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By representing up to 60.5% of Indonesia's GDP, Micro, Small and Medium-Sized Enterprises (MSMEs) have a major effect on the economic growth of the nation. This study intends to create a model that examines the association between social competence (SC) and Social Media use Intensity for CRM (SMIC) of their impact on business performance satisfaction (BPS) in MSMEs. The study furthermore examines how Social Media Sales Intensity (SMSI) may have an impact on this relationship. The association between SMIC, SC, SMSI, and BPS variables gonna be examined using structural equation modeling (SEM), from an online survey which was given to MSME owners. However, this study doesn't evaluate the model's results, rather it focused solely on describing the model. The analysis will provide beneficial recommendations for MSME owners who want to improve the performance of their businesses. [ABSTRACT FROM AUTHOR]

Determination of macroeconomic policies in real-time requires assessing the correct information regarding current economic conditions. This statement spurred researchers to develop methods involving high-frequency data for risk analysis. This paper extends the quarterly growth-at-risk (GaR) approach by involving a machine-learning approach based on the Mixed-Frequency Data Sampling Quantile Regression Neural Network (MIDAS-QRNN) model. This paper shows that the MIDAS-QRNN model has the best prediction accuracy and can show good PDB nowcasting. The monthly financial GaR can detect unusual economic growth movements during the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

This paper examines the relationship among Research and Development (R&D) expenditure, government effectiveness, and voice accountability in 15 Latin American countries. R&D expenditure is a crucial driver of innovation and economic growth, and effective governance and voice accountability are essential for promoting transparency and citizen participation in decision-making processes. The study utilizes a panel dataset from 2002 to 2021 and employs computer data analysis to estimate the effects of changes in government effectiveness and voice accountability on R&D expenditure. The findings reveal a positive impact of government effectiveness and voice accountability on R&D expenditure. A 1% increase in government effectiveness is associated with a 0.618% increase in research development expenditure, while a 1% rise in voice accountability corresponds to a 0.625% increase. These results highlight the importance of effective governance and citizen engagement in fostering R&D investment. [ABSTRACT FROM AUTHOR]

This article analyzes the advantages of the multi-objective dynamic input-output optimization model compared to the single objective dynamic input-output optimization model, and demonstrates the reason why the multi-objective model improves the stability of the solution of the dynamic input-output equation system by constructing a goal programming model. Based on the 2021 and 200 input-output table, a multi-objective dynamic input-output optimization model was established for the actual economic and social development of City A. The model includes five objective functions, including economic growth and comprehensive economic balance, and is solved using the goal programming method. The prediction results of the city's main economic indicators, such as GDP, tertiary output added value, and so on from 2021 to 2025, are presented. This result is basically the same as the results obtained using artificial neural network methods, and is more in line with the actual situation of the city. [ABSTRACT FROM AUTHOR]

Poverty is one of the world's main problems, which has been very difficult to overcome. The poverty rate has influences on economic growth in an area. The greater the poverty rate in an area, the more difficult it is for an area to grow economically. Many factors affect the level of poverty. Geographical location, level of education, population growth in each region, significantly affect the poverty level. The many factors that affect the poverty level make it difficult for us to predict which factors will influence the level of poverty in an area, making it difficult for us to solve the problem. This research was made to predict what factors influence the level of poverty in Papua, Indonesia. This study uses a Geographically Weighted Regression (GWR) method due to the existence of spatial heterogeneity. It produces model estimates that are local for each location and different from other locations to get a model with the most influential factors in each region. The results of this study are as follows. First, agricultural employees affected the poverty rate in each location in Papua. Second, house area and households with access to safe water are significant variables in Yapen, Biak Numfor, and Supiori. [ABSTRACT FROM AUTHOR]

The 2015 Paris Agreement, which was a global effort to address climate change and meet Sustainable Development Goals (SDG), established the Technology Mechanism Initiative as the key to facilitating technology transfer; however, the target SDGs of this initiative have not been identified. This study reviewed technical assistance (TA) project documents of the Climate Technology Centre and Network (CTCN), an organization under the Technology Mechanism Initiative, to analyze the general status of climate technology implementation, identify the targeted SDGs using sectoral classification, and examine the current national SDG statuses of TA-participating countries. While sectoral classifications have specific relationships with certain goals, SDGs 7 (Affordable and Clean Energy), 8 (Decent Work and Economic Growth), 9 (Industry Innovation and Infrastructure), and 13 (Climate Action) were primarily referenced as they focused on energy and cross-sector applications. The evaluations also revealed that countries should prioritize poverty- and food-related SDGs. Therefore, expanding TA contributions to SDGs by better grouping sectoral classifications based on regional and local needs was essential because SDGs were linked to both sector-specific and climate technologies. Thus, a climate technology package based on sectoral classifications was proposed to bridge the gap between SDG attainment and the climate change objectives proposed by the Paris Agreement. • Sustainable Development Goals (SDGs) targeted by technology assistance projects were identified. • Energy and cross-sector SDGs were the most commonly mentioned, but not food and poverty SDGs. • A climate technology package is proposed based on sectoral classifications and regional needs. • Technologies should be grouped according to their priority to accelerate sustainable development. [ABSTRACT FROM AUTHOR]

In 2016, China first proposed the concept of "digital inclusive finance", which effectively solved the problem of difficult and expensive loans for small investors, activated economic growth from all sides, and has become the trend of financial industry development. This article is based on data from 72 counties in Guizhou Province from 2014 to 2021, using the PSTR model and quantile model for empirical analysis, exploring the relationship between economic growth and digital inclusive finance in Guizhou Province. The research results show that the development of digital inclusive finance can promote economic growth in Guizhou Province. After crossing a certain threshold value, it will further promote the economy; the breadth and digitization of the second-level indicators of digital inclusive finance have a nonlinear impact on the economy of Guizhou Province. The depth of digital inclusive finance has a linear relationship with the economy of Guizhou Province; The results of the quantile test show that the effect of digital inclusive finance promoting the economy is more significant in underdeveloped areas. [ABSTRACT FROM AUTHOR]

The effort to achieve a balance between industrial development, environment, human health and economic growth in the world represents a driving engine of the latest strategies for resource usage and carbon footprint reduction, which include the application of the Circular Economy (CE) concept. The central idea of the CE concept is to increase the value of resources within a closed system to enable the use of a minimum number of natural resources while providing sustainable economic growth. The aim of this paper is to map the history and evolution of the CE concept to highlight its current application. Historical literary sources and scientific studies were used to map the CE concept evolution while policy instruments provided information mainly on current development. The overview indicates both success and failure of the CE projects over time listed by regions. Successful applications of the CE in the Czech Republic have been identified. The results provide useful information for further research seeking to define the CE concept in practical terms and consider potential opportunities that arise during its implementation. [ABSTRACT FROM AUTHOR]

Given the growing interest in understanding the social dimension of R&D investments better, approaches for measuring the societal impact of university-industry R&D collaborations (UICs) are called for. Several studies claim that such collaboration directly impacts innovation and, consequently, economic growth. In recent years, several papers have sought to assess the impacts of these collaborations. However, the interest seems to be focused on two of its main stakeholders: companies and universities. Few studies integrate university, industry and society outlooks on societal impact. Based on systematic literature review, this paper aims to provide a conceptual framework for the key elements that should be considered when measuring the societal impact of UICs, contributing to a theoretical understanding of the subject. [ABSTRACT FROM AUTHOR]

The article considers analysing the effect of sector-specific foreign direct investment (FDI) (the primary, secondary, and tertiary sectors) on economic growth in 19 developing countries over the period 2005–2018. Variables such as human capital, domestic investment, financial development, openness of the economy, labour force, and arable land were included as control variables. A robust two-step system generalised method of moments (GMM) was utilised for the analysis of the data. The study found that FDI's growth effect is indeed influenced by its sectoral composition in developing countries. The finding reveals that FDI in manufacturing has a positive and statistically significant influence on economic growth, whereas FDI in the tertiary sector has a statistically significant negative effect on economic growth, but FDI in the primary sector has a negative but negligible effect on economic growth. Lastly, it can be concluded from the above results that the more manufacturing FDI that countries attract, the greater their economic growth will be. In light of this, the countries should provide special incentives like tariff reductions, tax holidays, and cheap-rented land supplies in order to attract more manufacturing sector FDI. [ABSTRACT FROM AUTHOR]

Based on the four aspects of economic development, scientific and technological innovation, ecological environment protection and shared coordination, this paper constructs a regional high-quality evaluation index system on three dimensions, namely target layer, criterion layer and index layer. The entropy method, comprehensive evaluation method and Gini coefficient were adopted to evaluate regional high-quality development and they are used to explore the balance of high-quality development of cities regionally. As the object of research, the data from 2010 to 2019 of 11 cities in Hebei was collected and conducted or processed. The research results indicate that economic growth is a key factor to promote the high-quality development of Hebei; the evaluation results reveal that the high-quality development among the 11 cities in Hebei have different scores; the balance analysis demonstrates that the high-quality development differences of cities in Hebei present a decreasing trend. [ABSTRACT FROM AUTHOR]

We investigate the dynamic effect of external conflict risk on environmental transition by considering the impacts of eco-innovation, economic growth, and energy consumption in a panel comprising 26 European countries from 2011 to 2020. Using a non-parametric model represented by the panel QARDL, we find that in the short run, a 1% increase in external conflict risk statistically leads to a 0.25% and 0.13% increase in the likelihood of environmental transition for the median and extreme upper quantiles (50th and 95th percentiles), respectively. However, the same increase holds little importance when considering the lower quantile (5th percentile). The indicated effect substantially decreases in the long run, reaching zero across the different quantiles. We also note discrepancies in the impact of energy across various quantile levels. For instance, the effect of population is significant from the 5th to the 90th quintiles. Overall, our findings suggest that enhancing eco-innovation helps reduce environmental transition risk. The results are relevant to the development of environmental policies and provide valuable insights for energy officials, technology stakeholders, and policymakers in their attempts to strengthen resilience during an environmental transition. [ABSTRACT FROM AUTHOR]

Exploring pathways for China to achieve the dual goals of stabilizing economic growth and promoting green development provides important reference value for countries worldwide. This is particularly crucial in addressing global climate change and achieving carbon neutrality. This paper focuses on 108 cities within the Yangtze River Economic Belt in China, employing the Generalised Spatial Two-Stage Least Squares (GS2SLS) method to conduct an in-depth analysis of the impact of manufacturing agglomeration on green development performance. This study finds that, at the current stage, manufacturing agglomeration can effectively promote green development performance; however, the impact exhibits a U-shaped relationship. This means that the effect of manufacturing agglomeration on green development performance initially decreases and then increases. Additionally, knowledge spillover effects, resource allocation effects, and structural upgrading effects are important channels contributing to this nonlinear relationship. Extended analysis reveals that in the cities of the lower Yangtze River region, there is an inverted U-shaped relationship between manufacturing agglomeration and green development performance, while in the middle and upper reaches, the relationship is U-shaped. Furthermore, the expansion of city size positively promotes the green development effects of manufacturing agglomeration. These conclusions not only provide important guidance for China in achieving high-quality green development but also offer significant insights for developing countries worldwide in attaining the dual goals of economic growth and green development. [ABSTRACT FROM AUTHOR]

The study analyses empirically the role of FDI as an interactive factor in the democracy, corruption, economic growth, ICT and carbon emissions nexus in sub-Saharan Africa (SSA). We use the Method of Moments Quantile Regression (MMQR) technique with data from 37 SSA countries covering the period 1970–2019. We find evidence that corruption and democracy create a significantly negative association with carbon emissions across most quantiles for the SSA countries. Conversely, economic growth, ICT and FDI develops a significantly positive relationship with environmental quality. Thus, the paper confirms validity of the Pollution Haven Hypothesis in SSA countries. More results demonstrate that the interaction variables, corruption × FDI, democracy × FDI, economic development × FDI also produces positive and significant links with carbon emissions, but the link between ICT × FDI and emissions is insignificantly negative. In conclusion, our findings indicate the need for a targeted approach towards improving FDI to fight corruption, enhance democracy, ICT and economic growth in pursuit of green economy and sustainable development in SSA. [Display omitted] • Both corruption & democracy have a significantly negative association with carbon emissions (across quantiles). • Economic growth, ICT, and FDI are linked to higher environmental quality. • The Pollution Haven Hypothesis in SSA countries is validated. • Corruption, democracy & growth affect emissions more with high FDI. • FDI interactions with ICT has minimal negative effect on emissions. [ABSTRACT FROM AUTHOR]

This study aims to explore the asymmetric effects of income inequality, financial development, and human development on the ecological footprint in Türkiye between 1990 and 2021, as well as the symmetric impacts of energy consumption, economic growth, trade openness, and urbanization. The Nonlinear Autoregressive Distributed Lag method is employed to examine the short- and long-term relationships among the variables. This study distinguishes itself from previous research by examining the asymmetric effects of income inequality, human development, and financial development on the environment in Türkiye, where significant economic and social transformations have occurred in the past few decades and have had severe impacts on the environment. The study's key findings demonstrate that shocks in income inequality, financial development, and human development have significant impacts on the ecological footprint. Our findings indicate the importance of using disaggregated data in the analyses. The results related to control variables indicate that energy consumption and economic growth exacerbate ecological pressure, while urbanization mitigates it. These findings have significant implications for policymakers, who can achieve socioeconomic and environmental gains by addressing crucial issues such as green job creation, green technologies, green financing, and environmental education. [Display omitted] • Study tests impacts of inequality, human and financial developments on Türkiye's footprint. • Study includes factors like economic growth, energy use, trade openness, and urbanization. • The Nonlinear Autoregressive Distributed Lag methodology is employed. • Results indicate that shocks in the key independent variables affect ecological footprint. • The results show energy and economic growth raise environmental degradation. [ABSTRACT FROM AUTHOR]

The dynamic development of information and communication technology (ICT) reported in recent years has caused significant changes in almost all areas of social and economic life. The digitalization process resulting from this development is now becoming a determinant of both progress and modernity. This issue has been addressed in this paper, and thereby we present a methodology developed to study the level of digitalization and the use of innovative technologies among the enterprises of the EU-27 countries. The research was conducted using selected indicators—determinants (10) characterizing the main digital technologies and infrastructure associated with their implementation in the enterprises under study. Based on these indicators, the Entropy-Multi-Objective Optimization on the basis of Ratio Analysis (MOORA) method was used to determine the index (level) of digitalization among the companies of the EU-27. The level of use of digital technologies and infrastructure for Industry 4.0 was also determined. Another important goal of the study was to determine a relationship between the values of the digitalization index for the EU-27 countries and the economic parameters characterizing their economies. For this analysis, non-parametric tests such as the Kendall's Tau and Spearman's rank correlation coefficients were applied. The results significantly enrich the knowledge of methodology for studying the level of digitalization and its status among the enterprises of the EU-27. These findings provide great opportunities for interpretation and practical application, especially in terms of building an innovative knowledge-based economy. They show great diversity of the EU-27 countries in the field of digitalization and poor results reported in this area by the so-called "new EU" countries. Among the many interesting findings, it is worth pointing out the positive impact of spending on research and development on the process of digitalization of enterprises. The results should be used when creating a digitalization strategy for individual countries and their groups. [ABSTRACT FROM AUTHOR]

Successful implementation of digital solutions in a given region or country significantly depends on the implementation of this process by Small and Medium-Sized Enterprises (SMEs). This problem is very well understood in the European Union, where actions are being taken to accelerate this process and build a sustainable and competitive knowledge-based economy. This article addresses this issue by conducting a study of the digital maturity of SMEs among the EU-27 countries. The aim of the study was to determine the level of digital maturity of SMEs in the EU-27 countries as well as whether and how the economic parameters of individual EU countries affect the process of SME digitalization. The adopted objectives determined the developed research methodology and the applied methods. The research was based on data from the Eurostat database, on the basis of which 11 indicators characterizing technologies and digital solutions identified with the Industry 4.0 concept were specified and adopted for the study. The entropy-based Evaluation based on distance from average solution (EDAS) method was used to assess the EU countries in terms of the level of digital maturity of SMEs, and the Principal Component Analysis (PCA) method was used to analyze similarities between these countries in terms of technologies implemented in SMEs. On the other hand, to determine a relationship between the digital maturity index (digitalization) and the basic economic parameters of the economy, two nonparametric tests (Spearman and Tau Kendall) were utilized. Based on the determined digital maturity index, the EU-27 countries were evaluated in terms of the level of digital maturity of SMEs, dividing them into four groups. The results showed large discrepancies between individual EU-27 countries and between the old (EU-14) and the new (EU-13) EU countries in terms of SMEs digitalization. These results should be widely used to develop a digitalization strategy for the EU economy and policies to improve the degree of digitalization, especially in countries lagging in this area. The universality of the developed methodology creates wide opportunities for its use to study other countries and regions worldwide. [ABSTRACT FROM AUTHOR]

In line with the neoclassical growth theory, this study examines the complementary role of economic freedom and financial fragility in the foreign direct investment (FDI) – growth nexus for 36 Sub-Saharan (SSA) Africa countries spanning the period 1998 to 2016. The study hypothesises that for FDI to translate into growth, financial market development that account for fragility and economic freedom should be present in the host country. The uniqueness of this study lies in the use of financial market data that accounts for financial market fragility and aggregate score of economic freedom. Using fully modified ordinary least squares technique, the study reveals that economic freedom and a well-developed financial market complement FDI in promoting economic growth in SSA. This study highlights the need to strengthen the financial system and promote economic freedom to enhance FDI's effect on economic growth. [ABSTRACT FROM AUTHOR]

This paper takes 31 provincial regions in mainland China as the research object, measures the development level of digital finance through digital inclusive finance index, empirically analyzes the development of digital finance on regional economy, and further analyzes the breadth, depth and service support of digital inclusive finance. Research shows that digital finance can promote regional economic development, and digital finance also has a positive impact on economic development in terms of breadth, depth and service support. [ABSTRACT FROM AUTHOR]

• A novel heat-integration strategy to reduce sugarcane stillage generation is presented. • HIDiE reduced 45.7–69.3 % stillage generation with the equivalent steam as conventional wine distillation. • HIDiE optimizes stripping operations and reduces stillage volume without specialized equipment. • HIDiE produced less stillage (1.7–7.8 m3/m3) than CS (5.4–14.5 m3/m3) under the same boundary conditions. Sugarcane stillage, or vinasse, is the most voluminous byproduct generated in ethanol production, with an average volume ratio of 12:1. Fertigation is the simplest worldwide destination for stillage, but stricter environmental regulations require its distribution over wider areas to avoid soil oversaturation, demanding thus expensive transportation infrastructure. While reducing disposed stillage is critical, current concentration systems are inefficient and require additional energy (steam) and dedicated evaporators, which are prohibitively expensive for most installed industries. This study demonstrates, through performance comparisons with conventional distillation systems (CS), that a novel system, here denoted as HIDiE (Heat-Integrated Distillation and Evaporation), efficiently reduces the volume of stillage still during the stripping step, requiring no additional equipment and resulting in a leaner and cheaper approach. Process simulations in ASPEN Plus V11 software were used to validate premises using thermodynamic analysis and mass and energy balances. HIDiE produces significantly less stillage (1.7 - 7.8 m3/ m3 ethanol) than CS (5.4 - 14.5 m3/ m3 ethanol) under same steam consumption. Using HIDiE for wine with alcoholic grades ranging from 6 to 14 %v/v can result in gains of 45.7–69.3 %. This novel process concept contributes to the expansion of the economic radius for stillage fertigation, implying significant savings for the industry and the environment. [Display omitted] [ABSTRACT FROM AUTHOR]

Decoupling the dependence on carbon emissions from achieving high-quality economic development is a paramount objective for China. However, the often-overlooked aspect is the carbon emissions generated through trade activities, which can lead to an overestimation of decoupling progress. Our study quantified and compared the decoupling status of production-based and consumption-based carbon emissions from economic growth in Guangdong from 2002 to 2017 from the perspective of inter-provincial embodied carbon flow, and further investigated its driving factors. The results reveal that consumption-based carbon emissions consistently surpass production-based emissions, although they exhibited a steady decline in recent years. As a significant contributor to embodied carbon emissions, Guangdong outsources a considerable portion of its emissions to less developed regions such as Liaoning and Guangxi by importing raw or intermediate products with lower value-added raw, while it exports service products to provinces like Beijing and Zhejiang. Decoupling analysis indicated that Guangdong is progressively moving towards an optimal state of "double decoupling", where both production and consumption-based carbon emissions are decreasing. This represents a departure from the previous scenario of "fake decoupling", characterized by a reduction in production-based carbon emissions but persistently high consumption-based emissions. Additionally, our structural decomposition analysis highlights the potential for reducing carbon emissions and enhancing decoupling by increasing the utilization of clean energy and optimizing the trade input structure. These findings underscore the importance of accounting for embodied carbon emissions in decoupling studies and offer valuable insights for achieving high-quality development. • We compare the decoupling status of production and consumption-based emissions from GDP. • Multi-Regional Input-Output tables from 2002 to 2017 is used. • Guangdong outsources most of its emissions to less developed regions. • Guangdong achieves a double decoupling, where both production and consumption-based emissions are decreasing. • Increasing the utilization of clean energy and optimizing the trade input structure can enhancing decoupling. [ABSTRACT FROM AUTHOR]

Sustainable development has always been given priority by economic authorities, therefore pursuing both environmental emissions reduction and economic growth at the same time is required. However, energy structure is often disregarded in existing performance evaluation methodologies, despite its essential function in determining environmental efficiency or productivity. This study shows how ignoring the energy structure can lead to distorted policy recommendations as well as evaluation results. The present study provides a non-parametric estimating approach to quantify the difference between the optimal (theoretical) energy structure required to achieve sustainable development and the actual (observed) energy structure. This method may assess the energy transition process and evaluate the observed and optimal energy structure of a country or region. We demonstrate that using the countries of the Organization for Economic Co-operation and Development as an example, that only a limited number of countries are able to meet their objectives for carbon reduction and economic development simultaneously without transforming their energy structure. The relationship between energy structure and green total factor productivity (GTFP) was further studied using a two-stage least squares regression on the observed energy structure and GTFP. The findings indicate that most countries need to increase their share of renewable energy in order to achieve green growth. [ABSTRACT FROM AUTHOR]

In the domain of global socio-economic dynamics, the pivotal role of food production (FP) cannot be overstated. It constitutes the bedrock of fundamental human necessities while being inexorably linked with critical aspects such as economic expansion, societal equilibrium, and geopolitical interplays. The multifaceted nature of FP appears through its direct impact on macroeconomic indicators and its latent influence on international relations and policy-making. This critical nexus underscores the imperative for a comprehensive understanding and strategic management of food production processes to sustain and enhance global socio-economic stability and growth. Investigating the nexus between green finance (GF) and FP is pivotal for ensuring national security and promoting sustainable economic development. This research thus paper examines GF's impact on FP in China as outlined in the 2017 green finance policies. It employs the difference-in-differences (DID) method and analyzes a balanced panel dataset comprising 282 cities in China from 2009 to 2020. The results show that GF has an inhibitory effect on FP, and this remains valid after a range of reliability checks, including parallel trend assessments and placebo tests. Further findings of transmission mechanism analysis indicate that non-agricultural factors and financial exclusion are critical for GF's inhibitory effect on FP. Heterogeneity analyses show that GF's inhibitory effect on FP is more pronounced in the main food-producing areas, the main food-marketing areas, and cities with better infrastructure. The empirical results of this paper comprehensively illustrate GF's impact on FP and how it contributes to the achievement of food security objectives. [ABSTRACT FROM AUTHOR]

This study investigates the impact of digital innovation on the growth of the marine economy by optimizing the structure of the new media communication culture industry. Through the simulation of the particle swarm optimization (PSO) and Back Propagation (BP) computational network model, the Gross Domestic Production (GDP) of the marine economic zone is predicted, and the prediction effect of the PSO-BP computational network model on multivariate spatiotemporal transitions is further verified. The results show that the PSO-BP model has less prediction variance and a better fit than the BP model. The analysis of the joint prediction model reveals that there are differences in the publicity effects of different self-media modes in various types of sea areas. In terms of the economic peak of the overall data, Bilibili has the best publicity effect, followed by WeChat, Weibo, and Shake. The results show that the trend of macroeconomic indicators and the size of values in different regions affect the prediction effect. Region A has a higher annual average rate of change of macroeconomic indicators and has a better prediction effect. Region B has a faster macroeconomic development and has a more fluctuating prediction effect. Regions C and D have their advantages and disadvantages of the prediction effect under the self-media model. • Region A has a higher average annual rate of change in macroeconomic indicators and has a better prediction effect. • Region B has a rapid development of the macroeconomy and has a more fluctuating prediction effect; and regions C and D each have their advantages and disadvantages of prediction effect under the self-media model. [ABSTRACT FROM AUTHOR]

The propulsion of economic growth is a multifaceted construct, influenced by technology, capital, and resource management, with Small and Medium-sized Enterprises (SMEs) being a significant contributors to innovation and employment. This study examines the growth of Scottish SMEs across four sectors over a 14-year period (2008–2021) by employing a novel statistical approach to understand their development trajectories within the framework of open innovation. The paper engaged in a longitudinal analysis to assess trends and inform policy for sustainable growth by the utilization of open-access data. Theoretical metrics such as the Average Growth Rate, Compound Average Growth Rate (CAGR), and Year-Over-Year (YoY) Growth were applied to evaluate sectoral performance. The findings revealed varied growth patterns; the information technology sector exhibited a robust increase, while the telecommunications sector showed significant percentage growth. Conversely, the Information and Communication Technologies (ICT) sector experienced a decline that suggests a potential market gap. An affirmative trajectory in CAGR was observed in most sectors except ICT, which corroborates a shift in technological evolution and market needs. The study illuminates the dynamic economic landscape of Scottish SMEs, with telecoms emerging as the most prosperous sector in terms of growth rates, thus indicates a shifting economic focus. The study's limitations are briefly discussed, in addition to the need for updated databases and further research employing predictive modeling with machine learning to enhance forecasting capabilities and foster open innovation for sustainable economic development. [ABSTRACT FROM AUTHOR]

The bioeconomy, emerging as a beacon of sustainable development and global competitiveness, relies on renewable biological resources. This study investigates the interplay between institutional quality and bioeconomy performance in 28 European countries. By employing a Fixed Effect Regression and different sensitivity analyses, we unveil a robust, positive, and statistically significant relationship between the institutional quality and the socio-economic indicator for bioeconomy. The six institutional quality pillars - political stability, control of corruption, government effectiveness, regulatory quality, rule of law, and voice and accountability - positively impact the bioeconomy in Europe. These findings underscore the pivotal role of institutions in shaping bioeconomy performance, emphasizing the profound impact of political stability, regulatory standards, and anti-corruption measures. As a result, our research provides valuable insights for policymakers, highlighting the significance of enhancing institutional quality as a means to advance sustainability and stimulate economic growth through bioeconomy development. [ABSTRACT FROM AUTHOR]

Modern economies rely on economic growth for stability and prosperity. Further, periods of stagnation and recession are currently associated with poor health and wellbeing outcomes for citizens. However, 50 years of research indicates that this state of dependency is ecologically unsustainable. It is therefore critical that we better understand the growth dependency of our economies and welfare systems, and how to overcome it. In this paper we first offer a working definition of growth dependency, clarifying its core dimensions. Next, taking the UK's adult social care sector as a case study, we argue that growth dependencies emerge in the welfare state as a result of three distinct dynamics: 1) growth in manifest needs; 2) labour productivity growth; 3) the pursuit of economic rents. Lastly, we propose a novel, sector-led framework for identifying, analysing and transforming growth dependencies. We make the case that the growth dependency of the welfare state is not inevitable, but is instead the product of specific social, economic and structural factors that can be disrupted and transformed, if we can find the political will to do so. [ABSTRACT FROM AUTHOR]

This commentary responds to a recent article in this journal (Warlenius, 2023) purporting to identify the 'limits to degrowth'. We first clarify and set in context the tensions between growth rates and decoupling rates on which the argument is based. In particular, we show how failing to achieve sufficient decoupling appears to leave society torn between missing our climate targets and crashing our economies. This dilemma highlights the tough choices inherent in the climate transition. But it does not imply that critics of growth endorse economic collapse. On the contrary, the intention of postgrowth scholars is clearly to prevent this collapse by offering structural and social reforms, alongside technological options, as a way of meeting climate targets. Specifically we dispute the claim that growth is the best way to achieve high rates of decoupling. Counter to this, we present several mechanisms through which a growth-critical approach may be better aligned with the climate transition than an economic ideology founded on 'growth at all costs'. [ABSTRACT FROM AUTHOR]

It has become a global agenda for the transition toward sustainable energy systems; the Mercosur region faces unique opportunities and challenges in harnessing the potential of renewable resources. Against this backdrop, this study thoroughly investigates the determinants of renewable energy consumption (REC) for Mercosur nations. The research examined the influence of economic expansion, green finance, technological innovation, human capital, government effectiveness, and urbanization on the integration and transition of REC. Incorporating a comprehensive approach, the study integrated the CS-ARDL econometric model and panel data for over three decades (1990–2021). The analysis revealed that economic expansion, green finance, technological innovation, human capital and government effectiveness are advantageous and essential for advancing REC deployment in the Mercosur nations. In addition, the outcome espoused that urbanization is detrimental to the progress of REC. Moreover, there is a one-way causality between economic expansion, green finance, technological innovation and green finance to REC. Still, there is a bi-directional link between human capital, urbanization, and renewable energy consumption. The outcome of this paper contributes to the ongoing discussion on sustainable development, providing essential insight for stakeholders, policy-makers and researchers seeking to investigate the complexities of transitioning towards a more resilient and greener energy landscape. • The analysis revealed that EXP, HUC, TNI, GFN, and GEF are advantageous for the advancement of REC. • The empirical outcome espoused that URB is detrimental to the progress of REC. • There is one-way causality between EXP, GFN, TNI, and GEF to REC. • There exists a two-way causality between HUC, URB, and REC. [ABSTRACT FROM AUTHOR]

The extant body of academic literature has thoroughly examined the influence of political promotion institutions on various aspects of economic growth and corporate behavior. However, there remains a gap in the understanding the extent and mechanisms through which the establishment of economic growth targets influences firms' pollution emissions. Addressing this gap, we construct datasets that encapsulate both micro-level and macro-level perspectives to examine the impact of economic growth targets on corporate pollution. We find that an increase in economic growth targets leads to a significant rise in pollution emissions from industrial firms. To address potential endogeneity issues, we employ various strategies, and our results remain robust across these different approaches. We then estimate the heterogeneous impact of economic growth targets and demonstrate that the positive effect of these targets on pollution emissions tends to be less pronounced for firms situated in cities governed by female mayors. Conversely, the effect appears more pronounced for firms located in the western region, those operating in cities led by older mayors, and those in cities where mayors have lower levels of education. Finally, we explore potential mechanisms through which economic growth targets impact corporate pollution. Our results show that at the firm level, a higher economic growth target primarily leads to increased pollution emissions from enterprises by reducing firms' investment in pollution control. At the city level, an elevation in economic growth targets predominantly results in escalated enterprise-related pollution, chiefly due to its hindrance of urban green innovation, reduction in fiscal allocations for science and technology, and a decrease in educational fiscal outlays. These empirical findings strongly advocate for the implementation of measures aimed at dissuading prefecture-level city governments from formulating excessively ambitious economic growth targets, as a viable strategy for mitigating pollution stemming from manufacturing firms in developing nations. In view of this, our research is conducive to advancing the process of building a sustainable development path in China and providing reliable solutions to global ecological challenges. • Examines the effect of economic growth targets on pollution emissions by industrial firms. • Identifies the causal mechanisms linking economic growth targets to pollution emissions. • Explores the heterogeneous effects of economic growth targets on pollution emissions. • Finds increased pollution effects in western regions and in cities with older, less-educated mayors. • Advocates policy changes to curb pollution emissions arising from ambitious growth targets. [ABSTRACT FROM AUTHOR]

This study aims to provide insights into the decoupling of GDP growth and greenhouse gas (GHG) emissions in Morocco, a developing country with the ambitious goals of reducing GHG and strongly vulnerable to the negative effects of climate change. The Engle-Granger cointegration method was used in addition to the Tapio elastic analysis based on annual time series data from 1990 to 2018. The cointegration test indicates a significant long-term relationship between greenhouse gas emissions and Gross Domestic Product with a coefficient equal to 0.85. On the other hand, Tapio's decoupling index method presents mixed results both by pollutant and by time period. Nevertheless, total greenhouse gas emissions, with a decoupling index valued at 0.7, exhibit a weak impact decoupling throughout the entire sample period wherein emissions continue to grow at a lower rate than the Gross Domestic Product. The findings are coherent with the view that more aggressive carbon pricing initiatives (CPI) policies will likely be necessary to achieve the ambitious goals set by the Moroccan government to achieve absolute decoupling. [Display omitted] • Engle-Granger cointegration and Tapio's elastic analysis to study decoupling. • One of the first decoupling studies done for North Africa particularly Morocco. • Long-term relationship found between Gross Domestic Product and greenhouse gases. • Weak decoupling state was the most frequent in Morocco between 1990 and 2018. • Need for more aggressive policies such as carbon pricing initiatives (CPI). [ABSTRACT FROM AUTHOR]

The essence of China's contemporary green economic transition is to enhance the capacity of the green production system, emphasizing regional technological and intellectual capabilities as the primary force of green economic growth (GEG). Economic complexity can reflect hidden regional production capacity, providing a new analytical tool for exploring GEG. Using a city–year panel dataset from 2000 to 2016, this study incorporates economic complexity and GEG into a unified research framework, adopting a fitness–complexity algorithm to measure Chinese urban economic complexity to empirically examine the influence and mechanisms of economic complexity on GEG. The results show that increased economic complexity promotes GEG by enhancing green technological innovation capacity and facilitating industrial structure upgrading, with one standard deviation increase in economic complexity followed by a 2.1% rise in GTFP. In addition, we emphasize the moderating effect of the government and the public, arguing that increased government environmental attention and public environmental concern reinforce the contribution of economic complexity. Finally, the findings reveal that public policies focusing on improving the economic complexity of low-complexity areas can strike a good balance between fairness and efficiency. [ABSTRACT FROM AUTHOR]

China's adoption of an "ecological civilization" strategy since 2012 demonstrates its vision to move toward more sustainable development models while promoting green energy and strengthening environmental protection. However, China's continuing heavy reliance on fossil fuels, especially coal, masks the complex positive trends in energy use, more sustainable economic development, and environmental management. Through examining the evolving energy-GDP relationships in China over the past few decades, we elucidated the underlying complex nonlinear processes using environmental Kuznets curve analysis and showed that the energy–GDP relationship has fluctuated between positive and negative decoupling. Furthermore, fluctuating trajectories manifested as sharp regional divergences when early-transitioning coastal areas restructured toward services and exhibited robust decoupling, whereas the industrial interior remained fossil fuel reliant. We identified various forces related to these provincial disparities, where rapid urbanization, industrial realignment, and income growth were all important. By promoting service transitions and enabling low-carbon technologies in coastal hubs, these drivers also exposed infrastructure deficits and entrenched fossil fuel usage in the interior. These problems led to China's latest strategic plans emphasizing "higher quality" growth underpinned by clean energy transitions and coordinated regional policies. Ongoing declines in coal and the rise in renewable energy usage highlight promising momentum, but stable decoupling remains contingent on sustained policy coordination. The intricate balance between growth and environmental pressures in China provides essential lessons to help emerging economies achieve sustainability by catalyzing green transitions and attaining developmental milestones. [ABSTRACT FROM AUTHOR]

The rapid expansion of built-up land in China contributes to the great differences in regional development, which has impacted balanced regional development. Analysis on teleconnections of built-up land can better understand the mechanism of spatial imbalance, thus promoting the achievement of overall carbon neutrality. We attempt to quantify the degree of unbalanced regional development based on teleconnections of built-up land in China. Results reveal an increase in external dependence in developed regions, with the economic growth in these regions driving the expansion of built-up land in undeveloped regions. Undeveloped regions primarily serve as suppliers of land for the mining and manufacturing industry, while developed regions export substantial land for the service industry. There is considerable variation in the environmental-economic benefits among regions: While each province experiences economic gains from built-up land expansion, differences in land utilization efficiency contribute to a significant development gap among regions. This divergence in development levels exacerbates the unbalanced regional development in China, a trend that is currently widening. It is imperative for developed regions to assume greater responsibility in achieving carbon neutrality. This involves providing economic and technological support to undeveloped regions, fostering a more equitable and sustainable development path. [Display omitted] [ABSTRACT FROM AUTHOR]

Marine and port economy estimation is conducive to the understanding of the development law of marine economy degree. This study proposes a neural-learning network estimation model of the marine economy degree based on a priori architectural knowledge and adopts time-combined class array columns and multivariate modeling methods to estimate the indicators reflecting the development level of the marine economy degree in the ZJP region. The study adopts the PK_NN multivariate modeling method, taking cargo transportation volume, cargo turnover, cargo carrying value of ports near the sea, foreign trade throughput, port container throughput, and port container throughput as multivariate model inputs, and compared with the other modeling methods, the model of the time combination class array columns of type GM_11, which has a better comprehensive performance. Finally, the PK_NN time-combined class array column model is used to estimate the development level of the marine economy in the ZJP region near the seaport from 2011 to 2020, and the results show that the estimated value of the marine economy in the ZJP region is close to the actual planning value of the ZJP region. The algorithm was applied to estimate the economic degree curves of the five near-seaport areas of ABCDE under different harbor head construction art modes, and the results showed that the relative value error of the estimation was controlled between 4% and 10%, and the fluctuation ranges of each month's specific growth value area estimation were comparable. This proves the effectiveness and accuracy of the a priori marine neural-learning-based network algorithm in this paper. • The algorithm was applied to estimate the economic degree curves of the five near-seaport areas of ABCDE under different harbor head construction art modes, and the results showed that the relative value error of the estimation was controlled between 4% and 10%, and the fluctuation ranges of each month's specific growth value area estimation were comparable. • This proves the effectiveness and accuracy of the a priori marine neural-learning-based network algorithm in this paper. [ABSTRACT FROM AUTHOR]

This study examined the relationship between government environmental governance (GEG) and regional green development. The findings suggest that GEG boosts green innovation by promoting the "innovation compensation effect" while inhibiting regional green development due to increased environmental costs, supported by the "compliance cost effect". The relationship between GEG and regional green development is moderated by economic development and environmental pollution in an inverted U-shaped pattern. When economic development and environmental pollution are at lesser levels, the positive effect of GEG amplifies as economic growth and environmental pollution ascend. However, if economic growth and environmental pollution continue to escalate, the positive impact of GEG will lose its strength. In low-carbon pilot cities, GEG negatively affects regional green development, whereas the opposite effect is seen in non-pilot cities. Regardless, there is an inverted U-shaped moderating impact of economic development or environmental pollution in both low-carbon pilot and non-pilot cities, yet the inflection point varies across regions. This paper offers an original perspective by creating a theoretical link between green development and environmental governance and emphasizes the significance of a nonlinear viewpoint when examining the relationship between variables in the regional green development process, thereby expanding our understanding of green development phenomena. [ABSTRACT FROM AUTHOR]

The ongoing integration of artificial intelligence (AI) into the fundamental fabric of society constitutes a transformative process, with the potential to exert profound influence on various facets of human existence including environmental quality. Our research investigates the interaction of AI and renewable energy production in 22 leading robotics and innovative countries, providing crucial insights into a previously underexplored domain. The study's novelty and originality are in demonstrating the precise impact of AI in enhancing and revolutionizing renewable energy production, consequently addressing, and filling a critical study gap. Our analysis comprises both asymmetric and symmetric assumptions to cover the positive and negative shocks of artificial intelligence on renewable energy from 1991 to 2020. The findings from the panel NARDL analysis provide substantial support for the profound impact of changes in artificial intelligence (AI) on the substantial stimulation of renewable energy in the long-run. Furthermore, AI plays a substantial role in enhancing long-term renewable energy production in the panel symmetric ARDL. In the country-specific investigation, it is found that Austria, Germany, and New Zealand are the nations where both affirmative and adverse changes in AI improve clean energy structure significantly in the short run. Natural resources, information communication technology (ICT), and economic growth also enhance renewable energy production. Finally, policies are directed to increase renewable energy production. [ABSTRACT FROM AUTHOR]

This paper analyses threshold effects and transmission Channels of foreign aid on economic growth of WAEMU countries using the World Bank, the International Monetary Fund and the International Country Risk Guide databases to cover the period spanning from 1980 to 2018. After applying endogenous threshold approach to determine aid threshold above which its affects growth and estimate its long-term effects, Pagan's Residual-Generated Regressors method was used to identify channels that can modulate effects of aid on growth. Evidences strongly support the view that the relationship between aid and economic growth is non-linear with a threshold that lies between 12.37 and 14.08% of GDP. Above these values, the marginal effect of aid is 2.1%. Moreover, results indicate that only investment seems to be a potential channel through which aid would affect growth. Thus, aid within the WAEMU countries is beneficial. Its content and use should be the main concern of donors and policy-makers. [ABSTRACT FROM AUTHOR]

The United Nations 2030 Agenda brings a holistic and multi-sectoral view on sustainability via the Sustainable Development Goals (SDGs). However, a successful implementation of this agenda is contingent on understanding the multiple, complex interactions among SDGs, including both synergies and trade-offs, for informing planning for sustainability at the local level. Using a case study in the Goulburn-Murray region in Victoria, Australia, we prioritised global goals and targets for the local context, characterised the interactions between them, analysed the main synergies and trade-offs, and identified potential policy solutions to achieve local sustainability. We identified the five highest priority SDGs for the region as clean water and sanitation (SDG 6), agricultural activities (SDG 2), economic growth (SDG 8), climate action (SDG 13), and life on land (SDG 15). Across these five priority SDGs and their 45 targets, we found 307 potential interactions, of which 126 (41%) were synergistic, 19 (6%) were trade-offs, and 162 (53%) were benign. We highlight the most salient trade-offs, particularly how unsustainable agricultural practices could negatively affect water resources, the environment, and sustainable economic growth. Also, critical ongoing uncertainties like climate change, local policies on environmental water recovery, international markets, and emerging new technologies could pose risks for the future of agriculture and the economy. Our results provide important insights for local and regional sustainability policy and planning across multiple sectors. Our methodology is also broadly applicable for prioritising SDGs and assessing their interactions at local scales, thereby supporting evidence-based policy-making for the SDGs. • A successful implementation of SDGs depends on understanding of SDG interactions. • Our approach is participatory and systematic in capturing SDG interactions. • The most trade-offs are related to SDG 2 and SDG 8 with other local priority SDGs. • We design solutions to leverage synergistic interactions and limit the trade-offs. [ABSTRACT FROM AUTHOR]

The foreign and domestic investments have a significant contribution towards economic development for developing and developed economies especially for underdeveloped economies. The primary objective of this study is to investigate the causal connection between domestic and foreign private investment along with its impact on economic growth of Pakistan. Moreover, time-series data has been used from 1980 to 2017 and autoregressive distributed lags (ARDL) method is implied for the data analysis perspective. The long-run findings indicate that foreign private investment has a negative and insignificant impact on economic growth, whereas, domestic investment shows a statistical significance but positive impact on Pakistan economy. The short-run dynamic designates that both domestic and foreign private investment is significantly and positively associated with the growth rate. Whereas, error correction term (ECT) is correcting the disequilibrium of data 42.7% on annual basis. Finally, F-test shows that the overall model of this study is statistically significant. [ABSTRACT FROM AUTHOR]

This paper examines the effect of foreign direct investment (FDI) inflows on host country's economic growth for a group of 45 developing countries for the period 1990–2014. Using the pooled mean group (PMG) regression method, we estimate the long-run and the short-run impact of FDI inflows on growth rate of GDP per capita. The PMG regression results suggest that the growth rate of GDP per capita and its covariates are cointegrated, implying the presence of a long-run equilibrium relationship among the variables. Our results suggest that FDI inflows have significant positive impact on economic growth of the recipient countries both in the long-run and in the short-run. We find that the long-run effect of FDI inflows on economic growth is higher in the emerging market economies as compared to the non-emerging market economies. FDI inflows have significant positive effect on the long-run economic growth in Asia and Africa region. [ABSTRACT FROM AUTHOR]

• Economic growth optimisations towards socio-ecological objectives are failing. • Inclusive Development is irreconcilable with Inclusive or Green Growth. • Minimum inclusion via social floors is self-defeating without resource re-allocation. • Re-allocation in a limited ecospace relies on downscaling of over-consumption. • Downscaling can only be achieved through system change. The 2030 Sustainable Development Agenda rests on both economic growth and Inclusive Development (ID). However, since growth is entangled with socio-ecological exploitation and appropriation, it conflicts with ID where 'inclusive' encompasses social, ecological and relational dimensions, and fundamentally redefines 'development'. Using Toulmin's argumentative model, we show that: (a) inclusive green growth does not promote socio-ecological inclusion and ignores relational inclusion, as economic growth cannot be optimized towards those broader aims; (b) policies for inclusion through pro-poor 'access' without 're-allocation' of resources are self-defeating, as inequitable allocation of wealth and of a limited environmental utilization space impoverishes the poor and transfers ecological risks to them; (c) 're-allocation' requires a post-growth agenda involving a downscaling of overconsumption and overaccumulation by the global Centers, and a redefinition of development by the Peripheries; and (d) such an agenda is obstructed by the unequal distribution of wealth and political power. The only way forward is when science and social movements converge to demand system change on the streets and in the courts. [ABSTRACT FROM AUTHOR]

• The DPI ratio followed a reverse U-curve relationship with per capita GDP. • A reverse U-curve relationship between the DPI ratio and the MPC. • There was a U-curve relationship between the DPI ratio and the MPA. Introduction: Past empirical studies indicated that there is a Kuznets or reverse U-shaped relationship between road deaths and per capita income, such that the number of road death increases at a low level of per capita reverse U-shaped relationship was observed between road injuries and per capita income. While these studies explored the impact of per capita income on road deaths and road injuries, no studies have examined the relationship between per capita income and road death to road injury ratio (DPI). Method: Using a fixed effects panel regression analysis from 67 countries spanning over a period of five decades (1960–2013), the present study sought to explore the impact of per capita gross domestic product (per capita GDP) on the DPI ratio and the underlying factors responsible for the relationship. Results: Our result suggests that per capita GDP followed a reverse U-shaped relationship with DPI. Moreover, the relative improvements in higher mobility roads as compared to improvements in higher accessibility roads, motorcycle ownership to passenger car ownership ratio, percentage of population living in an urban area, infant mortality rate, and the percentage of population below 15 years of age and above 64 years of age contributed to this relationship. Practical Applications: This implies that, at lower level of economic growth where road deaths exceed road injuries, countries should implement low-cost measures to combat road deaths cases. Such measures include mandating wearing of quality helmets and daytime running headlights for motorcycles. On the other hand, at higher level of economic growth where road injuries surpass road deaths, countries are encouraged to devote more resources to improving medical technology and services to treat road injury victims, mandating seatbelt use, as well as enhancing and promoting public transportation service. [ABSTRACT FROM AUTHOR]

This paper examines the effectiveness of foreign capital in the form of FDI, remittances, and foreign aid in improving economic growth prospects in the South-Asian region. A sample of 8South Asian countries for the period 1990–2017 is being considered for this study. The study uses various econometrics tools such as the Johansen-Fisher Panel cointegration test, Panel FMOLS, and PDOLS to ascertain the long-run and short-run dynamics among the variables under consideration. We found that the long-run and short-run relationship exists among foreign aid, economic growth with other macroeconomic variables. Further, using the Granger causality framework, we found that unidirectional causality exists between foreign aid to economic growth, FDI inflows to economic growth, and there is no short-run causality between remittances and economic growth. On the other hand, we confirmed that the existence of long-run causality between foreign aid to economic growth and FDI to economic growth. [ABSTRACT FROM AUTHOR]

[Display omitted] • The determinants of CO 2 emissions in newly industrialised countries are explored. • FMOLS, DOLS and PMG estimation methods are applied. • Economic growth and human capital improved the environmental quality. • Energy use and exports deteriorated the environmental quality. • The existence of the EKC hypothesis was not found in NIC S. Environmental problem is a great concern world-wide which has been researched from various angles, including via the environmental Kuznets curve (EKC) hypothesis. EKC shows a hypothesized inverted U-shaped relationship between economic growth and environmental quality. As the severity of problem grows with industrial activities, this paper explores the impacts of economic growth, energy use, exports and human capital on the environmental quality of newly industrialised countries (NICs) over the period of 1979−2017. We have considered the cross-sectional dependence (CSD) issue, often ignored by most of the panel data studies. Using panel cointegration estimation technique, we have applied Dynamic Ordinary Least Squares (DOLS), Fully Modified Ordinary Least Squares (FMOLS), and Pooled Mean Group (PMG) estimation methods that address the CSD problem. Our findings exhibit the existence of CSD and long-run nexus among the variables used. In the long run, economic growth and human capital improved, and energy consumption and exports deteriorated environmental quality. The long-run elasticity for the energy variable is around one. DOLS and PMG methods provide similar results exhibiting that the effect of economic growth on CO 2 emissions is the highest followed by energy use, human capital, and exports. The study found no evidence of the presence of the EKC hypothesis in NICs. Policy suggestions are made based on the findings. [ABSTRACT FROM AUTHOR]

This study examines the effect of FDI, economic growth, energy consumption, human capital and biocapacity on carbon emissions in selected West African countries over the period 1970–2017. Employing the long run cointegration estimators, the empirical results confirmed the existence of U-shaped and N-shaped pattern between the estimated variables on CO2 emissions. However, the panel quantile estimates revealed that N-shaped exists only for high carbon emissions countries, but not in the middle and low carbon emissions nations. In addition, the results provide evidence of inverted U-shaped relationship between growth and CO2 emissions and this point to the fact that the EKC hypothesis is valid for ECOWAS countries. The panel quantile causality results indicated that FDI, biocapacity, energy consumption and human capital cause carbon emissions in all the estimated quantiles. The study provided suggestions for policymaking towards reducing carbon emissions in the region. [ABSTRACT FROM AUTHOR]

In this paper we investigate the causal relationship between foreign direct investment, trade openness and gross domestic product in BRICS countries over the period of 1990–2018. We applied auto regressive distributed lag model to test cointegration and the Dumitrescu and Hurlin Granger causality tests. Empirical results show that FDI and trade openness have a positive impact on long-term economic growth. We also find there is a long-run relationship from both real effective exchange rate and gross capital formation to economic growth. The main results of causality analysis reveal that there is bidirectional causality from foreign direct investment to economic growth, trade openness to foreign direct investment, and unidirectional causality from trade openness to foreign direct investment. [ABSTRACT FROM AUTHOR]

This paper constructs a digital financial inclusion evaluation system suitable for cross-country comparison. It uses the data of the World Bank and the International Monetary Fund to calculate the index of digital financial inclusion, and measure the level of digital financial inclusion in 105 countries. Then, we examine the relations between digital financial inclusion and economic growth by using spatial data and techniques for 86 neighboring countries. Our findings display that digital financial inclusion has a significantly positive effect on economic growth, and has spatial spillover effects on neighboring countries. [ABSTRACT FROM AUTHOR]

This study aims to examine digital technology adoption and globalization innovation implications on green sustainable economic growth on Asian Pacific selected countries (Malaysia, Indonesia, Singapore, Philippines, Thailand, Japan, India, Korea, China, New Zealand, Australia) via integrating digital technology adoption (digitalization and digitization), globalization, and environmental quality. This study employed the Hausman test to determine the appropriate estimation approach between random effect and fixed effect methods due to the digital adoption index (DAI) data limitation. The Hausman test confirms the random effect method for this analysis and the findings reveal that digital technology adoption promotes economic growth in Asian Pacific countries. Globalization was found an insignificant positive influence on Pacific countries' economic growth. The average growth rate of green total factor productivity (GTFP) as a Technology progress of innovation and environmental integration is positive, this might potentially be described by the high contribution of digital technology adoption and from the beneficial effects of labor, capital, CO2, and globalization positives contribution. The significant contribution of this study is filling the gaps via promoting green sustainable economic growth through inclusion of digital technology adoption and globalization in the growth accounting model that ignored. Technology adoption and globalization internalization plays a remarkable role to enhance innovations and knowledge and technology transfer, enabling companies to access wide-ranging markets, encouraging foreign direct investment, collaboration and smart partnerships along with conveying knowledge within and among the nations in technological creativity, globalization-based technology transfer, and intellectual property development to implement Sustainable Development Goals (SDGs). [ABSTRACT FROM AUTHOR]

Decoupling material use from economic growth is a prerequisite for alleviating the adverse effects of anthropogenic material use and achieving the Sustainable Development Goals. In this study, we combine dynamic material flow analysis with decoupling analysis to examine the relationship between the iron and steel cycle and economic growth in 23 industrialized countries from 1860 to 2018. Specifically, we employ both the quadratic and asymptotic functions to fit the relationship of per capita steel flow/stock indicators at six life cycle stages, including domestic production and apparent consumption of iron ore, pig iron, crude steel, finished steel, and fabricated steel, as well as in-use stock, against per capita GDP. A sequential decoupling between steel flow/stock indicators and GDP growth along the iron and steel cycle is evident. The historical dynamics of the comparative advantage of material flow indicators depict the wave-like geographic diffusion of industrialization. The mechanisms underlying the evolution of material-economy relationship can be attributed to resource endowments, industry policies, trade effects, and lock-in effect of in-use stock. Understanding this phenomenon can facilitate policy-making to promote dematerialization and improve material efficiency in developing countries. [Display omitted] [ABSTRACT FROM AUTHOR]