1. Introduction
Within the paradigm of sustainable development goals, countries in the European Union (EU) have accepted the green deal policy, which aims to decarbonize economic growth by 2050 [
1,
2]. Thus, the EU will become the first region with carbon-free economic development. However, although countries in the EU provide coherent policies, the EU has disparities and gaps in reducing carbon emissions and consequently achieving sustainable development goals (SDGs) [
3,
4,
5].
The concept of “green economic growth” is linked to the paradigm of sustainable development and reflects economic growth considering the rational use of natural capital, prevents and reduces pollution and developed opportunities to improve social well-being due to providing carbon-neutral economy [
6,
7,
8]. The concept of “greenfield investment” is wider and complex definitions, the scholars [
9] define it as the investment on environmental, social and governance projects which aims to achieve sustainable development goals in long-term. Based on the methodology of experts from the Division on Investment and Enterprise of UNCTAD [
10], within this study the green field investment is the value of announced greenfield foreign direct investment projects.
It should be noted that the transition to green economic growth requires green innovations and technologies that reduce environmental degradation, particularly carbon emissions. Scholars [
11,
12,
13,
14,
15] confirm that green innovations have a statistically significant impact on declining carbon dioxide emissions and boost the achievement of SDGs. At the same time, past studies [
16] emphasize that countries with strong institutions and effective implementation of sustainable development principles have higher capabilities for extending green innovations. In addition, new innovations and technologies require additional resources (financial, labor, etc.). Prior studies [
17,
18] have highlighted the crucial role of greenfield investment in boosting green innovations and technologies. Adeel-Farooq et al. [
19] confirmed that greenfield investment negatively affects environmental performance in Asia countries. At the same time, economic growth positively affects environmental performance. However, Neto et al. [
20] concludes that economic growth boosts the greenfield investment, however the reverse effect is not confirmed. At the same time, they showed that greenfield investment could have indirect effects on countries economic growth in developed and developing countries. Bayar Y. [
21] also showed that greenfield investment promotes the economic growth in EU countries. At the same time, the countries have disparities in attracting external and allocating internal green investment [
22]. Consequently, it could restrict the green economic growth of the country. On the other hand, countries with a high level of green economic growth are more attractive for investors. In this case, it is relevant to indicate if the greenfield investment has the direct effect on green economic growth. It should be noted that the scientific community has not accepted universal approaches for assessing green economic growth: (1) approaches based on the world indexes SDG Index, Global Sustainable Competitiveness Index, and Global Green Economy Index [
23,
24,
25,
26]; (2) approaches based on green GDP [
27,
28]; and (3) approaches based on desirable and undesirable outcomes [
29,
30]. This study bridges the theoretical gap in green economic growth by developing an approach that (1) assesses the green economic growth of the EU countries based on the Malmquist-Luenberger Global Productivity Index. It allows considering the input (labor, capital, energy), desirable (gross domestic product) and undesirable output (emissions to the environment); (2) to measure the impact of greenfield investment on green economic growth by using the Tobit model. The novelty of this study is developed approach of assesses the green economic growth, and how greenfield investment effect on which unlike the existing ones consider the desirable and undesirable outputs and based on Malmquist-Luenberger Global Productivity Index and Tobit model. The past studies [
31,
32,
33] which used the Malmquist-Luenberger Global Productivity Index focused on indicators of the sustainability of individual sectors or industries for the territory and the impact of environmental regulation and green economic growth achievement. While the overall analysis for EU member states and the EU as a whole union are not often investigated. At the existence studies did not consider key indicators for achieving a carbon-neutral economy and the Sustainable Development Goals: emissions to the environment and a share of renewable energy in primary energy consumption. Furthermore, for a deeper understanding of the countries’ green growth progress, this study evaluates the effectiveness of the relevant policies of EU countries. The findings of Tobit model are basis for policies suggestions within increasing green growth in the EU.
This study has the following structure: the Literature Review analyses the theoretical landscape of green economic growth and its core dimensions; the Materials and Methods section explains the variables and sources, methods and instruments to test the hypothesis of the research; the Results explain the empirical results of hypothesis testing; the Discussion and Conclusion summarize the findings, compare the analysis of the obtained results with the previous studies, limitations and further directions for investigations.
4. Results
Considering the empirical results (
Table 2) among EU countries, the highest values of green economic growth were found in the following countries: Cyprus—in 2012, the value was 1.072; Ireland—1.0527 in 2015; Luxembourg—1.0456 in 2006. The lowest value is in Malta —0.7419 in 2015 (
Table 2). In addition, Cyprus and Malta have the most uneven values of green economic growth among all the analyzed countries. The coefficients of the variation
for Cyprus and Malta are 0.10 and 0.08, respectively.
In 2010, the EU countries identified five goals of the development policy: employment, innovation, education, social inclusion, and climate change/energy. Within each goal, all countries have accepted the national indicative targets. Considering the findings of and , the following countries are involved in the Green Group: Austria, Denmark, Finland Germany, Netherlands, and Sweden. Countries from the Green Group provide an effective policy on the reduction in CO2 emissions, increasing energy from renewable sources and improving social and economic development. The Yellow Group includes Belgium, Croatia, the Czech Republic, Estonia, France, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, Poland, Portugal, Romania, the Slovak Republic, Slovenia, and Spain. The Red Group contains Bulgaria, Cyprus, Greece, and Malta. It should be noted that countries from the Red Group are far from the achievement of the national indicative targets, particularly SDG7: Affordable and Clean Energy (CO2 emissions from fuel combustion per total electricity output), SDG12: Responsible Consumption and Production (electronic waste, production-based SO₂ emissions, SO₂ emissions embodied in imports), and SDG13: Climate Action (CO2 emissions from fossil fuel combustion and cement production, CO2 emissions embodied in imports, CO2 emissions embodied in fossil fuel exports).
The study applies the panel Tobit regression model with random effects to assess the dimension’s impact on green economic growth. In the first stage, all data are checked for stationarity by applying Levin–Lin–Chu, Im–Pesaran–Shin, augmented Dickey–Fuller, and Harris–Tzavalis tests (
Table 3).
The values and
p-value (
Table 3) within the Levin–Lin–Chu test show that all data are stationary. However, the findings of the Im–Pesaran–Shin, augmented Dickey–Fuller, and Harris–Tzavalis tests allow rejecting the null hypothesis on the existence of a unit root for TO and WGI, and their minimal probability (
p value) and non-stationarity are 19.0% and 47.8%, respectively. This means that TO and WGI are non-stationary at this level. However, at the first difference, all data within all tests are stationary.
The variance inflation factor (VIF) allows for checking multicollinearity. It shows the coefficient regression’s impact on standard error for all independent variables. The square root of VIF indicates how much larger the standard error is compared with if the variable were uncorrelated with all other independent variables in the regression. The findings of multicollinearity are shown in
Table 4. The VIF values for all variables are less than 10, which confirms the absence of multicollinearity.
The findings of the impact of greenfield investment on the green economic growth for all countries and separate groups depending on the efficacy of the policy for green economic growth are shown in
Table 5. Columns (1), (3), (5) and (7) in
Table 5 contain the results with 9 considering only one explanatory variable in Model (4). Columns (2), (4), (6) and (8) show the results considering all control variables. The study provides a likelihood-ratio test to identify the reliability of using the panel regression method. The
p values for all countries and the green, yellow and red groups are less than 1%. This means that at least one of the regression coefficients in the model is not equal to zero. The impact of GI on green economic growth is positive and statistically significant for all types of samples. The addition of explanatory variables TO and WGI does not change the sign and statistical significance of the GI’s effect on Ged. This shows that in the EU, the tool for green structural changes and development is the intensification of green investments aimed mainly at technologies and equipment to increase renewable energy sources and reduce environmental pollution.
Targeted energy, environmental protection, and social policies could become important stimulators of green economic transformations, providing new sources of growth due to “low carbon” technologies and developing new markets, industries, and jobs. It should be noted that the quality of institutions plays a core role in providing green economic growth due to direct and/or indirect effects. Thus, an effective government policy based on financing green transformation, spreading green technologies, enhancing research and development, and promoting green products and services is conducive to green economic growth. Considering the empirical results, WGI (quality of institutions) has had a statistically significant effect on the green economic growth for countries from the Green Group. Thus, the growth of WGI by one point led to Ged growth by 0.116. At the same time, for countries from the yellow and red groups, WGI does not have a statistically significant impact on green economic growth. In addition, trade openness has statistically significant impacts on green economic growth for all country groups. The intensification of the goods and capital movement among countries along with the corresponding targets for achieving the SDGs is a kind of incentive for changing the behavior of producers and consumers to use resources more effectively, considering the consequences for the environment. The findings of the analysis of the relationship between greenfield investment and green economic growth for each country are summarized in
Table 6.
Countries within the EU have tried to improve the quality of the environment by improving renewable energy sources and extending green technology. However, the green economic growth differs from country to country. GI has a positive statistically significant impact on the green economic growth in Austria, Belgium, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Italy, Latvia, Malta, the Netherlands, Portugal, Slovakia, Slovenia, Spain and Sweden. This means that the growth of green investment develops the appropriate conditions for the green economic growth due to developing new workplaces and increasing the efficiency of production. In this case, the government of the country from the Yellow and Green Group should enlarge investment in green projects and technologies that aim at extending renewable energy. In addition, the positive statistically significant impact of trade openness on the green economic growth justifies the necessity to develop common international projects to enhance collaboration between countries in spreading renewable energy. Furthermore, it is necessary to improve the quality of institutions that allow for the development and implementation of effective strategic decisions that meet the demands in the energy sector, improving the qualifications of the workforce, update the fixed capital to reduce the anthropogenic impact and increase the competitiveness of countries.
5. Discussion and Conclusions
The concept of the green economic growth is the most important element of development strategy for the EU countries. This meant promoting the most resource-effective, ecological, and competitive economy. In addition, EU countries actively consider ecological issues under industrial production, and attracting greenfield investment and renewable energy consumption are conducive to the green economic growth. At the same time, the EU countries have disparities in achieving green economic growth. On the one hand, it is caused by the differences in macroeconomic conditions (labor, capital, gross domestic product); on the other hand, it is the result of targeted implementation of the sustainable development goals.
This study contributes to the theoretical framework on green economic growth within sustainable development goals by developing an approach to estimate the green economic growth of the EU countries which are in contrast to the existing ones based on the Malmquist-Luenberger Global Productivity Index and consider the gross domestic product (as the desirable output) and emissions to the environment (as the undesirable output). Moreover, this investigation contributes to the field of green investment within the developed approach (which the Tobit model is based on) for assessment of the impact of greenfield investment on green economic growth.
The empirical findings confirm that GI, TO and WGI impact differences in achieving green economic growth, which is consistent with prior studies [
27,
45,
48,
54]. Thus, GI, TO and WGI positively affect Ged. Thus, the growth of GI, TO and WGI by one point led to an increase in Ged by 0.015%, 0.180% and 0.002%, respectively. However, despite the differences in the green economic growth, the obtained findings are similar to those of the studies referenced in [
34,
41,
47], indicating that the universalization mechanism of green economic growth is based on a formula that includes the need to increase green investments, the quality of institutions and openness of the economy.
It should be noted that GI has a positive and statistically significant effect on the green economic growth for all types of models, considering the explanatory and control variables. From a quantitative point of view, after including the control variables and other equal conditions , the growth of GI by one point led to improvement in green economic growth by 0.026%, 0.003% and 0.019% for the green, yellow and red groups, respectively. These results are coherent with previous studies [
84,
85,
86], which showed that greenified investment is conducive to green economic growth in the long term. At the same time, the obtained findings are opposite to those from past studies [
19,
20], which prove that greenfield investment could not lead to green economic growth.
Considering the abovementioned results, the following policy implications could be developed:
The EU countries should enhance the common green innovative projects which boost the sharing of the best knowledge and practices, and the development of the network of green investors. Moreover, it allows increase the openness of economy within circulation not only capital and resources but also knowledge and technologies.
The EU commission should provide the obligatory response to publish non-financial statements at all levels (companies, local authorities, etc.). It will increase the transparency and accountability of the greenfield investment during the entire cycle.
It should continue to provide the digitalization of state services which simplify the communication between green investors, business, and authorities during the realization of green projects. Moreover, it allows for a decline in corruption, and increased transparency and trust in the government.
It should improve the legislation base for the circulation of green bonds, which attract new investors to the country. Consequently, it promotes the appropriate climate for developing green innovation projects which act as a catalyst for the green economic growth of the country.
It should continue to intensify the fiscal incentives for green investors minimal loan rates, preferential taxation of green projects, etc.
It should promote green education and implement targeted programs to promote green consciousness and awareness among green investors, businesses, local community, and government.
It should be noted that this research could be further advanced from the following aspects. First, this study explored the linear and direct effects of green investment on the green economic growth while eliminating the transmission impact of other mediating factors. Thus, further research should analyze the nonlinear impact of green investment on the green economic growth and the mediating effect, which could be caused by other variables (corruption, governance efficiency, green innovations, etc.). Second, this study focuses on the analysis of the EU countries for the period 2006–2020, which limits comparisons with other countries (the USA, China, India, etc.). In this case, the next stage of research should enlarge the number of countries for analysis. Third, it is necessary to analyze whether digitalization allows the promotion of green investment in the countries with sustainable development goals. Furthermore, past studies [
45] confirmed the positive effect of crypto trading on renewable sources of energy, which is the basis of green economic growth. Moreover, crypto currency could be an additional financial resource for green innovation.