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Urbanization and the release of carbon emission are two significant features of contemporary economic and social progress in China. However, there are few studies that consider how urbanization policy goals affect carbon emission. This paper aims to study the nonlinear effects of urbanization policy goals on carbon emission in 13 cities of the Beijing-Tianjin-Hebei region. In this paper, a multi-dimensional spatial disturbance grey model is proposed. Based on matrix perturbation theory, this paper explores the spatial perturbation bounds of the novel model and verifies that the spatial property of the model is consistent with the viewpoint of the First Law of Geography. Then, the novel model is used to predict the urban carbon emission under different urbanization policy goal scenarios. The results showed that the novel model has spatial regional correlation in spatial region prediction. With the development of urbanization level, carbon emissions show a downward trend in more than 50% of cities from 2022 to 2025. In addition, the improvement of urbanization policy goals will promote the carbon peak time of most cities. The carbon emission intensity will exhibit an inverted U-shaped trend distribution in space. The research results are conducive to providing scientific guidance for the formulation of new-type urbanization policies and helping to achieve the dual carbon goals. • A multi-dimensional spatial disturbance grey model is proposed. • The novel grey model is consistent with the viewpoint of the First Law of Geography. • The spatial distribution of carbon intensity showed an inverted U-shaped pattern. [ABSTRACT FROM AUTHOR]

• A system of indicators has been established for the high-quality economic development index developed by the Chinese government. • High-quality economic development is divided into five dimensions. • Reliance on the resource industry has significantly reduced the level of high-quality economic development. • The theoretical mechanisms of the impact of resource industry dependence on high-quality development are analyzed. • Government governance capacity weakens the impact of resource industry dependence on high-quality economic development. In resource-dependent regions, the meaning of high-quality economic development has yet to be clarified by published research, despite substantial scholarly interest in the topic. With the help of the economic development index developed by the Chinese government, this paper accurately measures high-quality economic development in 30 provinces in China and investigates how resource dependence and government governance capability affect regional high-quality economic development. Research has found that resource industry dependence has a significant inhibitory effect on high-quality economic development. Additionally, the analysis of the mechanisms revealed that resource industry dependence reduces high-quality economic development through a series of effects including crowding out innovation, weakening coordination, lagging green development, hindering global openness, and sharing in weakening. Further research has revealed that government governance capacity weakens the impact of resource industry dependence on high-quality economic development. A detailed analysis of three subsystem indicators of government governance capacity, namely policy planning, capability commitment, and performance assessment, indicates that they all have a weakening effect. To this end, the paper proposes policy recommendations, including increasing innovation inputs, advancing industrial restructuring, promoting green development, enhancing marketization levels, and constructing a diversified employment system. These measures aim to transform resource disadvantages into resource advantages and facilitate high-quality economic development. [ABSTRACT FROM AUTHOR]

China's New Energy Vehicle (NEV) industry has entered an accelerated development stage, with the technology innovation efficiency becoming an essential factor affecting the speed of its development. Therefore, to explore ways to improve the efficiency of technology innovation, this paper divides the technology innovation process into two stages: the research and development (R&D) stage and the commercialization stage. This paper introduces a framework for evaluating the technology innovation efficiency of NEV enterprises based on data envelopment analysis (DEA), meta-frontier, and tobit regression. Then, the technology innovation efficiencies of 45 vehicle, battery, and motor & electronic control NEV enterprises are analyzed. The results show that: (i) During the survey period, the overall technology innovation capability of Chinese new energy vehicle enterprises is not strong, especially regarding economic transformation. However, the general development trend is on the rise. (ii) Different types of enterprises have different technology gap ratios in the two stages. The technology innovation efficiency level of motor and electronic control enterprises is relatively weak in the new energy vehicle industry. (iii) Many measures can be implemented to help improve technology innovation efficiency: encouraging the large-scale development of enterprises, reasonably increasing the shareholding ratio of significant shareholders, improving the ratio of capital investment, stimulating the vitality of innovation within the enterprise, and optimizing the number of employees. [ABSTRACT FROM AUTHOR]

Ports are essential and strategic nodes of international trade and economic activities. The integration of port resources helps enhance the optimal division of port functions to further promote economic development. This paper explores the evolutionary trends of port integration policy from 2011 to 2021 in China through a text-mining approach. We first used the Latent Dirichlet Allocation (LDA) topic analysis method to analyze the port integration policies and summarize the evolutionary trends of port policies. In addition, an association analysis was conducted to explore port integration policies' impacts by examining their relationships among the environmental protection, digitalization level, and port development scale. Our findings suggested that China's port integration policy has evolved from specific and simple to abstract and complicated at the managerial level. Port development has enriched from infrastructure construction to the ideology of economic development. Our findings show that China's port integration is gradually improving the port operation. The findings of the study contribute to the extant literature by analyzing the port integration policy evolution in China and can be referred to by other countries. • Text mining method was used to explore the port integration policy evolution. • Port integration policy evolved from specific and simple to abstract and complicated. • Port development enriched from basic infrastructure to the governance model. • The evolution of port integration policy was related to reducing carbon emissions in the port sector. • The evolution of port integration policy made the ports intelligent in association with digital technology such as big data and AI. [ABSTRACT FROM AUTHOR]

This paper analyzes the role of networks in the spatial diffusion of local economic shocks in Africa. We show that geographic connectivity, along with road and ethnic connectivity, are important for diffusing economic spillovers over longer distances. We then determine the key players, that is, which districts are key in propagating local economic shocks across Africa. Using these results, we conduct counterfactual policy exercises to evaluate the potential gains from policies that increase economic activity in specific districts or improve road connectivity between districts. [ABSTRACT FROM AUTHOR]

• New panel dataset of Marxist variables for 43 countries from 2000 to 2014. • Dataset includes rates of surplus value, composition of capital, shares of productive activity, and profit rates for the global economy. • The paper tests Marx's hypotheses on economic development at the world level. • Marx was right at the global level: capital intensity rises faster than exploitation rate, and the global profit rate declines. • Productive capital relocated to China, and unproductive activity increased in developed countries. We assess Marx's hypotheses about capitalist development on a global scale by constructing a new dataset of Marxist variables (profit rates, exploitation rates, composition of capital, and shares of productive activity) for 43 major economies, derived from world input-output data and national accounts in the 2000–2014 period. Consistent with Marx's hypotheses, the average profit rate declines at the world level, between countries, and within countries. The global rate of exploitation increases until 2008 but stagnates after the financial crisis, while capital intensity continued to increase. At the cross-country level, rich countries became increasingly dominated by unproductive activity. China absorbed much of the world's productive activity and kept the labor share of value added roughly constant at the world level. [ABSTRACT FROM AUTHOR]

In the context of significant environmental changes, the urgency of adopting green innovation has become increasingly apparent as a central mechanism for adjusting industrial structures in China. This transition serves not only as a crucial way to address pressing environmental challenges, but also as a fundamental strategy to improve the ecological efficiency of urban areas. Existing research mainly keeps a close eye on the unidirectional relationship between variables such as technological innovation and environmental protection. There is less relevant literature that has researched the cointegration relationship among green innovation, industrial structure, and eco-efficiency of cities. The essential role of green innovation and industrial structure in reaching a higher eco-efficiency of city are discussed in this research and the relationship among these three variables are analyzed by the evidence from cities in China from 2011 to 2019. The fact that the variables are cointegrated in the long run is evidenced by the results for the full sample. The sub-sample results report that in the eastern region, green innovation, industrial structure upgrading, and industrial structure rationalization could improve urban eco-efficiency. However, in Midwest regions where economic development is relatively backward, green innovation's effect on urban eco-efficiency is not in a significant positive way. The results obtained in this paper have implications for different cities in China to formulate corresponding policies on green innovation, industrial structure, and urban eco-efficiency. [ABSTRACT FROM AUTHOR]

How to improve carbon emission efficiency (CEE) to achieve sustainable economic development has triggered contemplation among society and policy-makers. Previous studies have confirmed that e-commerce development can reduce local carbon emissions, but the impact of e-commerce development on CEE is unclear. This paper investigates the impact of e-commerce development on CEE and its spatial spillover effect using Chinese city-level panel data, taking the National E-commerce Demonstration City (NEDC) policy as a quasi-natural experiment. Results show that the NEDC policy significantly improves local CEE by promoting industrial structure upgrading, green technology innovation, and improving energy efficiency. The influence is more pronounced in regions with inadequate information infrastructure, unfavorable business environment, and limited marketization. However, the NEDC policy has a negative spatial spillover effect, reducing surrounding cities' CEE. The findings unveil the complicated impact of e-commerce development on CEE and offer policy implications for improving inter-regional carbon reduction synergy and low-carbon economic transformation. [ABSTRACT FROM AUTHOR]

With the construction of smart cities, smart ports are developing rapidly, providing favorable conditions for enhancing port competitiveness, promoting industrial upgrading, and economic transformation. With the continuous progress of society and science and technology, the safety risks of intelligent ports are also increasing. In order to better address these risks, it is necessary to establish a stable and efficient management system. This paper applies data mining and fuzzy control theory technologies for large-volume, high-precision real-time information collection, based on the research of the BP neural network algorithm. By establishing and analyzing a safety risk management system model based on the BP multilayer neuron network, it provides a rationality evaluation method and design concept. After designing the safety risk management system, this paper conducts a performance test on the system. The test results show that through optimization, the accuracy, generalization ability, and reliability of the model can be improved. Its accuracy is as high as 92% or more, fully demonstrating the system's reliability and superiority! [ABSTRACT FROM AUTHOR]

To cope with the severe challenges related to traditional economic-centered urbanization, the Chinese government has proposed a people-oriented new-type urbanization strategy, which focuses on promoting the coordination and sustainable development of the environment, economy, and society. The existing literature has studied the impact of traditional urbanization on energy use but has not yet revealed the mechanisms and effects of the new transformation of urbanization on energy efficiency. Based on socio-economic-natural complex ecosystem theory, this paper systematically explains how new-type urbanization affects energy efficiency. By adopting a newly developed dynamic panel threshold model, the paper examines the complex impact of new-type urbanization on energy efficiency using panel data of 285 cities in China from 2003 to 2017. The results show that new-type urbanization has a significant double-threshold effect on energy efficiency. As the new-type urbanization level increases, the improvement effect of new-type urbanization on energy efficiency presents the change features of "strong-weakened-stronger." The heterogeneity analysis shows that under the constraints of multiple factors, such as new-type urbanization stages, geographic regions, economic development levels, and resource endowment, the impact of new-type urbanization on energy efficiency varies significantly. Targeted and differentiated policy recommendations for promoting new-type urbanization and energy efficiency are proposed. [ABSTRACT FROM AUTHOR]

Most migration studies and theories focus on understanding the initial migration of people from their home country. Less attention has been paid to the factors influencing immigrants' preferences to either permanently settle in the host country, return to their home country or move onwards to another destination. Understanding the characteristics and motives of those who aspire to leave the host country is, however, valuable for both host and home countries to formulate appropriate and effective policies in order to retain their valued immigrants or citizens and foster their successful (re-)integration. This paper provides a comprehensive global analysis of the characteristics and circumstances that shape first-generation immigrants' aspirations to stay, return or migrate onwards, based on individual-level data from the Gallup World Polls across 138 countries worldwide between 2009 and 2016. Our study reveals that immigrants' stated preferences are strongly influenced by demographics, human and spiritual capital, as well as by soft factors, such as social ties and sociocultural integration, while economic factors have a more feeble influence. Changes in circumstances in the home and host countries are also important determinants of locational aspirations. Some interesting exceptions to our results stand out when we differentiate home and host countries by their economic development levels. [ABSTRACT FROM AUTHOR]

For a long period of the 20th Century, industrialization was seen as the quickest and more effective path for progress and productive diversification, influencing the choice of public policies adopted by Latin American governments since the inter-war period up until the debt crisis and the lost decade of the 1980s. Using a long-term macroeconomic database for the period 1913–2013 and 11 Latin American countries, complemented with a dataset of exports by product for the same countries and years, a positive relationship between industrialization and economic growth was found, both for the long run and for episodes of acceleration and deceleration. This correlation seems to be stronger for large than for small economies, reflecting the importance of the size of the domestic market in order to take advantages of economies of scale in the process of industrialization. Three economic channels that may explain this positive correlation are empirically tested. The first one is the contribution of manufacturing to the different components of productivity growth (within- and shift-effects), for which a shift-share decomposition was estimated, both for the long-run, for subperiods and for acceleration and deceleration episodes. The second channel is the contribution of industrialization to gross capital accumulation, where a positive relationship was found between the change in the share of employment in manufacture with the rate of growth of physical capital. Finally, the learning-by-doing hypothesis is tested using the skill-level composition of manufacturing exports, finding a positive relationship between cumulative manufacturing production and the share of mid- and high-skill products in the exports' matrix. The main contributions of the paper are twofold: the empirical identification of the mechanisms through which industrialization can promote economic development, and the extension of the analysis of Latin American economies to the first half of the 20th Century, which is scarce in the literature because of lack of reliable data. [ABSTRACT FROM AUTHOR]

Since 2015, the United Kingdom (UK) has increased its investment in transportation infrastructure to compensate for years of underinvestment in comparison with peer countries. It is of critical importance to evaluate the effect of these recent investments, as well as historical ones, on economic development, both theoretically and empirically, to provide guidance on future infrastructure investment. However, few research looks into such policy adjustment on economic growth in the UK. To fill this gap, this paper investigates the relationship between transport infrastructure development and economic growth in the UK from different time spans. Principal component analysis (PCA) is used to construct a comprehensive measure of transport infrastructure development. This paper then applies Vector Error Correction Model (VECM) to investigate both long-run and short-run relationships between transport infrastructure development and economic growth from 1970 to 2017 in the UK. Empirical results suggest that transportation infrastructure has a long-run promotive effect on economic development. However, in the short run, this effect turns out to be significantly negative. The analysis of this paper indicates differentiated roles that the UK's transport infrastructure played in economic growth, which should be considered in future policy design of achieving economic sustainability in the UK. • This paper investigates the relationship between transport infrastructure development and economic growth in the UK. • Transportation infrastructure has a long-run promotive effect on economic development. • In the short run, transportation infrastructure fails to promote economic development. [ABSTRACT FROM AUTHOR]

The development of information technology proves the possibility of acquiring large samples of policy text information and promotes innovative research based on the policy informatics approach of fusing data from multiple sources. This paper constructs a new public policy model based on existing data on economic system reform, and uses multi-types of textual big data such as government website, official weblog, and social media as the object of collection, to conduct a big data measurement on policy concerns related to the theory and practice of economic system reform since the reform and opening up. And this paper constructs a fine-grained measurement and portray the evolutionary trend of policy concerns and policy implementation. Based on the database, this paper helps to analyse the economic development trend since the reform and opening up, evaluate and monitor the implementation effect of different incentive policies and establish an iterative feedback mechanism, and provides a reference for relevant decision-making departments. [ABSTRACT FROM AUTHOR]

• The paper documents developments in Indian economic performance and the role of structural change in this performance. • Manufacturing is dominated by informal labor, which has a deleterious effect on overall manufacturing performance. • Productivity growth is driven by within sector growth, with positive contributions of formal and informal activities to this. • Labor reallocation to the informal segment of the manufacturing sector is growth reducing in the Indian manufacturing sector. • A shift to more productive informal activities across sub-sectors exists, but this doesn't offset the negative within effect. This paper examines the role of structural change in India's performance, and in particular the role of the informal segment in the stagnant growth of the Indian manufacturing sector. Using counterfactual analysis – including a modified shift-share approach – the paper considers to what extent the informal sector can help explain the poor performance of Indian manufacturing over the period 1980-2011. The results suggest that the informal segment of manufacturing has been a drag on overall manufacturing productivity growth, with the informal manufacturing segment unable to provide a productivity bonus when absorbing workers from the agricultural sector. Results from the shift-share analysis indicate that labor reallocation to the informal segment of the manufacturing sector is growth-reducing, with structural change being the main source of this reduction, an effect which in turn is driven by movements of employment within manufacturing sub-sectors. [ABSTRACT FROM AUTHOR]

• We present a methodology for relating traded products to aggregate country indicators. • We identify imported and exported products that correlate with growth and income per capita. • Catching-up economies characterized by frugality in consumer demand and the prominence of mass-production industries. • Mature economies distinguished by the importance of consumer demand and the export of knowledge-intensive goods. Using a novel methodology to relate traded products to aggregate country indicators, this paper identifies imported and exported goods that correlate with growth and income per capita, and based upon that, determines the productive and demand structure of mature and catching-up economies. The methodology in question first uses Principal Component Analysis on the products that countries specialize in importing and exporting, to reduce the number of variables that will, later, be linearly related to income and growth using Canonical Correlation Analysis. It is shown that fast growing or catching-up economies are characterized by the export of mass-produced manufactured goods, and the import of capital and intermediates – but not consumer goods. Frugality in consumption demand and congruence between exports and imports explain the high growth rates of catching-up or transitioning economies. In contrast, high income and slow growth mature economies are characterized by the export of goods whose production requires advanced technological capabilities. Their demand structure is characterized by the prominence of consumption rather than means of production. [ABSTRACT FROM AUTHOR]

Analysis of the vulnerability of rail transport systems has received considerable attention in the literature over several decades. Since economic development is usually associated with increasing demand for railway transport as more and more passengers rely on railways, the consequence of disruptions to the railway system becomes unaffordable and creates significant impact on society and economies. Hence, there is a growing need for effective mitigation strategies and greater appreciation of the linkage between vulnerability analysis and policy implementation. This paper reviews recent studies of methods applied for vulnerability analysis of rail transport systems and assesses their policy or strategy-related content. The result shows the predominance of topological approaches in the railway vulnerability analysis context; however, very few provide concrete policy- or strategy-related implications and suggestions. The findings also show that the link between research in the context of vulnerability analysis and risk analysis is weak, and practice-oriented studies are limited; this is identified as an area for future work. Overall, this paper provides a comprehensive insight into the state-of-the-art vulnerability analysis of rail transport systems, drawing on both research and practice and offers a guide for future studies. The remaining gap between theory and policymaking is clearly elaborated. • A review focusing on policy-related vulnerability analysis of rail transport systems is conducted. • Co-occurrence of critical keywords in abstracts of reviewed papers is displayed virtually. • The result shows very few provide concrete policy-related implications and suggestions. • The link between research in vulnerability and risk analysis is weak, practice-oriented studies are limited. [ABSTRACT FROM AUTHOR]

From the perspective of economic cycle, this paper describes the failure mechanism of the associated credit risk contagion among enterprises by constructing a cascade effect model, and further simulates and analyses the anti-credit risk capability of the enterprise network. It is found that the anti-credit risk capability of the associated enterprise network is enhanced with the increase of enterprises redundant resources. In the process of the prosperity and development of the economic cycle, the credit risks encountered by large enterprises are more likely to cause cascade effect in the enterprise network. This paper expands the application scope of the cascade effect model, and provides a new perspective for enterprises to manage and control credit risk. [ABSTRACT FROM AUTHOR]

The total electricity consumption (TEC) reflects the operation condition of the national economy, and the prediction of the total electricity consumption can help track the economic development trend, as well as provide insights for macro policy making. Nowadays, novel neural networks provide a new perspective to predict the total electricity consumption. In this paper, a time series forecasting method based on Transformer model, Trans-T2V model, is proposed and applied to TEC forecasting. Transformer is the first network structure that completely relies on self-attention to calculate input and output. In this paper, the Time2vec method is used to improve the existing Transformer model, as embedding the month sequence more efficiently in the Transformer model. By comparing with the existing Transformer models and other intelligent algorithm models, the robustness and superiority of the proposed method framework are verified, and the highest accuracy reaches 97.36%. The method presented in this paper provides valuable insights in the field of time series prediction. [ABSTRACT FROM AUTHOR]

"Rural Australia" has long been a special site of political contestation. Staking the terms of public depictions of "the rural", "the bush", or "country life" is a constitutive thread running through Australian settler colonial identity and a cornerstone of national electoral politics. This paper analyses major News Corporation media outlets' presentation of an evolving political campaign, comparing contesting representations of farming and rural Australia deployed by the Morrison Coalition government and advocacy group Farmers for Climate Action, in the period between the government's re-election in May 2019 and July 2021. The paper steps through the key tactical discursive moves made by these contesting parties. It argues that in their depictions of rural Australia there are two important features that these perspectives share. Both embrace a discourse of increased agricultural productivity inspired by high-tech innovation, and both are silent on the related social and economic transformations that undergird the "crisis" of the rural. Consequently, public political contestation over rural policy unfolds without engaging transforming structural arrangements that fundamentally organise work and life on the land. • Presents comparative depictions of rurality by the Australian prime minister and advocacy group Farmers for Climate Action. • Political contests over the representation of the rural during the time of accelerating climate change are shown to have strong temporal framings. • Both government and Farmers for Climate Action embrace a discourse of increased agricultural productivity inspired by high-tech innovation and both are silent on socio-economic transformations. • Farmers for Climate Action have made significant steps towards normalising the idea that farming and climate activism go hand in hand. [ABSTRACT FROM AUTHOR]

• Impacts of export quality on economic progress are examined. • The role of economic complexity for economic growth is investigated. • 28 OECD country's data is utilized from 1990 to 2019. • Export quality and economic complexity induce sustainable growth. • Institutional quality is a significant determinant for economic growth. It is important to unearth the role of structural change factors for sustainable growth in developed economies. Economic complexity, export product quality, and institutional indicators represent the overall structural change and transformation in an economy. This paper probed the influence of export product quality and economics of complexity on economic growth for 28 OECD (Organization for Economic Co-operation and Development) countries using the data from 1990 to 2019. In doing so, the study employs three-panel data econometric models to investigate the role of economic complexity, export quality, and institutional quality on economic development. The paper performs the empirical tests, including the cross-sectional related dependency methods and cointegration techniques. As per the results emerging from fully modified OLS (FMOLS) and dynamic OLS (DOLS) estimation, export quality and financial development positively and significantly strongly impact growth in the long run. The empirical conclusions report detailed discussion on sustainable growth and discuss novel implications concerning product quality and institutional performance. The conclusions stress the practical implications for sustainable economic growth of OECD economies. [ABSTRACT FROM AUTHOR]

As a novel form of infrastructure, 6G is poised to become an indispensable component of the future digital economy and serves as a solid guarantee for the development of human society. Given that technological innovation inherently possesses purpose and direction, its progress cannot be divorced from the correct value orientation. However, scholarly attention towards investigating the value proposition of 6G remains limited. Establishing a scientific and rational value system assumes paramount importance in shaping future investments and deployments of 6G and fostering advancements in associated technologies. This paper presents a comprehensive analysis of the value proposition of 6G, examining it from multiple perspectives including economic, social, ecological, cultural, and strategic dimensions. In addition, we explore the four vertical value dimensions of nation, industry, firm and individual. By integrating the technology life cycle framework into our consideration, we elucidate how value is realized and evolves across different stages. The primary objective of this paper is to enhance comprehension regarding the value of 6G and forthcoming technologies while extensively expounding on the potential contributions of 6G towards future economic and social development. • This paper provides a comprehensive analysis of the value proposition of 6G and examines it from a demand perspective. • We discuss 6G values in the horizontal dimension, including economic, social, ecological, cultural, and strategic values. • We explore the value of 6G in four vertical dimensions related to nation, industry, enterprise, and individual. • Combined with the technology life cycle, we analyze the realization and evolution process of 6G value in four stages. [ABSTRACT FROM AUTHOR]

• We frame creative clusters funding as a top-down mechanism for creative placemaking. • We query the effectiveness of spatial imaginaries used in regional economic policy. • We contribute fine-grained qualitative data on the + and − impacts of clustering. • We recommend an ecological approach best serves existing creative communities. • Our learnings are relevant for new global policies on superclusters and multi-city regions. Creative clusters – geographic concentrations of creative industries sector activity, its skilled individuals, organisations and institutions – have attracted significant investment globally, becoming an important driver of economic growth. In this paper, we frame investment in creative clusters as a mechanism for creative placemaking. Creative placemaking occupies a dual role as a driver of economic development via arts-led 'regeneration' of high streets and flagship infrastructural projects like cultural quarters, yet also as a sustained stewarding of creative places through social engagement and community-centred decision-making about cultural projects. This distinction is typically framed as 'top-down' versus 'bottom-up' creative placemaking. We use the Bristol+Bath Creative R+D (BBCRD) programme as a case study to show how this distinction becomes less black and white. BBCRD created a 'twin city' spatial imaginary distinct from the geography of existing cultural or placemaking policy remits. The novel contribution of this paper is in how it evidences the intersecting scales of creative placemaking and unpacks the effectiveness of multi-city regionality for creative clustering, using fine-grained empirical data on the impact of top-down placemaking initiatives for the existing creative ecology of a place. This type of data and analysis is largely missing from literature on both clustering and placemaking. Given the continued international replication of the clusters model, recently renewed via 'supercluster' and 'creative corridor' discourses, we propose that an ecological understanding − that takes place specificity, relationality and scale into consideration – is pressing, and offers a route for complementarity between top-down and bottom-up creative placemaking. [ABSTRACT FROM AUTHOR]

• Ecological restoration is not just an environmental issue and it is a societal problem. This paper analyzes ecological restoration and its impact on society in coal resource-based areas, focusing on the Ruhr region in Germany and Liulin County in China. Through the analysis and comparison, the study not only reveals the unique ecology-social system and explain the reasons for dependence on coal, but the finding shows that industrial transformation is a key factor in determining ecological restoration of coal resource-based regions. • The industries abandoned by the Ruhr area were taken over by China. Shanxi Province is very similar to the Ruhr area in terms of ecological destruction and social development at that time. The Ruhr region has become one of the most polluted areas in the world due to its coal and steel industry. After nearly 40 years of arduous practice, ecological governance and economic transformation in the Ruhr area achieved initial success. • Shanxi Province in China is a hub for energy and heavy chemical industries, and it ranks first in coal production nationally.. The Liulin county is located in the west of Shanxi Province, it is a typical coal mining subsidence and is scattered with numerous villages affected by subsidence due to coal mining. Shanxi Province and the Liulin county is undergoing difficult industrial transformation. • The author of this work visited the Duisburg-Essen University for a year, located in the Ruhr area of Germany, and learned about the ER and transformation in the Ruhr. When the author returned to China, she conducted field research for a two-month survey in Liulin County. Therefore, the author collected a large amount of literature ,data sources and gained practical experiences in these two areas. The coal resource-based areas rely on coal resources and primary processing as their pillar industries, such as the old industrial areas in China and Germany. Long-term, large-scale coal mining has significantly damaged the ecological environment of mining areas. Environmental restoration refers to repairing, rehabilitating, or revitalizing ecosystems that have been degraded, damaged, or destroyed by human activities or natural disasters. In fact, ecological restoration is not just an environmental issue and it is a societal problem. Ecological restoration is closely linked to natural resources, the environment, the economy, society, and politics. These factors form a social ecological system and it is the basis for local stability and sustainable development in the coal resource-based areas. In this process, the relationship between government, enterprise, and local people is constantly being reshaped and defined, then it causes changes in the local social ecology and political ecology. The paper researches the Ruhr area in Germany and the Liulin County in China, the former is a world-famous old industrial and the latter is a typical coal mining subsidence district. By analyzing and comparing the ecological restoration and significant social changes in the Ruhr area and the Liulin County at different periods, the findings show the unique ecology— social system of the coal resource-based area, then enhances the effective measures for ecological restoration and sustainable development of the coal resource-based areas. [ABSTRACT FROM AUTHOR]

Network infrastructure is one of the most significant technological developments in recent decades, as well as a powerful boost for economic growth in both urban and rural area. However, whether improving network infrastructure reduces urban-rural income inequality (URII) remains uncertain in the previous literature. Considering that URII is an important research issue in the field of social change, it is worthwhile to investigate the causal relationship between network infrastructure and URII. Based on the exogenous shock from a quasi-natural experiment of "Broadband China" demonstration cities, this paper utilizes a time-varying Difference-in-Differences (Time-varying DID) model to identify the causal impact of the improvement of network infrastructure on URII in China. The results show that: (1) After controlling the impact of other commonly acknowledged factors, network infrastructure remains a significant factor in URII reduction. (2) The mechanism analysis confirms that the mediating effect of digital financial inclusion plays a vital role in the impact of network infrastructure on URII. (3) Further regional heterogeneity analysis reveals that the impact of network infrastructure on reducing URII also relies on region's characteristics, such as geographical location, traditional infrastructure level, and administrative level. This paper has figured out the causal relationship between network infrastructure and URII, thus inspiring policy-makers who aim to reduce inequality between urban and rural areas to commit to improving network infrastructure with an emphasis on digital financial inclusion mechanism and comprehensive consideration of regional heterogeneity. • Network infrastructure construction can significantly reduce urban-rural income inequality. • Time-varying Difference in difference method (Time-varying DID) was adopted to investigate the "Broadband China" Policy. • The mediating mechanisms and heterogeneity of network infrastructure development on urban income inequality are discussed. • The value of the "Broadband China" Policy for urban-rural development is shown. • Our findings offer advice for developing countries and local governments. [ABSTRACT FROM AUTHOR]

Renewable energy adaptation can play a critical role to halt climate change, although many researchers in the past tried to estimate its effect toward the environment, but the findings are still unclear and complex due to limitation of data and adopted methodologies. Therefore, to overcome the weaknesses, this paper aims to re-investigate the role of renewable energy adaptation, financial development and globalization toward environmental quality and economic progress in leading economies, we call it big five economies (B5) of the world. These economies (USA, China, UK, Germany, and Japan) were chosen based on ranking by the IMF. In this paper, we applied panel techniques for data analysis including panel data unit roots test, padroni cointegration analysis and panel data FMOLS and panel DOLS. Further, to explore country specific results and to ensure the robustness of findings, frequency domain causality test was applied. Results of estimation reveal that renewable energy adaptation mitigate the environmental impact to improve environmental quality and reinforce economic progress in B5 countries. Although, financial development, capital formation, natural resources and globalization improve economic progress, but these factors create adverse consequence for the environmental quality. Similarly, it can be stated that it's a tradeoff between economy and the environment. Further, the role of trade is found as constructive for environmental quality and economic progress in B5 economies. We believe that the conclusions of our study hold promise for key insights for the policy development. • This paper adopted panel of Big five economies. • Renewable energy adaptation holds a critical role for the environment. • Financial development in selected economies boost the economic output. • Resources utilization reinforce economic progress and environmental degradation. [ABSTRACT FROM AUTHOR]

• This paper investigates the relation between democracy and income per capita over the period 1870–2010. • I use both cross-sectional and panel fixed effects regressions to explore how this relation changed over time. • Results show that democracy positively affects income per capita in the period post-1950, especially after 1990. • Yet, democracy has no significant effect in the period prior to 1950. • In the years before World War II, income per capita is mostly explained by prior income levels and education. Economists and political scientists have long investigated the effect of political institutions on economic development, mainly focusing on cross-sectional analyses for the years after World War II. This paper takes a historical perspective and studies whether this effect can be traced back to 1870 and how it changed over time. Using both cross-sectional and panel fixed effects regressions, I show that democracy positively affects income per capita in the post-1950 period. The effect increases as time passes and becomes especially larger after 1990, i.e. with the great democratization wave induced by the Fall of the Iron Curtain. Yet, I find no effect for the period before 1950, when the variation in income per capita is mostly explained by prior income levels, and in particular, by education. These findings are robust to accounting for income dynamics as well as to using different data sources to measure political institutions. [ABSTRACT FROM AUTHOR]

Agriculture is under transformation in sub-Saharan Africa where millions still do not have access to a healthy diet. Policy makers in this region should find ways to accelerate agricultural transformation while increasing access to healthy diets. Optimizing agriculture's public budget stands out as a handy option. By combining a dynamic computable general equilibrium model and a multi-criteria decision-making technique, and applying them in the context of Ethiopia, this paper points to an important trade-off that policy makers should keep in mind. An optimal allocation of agriculture's public budget aimed at increasing agri-food output, creating off-farm jobs and reducing rural poverty, which are agricultural transformation objectives, will help to reduce the cost of a healthy diet, allowing around 2 million more Ethiopians to afford it. This number could even be higher should policy makers allocate the budget optimally aiming at only lowering the cost of a healthy diet, but at the cost of reducing household income and slowing down transformation. [ABSTRACT FROM AUTHOR]

This paper investigates the nexus between foreign aid (in both forms: grant and loan), poverty trap, and economic development in a recipient country by using a Solow model with two new ingredients: a development loan and a fixed cost in the production process. The presence of this fixed cost generates a poverty trap. We show that foreign aid may help the country to escape from the poverty trap and converge to a stable steady state in the long run, but only if (i) the country's characteristics, such as saving rate, initial capital, governance quality, and productivity are good enough, (ii) the fixed cost is relatively low, and (iii) the loan rule is generous enough. We also show that our model with foreign aid has room for endogenous cycles, unlike the standard Solow model. • We investigate the effects of foreign aid (in both forms: grant and loan) on the recipient country's economic dynamics by using a model à la Solow (with two new ingredients: a fixed cost and a foreign aid). • A fixed cost in the production process may generate a poverty trap. • Foreign aid may help the country to escape from the poverty trap and converge to a stable steady state, but only if (i) the country's characteristics are good enough, (ii) the fixed cost is relatively low, and (iii) the loans rule is generous enough. • Unlike the standard Solow model, there is room for endogenous cycles in our model with foreign aid. [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 paper investigates the relationship between financial development and access to electricity for rural and urban India by incorporating economic growth, trade, and foreign direct investment in energy production function. In doing so, we have applied autoregressive distributed lag bounds testing to examine long run cointegration between the variables by accommodating structural break(s) stemming in the series. Our empirical results indicate the presence of cointegration association between access to electricity and its determinants. We note that financial development enhances access to electricity in rural India but declines it in urban India. Economic growth has positive effect on access to electricity. Trade openness and foreign direct investment lower access to electricity in rural India. In urban India, trade openness and foreign direct investment increase access to electricity. The association between financial development and access to electricity is inverted-U shaped for rural and urban India. This paper would present new policy direction for Indian government to enhance access to electricity by using financial development as an economic tool. • Financial development and access to electricity have a strong linkage. • In India financial development enhances access to electricity in rural area but has adverse effect in urban area. • Rise in economic growth of India has increased the access to electricity. • Growth of Trade Openness and Foreign Direct investment increase access to electricity. [ABSTRACT FROM AUTHOR]

This paper seeks to answer the puzzling question whether Industry 4.0 inevitably triggers a sociogenesis that results in new attitudes toward the nature of the socio-economic innovation ecosystem. It asks whether Industry 4.0, as a shifter of techno-economic paradigm, may carry higher exaptation potential, and if so, which technology could catalyse this effect. Prevailing literature suggests that graphene technology can easily become a pathfinder in this respect. The paper does not only consider why and how a graphene-based unfolding of Industry 4.0 can fulfil this function (i.e., making exaptations easier in a broader scale), but it also takes into account the wider context for exaptations by asking whether the current configuration of the real economy, the financial universe and the public sector offers a supportive ground for innovation and exaptation seeker behaviours. • I call for the rejuvenation/extension of research on exaptation by encapsulating techno-economic paradigms via systems view. • I extend the literature on Industry 4.0 by examining its exaptationary power via the neglected graphene technology. • I call for systems view when dealing with graphene-aided Industry 4.0 due to asymmetry between finance and the real economy. • I decipher zombification as a side-effect of the asymmetry acting against the sustainable and exaptationary Industry 4.0. • I propose six policy-oriented insights to make a sociogenesis toward qualitative growth more possible. [ABSTRACT FROM AUTHOR]

Improving the level of innovation factor allocation is an important route to achieve high-quality economic development in China and has received much attention from scholars. As a policy system to change the old and new dynamics of innovation, the impact of innovation pilot cities on the allocation of innovation factors is of great importance. Using a sample of 254 prefecture-level cities in China from 2006 to 2019, this paper empirically analyses the impact of innovative pilot city policies on the allocation of innovation factors and their paths of action using a multi-temporal double-difference model. The study finds that the innovative pilot city policy significantly improved the level of innovation factor allocation, and this result held true after considering a series of robustness tests and endogeneity tests. Mechanistic tests show that the innovation pilot city policy has an impact on the allocation of innovation factors through the factor mobility effect and the innovation environment effect. Heterogeneity test shows that the influence of innovation pilot city policies on innovation factor allocation is greater in cities with higher administrative levels and better geographical locations. The economic consequences show that the innovation pilot city policy can significantly promote high-quality regional economic development. This study provides useful lessons for giving full play to the innovation-driven policy's innovation factor allocation effect, thereby enhancing China's high-quality economic development. • This paper studies the influence of innovative pilot cities on the allocation of innovation factors. • It provides a new method for measuring innovation factor allocation. • The basic results were confirmed by a series of robustness tests and endogeneity tests. [ABSTRACT FROM AUTHOR]

[Display omitted] • The COVID-19 has impacted climate change researchers, creating additional work. • The use of communication technologies has helped to alleviate the problems. • A positive impact is that researchers were able to develop new research ideas. • The pandemic is likely to alter the course of climate change research. • Most of the surveyed respondents report that they can adequately cope with the problems. Since January 2020, the COVID-19 pandemic has dominated the media and exercises pressure on governments worldwide. Apart from its effects on economies, education systems and societies, the pandemic has also influenced climate change research. This paper examines the extent to which COVID-19 has influenced climate change research worldwide during the first wave at the beginning of 2020 and how it is perceived to exploit it in the future. This study utilised an international survey involving those dedicated to climate change science and management research from Academia, Government, NGOs, and international agencies in 83 countries. The analysis of responses encompasses four independent variables: Institutions, Regions, Scientific Areas, and the level of economic development represented by the Human Development Index (HDI). Results show that: (1) COVID-19 modified the way the surveyed researchers work, (2) there are indicators that COVID-19 has already influenced the direction of climate change and adaptation policy implementation, and (3) respondents perceived (explicitly concerning the COVID-19 lockdowns of March-April 2020), that the pandemic has drawn attention away from climate policy. COVID- 19 has influenced the agenda of climate change research for more than half of the respondents and is likely to continue in the future, suggesting that the impacts on their research will still be felt for many years. The paper concludes by outlining critical implications for policy-making. [ABSTRACT FROM AUTHOR]

The current energy structure of most economies must be upgraded to a renewable energy source (RES) to help mitigate ecological dilapidation and achieve sustainable development goals. The transition to RES has recently received attention from energy experts, international bodies and environmental scientists. However, there is contrasting evidence on what factors affect the evolution and deployment of RES, especially from the perspective of emerging African economies. Hence, the current analysis sought to explore the influence of economic development (ECD), carbon emission (CEM), human capital (HUC), financial development (FID), and the country's risk factors, such as political risk (POR) and institutional quality (INQ) on the development of RES. The research employed a panel dataset from 1990 to 2020 and used the newest estimation approach of Cross-Sectional Augmented autoregressive Distributed Lag (CS-ARDL) to establish the long-run connection among the variables. The study confirmed the prevalence of the "energy-led ECD hypothesis". In addition, the empirical findings indicated that RES deployment could be facilitated through ECD, CEM, FID and HUC. Moreover, the country's risk factors, which include POR and INQ, had an inverse connection with the deployment of RES. Lastly, there is a unidirectional causality between CEM, FID, HUC, INQ and RES, while a directional causality exists between ECD, POR and RES. The paper highlights a variety of policy angles to help with the expansion of RES in emerging regions. • The study confirmed the prevalence of the "energy-led ECD hypothesis. • RES deployment could be facilitated through ECD, CEM, FID and HUC. • POR and INQ, had an inverse connection with the deployment of RES. • A directional causality exists between ECD, POR and RES. [ABSTRACT FROM AUTHOR]

In bioarchaeology, the biometry of archaeozoological remains is an important component of studies on domestic species and size has been used for multiple purposes from identifying domestication, to track environmental changes or evolution of husbandry practices. The establishment of the Roman Empire has been accompanied by social, political and economic transformations that also reflect in farming practices and animal husbandry. In southern France, biometric variation has already been partially perceived during Roman times, particularly for cattle, but lack chronological accuracy and statistical validation. This paper presents a diachronic analysis of linear measurements of post-cranial bones belonging to the domestic triad (sheep, goat, cattle and suids) in western Gallia Narbonensis (France), between the Roman conquest and Late Antiquity, i.e. from 200 BCE to 400 AD. Biometric data from 64 archaeological sites, excavated and studied over more than 30 years of preventive archaeology, were analysed using a Log Size Index (LSI) approach using time as a continuous variable. The analysis of 5533 measurements first analysed per bone and variable, then separating length, breadth and depth dimensions, revealed different trends, highly influenced by the number of measurements, reflecting allometric differences but also cases of asynchronous evolution. However, these allometries within species are small when compared to interspecies differences. Overall, the size of the four taxa increased from the 2nd century BC to the 2nd century AD. Cattle and pig sizes then decreased from the 2nd century AD and only from the 4th century onwards for goats, while sheep size tends to increase during the 3rd-4th centuries. If the Roman conquest influences the size of the domestic animals, this does not affect the four species in the same way. This potentially reflects differentiated agropastoral strategies for each of the species in the western part of Gallia Narbonensis during the Roman period. This study, which provides a diachronic and cross-species study framework, should be seen as a first step for a more in-depth understanding of micro-regional and socio-economic variation in domestic species morphologies. [ABSTRACT FROM AUTHOR]

This paper investigates the heterogeneous, long, and short-run and causal relationship between the size of the informal economy and three usual variables related to each of the most important theoretical approaches on informality, namely, the dualist, legalist, and structuralist view. Specifically, we consider GDP per capita, institutional quality and trade openness. We explore this relationship, using novel econometric techniques such as CS-ARDL panel data approach to analyses a sample of 133 countries over the period 1995 to 2017. The results show a long-run relationship between the variables at the global level and by country group. GDP per capita, institutional quality and trade openness are negatively associated with the size of the informal economy. The signs confirm the dual and legal hypothesis; however, the sign is opposite to that suggested by the structuralist hypothesis. Additionally, we obtain a U-shaped relationship between the size of the informal economy and the level of economic development. This means that the informal economy does not tend to disappear in the long run. In terms of policy implications, we provide support about the effectiveness of GDP per capita, institutional quality and trade openness in diminishing the size of the informal economy. Nevertheless, based on our results of a U-shaped relationship between informality and GDP per capita, public policy should be designed conditional on the level of development of a certain country. [ABSTRACT FROM AUTHOR]

• Urban green spaces have direct and indirect effects on improving residents' health. • The health benefits of urban green spaces exhibit regional heterogeneity. • Economic development weakens the health benefits of urban green spaces. • Environmental regulations can enhance the health benefits of urban green spaces. Urban green spaces have long been cherished as the "lungs of the city", it can not only improve air quality and enhance residents' health. The impact of urban green spaces on air pollution and residents' health has attracted great attention. In this paper, we select 31 provinces in China as research samples and use ArcGIS software to draw spatial distribution maps of urban green spaces, air pollution, and residents' health in China, characterizing their spatiotemporal changes in order to explore whether there is a correlation among the three. On this basis, this paper utilizes panel data of Chinese provincial-level from 2010 to 2020 and conducts empirical tests through a two-way fixed effect model and a threshold regression model. The research findings are as follows: (1) Urban green spaces not only bring environmental benefits, but also health benefits, and the health benefits are greater than the environmental benefits. (2) There is a health risk of air pollution in northern China, and the health benefits of urban green spaces are not significant. Conversely, there is no health risk of air pollution in southern China, and the health benefits of urban green spaces are significant. (3) Although environmental regulations can enhance the health benefits of urban green spaces, the role of environmental regulations in enhancing the health benefits of urban green spaces may be further weakened as the economy develops. [ABSTRACT FROM AUTHOR]

In the decade passed, considerable affords were made to develop effective trading systems based on different assumptions concerned with the market nature, methods for data processing and uncertainty modeling. Such systems are often so sophisticated that they can be applied only by their authors. Another limitation of them is concerned with the focus on the development of a universal single best model. Besides, any model works well only in limited time periods and fails when noticeable changes in the market behavior occur. Then a major revision or the development of a new model is inevitable. Unfortunately, usually this needs too much time. Therefore, in this paper, to avoid the above problems, the simple multi-model approach to the development of trading systems in the Forex market is proposed. It is based on some working hypotheses, which are justified in this paper. The first of them is based on the observation that the Forex is the aggregation of numerous streams (strategies) provided by the broad trades community. Therefore, we can expect that even a very simple model based on the particular trading idea or ideas may catch such a string to be profitable, at least during a small period. If we have developed a set of such simple models optimized for different currency pairs, in each trading period we can use the model providing maximal profit for a certain currency pair. The profitability of the proposed approach is illustrated by the trading results obtained on the symbols EURUSD,GBPUSD, AUDUSD and USDJPY for the timeframes H1 and H4 with the use of the Meta Trader 4 platform. • Technical analysis indicators and trading rules. • Positive and Negative Overfitting effects. • Algorithmic trading systems and their open access software. • Multi-model based trading strategy and the leader correction method. • Forex market and trading platform. [ABSTRACT FROM AUTHOR]

Improving the labor reallocation effect can promote the transformation of the driving force of economic growth and enable high-quality development. Therefore, this study constructs a growth source model from the perspective of human capital, considering labor price distortion and time-varying factor elasticity to measure the effect of labor reallocation under the crossover of provincial industries and analyze the impact of labor reallocation on employment share. The relevant findings are threefold. Aoki (2012)) The distortion of labor price is the largest in the primary industry, followed by the tertiary and secondary industries. Bai and Liu (2018)) Measuring the labor reallocation effect from the perspective of human capital allocation reveals a 3.7 % overall loss of the effect under allocation distortion compared with that under effective allocation. Bakas et al. (2017)) In terms of industrial structure adjustment, compared with the labor share under effective allocation, that of the primary industry still requires a 0.25 reduction, and that of the secondary and tertiary industries should be reduced by 0.07 and 0.18, respectively. The research results provide valuable insights for Chinese policymakers to further improve the market economy system and adjust the industrial structure to optimize resource allocation and advance economic growth. • This paper relaxes the constant factor output elasticity hypothesis in the multi-sector general equilibrium model proposed by Aoki, and introduces the time-varying elastic production function model to re-measure the labor reallocation effect of industries in China's provinces. • Unlike the existing studies, which mostly measure the factor mismatch of provinces or industries, this paper measures the labor reallocation effect under the industrial intersection of China's provinces. • From the perspective of factor measurement, considering the heterogeneity of labor quality, the effect of labor reallocation is measured from the perspective of human capital allocation. [ABSTRACT FROM AUTHOR]

Over the past decades, microfinance has become a pillar of economic development policies. However, despite the great popularity of micro-credit programs, the results of empirical studies are mixed. Thus, more research is needed to help us understand how effective microfinance is in achieving poverty reduction, economic development, and financial inclusion. This paper contributes to the literature by relying on a unique dataset from one of the biggest Fintech companies in Brazil to study the impact of microcredit on small firms' outcomes. Using a difference-in-difference approach, we find that access to credit increases monthly revenues and profits by nearly 4.5%. We show that the effects are stronger for women-led businesses and less experienced entrepreneurs. In addition, we find that credit renewal strengthens the benefits of credit access. We discuss several policy implications from our results. In particular, the permanent availability of credit – as opposed to one-time/short-term interventions -- has greater potential to generate virtuous cycles of ever more reinvestment and growth, indicating larger gains from relaxing borrowing constraints in the long run. [ABSTRACT FROM AUTHOR]

By considering the significant role economic growth has played in environmental function between 1990 and 2019, this paper examines the relationships between renewable energy development, trade openness, and institutional quality in the development of green finance in South Asian countries. The effectiveness of institutions and trade transparency are factors in green finance. We use a panel data model to ascertain the cointegration among the variables. The study employs the OLS fixed pool method along with a quantile regression to assess the model and reveal that, although growth in renewable energy development and trade openness worsen the ecological environment, institutional quality and the use of renewable energy promotes green finance development. The findings indicate that trade openness and institutional quality have a positive link with green financing. Institutional quality drives the use of renewable energy, whereas gross domestic product (GDP) drives the environmental impact. In light of these findings, policymakers can put in place beneficial policies for renewable energy development as an economic instrument to minimize ecological footprints and enhance green finance development. • Trade openness. • Renewable energy development. • Green finance. • Institutional quality. [ABSTRACT FROM AUTHOR]

Currently, China is at a critical stage of economic transformation and pollution control. The environmental pollution control efficiency (PCE) deserves more in-depth study. This paper adopts a three-stage global data envelopment analysis (DEA) model and a global Malmquist index model to measure the PCE and the sources of its changes in China from 1991 to 2019. Study shows that: (1) the overall level of PCE has remained low over the past 29 years, and it has a slowly fluctuating upward trend, with an average annual growth rate of only 0.92 %; (2) the lower pure technical efficiency hinders the effectiveness of environmental pollution control, which is mainly affected by the slow technological progress; and (3) at the provincial level, the overall efficiency of Shanghai and Guangxi has long been above 0.9, while the efficiency of other provinces has been below 0.9 for quite a long time. At the regional level, the Yangtze River Delta is the most effective area, while the Yellow River Basin is the most ineffective area. In consideration of this, we provide specific strategies for improving PCE of each province, from three aspects of increasing the capital input, optimizing the scale structure, and upgrading technology level. [Display omitted] [ABSTRACT FROM AUTHOR]

The world is adjusting to regain control over direct economic impacts of the COVID-19 pandemic. This adjustment is occurring whilst global collective action is also gearing up to tackle climate change, avert biodiversity collapse and redress unsustainable growth practices that featured in pre-Covid era global economic activity for decades. COVID-19 pandemic experience since December 2019 has been a period of pronounced anxiety and inspiration. Despite the angst of widespread calamity, and the loss of over six million lives, a coordinated global effort helped contain the impacts well short of initial predictions. Progress toward eliminating poverty, the central goal in rural economic transformation, has been set back by decades. The strength in organising — through social and business processes — marked the resilience endured. The recovery is patchy and uneven across individual nations, and the medium-term prospects remain contingent on the efficacy of funding essential human services and clear market bottlenecks. Bridging capacity constraints across the rural–urban continuum also remain a need to ease the regulatory burden as the world tackles widespread externalities of the past to create new growth opportunities. In this special issue, emerging and established academics from the Asian region and beyond, 1 1 These papers were drawn from presentations made at a conference organised by the Asian Development Bank Institute on 'Rural economic transformation: embracing opportunities in better living in Asia' held during 15–17 November 2021. All contributors are from Asian Development Bank member nations. draw insights from research and analysis on the challenges facing policy makers, businesses, and households in raising living standards and inspiring the pursuit of individual and social affluence during these uncertain but opportune times. [ABSTRACT FROM AUTHOR]

The growing and expanding zone of the free-market economy results in increasing competition in the global market, which leads companies to seek and implement solutions that will give them a competitive advantage. The authorities of countries and regions are also increasingly involved in this process, seeing it as an opportunity to develop and build a knowledge-based economy. One of the main factors improving competitiveness and providing opportunities for development is innovation, particularly developed at the local level. For this reason, activities that support research and development of innovation at the regional level are increasingly appreciated and gain greater importance. This article refers to regional innovation in Poland by analyzing its level between 2010 and 2020. The basis of the analysis was 15 selected indicators characterizing three dimensions related to the innovative development of regions, namely innovative capacity, innovative position, and economic development. This assessment was regarded as a multi-criteria problem, for which the CODAS method was used. Its application made it possible to achieve the main objective of this paper, which was to determine the level of innovation of studied regions and, on this basis, to create their ranking. In addition, the evaluation of the level of innovation of the regions for each of the analyzed dimensions was also carried out, and the relationship between the level of economic development and the capacity and innovative position of the regions was specified. The measure for evaluating the level of innovation, for each case studied, was the value of the Hi index, taken as a synthetic measure of regional innovation. The results show that the level of innovation for the regions in Poland varies widely as a function of time as well as the location of these regions. Differences in the dynamics of change and different levels of development of the analyzed dimensions characterizing innovation are evident. The results provide new knowledge in the field of regional development and should be used when creating a regional development strategy for individual regions, Poland, and the EU. [ABSTRACT FROM AUTHOR]

This paper revisits the thesis of Levine (1991) on the positive contribution of the financial market on the rate of economic growth. According to the author, the stock market performs, because it facilitates the formation of capital by increasing the liquidity of the market. In contrast, the economy private financial markets would be less effective. Such a conclusion is yet far from obvious. From the model of Levine (1991), we examine the equilibrium proportion invested in high-return (illiquid) projects and we show that the self-financing economy can record a growth rate higher than that of the economy of financial markets. Regardless of the stock market, economic growth is related to the interactions between the aversion to risk and the parameters of the set of production. [ABSTRACT FROM AUTHOR]

Under the background of high-quality development, the e-commerce industry needs to seek more comprehensive development, and the logistics industry should not only maintain higher efficiency, but also meet the requirements of green and low-carbon transportation. This study aims to investigate the link between the logistic density and the proportion of e-commerce transaction scale. There are few studies on how logistics density affects the development of e-commerce quantitatively. In order to solve this gap, this study establishes an impact model of high-quality growth of e-commerce, and based on Solow production model, constructs a calculation method of logistics density, and analyzes the impact mechanism of logistics density on the scale ratio of e-commerce transactions. Using the bidirectional fixed effect model, this paper makes an empirical analysis of the panel data of 31 provinces consisting of 248 observations and autonomous regions in China from 2014 to 2020. The results show that logistic density has a positive and significant impact on the growth of e-commerce, thus promoting the optimization of economic structure. The acceleration of logistics density decreases the expansion of the ecommerce. Finally, there are obvious regional differences between the development of e-commerce and logistics infrastructure in China. Finally, based on the empirical result, this paper puts forward recommendations for government and companies. [ABSTRACT FROM AUTHOR]

Roughly 3 billion citizens remain offline, equating to approximately 40 percent of the global population. Therefore, providing Internet connectivity is an essential part of the Sustainable Development Goals (SDGs) (Goal 9). In this paper a high-resolution global model is developed to evaluate the necessary investment requirements to achieve affordable universal broadband. The results indicate that approximately $418 billion needs to be mobilized to connect all unconnected citizens globally (targeting 40–50 GB/Month per user with 95 percent reliability). The bulk of additional investment is for emerging market economies (73 percent) and low-income developing countries (24 percent). To our knowledge, the paper contributes the first high-resolution global assessment which quantifies universal broadband investment at the sub-national level to achieve SDG Goal 9. • Over one third of the global population remain unconnected. • A high-resolution global model is developed to evaluate necessary broadband investment. • $418 billion needs to be mobilized to connect all unconnected citizens globally. • The baseline targets 40–50 GB/Month per user with 95 percent reliability. • Universal broadband assessments must be explicit about capacity and Quality of Service. [ABSTRACT FROM AUTHOR]

• GIS grid technology can monitor the EEQ of industrial park. • Environmental planning and design of industrial park can better address pollution issues. • The EKC and CCD models provide insight into the synergy between EEQ and ED. Industrial Park is a part of urban development and plays an indispensable role in promoting regional economic development. However, the high consumption of resources and the concentrated emission of pollution pose a great threat to the ecological balance and human health. Therefore, the future of industrial park needs to be balanced with economic growth while realizing resource conservation and environmental improvement as much as possible. However, there is still a research gap in analyzing the relationship between ecological environment quality (EEQ) and economic development (ED) at the industrial park scale. This paper first constructs the new remote sensing ecological index (RSEInew) model to measure the EEQ of Suzhou Industrial Park (SIP) from 2000 to 2020. Then this study constructs an ED index system to evaluate its economic situation. Finally, this paper utilizes the Environmental Kuznets Curve (EKC) model and the coupled coordination degree (CCD) model to deeply analyze the relationship between EEQ and ED. The results show that: (1) The average annual growth rate of EEQ in SIP is −1.50 %, with a general downward trend. Over the past 20 years, the ecological environment of SIP has not deteriorated extensively. (2) The ED of SIP is steady and rising, with an average annual growth rate of 10.17 %. (3) From 2000 to 2020, the EKC between EEQ and the ED of the SIP takes on an inverted "N" shape, with its CCD rising from barely coordinated to highly coordinated. This study can provide a reference for studying the quality development of areas at the industrial park level. [ABSTRACT FROM AUTHOR]

In the digital era, digitalization brings great opportunities and challenges for cities' environmental governance and economic growth. However, it is worth noting that the impact of digitalization on cities' green transition has not been studied from the perspective of Metcalfe's Law. This paper uses the principal component method and non-radial directional distance function (NDDF) to calculate the digital development level and the green economic performance of 269 Chinese cities from 2003 to 2019. (1) The empirical findings demonstrate that digitalization has become a strong driver for cities' green economic transformation. (2) Digitalization indirectly promotes green transition through industrial structure optimization and green technological innovation. (3) The heterogeneity results show that the positive effect of digitalization on green development is more obvious in eastern and economically developed cities. (4) Using the partially linear functional-coefficient model (PLFC), this paper studies the non-linear nexus between digitalization and green economic transition from the perspective of Metcalfe's Law. Thus, Metcalfe's law is confirmed in the green transition of Chinese cities. Some policy recommendations are offered for realizing the coordinated development of digitalization and greening of the urban economy. [ABSTRACT FROM AUTHOR]