Recent Developments and Challenges in Projecting the Impact of Crop Productivity Growth on Biodiversity Considering Market-Mediated Effects.

The effect of an increase in crop productivity (output per unit of inputs) on biodiversity is hitherto poorly understood. This is because increased productivity of a crop in particular regions leads to increased profit that can encourage expansion of its cultivated area causing land use change and ultimately biodiversity loss, a phenomenon also known as "Jevons paradox" or the "rebound effect". Modeling such consequences in an interconnected and globalized world considering such rebound effects is challenging. Here, we discuss the use of computable general equilibrium (CGE) and other economic models in combination with ecological models to project consequences of crop productivity improvements for biodiversity globally. While these economic models have the advantage of taking into account market-mediated responses, resource constraints, endogenous price responses, and dynamic bilateral patterns of trade, there remain a number of important research and data gaps in these models which must be addressed to improve their performance in assessment of the link between local crop productivity changes and global biodiversity. To this end, we call for breaking the silos and building interdisciplinary networks across the globe to facilitate data sharing and knowledge exchange in order to improve global-to-local-to-global analysis of land, biodiversity, and ecosystem sustainability.

Efficiency and productivity gains of robotic surgery: The case of the English National Health Service.

This paper examines the effect of new medical technology (robotic surgery) on efficiency gains and productivity changes for surgical treatment in patients with prostate cancer from the perspective of a public health sector organization. In particular, we consider three interrelated surgical technologies within the English National Health System: robotic, laparoscopic and open radical prostatectomy. Robotic and laparoscopic techniques are minimally invasive procedures with similar clinical benefits. While the clinical benefits in adopting robotic surgery over laparoscopic intervention are unproven, it requires a high initial investment cost and carries high on-going maintenance costs. Using data from Hospital Episode Statistics for the period 2000-2018, we observe growing volumes of prostatectomies over time, mostly driven by an increase in robotic-assisted surgeries, and further analyze whether hospital providers that adopted a robot see improved measures of throughput. We then quantify changes in total factor and labor productivity arising from the use of this technology. We examine the impact of robotic adoption on efficiency gains employing a staggered difference-in-difference estimator and find evidence of a 50% reduction in length of stay (LoS), 49% decrease in post-LoS and 44% and 46% decrease in postoperative visits after 1 year and 2 years, respectively. Productivity analysis shows the growth in radical prostatectomy volume is sustained with a relatively stable number of urology surgeons. The robotic technique increases total production at the hospital level between 21% and 26%, coupled with a 29% improvement in labor productivity. These benefits lend some, but not overwhelming support for the large-scale hospital investments in such costly technology.

Climate risk and green total factor productivity in agriculture: The moderating role of climate policy uncertainty.

In light of the escalating global warming and the escalating frequency of extreme weather events, the agricultural sector, being a fundamental and pivotal industry worldwide, is encountering substantial challenges due to climate change. Using Chinese provincial panel data for 2000-2021, this paper utilizes a two-way fixed-effect model to investigate the impact of Climate Risk (CR) on green total factor productivity in agriculture (AGTFP), with China's climate policy uncertainty (CPU) being introduced as a moderating variable within the research framework to scrutinize its influence in this context. The findings reveal a noteworthy adverse effect of CR on AGTFP, further exacerbated by CPU. Heterogeneity analysis results show that there is a clear regional variation in the effect of CR on AGTFP across different Chinese regions, with CR significantly inhibiting AGTFP development in the northern regions and provinces in major grain producing regions. Consequently, there is a pressing necessity to bolster the establishment of climate change monitoring infrastructures, devise tailored climate adaptation strategies at a regional level, and enhance the clarity and predictability of climate policies to fortify the resilience and sustainability of agricultural production systems.

The impact of urbanisation on green total factor productivity: Exploring threshold and mediating effects of human capital.

Green development is main direction of high-quality economic development in China. Urbanisation and human capital (HC) are important factors affecting green development. This study examines effects of urbanisation and HC on green total factor productivity (GTFP) using least squares dummy variable model, based on provincial data in China from 2001 to 2019. This study then explored impact of urbanisation on GTFP through HC (educated HC, healthy HC, and HC structure), adopting mediating effect and threshold effect model. The results showed that urbanisation and three types of HC promote GTFP in China and coastal region. In inland region, urbanisation has insignificant impact on GTFP, while educated HC and HC structure improve it. The mediating analysis revealed that educated and healthy HC in China and coastal region enhance promotion effect of urbanisation on GTFP, whereas HC structure hinders it. In inland region, only healthy HC stimulates promotion effect of urbanisation on GTFP. Considering threshold effect of educated and healthy HC, promotion effect of urbanisation on GTFP is weaker than threshold value; but effect is stronger above threshold value. The promotion effect of urbanisation on GTFP is stronger when value of HC structure is below the threshold, while effect is weakened as value exceeds threshold value. Policy implications are documented to promote urbanisation in a differentiated manner, increase investment in HC, and strengthen coordination between urbanisation and HC.

Which productivity can promote clean energy transition -total factor productivity or green total factor productivity?

Developing clean energy is a key pathway and an inevitable choice for achieving the goals of carbon peak and carbon neutrality. From a global perspective, technology is increasingly affecting the trajectory of energy transition, driving clean energy into a stage of rapid development. Therefore, this paper focuses on exploring the dynamic evolutionary characteristics of clean energy transitions driven by different productivity. Using panel data from 171 economies from 1990 to 2019, this paper systematically examines the impact of Total Factor Productivity (TFP) and Green Total Factor Productivity (GTFP) on clean energy transitions. The empirical results indicate that both TFP and GTFP positively impact clean energy transition. Specifically, clean energy consumption increases by 3.35% and 6.03%with a one standard deviation change in TFP and GTFP respectively. Upon decomposing TFP and GTFP, it was found that Green Efficiency Change (GECH) and Green Technical Change (GHCH), especially GECH, are the main factors driving the clean energy transition. Heterogeneity analysis shows that, in developed economies, GTFP has a larger positive impact on clean energy transition than TFP. Furthermore, GTFP demonstrates a significant positive impact on the clean energy transition both before and after the 2008 financial crisis, whereas TFP's positive impact is only evident before the crisis. Our findings emphasize the social benefits of further investments in GTFP.

The impact of digital economy on carbon total factor productivity: A spatial analysis of major urban agglomerations in China.

Amid global climate imperatives and intensified economic competition, pivoting from China's conventional growth paradigms to innovative economic catalysts emerges as pivotal for its transformative agenda. Drawing on panel data from 141 principal urban conglomerates spanning 2011-2021, this investigation delves into the intricate nexus between the digital economy and carbon total factor productivity. Our empirical analysis unveils a U-shaped trajectory characterizing the digital economy - carbon total factor productivity interplay, accompanied by a congruent spatial spillover dynamic. While digital economy fortifies environmental governance mechanisms through amplified data and media channels, such regulatory frameworks, albeit efficacious in emission abatement, may inadvertently impede economic vitality, thus attenuating carbon total factor productivity. Progressing from digital economy's foundational phase to its comprehensive deployment, its reverberations on capital productivity manifest in a U-shaped curve, invigorating local carbon total factor productivity while potentially undermining adjacent regions. This digital economy - carbon total factor productivity interrelation is accentuated in advanced, non-resource-reliant metropolises with subdued innovation propensities. This discourse proffers nuanced policy implications for sculpting digital economy trajectories and bolstering carbon total factor productivity in a sustainable context.

Exploring the dual impact: Dissecting the impact of tourism agglomeration on low-carbon agriculture.

Despite extensive research on the relationship between tourism and agriculture, the specific impact of tourism on agriculture's low-carbon transition has not been thoroughly investigated. This study analyzes the effects of tourism agglomeration on agricultural carbon intensity across 30 Chinese provinces from 2001 to 2020. It is framed within the context of rural digitalization, with a particular emphasis on the integration of agro-tourism and the total factor productivity of agriculture. Utilizing spatial econometric models, we find that tourism agglomeration hinders the low-carbon transition in agriculture by influencing carbon intensity both directly and indirectly. At the national level, the impact of tourism agglomeration follows an inverted-U curve with respect to agro-tourism integration and carbon intensity. At the regional level, the effects vary, with weaker indirect influences in major grain-producing areas. Furthermore, rural digitalization appears to lessen the adverse impacts of tourism on carbon intensity. This study also identifies significant spatial spillover effects from tourism agglomeration. The findings suggest that provinces with high tourist influx should enhance investments in climate-smart agricultural practices and technologies to counteract these negative impacts. Moreover, integrated governance of tourism and agriculture is essential for achieving carbon neutrality in both sectors.

Does government environmental attention drive green total factor productivity? Evidence from China.

Based on city-level panel data spanning 2008 to 2021, this study investigates the impact of government environmental attention (GEA) on green total factor productivity (GTFP). The findings suggest that increased GEA substantially enhances the growth of GTFP. After conducting robustness and endogeneity tests, the study's results consistently show reliability and robustness. Further analysis elucidates several mechanisms through which GEA influences GTFP, including fostering green technology innovation, optimizing resource allocation, and promoting upgrades in industrial structure. Heterogeneity analyses reveal that the impact of GEA on GTFP is notably pronounced in eastern cities, as well as in cities characterized by low resource dependency, mature industrial development, and high market competition. Conversely, the influence of GEA on GTFP is less discernible in cities prioritizing economic development goals, possibly due to differing policy orientations and resource allocation strategies. This study offers a novel perspective on understanding how GEA shape green development and provides empirical support for policy formulation.

Can green credit policy with dual-carbon targets make highly polluting enterprises "green": A micro-analysis of total factor productivity growth.

Reducing carbon emissions from highly polluting enterprises is crucial to meeting the world's overall carbon emission reduction targets. Green credit policy can be effective in guiding enterprises to reduce their carbon emissions and is essential to achieving the dual-carbon targets. This study uses micro-data from a 2017-2022 follow-up survey of industrial enterprises in China and a quasi-natural experiment to evaluate whether green credit policy aligned with the dual-carbon targets enable highly polluting enterprises to become "green" by reducing emissions. The results show that green credit policy can lead highly polluting enterprises to significantly reduce carbon emissions, and total factor productivity (TFP) growth plays an intermediary role in this transition. The different impact of green credit policy on TFP may impede the greening process for highly polluting enterprises, with this hindering effect exhibiting scale heterogeneity. This study offers empirical evidence for evaluating green credit policy aligned with China's dual-carbon target and provide insights into leveraging green credit policy to advance this process.

How does artificial intelligence affect the transformation of China's green economic growth? An analysis from internal-structure perspective.

Artificial intelligence (AI) has been proved to be an important engine of green economic development, yet how it will affect the internal structure of green economy is unknown. The aim of this study is to examine the impact and its mechanism of AI on green total factor productivity (GTFP) from the internal-structure perspective, by using provincial panel data of China from 2009 to 2021 and global Malmquist index. The main research results show that: (1) the development of AI contributes to China's GTFP growth. And this effect is more significant in undeveloped areas; (2) AI promotes China's GTFP growth mainly by improving resource allocation efficiency, while it exerts little impact through the paths of technological progress and scale efficiency; (3) the transmission mechanism of AI on GTFP varies greatly among China's three main regions. In the eastern region, AI improves GTFP mainly by both advancing technological progress and improving resource allocation efficiency, while in central region AI contributes to GTFP growth mainly through technological progress. Compared with the eastern and central regions, AI in the western region plays a stronger impact on GTFP through the channel of improving scale efficiency. This study helps to understand the pathways of artificial intelligence affecting the transformation of green economic growth and formulate differentiated regional policies in light of local conditions.

Do renewable energy, environmental regulations and green innovation matter for China's zero carbon transition: Evidence from green total factor productivity.

Rapid developments in environmental infrastructure have contributed to significant improvements in green total factor productivity, but further investigation is required to provide a detailed assessment to understand the policy mechanisms involved. This paper analyzes environmental progress in China through MMQR, CCEMG, and AMG as empirical strategies for 30 provinces in China. Our empirical results reveal that energy optimization through renewable energy is the most effective channel to improve green total factor productivity, though it is not the only available option. Since environmental regulations, infrastructure development, and green technology innovation also directly impact energy efficiency, adopting these within policy channels will positively impact environmental sustainability. Our empirical approach helps suggest novel environmental policy suggestions. In particular, policymakers must introduce structural changes within energy developments to foster renewable energy. Furthermore, China must increase environmental spending to upgrade its energy infrastructure further and solve ecological issues. These insights offer valuable policy guidance for decision-makers in China and globally, aiming to foster economic and environmental sustainability and achieve zero-carbon transition goals.

From bits to green: Unraveling the digital economy's influence on natural resource efficiency.

This study explores the impact of the digital economy (DE) on natural resource efficiency (NRE) across 275 Chinese cities between 2011 and 2021. Through a comprehensive empirical analysis, we find that the DE significantly positively affects NRE. A key moderating factor in this relationship is green technological innovation (GTI), focusing on the quality rather than the quantity of green technology. Our study also uncovers regional variations of moderating effect. Additionally, we identify several mechanisms through which the DE contributes to enhanced NRE, including the transformation of industrial structure and improvements in green total factor productivity. A detailed heterogeneity analysis shows that the DE's impact on NRE varies according to city-specific factors such as natural resource endowment, city size, environmental regulations, and administrative levels. These findings provide a more nuanced understanding of how the DE influences NRE at the urban level, contributing to the broader discourse on sustainable development in the digital age. Our research offers policy recommendations and potential pathways for cities to leverage the DE for greater natural resource efficiency.

Administration or marketization: Environmental regulation, marketization and agricultural green total factor productivity.

The mature market can effectively reflect the value of green agricultural products, but the market in developing countries is developing slowly, so how to implement administrative environmental policies while cultivating the market has become the key to the green development of agriculture. In this paper, the government and the market are discussed under the common goal of agricultural green development. Based on the provincial panel data of China, taking agricultural green total factor productivity (AGTFP) as a breakthrough point, the relationship between environmental regulation tools, marketization processes and agricultural green development, specific applicable conditions and transmission mechanisms are explored, and further subdivided into factor and product markets to verify their correlation with AGTFP. The results show that environmental regulation and marketization processes and AGTFP are positively correlated. The former can establish a positive relationship with AGTFP through resource reallocation and technological innovation, and the latter can do so by improving the level of information and land transfer and perfecting infrastructure construction. These findings will provide new ideas for developing countries similar to China's agricultural development and enlighten developing countries pay full attention to and cultivate the market while formulating appropriate environmental regulation policies. In addition, they also need to coordinate the development of technology and organizations.

Research on the impact of the national ecological demonstration zone on green total factor productivity: Evidence from China.

China is currently confronted with the dilemma of achieving its green development goals while maintaining economic growth. The National Ecological Demonstration Zones (NEDZs) represent an innovative attempt by local governments to balance economic development with ecological civilisation, potentially offering a solution to this issue. This study calculated the Green Total Factor Productivity (GTFP) for 1925 districts and counties from 1999 to 2018. Using the selection of NEDZs as a quasi-natural experiment, a difference-in-differences model was employed to empirically analyse the impact of NEDZs on GTFP. The results indicated that the establishment of NEDZs led to an average increase in GTFP of 0.2175 compared to the control group. The primary mechanisms involved are innovation, structure, and enforcement. Moreover, the green development effects of the NEDZs exhibited regional heterogeneity. Compared to the western regions, the central and eastern regions showed limited green development effects. Areas with smaller populations, lower human capital, and lower administrative levels demonstrated significant improvements after the implementation of the NEDZ. Further analysis reveals a significant spatial agglomeration pattern of GTFP and the NEDZs exert a strong 'siphon effect' on the GTFP of neighbouring areas. This study provides a new perspective on the GTFP research and offers theoretical and practical evidence for assessing the impact of NEDZs.

Going green while getting lean: Decomposing carbon and green total factor productivity.

While research on carbon productivity is growing rapidly, the role of structural change in green transition remains unexplored due to the scarcity of firm-level emission data. This study addresses this gap by utilizing unique register-based greenhouse gas emission data from Finland's energy-intensive manufacturing firms for 2000-2019. Applying a structural change productivity decomposition, we break down the sector's carbon productivity and green total factor productivity into four components: contributions from non-switching continuing firms, industry-switching continuing firms, the effects of entry and exit, and resource allocation. The findings highlight the important role of structural change in the sector's productivity. Non-switching continuing firms emerged as the key drivers of both carbon and green total factor productivity growth. The contribution of entry and exit was negative during the financial crisis, while inefficient resource allocation significantly hindered productivity growth throughout the study period. These findings emphasize the importance of public subsidies targeted at environmentally efficient firms to enhance their competitiveness under challenging market conditions. Furthermore, the establishment of a stable yet positive carbon price would incentivize less-productive firms to adopt environmentally friendly technologies.

The role of renewable energy and total factor productivity in reducing carbon emissions: A case of top-ranked nations in the renewable energy country attractiveness index.

On the one hand, economies, particularly developing ones, need to grow. On the other hand, climate change is the most pressing issue globally, and nations should take the necessary measures. Such a complex task requires new theoretical and empirical models to capture this complexity and provide new insights. Our study uses a newly developed theoretical framework that involves renewable energy consumption (REC) and total factor productivity (TFP) alongside traditional factors of CO2 emissions. It provides policymakers with border information compared to traditional models, such as the Environmental Kuznets Curve (EKC), being limited to income and population. Advanced panel time series methods are also employed, addressing panel data issues while producing not only pooled but also country-specific results. 20 Renewable Energy Country Attractiveness Index (RECAI) nations are considered in this study. The results show that REC, TFP, and exports reduce CO2 emissions with elasticities of 0.3, 0.4, and 0.3, respectively. Oppositely, income and imports increase emissions with elasticities of 0.8 and 0.3. Additionally, we show that RECAI countries are commonly affected by global and regional factors. Moreover, we find that shocks can create permanent changes in the levels of the factors but only temporary changes in their growth rates. The main policy implication of the findings is that authorities should implement measures boosting TFP and REC. These factors are driven mainly by technological progress, innovation, and efficiency gains. Thus, they can simultaneously reduce emissions while promoting long-run green economic growth, which addresses the complexity mentioned above to some extent.

Information disclosure, multifaceted collaborative governance, and carbon total factor productivity-An evaluation of the effects of the 'environmental information disclosure pilot' policy based on double machine learning.

As an environmental institutional arrangement related to the information factor of the diversified participation of the government, enterprises, the media and the public, the environmental information disclosure pilot policy, can and how to affect the carbon emission efficiency through multiple collaborative governance? This study uses the Environmental Information Disclosure Pilot Policy implemented in China in 2007 as a quasi-natural experiment. It examines 284 prefecture-level cities from 2004 to 2021 and A-share listed companies from 2004 to 2021, constructing an evolutionary game dynamic model involving government, public, enterprises, and media. Through mathematical derivation and assignment analysis, it explores how environmental information impacts carbon emission efficiency under multifaceted collaborative governance, assessing the strategic choices and evolutionary paths of stakeholders before and after policy implementation, using methods like double machine learning for empirical testing. The study highlights several key findings: First, the implementation of the Environmental Information Disclosure Pilot Policy significantly enhanced carbon total factor productivity in pilot cities, as revealed through Double Machine Learning (DML) policy effect evaluation. Second, adjustments for potential estimation biases using Doubly Debiased LASSO (DDL) regression indicated that environmental information disclosure impacts carbon productivity via a governance mechanism involving government, public, media, and enterprises. Third, a causal pathway analysis suggested a sequential logic in governance effectiveness, starting from governmental environmental focus to corporate environmental responsibility. Lastly, integrating DML with a moderation effect model revealed a regulatory role for environmental legislation construction, offering new insights for achieving dual carbon goals and enriching empirical evidence on information's impact on carbon emission efficiency.

Does the integration of digital and real economies promote urban green total factor productivity? Evidence from China.

Enhancing urban green total factor productivity (UGTFP) is of great significance in driving the green transformation of cities. The integration of the digital economy and real economy (IDR) offers a novel approach to improving UGTFP. This paper constructs a theoretical analytical framework to examine the impact of IDR on UGTFP. Utilizing a range of econometric models and Chinese urban data, this paper empirically analyzes the influence, mechanism, and spatial spillover effect of IDR on UGTFP. The findings reveal that China's IDR is currently at a stage of low integration, exhibiting significant regional disparities, with a spatial distribution pattern declining from east to west. IDR can significantly enhance UGTFP, and the conclusion is supported by robustness tests. Heterogeneity analysis indicates that the positive effect of IDR on UGTFP is more pronounced in the eastern and western regions, as well as in areas with a large Internet scale. The mechanism test suggests that economic agglomeration can significantly amplify the promotional effect of IDR on UGTFP. IDR can boost UGTFP by elevating innovation levels and optimizing labor resource allocation. Further exploration reveals a significant positive spatial spillover effect of IDR on UGTFP. These insights not only offer a practical pathway for green transformation but also provide empirical evidence for policymakers to formulate scientific policies, enhance coordination, and improve data governance, thereby facilitating high-quality and green economic development.

How does digital inclusive finance affect the ecological environment? Evidence from Chinese prefecture-level cities.

Digital inclusive finance (DIF) is playing an increasingly prominent role in green development. This study analyses the ecological effects generated by DIF and its mechanism of action from the perspectives of emission reduction (pollution emissions index; ERI) and efficiency gains (green total factor productivity; GTFP). Using panel data from 285 cities in China from 2011 to 2020, we empirically test the effects of DIF on ERI and GTFP. The results reveal a significant dual ecological effect of DIF in terms of ERI and GTFP, but there are differences in the various dimensions of DIF. Influenced by national policies, DIF produced more substantial ecological effects after 2015, which are more pronounced in developed eastern regions. Human capital significantly enhances the ecological effects of DIF, and human capital and industrial structure are critical paths for DIF to reduce ERI and increase GTFP. This study provides policy insights for governments to leverage digital finance tools to advance sustainable development.

How does mandatory energy conversion affect sustainable development: Perspectives of regional heterogeneity and efficiency decomposition.

Clean energy conversion is a core approach and development trend to tackle climate change, while the severe drawbacks such as supply deficiency and cost increase restrict regional sustainable development. This paper employs a natural experiment of coal-to-gas conversion of the Chinese government to study the effect of such policy on regional sustainable development, as well as the underlying mechanism. Based on a city-level dataset from 2006 to 2019, this paper measure green total factor productivity (GTFP) using data envelopment analysis (DEA) combined with the Malmquist‒Luenberger productivity index. Then, this paper evaluates the impact of the CTG policy in pilot cities using the Difference-in-Difference (DID) with Propensity Score Matching (PSM) approach. This paper finds that the CTG policy increased the GTFP of the pilot cities by 2.25% (0.0229/1.02). A series of robustness tests confirmed the findings. Subsequent mechanism analysis shows that the CTG policy increases the GTFP of pilot cities mainly by increasing technical efficiency. In addition, the mechanism of the CTG policy's impact differs between central and noncentral cities. In particular, the CTG policy increases the technological innovation indicator (TC) of provincial capital cities by 2.35% while it increases the technical efficiency indicator (EC) of other cities by 1.89%, which proves the Porter effect in provincial capital cities. Finally, several implications are provided for policymakers to promote other types of renewable energy.