Green GDP Research Articles

Assessing the Environmental Impact of Green Finance, Tourism, and Globalization in Pakistan

The fast development of technology in the last several decades has created new problems for the environment. The current study evaluates how green finance, tourism, globalization, and GDP affect environmental sustainability in Pakistan during 1989 to 2022. This study utilized ARDL approach to probe the long run tie between studied variables. The empirical evidence of this study revealed that tourism, GDP and globalization deteriorate the environmental sustainability, yet green finance mitigate CO2 emissions. Policy suggestions are provided to regulate the environmental laws to control the adverse impact of globalization and tourism and to transit the economy towards green economy. The policymakers should encourage the green technology for sustainable environment.

Regional Coexistence in the Digital Era: Spatial–Temporal Evolution and Sustainable Strategies of the Coupled System in the Yangtze River Basin, China

Against the backdrop of globalization and ecological civilization, this study aims to analyze the patterns of system coupling coordination development in the Yangtze River Basin under the interacting influences of population growth, ecological conservation, energy utilization, and digital economic development. Using a multisource model, this paper explores the state of coordinated development, spatial–temporal evolution characteristics, and influencing factors in the Yangtze River Basin from 2011 to 2020. The results indicate the following: (1) The overall degree of coupling coordination in the Yangtze River Basin shows better performances in the eastern coastal areas compared to the central and western regions. Over time, the spatial autocorrelation of coupling and coordination increases, exhibiting a significant spatial clustering trend. (2) The Moran’s I index increased from 0.327 to 0.370, with high–high clusters primarily distributed in economically developed coastal provinces, while low–low clusters were observed in remote provinces in the central and western regions, revealing regional development imbalance issues. (3) The driving force analysis shows that green coverage and GDP are the core factors influencing the spatial differentiation of coupling coordinated development. Factors such as the urbanization rate, nighttime light index, and energy consumption had significant impacts in certain years but are generally considered minor factors. The results of this study not only contribute to understanding the dynamic mechanisms of regional coupling and development but also provide a scientific basis for formulating regional coordinated development policies, promoting the achievement of win–win goals of economic growth and ecological civilization in the Yangtze River Basin and similar regions.

Evaluating the Impact of Chinese FDI in the Energy Sector on Green GDP Growth: A Spatial Econometric Analysis of MENA Countries

This study analyzes the impact of Chinese foreign direct investment (FDI) in the energy sector on the green GDP (GGDP) growth of seven Middle East and North Africa (MENA) countries based on data from 2009 to 2019. Using panel regression analysis, the study focuses on the effects of FDI, economic development level, population size, energy consumption structure, environmental regulation intensity, government fiscal expenditure, and the KOF Economic Globalization Index on GGDP growth. By comparing fixed-effects and random-effects models and applying the Hausman test to select the most appropriate model, the research indicates that the random-effects model is the most suitable. The results show that FDI, economic development level, and population size have significant positive effects on GGDP, while shifts in energy consumption structure also promote sustainable economic growth. In contrast, environmental regulation intensity and the globalization index have no significant impact on GGDP, suggesting that GGDP growth in MENA countries relies more on internal economic policies and the efficiency of resource allocation.

Assessing the Effects of Chinese Foreign Direct Investment on Green GDP Development in North and South American Regions

This study aims to investigate the impact of foreign direct investment (FDI) on the growth of green GDP (GGDP) in North America and South America. The research is based on a comprehensive dataset covering the period from 2009 to 2019, drawn from multiple countries. By employing a two-way fixed-effects model, the study analyzes the effects of key factors, including FDI, trade openness, economic development level, urbanization level, population size, and industrial structure on GGDP growth.The findings indicate that, in North America, both FDI and the level of economic development exert a significant positive influence on GGDP growth, whereas trade openness demonstrates a negative impact, suggesting that increased trade activities may exacerbate environmental pressures. In South America, while the level of economic development shows a significant positive correlation with GGDP, the effect of FDI is not statistically significant. The study recommends that policymakers focus on enhancing the effectiveness of foreign investment and implement stricter environmental protection policies to ensure that trade activities do not adversely affect the environment. Furthermore, there is an urgent need to adjust the current industrial structure to promote a transition toward more sustainable development models. Ultimately, this research emphasizes the importance of ensuring environmental sustainability while fostering foreign investment and economic growth to achieve long-term growth in green GDP.

Factors Influencing Green GDP Growth in Southeast Asia: The Role of Foreign Direct Investment, Trade Openness, and Economic Development

Factors Influencing Green GDP Growth in Southeast Asia: The Role of Foreign Direct Investment, Trade Openness, and Economic Development

Policy lessons from green gdp convergence over five decades: Enhancing sustainability and economic outcomes

This study analyzes the convergence of Green GDP among 160 countries from 1970 to 2019, emphasizing the pivotal role of environmental policies in shaping sustainable economic outcomes. By comparing traditional and Green GDP (includes environmental degradation), this paper identifies distinct economic clusters or “convergence clubs” and reveals how policy-driven changes influence these classifications. The findings highlight the significant impact of environmental policies on economic convergence and propose applicative policy recommendations to foster sustainable growth, making this study essential for policymakers engaged in economic and environmental planning. This study demonstrates the long-term convergence of the selected countries' economic growth, influenced by their disparate commitments to sustainable practices and regulatory frameworks that govern environmental protection. Thus, regardless of the variations across countries and their environmental policies, diverse economic strategies tend to produce similar outcomes in the long term.

A better strategy: using green GDP to measure economic health

A better strategy: using green GDP to measure economic health

Green GDP -- Research on the development of green GDP and ecological environment cost based on regression model

Green GDP -- Research on the development of green GDP and ecological environment cost based on regression model

Study of Green GDP Based on the Ecological Footprint Model

Study of Green GDP Based on the Ecological Footprint Model

Pathways to Sustainability in Sub-Sahara Africa: Are Institutional Quality Levels Subservient in Achieving Green GDP Growth?

AbstractThere is a growing need for a transition to green economic growth (GGDP) given that the current economic system is largely environmentally unsustainable. This study thus addresses GGDP enhancement in less developed countries using the case of Sub-Sahara Africa (SSA) countries where institutional deficiencies are typically at the root of most resource depletion and environmental degradation issues. Six institutional quality measures were used namely corruption control, government effectiveness, political stability, regulatory quality, rule of law, and voice of accountability while controlling for other factors like industrialization, energy use, and population growth in the region. The study applied a battery of second-generation panel econometric techniques in the empirical analysis after which both Bootstrap Quantile regression (BQR) technique and panel ordinary least squares (OLS) estimation approaches were applied to observe the variables' roles on GGDP advancement in SSA. From the findings, corruption control and government (policy) effectiveness favorably impact Green GDP in SSA. However, both rule of law and regulatory quality performed poorly as they were insignificant to GGDP enhancement. Furthermore, all control variables promote GGDP except for population growth. Thus, the findings buttress the need to strengthen institutions for effective governance and quality environmental regulations to enhance GGDP growth towards actualizing sustainable development goals (SDGs) in the SSA region.

Research on the Accounting and Spatial Effects of Emergy Ecological Footprint and Industrial Green GDP--The Case of Yangtze River Economic Belt

The booming development of industrial enterprises at the cost of ecological resource consumption has inevitably harmed the ecological environment, especially since the phenomenon of water resource pollution is more serious. Exploring the relationship between the ecological environment and the industrial economy is crucial to the green and sustainable development of the region. This study uses the Spatial Durbin Model (SDM) to investigate the impact of emergy ecological footprint on the industrial green of gross domestic product (GDP) under the perspective of water resources, based on the panel data of 11 provinces in Chinas Yangtze River Economic Belt (YREB) from 2012 to 2021. The results show that first, the overall industrial green GDP of the YREB has increased year by year, and the effect of water resource protection is outstanding. Second, the emergy ecological footprint has a significant positive effect on industrial green GDP, and the spillover effect is also significant. Third, heterogeneity analysis shows that the spatial relationship between emergy ecological footprint and industrial green GDP is different in different regions, and the local effect and neighborhood effect of the high industrial green economic development areas are consistent with those of the YREB, while the relationship between the low industrial green economic development areas is not obvious. This paper is of great significance for the green development of industrial enterprises in the YREB and guides the formulation of sustainable development policies.

Policy and Institutions for Environmental Sustainability and Green Growth: The Moderating Effect of Renewable Energy and CO2 Emissions

Reducing environmental degradation due to the waste of natural resources and increasing global warming have been the main sustainable development goals for preserving biodiversity and ensuring sustainable growth established by the United Nations since 2015. Elucidating these goals requires effective and efficient environmental policies, substantial financial resources, and technological innovation to ensure an energy transition and reduce fossil fuel divestment and polluting technologies. In this context, this paper aims to examine the impact of environmental sustainability policy and institutions on green economic growth. Using a CS-ARDL panel model for a sample of 69 low-income countries in Africa, Asia, Europe, and North America over the period 2005-2020, we find that the effect of environmental sustainability policy and institutions on green GDP per capita is positive and statistically significant. The intensity of this effect is moderated by increases in renewable energy consumption and decreases in CO2 emissions. Furthermore, the subsample analysis indicates that the relationships between environmental sustainability policy and institutions and green growth remain positive for the four continents. In the long run, the intensity of this effect is stronger in Europe and Asia than in America and Africa. Moreover, these impacts are more effective as renewable energy increases and CO2 emissions decrease. It seems to be more important in Europe and Asia than in America and Africa. Overall, low-income countries should pay particular attention to policy and institutional index for environmental sustainability to promote green growth, taking into account the moderating effect of renewable energy consumption and CO2 emissions reduction.

Research on the Application of Machine Learning Algorithms in Green Economy Indicator Modeling and Sustainable Development Evaluation

This study presents a comprehensive modeling and analysis framework for investigating the impact of green GDP on climate factors and its potential for promoting sustainable development. Our model utilizes the entropy weight method (EWM) and grey correlation analysis (GRA) to optimize and process data, while employing a BP neural network for model training. Results indicate that green GDP leads to smaller global climate damage compared to traditional GDP, indicating its potential to alleviate the global climate crisis and promote green development.Furthermore, we built a green GDP prediction model using LSTM to forecast future changes. From the perspective of economy and management, the results indicate that transitioning from GDP to green GDP initially leads to a decrease in the index, followed by an increase. This suggests that green GDP development has short-term drawbacks but long-term benefits, including reduced resource consumption, improved economic conditions, and contribution to sustainable development. Finally, we analyzed the learning rate, number of iterations, and thresholds of related parameters through Logistic binary classification. Results demonstrate that our model is relatively stable, highlighting how green GDP addresses ecological challenges while promoting economic prosperity. These findings underscore the urgency of adopting the concept of green GDP in the contemporary era for achieving sustainable development goals.Overall, this research provides critical insights on the potential benefits and feasibility of green GDP as a crucial tool for mitigating climate risks and enhancing global prosperity.

Research on the Influence Mechanism of Green GDP, Green Network Security, and Digital Economy Based on Gray Correlation Model

This paper explores the impact that using GGDP (Green GDP) as an important indicator of a country's economic health will have on global climate mitigation. The GGDP values of 24 EU countries are calculated based on Eurostat data, and greenhouse gas emissions, precipitation, etc. are selected as variables, global data are collected for five years from 2015 to 2019, and the expected impact is estimated using gray correlation model and ridge regression model, which concludes that GGDP is negatively correlated with the climate indicators, and has a significant impact on climate mitigation. The resultant research is applied to the impact of green network security on network ecology and digital economy, selecting network ecological cleanliness, network energy utilization efficiency, and network security inputs as variables to be applied to the model, and the study concludes that green network security has a positive positive impact on the digital economy, and can promote the sustainable development of the digital economy.

Research of Green GDP Evaluation System Based on AHP Model

GDP (Gross domestic product) is of extraordinary significance in measuring national economic development, while it tends to have inaccuracy. The concept of Green GDP (hereinafter referred to as GGDP), which introduces environmental factors into the accounting system, is more conducive to sustainable development and the building of a harmonious economy. This paper selects main factors and establish a GGDP evaluation index system using the AHP model, then conducts the robustness test by one-dimensional linear regression model and "children dropping out of school" model. Finally, a sensitivity analysis is carried out to prove the accuracy. The results indicate that GGDP system contributes to improving environmental conditions and promoting sustainable development.

Exploring the convergence of ICT, digital financial inclusion, environmental pressures, and free trade and their significance in driving sustainable green investment initiatives under carbon neutrality targets

Due to its rapid economic development over the past few decades, China is now at the forefront of environmental issues, necessitating creative solutions that combine ICT, digital financial inclusion, environmental pressure, and free trade to encourage green investment. This study aims to investigate the linkage between ICT, digital financial inclusion, environmental pressure, free trade, and green investment in China from 1996 to 2022 by employing the Partial least squares structural equation modelling (PLS-SEM). As per our results, the statistical values of Cronbach's alpha, composite reliability, and average variance are all above the cutoff point, demonstrating the applicability of this methodology. According to the structural model's results, the path coefficients between digital financial inclusion and green investment, environmental pressure and green investment, and GDP and green investment are positively significant, implying that these three factors are crucial for boosting green investment in China. In addition, our vector autoregressive model results suggest that ICT, digital financial inclusion, environmental pressures, free trade, and GDP cause green investment to rise in China. Thus, the policymakers in China should focus on developing comprehensive policies to encourage green investment in China, which is crucial for economic and environmental sustainability.

The Impact of Foreign Direct Investment, Green Technology Innovation and GDP on CO2 Emissions in Western China: A Static Panel Data Analysis

This study investigates the impact of FDI, green technology innovation and GDP on CO2 emissions in the western region of China. This study applies the extended STIRPAT model, selects the relevant data of nine provinces in western China from 2000 to 2019, applies the static panel data analysis method, compares and analyses the estimation methods of Pooled OLS, fixed effect and random effect, and finally adopts the robust standard error estimation method of fixed effect. The results of the robust standard error estimation indicate that, in addition to the negative impact of green technology innovation on CO2 emissions, CO2 emissions are positively impacted by FDI, GDP, population, and the proportion of the secondary and tertiary industries. Therefore, reasonable introduction of FDI and improving green technology innovation levels are crucial in reducing CO2 emissions in the western region of China.

Green policies and financial development in G7 economies: An in‐depth analysis of environmental regulations and green economic growth

AbstractThis comprehensive study explores the nuanced relationship between financial development and its determinants within the G7 nations, spanning the years 1990 to 2020. Motivated by the need to understand long‐term financial trends, we meticulously analyze key variables including total natural resource rent, Environmental Policy Stringency Index, total energy consumption, green gross domestic product (GDP), and foreign direct investment inflow. Employing rigorous diagnostic tests to ensure the robustness of our findings, advanced methodologies such as “Method of Moment Quantile Regression,” along with simulations of “Bootstrap Quantile Regression," “Panel Corrected Standard Errors,” and “Feasible Generalized Least Squares” regressions uncover the statistical significance and practical implications of our results. Our pivotal findings carry substantial implications for both individual G7 member states and the collective group. Highlighting a positive correlation between stringent environmental policies, measured by the Environmental Policy Stringency Index, and financial development, our study emphasizes the imperative for these nations to align economic and environmental policies. Striking a harmonious balance between resource management and sustainable environmental regulations not only fosters financial growth but also addresses global environmental concerns. Furthermore, the adverse impact of total energy consumption on financial development underscores the urgent need for G7 nations to prioritize energy efficiency and transition to sustainable sources, aligning with the global trend towards eco‐friendly practices. In response to these critical findings, we propose actionable policy measures. To align with the growing climate crisis and standardize green finance practices, we advocate for the establishment of a jointly funded Climate Resilience and Adaptation Fund and a unified Green Bond Framework within the G7. These measures not only enhance climate resilience and streamline sustainable investments but also demonstrate the G7's collective commitment to a greener and more prosperous future.

Study on the Impact of Green GDP Accounting System on Climate - Based on Integrated Evaluation and Markov Modelling

GDP does not consider the impact of economic development on environmental hazards and resource consumption. Therefore, our team developed a reliable model and utilized the GGDP to assess the fiscal health of countries with the hope that governments will adopt policies to mitigate the impact of economic development on the global climate. To measure the financial health of each country's system, we selected raw data on five critical factors for 50 countries from 2010 to 2020. We then validated the data distribution patterns and selected the 80% quartile as the healthy range for each indicator. We used analytic hierarchical process (AHP) to determine the weights of each hand. Finally, we introduced the concept of the Economic Health Index (EHI) concept, which represents an economy's actual health. We also use Markov chains to predict the future global climate impact of flexible government policy measures to promote GGDP growth after GGDP replaces GDP. To measure the effect on global climate, we use the achievement of the GHG emissions and energy consumption targets agreed upon by countries in the Paris Agreement.

Enhancing labor productivity as a key strategy for fostering green economic growth and resource efficiency

Amidst a time when uncontrolled economic growth has frequently harmed the environment, it is crucial to reassess our strategy toward economic progress. The necessity to tackle climate change, resource depletion, and environmental deterioration demands a profound transition towards ecologically sound and sustainable economic development. This study examines the crucial significance of labor productivity in promoting sustainable economic growth and the effective utilization of resources in Asia, Europe, and South America from 1990 to 2020. To accomplish this, we utilized the Data Envelopment Analysis (DEA) methodology to examine a range of input and output characteristics thoroughly. These parameters included labor productivity, renewable energy usage, material efficiency, Green GDP, carbon footprint, and water footprint. The results of our study demonstrate significant regional variations in the efficient utilization of labor and resources to promote sustainable economic development. The findings of the DEA model emphasize that countries with higher labor productivity are more capable of pursuing an environmentally benign and sustainable financial path. Moreover, our research demonstrates a substantial association between enhanced labor productivity and diminished carbon and water footprints. This highlights the importance of labor productivity as a fundamental element for maximizing resource efficiency. In addition, we propose policy suggestions that motivate and improve worker efficiency as a practical strategy to accomplish both economic growth and environmental sustainability.