the quality of language education on the green growth of China. In this research, the explained literature gap is considered, and the relationship between the quality of language education and green economic growth in 23 provinces of China is investigated. Filling this literature gap will make an essential innovative contribution to the literature on economic growth and education.

Theoretical background

Education, as one of the social indicators, has a positive effect on education and increases the level of understanding and recognition in society. This part of the article examines the transmission channels of education on green economic growth. The first channel of education’s impact on sustainable growth is increasing sustainable literacy in society. With the increase in the quality of education in schools and universities, society’s general literacy will be expected to increase regarding environmental issues, waste management, the circular economy, and the fight against the threat of global warming and climate change. Goldman et al. (2018) and Rahai et al. (2023) expressed that any improvement in quality education can lead to the sustainable development of the broader community through spreading green literacy and conferring wisdom and awareness regarding environmental impacts and protection. Another channel of the effect of education on sustainable economic growth is the training of the workforce in green jobs. Increasing the quality of education can provide learners with the diverse skills needed for green jobs. Therefore, increasing people with green skills will make it easier to supply people with green jobs and, as a result, increase the activities of green growth in society. Sulich et al. (2020) mentioned the importance of green job development to promote greening economic sectors in countries. The paper concluded that eco-jobs need labor forces with green skills. Quality education can scale up the numbers of sustainable skilled labor forces. Xie et al. (2020) and Shamzzuzoha et al. (2022) discussed that education is the most appropriate way to increase skills for green economy and innovation. Another transmission channel for the relationship between the quality of education and green economic development is the transformation of educational institutions and universities into leading poles in the sustainable development of countries. Creating green campuses (Ribeiro et al., 2021), green buildings, and green dormitories (Atici et al., 2021) in universities are policies to advance the goals of sustainable development (quality education of green economy) that universities and educational institutions can be successful in this issue due to their high interaction with society. Knowledge of alternative sources of fossil energy is another vital transmission channel to influence the quality of education on green economic growth in a country. By increasing the quality of education, people’s awareness of alternative sources of fossil energy can be increased, it is possible to develop sustainable power plants in different geographical areas, and we can even expect the participation of the private sector (households) in financing local green electricity projects. For example, the research by Shang et al. (2023c) has shown us that green finance plays a promoting role in the deployment of green energy in the tourism industry. Lucas et al. (2018) believe that education gaps exist regarding renewable energy development. Hence, an increase in renewables quality education may effectively surge the size of renewable energy consumption.

According to the mentioned transmission channels, renewable power generation, green jobs, green investment, green growth, quality language education, and waste generation are selected as the variables for the empirical model.

Data and estimation procedure

The paper seeks to find how green growth is affected by quality education in 23 Chinese provinces. The panel data framework for the annual data from 2010 to 2021 is chosen to evaluate the coefficients of the variables. The green growth index for Chinese provinces is calculated based on the weighting TOPSIS (The Technique for Order of Preference by Similarity to Ideal Solution) method proposed by Lin and Zhou (2022). The calculated variable is added to the empirical model as the dependent variable. The Chinese General Social Survey data’s quality language education is collected and considered the main explanatory variable. Regarding the control variables, renewable power generation, waste generation, green investment, and green jobs are selected. Table 1 discusses the details information for the selected variables as follows:

Table 1 Definitions, units, symbols, and sources of variables.
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It is expected that the quality of education has a favorable effect on green economic growth in the provinces of China. Increasing the quality of education means the intellectual and analytical preparation of the people of the society for energy transition, development of clean energy, conservation of natural resources, and fight against carbon dioxide emissions. Sustainable electricity production is expected to affect the sustainable growth of China’s provinces positively. Sustainable electricity production will provide broader and cheaper access to electric energy for the people of different regions of China, reducing the energy poverty gap, increasing the income level, and creating green economic prosperity. Waste generation is predicted to affect sustainable growth goals in Chinese provinces adversely. Generating more waste means not developing a circular economy and consuming natural resources. Sustainable investment is expected to promote green economic growth in Chinese provinces. More sustainable investment means implementing more environmentally friendly projects and, as a result, green economic prosperity. Green job creation is predicted to be positively related to sustainable growth. Green job creation means creating jobs with low environmental impact, which is one of the crucial components of sustainable development and green growth in countries.

Before running econometric estimations, the multicollinearity issue is checked using the variance inflation factor (VIF) approach. Then, the cross-sectional dependency (CD) aspect is explored by conducting the CD test of Pesaran (2004) through Eq. 1:

$${\rm{CD}} = \sqrt {\frac{{2T}}{{N\left( {N - 1} \right)}}\left( {\mathop {\sum}\nolimits_{i = 1}^{N - 1} {\mathop {\sum}\nolimits_{j = i + 1}^N {( {\rho _{ij}})} } } \right)}$$
(1)

In continuation, the CIPS panel unit root test as the second generation of stationary tests are applied to discover the stationary of variables (the second generation stationary tests allow cross-sectionally dependency in the panel). Integration of variables with different orders (0 and 1) ensures the appropriateness of employing the ARDL (autoregressive distributed lag) with the PMG (pooled mean group) estimator.

Empirical results and discussion

In this section, the empirical findings are represented and interpreted. First, the multicollinearity issue is studied by using the VIF approach. Table 2 reports the results and confirms that multicollinearity is not present in the examined panel of variables.

Table 2 Multicollinearity test results.
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In the following step, Pesaran’s CD test checks the cross-sectional dependency among cross-section units of the panel of the Chinese provinces. Table 3 lists the results of the CD test, expressing a CD relationship in the panel.

Table 3 Cross-sectional dependency relationship check.
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The confirmation of cross-sectional dependency association clarifies that the conventional panel unit root tests (first generation) are not fruitful, and the second generation needs to be employed. Table 4 represents the results of the CIPS (cross-sectionally IPS) test and confirms that the variables are stationary at I (0) and I (1).

Table 4 CIPS stationary test.
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The following process comprises the test for checking the co-integration association between the variables. Table 5 demonstrates the co-integration test’s findings and expresses that the variables are co-integrated in the long run.

Table 5 Co-integration association check.
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The ARDL conducts the estimations of coefficients- PMG estimator, reported in Table 6 as follows:

Table 6 ARDL-PMG estimation findings.
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Based on the estimated coefficients, in the long and short term, the quality of language education promotes sustainable economic growth in Chinese provinces. A 1% increase in the quality of language education in Chinese provinces leads to an increase in sustainable growth by 0.013% and 0.69% in the long and short term, respectively. This finding confirms the results of earlier studies like Goldman et al. (2018) and Rahai et al. (2023), who depicted the positive impact of education on sustainable development progress. The development of sustainable electricity production, both in the short and long term, is the increasing factor of green economic growth in Chinese provinces. The development of sustainable electricity generation reduces the use of fossil power plants, which significantly impacts reducing carbon dioxide emissions and consumption of natural resources. Waste generation is an obstacle to green economic growth in Chinese provinces. A 1% increase in the volume of produced waste will reduce the sustainable economic growth of Chinese provinces by 0.57% and 0.15% in the short and long term, respectively. The volume of green investment has a positive and significant relationship with sustainable growth in Chinese provinces. Increasing the amount of investment in environmentally friendly projects can be used both in the short term and in the long term as an essential lever in promoting green economic growth. In the short term, the sensitivity of sustainable economic growth of Chinese provinces to the quality of education (0.69%) and waste generation (0.57%) is more than other independent variables. In contrast, in the long term, the sensitivity of green economic growth to green investment (0.25%) and stable electricity production (0.254%) is more. Green employment has a favorable positive effect on green economic growth in Chinese provinces. In both the short and long term, the development of green job creation will lead to capacity building for the development of green economy activities in the country and, as a result, green economic growth.

In order to ascertain the validity of empirical estimations, a robustness check through changing the dependent variable is conducted. To this end, the composite green growth index based on Zhao and Rasoulinezhad (2023) is calculated and used instead of the last green growth index. Table 7 reports the re-estimation findings by the ARDL-PMG technique. According to Table 7, the signs of the variables’ coefficients align with the results in Table 6, confirming the reliability of the results.

Table 7 Robustness check through changing the dependent variable.
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Conclusion and policy recommendations

The concept of “green economic growth” has been proposed as a severe solution to countries facing environmental threats in the past decades. Implementing the concept of green economic growth requires prerequisites and requirements that can be divided into two categories: social and economic requirements. Economic requirements have been widely discussed in previous studies. However, social requirements have yet to be addressed in previous studies. In this research, the effect of education quality as one of the essential social factors on sustainable economic growth in 23 provinces of China during the period of 2010–2021 was investigated. Based on the obtained results, the following summary can be explained: the quality of education is an effective way to advance the goals of sustainable economic growth in China in the short and long term. Developing sustainable electricity production is a practical component of sustainable growth in the provinces of China. The development of green electricity in different geographical regions of China can provide cheaper and more accessible electric energy, which will reduce the energy poverty gap, and social welfare, reduce the exploitation of fossil fuels and ultimately achieve green economic flourishing. Waste generation is considered to be the disruptive factor of the drivers of green prosperity in Chinese provinces. Creating more waste means less circulation of resources, ecosystem destruction, environmental pollution, and all considered obstacles to green economic growth. Green investment and green employment are also favorable factors in achieving the goal of sustainable growth in Chinese provinces. By increasing the investment in green projects and creating sustainable employment, renewable energy consumption will increase, and countries’ dependence on fossil fuels will decrease. It is expected that with the growth of green investment and employment, the restoration and conservation of natural resources will be promoted.

As practical policies, China should have a more detailed plan to increase the quality of education in schools and universities to use the various education capacities for sustainable development. Increasing the quality of the education package for sustainable development, using virtual education, greening university buildings and student dormitories, and holding specialized training courses for managers and policymakers can be efficient tools for implementing the policy of education for sustainable development (ESD). It is suggested that training on sustainable electricity and its advantages over conventional electricity production from fossil fuels should be held in educational institutions in China so that the development of sustainable electricity production with the participation of households and the private sector in different provinces of China can be established. It is suggested to use government incentive packages to develop a circular economy in Chinese provinces. A circular economy increases the circulation of resources in the economy, which reduces the consumption of natural resources and fights environmental pollution. Another important applied policy is green job creation through small and medium enterprises in China. Small and medium enterprises play an essential role in creating jobs and innovative entrepreneurship in the macroeconomics of every country. Therefore, with the support of the government and the training of these enterprises, it provides the possibility of developing green employment in the provinces of China.

In future research, it is better to study the effect of education quality on sustainable growth at the provincial level to determine the relationship between the variables for each province. In such a case, provincial policymakers in China can formulate more detailed educational programs for the province’s sustainable development. Also, it is suggested to study the effect of universities’ use of renewable energy on China’s economic growth in the future. As leading educational institutions in sustainable development in China, universities can perform better by expanding renewable energy sources.