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We investigate the labor market effects of a loan guarantee program targeting French SMEs during the financial crisis. Exploiting differences in regional treatment intensity in a border discontinuity design, we uncover a central trade-off for such interventions. While the program has a positive impact on workers' employment and earnings trajectories that translates into positive aggregate employment effects, it dampens the worker reallocation toward more productive firms that happens following recessions, and particularly so for high-skill workers. This labor allocation effect is economically significant and translates into a reduction in aggregate productivity. [ABSTRACT FROM AUTHOR]

We find firm-level evidence that removing labor market rigidities can harm productivity growth. This holds, in particular, in industries with a high 'cumulativeness' of knowledge, i.e. when accumulation of worker-embodied (and often 'tacit') knowledge from experience is important for innovative competencies. We conclude that there is a trade-off between the efficient allocation of scarce resources in a static neoclassical perspective and dynamic Schumpeterian efficiency, the latter requiring rigidities in labor markets that are valuable for innovation. [ABSTRACT FROM AUTHOR]

This paper evaluates the productivity impacts and the subsequent adjustment costs associated with hiring different knowledge workers. I focus on the difference between hiring former entrepreneurs, employees who change jobs, and unemployed individuals. I am the first to evaluate the direct impact that hiring former entrepreneurs has on firm productivity and the heterogenous adjustment costs associated with the different types of new hires. I find no difference between the first-year adjustment costs of entrepreneurs and those of regular-wage employees. Hiring former entrepreneurs is a way to increase productivity after the first year of employment only if the former entrepreneurs are from the highest end of the ability distribution. [ABSTRACT FROM AUTHOR]

The diffusion of knowledge is an important determinant of economic development. International trade has been established as a key mechanism in facilitating diffusion. The rise of global value chains (GVCs) has transformed trade in recent years. Yet the role of GVCs in giving rise to knowledge spillovers remains under-explored. In this paper, we study the elasticity of industry-level total factor productivity (TFP) to technology that is imported through intermediate trade in GVCs. To do so, we combine novel input–output decomposition methods with recent insights from the literature on the factor content of trade. We focus on a panel of 32 countries and 39 sectors over the 2000–2014 period using WIOD and OECD data. We find that domestic TFP is elastic to knowledge flows arising from GVCs and that the magnitude of this effect is larger relative to all other knowledge flows. We also find that GVC participation is particularly conducive to technology upgrading in countries that are far away from the technology frontier, and that GVC-related spillovers persist over large geographical distances. [ABSTRACT FROM AUTHOR]

I examine whether competition from domestic industry rivals affects firms' proclivity to undertake foreign direct investment (FDI) and their country location choices. I find that competition affects foreign production decisions and the geography of international investments. While firms enduring stiffer competition are significantly less likely to undertake FDI, this effect is heterogeneous across firms. Competition deters FDI more strongly when costs are heavier, whereas it has weaker effects when efficiency is higher, growth opportunities are valuable, and cash reserves are higher. FDI location models suggest that when going abroad, firms facing stronger competition are more likely to pursue economies of productivity and taxation. [ABSTRACT FROM AUTHOR]

This paper investigates the productivity effects for domestic suppliers from joining and exiting the value chains of foreign-owned multinational enterprises (MNEs). Our econometric analysis is based on firm-to-firm transactions recorded in the value-added tax declarations' data from Estonia and use of propensity score matching and difference-in-difference regression approach. The treatment analysis based on period 2015–2019 suggests that starting to supply the foreign-owned firms initially boosts the value added per employee of the domestic firms, including the effects on the scale of production and the capital–labor ratio. These first linkages to the foreign-owned MNEs do not affect the total factor productivity (TFP) of domestic firms, suggesting that the TFP effects take time to materialize. We find no significant positive effects on the second-tier suppliers: the positive effects are limited to the first-tier suppliers with direct links to foreign-owned firms. One novel result is the evidence that the productivity of suppliers does not fall, on average, after decreasing or ending supplier relationships with the foreign-owned firms. However, this average effect hides significant heterogeneity. Domestic firms with prior high levels of productivity and those at the time of exit from the MNE relationship start to export, gain in productivity in next periods, whereas the firms with low prior productivity levels lose. [ABSTRACT FROM AUTHOR]

Introduction: The rapid aging of the labor force has serious implications for socioeconomic development and poses challenges to food sustainability. Existing studies have focused on the impact of labor force aging on land productivity, but little attention has been paid to the comprehensive capacity of agricultural production, namely the total factor productivity of agriculture. Methods: We estimate the impact of labor force aging on total factor productivity in agriculture using data from 170,506 sample farm households from the National Fixed Point Survey data from 2003 to 2020. We estimate the results using a panel fixed effects approach and mitigate the endogeneity problem using an instrumental variables approach to ensure the robustness of the estimates. Results and discussion: The results show that labor force aging has an adverse effect on the agricultural total factor productivity of farm households and remains robust after addressing endogeneity and substituting explanatory variables. The aging effect shows significant heterogeneity across different food functional areas with different types of farm households. The negative impact of labor force aging on total factor productivity in agriculture is mainly concentrated in the main grain-production and grain-producing and marketingbalanced areas. We also find that the negative impact of labor force aging is more significant among large-scale farmers. The mechanism analysis finds that the aging of the labor force adversely affects the agricultural total factor productivity by inhibiting technological progress and reducing the efficiency of agricultural resource allocation. These insights, when considered in the light of global trends towards agricultural labor aging, suggest that policy interventions aimed at promoting technological adoption, enhancing resource allocation efficiency, and supporting the transitioning of older farmers may hold promise for maintaining food sustainability and addressing the challenges posed by an aging agricultural workforce in numerous developing nations. [ABSTRACT FROM AUTHOR]

This paper seeks to draw a research agenda for unveiling the underlying bottlenecks and possibilities for improving the agricultural total factor productivity in the European Union (EU). To this aim, the paper first surveys the key challenges for the modern agricultural economy. Then, the case of the EU is discussed by looking at the convergence in the partial productivity indicators (including the GHG emission) and growth efficiency that relate to the gap in the total factor productivity growth. The results suggest that the EU member states exhibited growth inefficiency (i.e., a gap in the total factor productivity growth) of 5–9% on average during 2004–2021. The paper also discusses the possibilities to utilize the production theory for assessing the pathways towards improvements in the productivity and sustainability of the EU agriculture. [ABSTRACT FROM AUTHOR]

This study investigates the impact of China's carbon emission trading (CET) framework on the green development of the construction sector, a topic that has been underexplored. Utilizing annual data from 107 publicly listed construction companies from 2007 to 2022, we apply green total factor productivity (GTFP) as a metric for green development. Our findings reveal that GTFP increased by 0.36 during this period. Using the Difference-in-Differences (DID) methodology, we account for factors such as market dimensions, ownership structure, financial stability, geographical location, and state financial aid. The interaction term coefficient in our model is 0.0089, significant at the 1% level, indicating that CET implementation has significantly improved GTFP in construction enterprises. Heterogeneity analysis further shows that the CET's impact is more pronounced in large-scale, state-owned, highly indebted enterprises, those located in the eastern region, and those receiving government subsidies, with coefficients of 0.112, 0.0108, 0.0092, 0.0133, and 0.0099, respectively, all significant at the 1% level. These results underscore the importance of unified market development and tailored governance strategies. The study concludes with policy recommendations and calls for further research to explore CET's nuanced impacts across different sectors and regions. [ABSTRACT FROM AUTHOR]

The power industry's low carbon transition is pivotal for achieving carbon reduction and sustainable development. This study uses the super epsilon-based measurement (Super-EBM) model and the Malmquist index to evaluate the power industry's low carbon transition efficiency using data from 30 provinces in China from 2010 to 2020, and utilizes the Tobit model to comprehensively analyze the factors affecting the low carbon transition of power industry. In addition, this paper examines the spatial differences in the power industry's low carbon transition efficiency as well as its distributional characteristics and dynamic evolutionary patterns. Conclusion is drawn as follows this paper analyzes the regional differences, spatial distribution characteristics and dynamic evolutionary trends of the power industry's low carbon transition. The main conclusions are as follows: (1) The power industry's low carbon transition efficiency in China shows an uptrend, with the western China region having the highest overall level of efficiency, greater fluctuations in the central China region, and more stability in the eastern China region, technological progress is a central factor in increasing total factor productivity, the efficiency of the power industry's low carbon transition is positively influenced by the electricity prices, and negatively influenced by the energy structure, environmental regulations and economic structure; (2) the Intraregional differences and hypervariable density are the main reasons sources of the overall differences in the efficiency of the power industry's low carbon transition; Intraregional differences in the eastern, central, and western China regions are decreasing year by year, but the efficiency of the power industry's low carbon transition in the western China region is still distributed in a multipolar way; (3) The dynamic evolutionary trends of the efficiency distribution of the low carbon transition in power industry is influenced by the type of spatial lag in the neighboring area. Where areas with low efficiency makes it difficult to achieve short-term leapfrog development, and areas with a cluster of high-efficiency provinces are prone to "Siphon Effect". The findings provide a theoretical basis for promoting the efficiency of the power industry's low carbon transition and coordinating the strategic adjustment of economic and environmental green development. [ABSTRACT FROM AUTHOR]

Pilot Free Trade Zones (PFTZs) are a crucial new platform for China to build a more open economic system. Existing literature primarily focuses on the 'Bring In' effect of PFTZs, often overlooking the importance of 'Going Out' aspects. To bridge this gap, this paper uses data from China's Shanghai and Shenzhen A-share listed enterprises from 2007 to 2021 and constructs a time-varying difference-in-differences (DID) model to test the impact of establishment of PFTZs on international expansion of enterprises. The study finds that establishment of PFTZs can significantly promote international expansion of enterprises, with a more pronounced effect on the scope of international expansion than on its depth. Mechanism analysis reveals that PFTZs can facilitate international expansion of enterprises by driving digital transformation, enhancing total factor productivity and management efficiency, and alleviating financing constraints. Notably, senior managers with overseas work experience play a crucial role in enhancing this relationship. Further, PFTZs not only have a linkage effect with the Belt and Road Initiative but also a radiation effect on neighboring cities. This study provides an analytical perspective and empirical evidence for evaluating policy effects of PFTZs and offers valuable insights that will enable PFTZ policies to be refined and facilitate successful implementation of the 'Going Out' strategy. [ABSTRACT FROM AUTHOR]

This paper studies the knowledge spillover effect through industrial correlation in the process of interregional textile industry transfer and its effects on the TFP of China's textile industry. The paper calculates the industrial similarity coefficients of subdivided industries with the textile industry and identifies the related industries of China's textile industry by using the data of China's input-output table and extension tables from 2002 to 2017. Then, the paper defines the industrial correlation spillover as the weighted sum of the indirect R&D investment of one industry from its related industries and constructs a quantitative method to qualify the industrial correlation spillover. Furthermore, the paper makes two empirical analyses on the existence of industrial correlation spillover in the interregional industrial transfer and its effects on productivity using the panel data of two-digit subdivided industries in 30 provinces. The results show that the correlation spillover effect does exist and promotes the interregional textile industry transfer from the eastern coastal region to the central and the northern-coastal regions; the correlation spillover from the related tertiary industries in industrial transfer promotes the TFP of China's textile industry, but the correlation spillover from the related secondary industries impedes the TFP of the textile industry. [ABSTRACT FROM AUTHOR]

The key to high-quality development in the textile and apparel industry lies in enhancing technological innovation and optimizing the efficiency of technological innovation. Based on data from 60 A-share listed companies in the textile and apparel sector in China from 2013 to 2022, this study employs a three-stage DEA model and the Malmquist index model to measure changes in technological innovation efficiency from static and dynamic perspectives. Additionally, it uses a Tobit model to analyze the impact and mechanisms of management and financial factors on technological innovation efficiency. The results indicate that: (1) Compared to the manufacturing industry and its sub-sectors, the overall technological innovation efficiency of listed textile and apparel companies was relatively low and showed a declining trend between 2013 and 2022; (2) Over the decade, the average total factor productivity of these listed companies increased by 1.7%, exhibiting a "W" shaped fluctuation, with technological progress, pure technical efficiency, and scale efficiency all showing weak improvement; (3) Management and financial factors significantly influence technological innovation efficiency. Specifically, employee quality, profitability, and operational capability are positively correlated with technological innovation efficiency and have long-term effectiveness, while firm age, management costs, equity concentration, development ability, and debt repayment capacity are negatively correlated with technological innovation efficiency; (4) Different types of enterprises show differences in the significance of management factors, while whether the same person holds both managerial positions significantly affects financial factors. [ABSTRACT FROM AUTHOR]

This study explored the impact of transportation systems in urban areas on economic activity. We examined the effect of traditional Chinese railway construction fencing on urban spatial development using nighttime luminance and railway data from prefecture‐level cities. The study found that the fencing effect exacerbated uneven development on either side of the railway, especially in economically underdeveloped areas. These results were supported by different measures of development and a placebo test. The fencing effect was also found to affect the location of newly registered firms and the total factor productivity of industrial firms, leading to unbalanced growth on either side of the railway. [ABSTRACT FROM AUTHOR]

In the context of the ongoing process of high-quality development in the new era, which is focused on improving total factor productivity, it is of great importance to explore the spatial and temporal variations of total factor productivity growth and its driving factors in China's county regions' grain cultivation industry. This paper employs a three-stage DEA-Malmquist productivity method, the Gini coefficient method, and a panel fixed-effects model to analyze data from Chinese counties between 2009 and 2019. The analysis indicates that the growth of county food total factor productivity (FTFP) exhibits a fluctuating upward trend during the examination period, with an average annual growth rate of 2.43%. This is primarily driven by technological progress, yet the core driving role of technological efficiency is not effectively played. The average annual growth rate of county FTFP varies across different regions. The highest average annual growth rate of county FTFP in the eastern region and the primary grain-producing area is 2.75 and 3.04%, respectively. The lowest growth rates were observed in the western region and the main grain marketing area, at 1.44 and 1.23%, respectively. Secondly, the Gini coefficient of county FTFP continues to demonstrate a persistent upward trend during the examination period, with an average annual growth rate of 14.729%. The primary factor contributing to the observed variation in total factor productivity growth of the food sector at the regional level is the existence of disparate technological progress. Thirdly, there is a notable positive correlation between county financial deepening and financial self-sufficiency rates and county FTFP growth, with impact coefficients of 0.0503 and 0.0924, respectively. Conversely, county population density, degree of economic development, farmers' income level, and industrial structure exert a significant negative influence on county FTFP growth and technological progress. [ABSTRACT FROM AUTHOR]

• Robot adoption led to a 10 % increase in productivity within China's manufacturing firms. • The impact was more pronounced in the first two years following adoption. • The impact was likely to be greater for small-size firms. • Multi-functional robots had more pronounced effects than single-functional ones. • Industry-city robot exposure had positive spillover effects on non-adopting firms. This study investigates the effect of industrial robots on firm productivity in China. Employing propensity score matching (PSM) and staggered difference-in-difference (SDID) estimations, we find a statistically significant and positive casual effect of robot adoption on firm productivity at the 1 % significance level, leading to an approximate 10 % increase in total factor productivity (TFP) among manufacturing firms in China. The effect was most pronounced in the first two years following adoption but lost statistical significance from the third year onward. Additionally, we find that robot exposure, measured by both adoption rate and adoption intensity, had positive and statistically significant spillover effects on large-scale non-adopting firms within the same industry and city, leading to significant improvements in their TFP. Furthermore, the effect of robot adoption on firm productivity varied by robot type, firm size, and industry. Multi-functional robots (MFRs) exhibited a more substantial effect compared to singlefunctional robots (SFRs). The automotive, plastic/chemical, and metal industries had great productivity gains compared to other industries. These results withstand various rigorous robustness checks, reaffirming the validity and consistency of our findings. [ABSTRACT FROM AUTHOR]

The study re-examines convergence among Indian states by estimating their total factor productivity (TFP) for the period 1990/91–2018/19. The novelty of the study is the decomposition of TFP change into efficiency change and technological change using the Malmquist index in a spatial dependence framework to test convergence. Findings reveal that, on average, productivity increased at an aggregate level for the entire period on account of the impressive growth of technological innovation. However, technological growth convergence could not lead to productivity growth convergence in the second sub-period because of no convergence in efficiency growth. Alongside, while we witness significant spatial spillovers in both technology and efficiency, convergence was observed only with respect to technology growth in the second sub-period. The congruence of technological convergence and significant spatial spillovers indicates that while states may be converging in technology, they do not do so independently but display movements similar to their regional neighbours. [ABSTRACT FROM AUTHOR]

Industrial convergence refers to the dynamic process in which different industries gradually form new industries through mutual penetration and cross. As an advanced form of industrial synergy, industrial convergence is crucial in building a modern economic system. Using a panel data set covering China's 30 provinces during 2006–2018, this study explores the impact of industrial convergence on regional high-quality development. The findings suggest that: (1) Industrial convergence is conducive to high-quality development, and this conclusion remains robust after a series of tests. (2) For heterogeneity, the positive impact of industrial convergence on high-quality development is greater in regions with optimized energy structure and high investment outward, as does the regions with reasonable financial structure and moderate economic agglomeration. (3) Productivity improvement and industrial upgrading are the mediating paths by which industrial convergence promotes high-quality development, and the former plays a greater role. [ABSTRACT FROM AUTHOR]

The establishment of Green Finance Reform and Innovation Pilot Zones represents a novel endeavor aimed at paving a "bottom-up" pathway for the advancement of green finance and, consequently, holds immense significance in fostering economic growth that is environmentally sustainable. Drawing on data spanning the years 2013–2019 from 278 prefecture-level cities across China, we delve into the influence of the Green Finance Reform and Innovation Pilot policy on urban Green Total Factor Productivity. We found that: Firstly, the Green Finance Reform and Innovation Pilot policy has demonstrated a discernible enhancement in Green Total Factor Productivity within the designated pilot regions. Secondly, there is heterogeneity in the promotion effect of this pilot policy on Green Total Factor Productivity. As the geographical advantage and economic development level decrease, this promotional effect gradually diminishes. Thirdly, it is evident that the Green Finance Reform and Innovation Pilot policy primarily elevates Green Total Factor Productivity in the pilot regions by improving resource allocation efficiency, fostering innovation in green technologies, and facilitating the upgrading of industrial structures. This research not only underscores the efficacy of green finance in the context of economic transition but also provides empirical substantiation for the strategic utilization of pilot zones to propel nationwide initiatives aimed at sustainable green development. [ABSTRACT FROM AUTHOR]

Total factor productivity in the green economy is a major step forward in fostering robust growth in the economy. Urban green total factor productivity (GTFP) may be increased and carbon emissions decreased through the low-carbon transformation of the transportation sector. To analyze how the pilot policy of low-carbon transportation system construction affects urban GTFP, this study builds a DID model and a spatial Durbin model using panel data from 282 Chinese cities between 2006 and 2021. The findings show that low-carbon transportation systems boost urban GTFP. In addition, the mechanism test shows that low-carbon transportation development increases urban GTFP by optimizing urban industrial structure, expediting economic agglomeration, and encouraging technological innovation. Lastly, the geographical correlation test shows that GTFP is geographically associated and that spatial spillover reduces the impact of low-carbon transportation growth on GTFP. The findings affirm the need to vigorously promote low-carbon transportation systems to aid in the achievement of the carbon neutrality target. [ABSTRACT FROM AUTHOR]

We study the currency risk premium and the forward premium bias in a two‐country New Keynesian model with production, no physical capital, and recursive utility. Monetary policy follows an interest rate feedback rule and exogenous total factor productivity (TFP) growth follows a long‐run risk process with stochastic volatility, which we estimate from data. With cross‐country heterogeneity in TFP and monetary policy, reasonable currency risk premia emerge under complete and incomplete markets but the forward premium bias is trivial. We diagnose the challenge faced by this fairly standard production model to explain the forward premium bias. [ABSTRACT FROM AUTHOR]

We use the DID method to estimate whether the binding pollution control policy can achieve both "pollution reduction" and "efficiency enhancement" for industrial enterprises after implementing this command‐and‐control environmental regulation of the eleventh Five‐Year Plan in China. We also analyze its influence mechanism in detail. It has been shown that (1) Constrained by binding pollution control policies, enterprises could reduce their pollutant emissions but simultaneously suppress their total factor productivity (TFP), which indicates that command‐and‐control environmental regulations do not achieve both "pollution reduction" and "efficiency gains" for firms. (2) The mechanism analysis shows that under the constraint of the binding pollution control policy, enterprises increase the pollution treatment at the front end of production, such as investment in environmental protection facilities, and adjust the production schedule, such as pollution treatment at the end of production. These pollution treatment measures reduce pollutant emissions while bringing "compliance costs" to enterprises. However, the "innovation compensation effect" fails to compensate for the "compliance cost" brought by pollution control. (3) Further study finds that the binding pollution control policy effectively reduces the pollutant emissions of enterprises with low financing constraints. [ABSTRACT FROM AUTHOR]

This paper studies how firms adapt to demand shocks when facing capacity constraints. I show that increases in government purchases raise total factor productivity in quantity units at the production line level. Productivity gains are concentrated in plants facing tighter capacity constraints, a phenomenon I call "learning by necessity." Evidence is based on newly digitized archival data on US World War II aircraft production. Shifts in demand across aircraft with different strategic roles provide an instrument for aircraft demand. I show that plants adapted to surging demand by improving production methods, outsourcing, and combating absenteeism, primarily when facing tighter capacity constraints. (JEL D22, D24, E62, L93, N12, N42, N62) [ABSTRACT FROM AUTHOR]

In the past, China divided its citizens into "agricultural hukou" and "non‐agricultural hukou" to limit rural–urban migration, which contributed to China's early industrialization. However, the binary household registration system no longer suits China's development, and cities in China have successively carried out hukou reforms. Based on the reforms that trigger rural–urban migration, we investigate the impact of low‐cost and low‐skilled migrant workers on firm‐level total factor productivity (TFP). We employ a staggered difference‐in‐differences (DID) strategy to show the following results: (1) The hukou reform substantially reduces the listed firms' TFP by 6.9%. (2) The hukou reform has increased the number of employees and the labor intensity, as well as reduced average employee salaries, employee responsibility, and R&D in enterprises, revealing the mechanism by which hukou reform affects firm productivity. (3) Our findings are particularly pronounced in non‐state‐owned enterprises (non‐SOEs), enterprises with more stringent financing constraints, and cities with wider rural–urban income gaps. [ABSTRACT FROM AUTHOR]

This paper examines the impact of manufacturing servitization, service trade openness, and their interaction on the total factor productivity (TFP) of the manufacturing industry. Using panel data covering 43 economies, the study finds that higher levels of manufacturing servitization and service trade openness lead to higher TFP in the manufacturing industry. In addition, the positive impact of manufacturing servitization on TFP is greater in economies with higher levels of service trade openness. The study also shows that trade creation and research and development innovation mediate the relationship between manufacturing servitization, service trade openness, and TFP. Finally, the paper finds that the positive impact of manufacturing servitization, service trade openness, and their interaction on TFP is greater in developing countries and in low‐ and high‐TFP manufacturing industries. This research contributes to understanding the intricate relationship between manufacturing servitization, service trade openness, and manufacturing TFP. [ABSTRACT FROM AUTHOR]

China's higher education system is shifting from quantitative expansion to connotative development to advance its quality. Since 2015, Chinese governments have been implementing a strategic policy for higher education called "double first-class", which aims to promote a number of Chinese top universities to construct world-class universities or to establish world-class disciplines. "Double first-class" universities have received a large amount of educational resources through this policy. Taking advantage of resources efficiently is an important element in promoting the development of higher quality higher education. However, research on resource allocation in China's "double first-class" universities is incomplete. Current research has not clarified the level of resource allocation efficiency or the factors affecting China's "double first-class" universities. With the help of the superefficient data envelopment analysis (DEA)-Malmquist–Tobit model, this study actively explores the current status of the resource allocation efficiency of China's "double first-class" universities to fill this gap in the field. Specifically, the development level and change trend of the resource allocation efficiency of 13 "double first-class" universities in China from 2015 to 2019 were measured with the help of the superefficient DEA-Malmquist model. The internal and external factors affecting the resource allocation efficiency of "double first-class" universities are also analysed with the help of the Tobit model. The overall level of resource allocation efficiency of "double first-class" universities is high, but the internal variability is large. From the perspective of efficiency decomposition, it is found that both technical efficiency change (EFch) and technical progress efficiency (TEch) play important roles in improving the total factor productivity (TFP) of resource allocation. Compared with TEch, EFch plays a more significant pulling role. This study confirms that the factors affecting resource allocation efficiency are complex. Among them, the regional economic environment, faculty title structure, and degree of international exchange have significant roles in promoting the resource allocation efficiency of "double first-class" universities, but local financial support and the time of policy implementation have certain negative effects. [ABSTRACT FROM AUTHOR]

There is a growing emphasis on fostering green growth and lowering carbon emissions in order to achieve sustainable economic development. This study uses the Tapio decoupling model and analyzes the factors influencing changes in carbon emissions from manufacturing in India utilizing the log mean Divisia index (LMDI) techniques. Furthermore, the nexus between carbon emission intensity, information and communication technology (ICT), total factor productivity (TFP), skill, and energy intensity has been analyzed using the system-GMM approach. It is based on the plant-level Annual Survey of Industries (ASI) datasets for the organized manufacturing sector of India from 2001 to 2002 to 2019 2020 for the major 21 Indian states/UT. The findings reflect the presence of weak decoupling in the manufacturing sector both at the aggregate level and in states. This indicates that both output and emissions are increasing; however, output growth surpasses emission growth, which signifies an effort to transition towards more environmentally friendly production methods and enhanced energy efficiency. The output and population effect are found to be leading factors in carbon emissions, while energy intensity is found to be reducing the effect. Further, the system-GMM estimates show that ICT and energy intensity positively affect total factor productivity, while with an increase in carbon emission intensity, productivity declines. The study confirms the existence of an inverted N-shaped Kuznets curve in the sector. This present study will contribute to formulating energy and environmental strategies to reduce emissions and promote adopting cleaner energy sources. These efforts will facilitate the attainment of carbon neutrality and enhance energy efficiency within the sector. [ABSTRACT FROM AUTHOR]

In the digital era of governance, few studies have analysed the influence of digital government on micro economies. To fill this gap, we explore the nexus between digital government and firm total factor productivity (TFP), and uncover the potential transmission channels behind this connection by focusing on Chinese listed firms from 2010 to 2017 and utilizing panel regression with firm-, year-, and province-fixed effects. Our findings confirm that digital government has constructive effects on firm TFP. Furthermore, empirical results suggest that this favourable impact can be transmitted through three channels of firm transaction costs and innovation, digital infrastructure construction, and government-market relationships. Further analysis reveals that the beneficial effect of digital government on firms is more significant in provinces with low fiscal transparency and complex topography, indicating that digital government compensates for the disadvantages of low fiscal transparency and inconvenience of steep terrain. Based on these conclusions, we provide suggestions for government digitalization to improve the performance of government-microeconomic complementation. [ABSTRACT FROM AUTHOR]

While promoting manufacturing growth is imperative to boost economic growth, potential adverse consequences on natural resources and ecology have created sustainability-related concerns and challenges. In India, with the reform processes deepening further and the business environment becoming more market-oriented over the years, the adoption of appropriate measures for sustainable manufacturing growth under such conditions would require a deeper investigation of the underlying dynamics, particularly to address the impacts of external shocks. This is especially true when external shocks alter market dynamics and, hence, input is used significantly in the manufacturing sector. Given this backdrop, the present paper examines how the major external shocks to the Indian economy during in the post-reform era have altered the resource use patterns in selected manufacturing industries. The paper uses secondary data collected from the KLEMS database of the Reserve Bank of India for the period from 1980–81 to 2019–20 and applies descriptive statistics and econometric techniques to address the research objective. It is found that energy intensity, vertical integration, capital intensity, and rate of growth of total factor productivity decreased over the decades, whereas labour productivity experienced an increasing trend in most industries. However, the trends are mixed in the case of material intensity. Further, the regression results indicate significant effects of external shocks on resource use, factor productivity, and structural changes. There are also industry-specific differences in the nature and extent of such changes. Hence, a deeper investigation of the underlying factors and impacts at a disaggregate industry level is necessary to draw more robust insights. [ABSTRACT FROM AUTHOR]

India is often referred to as the next development superpower, and generally, becoming a large-scale industrialization center is seen as an achievable goal for the country. This article investigates the output elasticity, substitution elasticity, and technological advancement between the various factors (i.e., labor, capital, and energy use) in the industrial sector of India. To investigate the factor's productivity, a trans-log production function was applied; however, ridge regression was used to analyze the various parameters to check the multicollinearity issue. The results show that (1) the analyzed inputs are optimistic and return-to-scale averages of 1.18, 1.41, and 1.24 between labor, capital, and energy, respectively, are increasing; (2) the pairs substitution between labor--industrial energy utilization and capital--industrial energy consumption is found to be 0.96 and 0.98, respectively, on average, indicating that capital, labor, and energy are good substitutes that need more attention in the production process; and (3) the technological progress between factors ranges from -0.4 to 0.02, in which labor--energy and capital--energy utilizations provide quicker outcomes than a capital--labor utilization. Finally, the industrial sector can attain maximum productivity if capital and skilled labor are improved under the sustainable development goals, as energy and capital are optimized for maximum efficiency. Finally, energy substitution and low-carbon technological efforts can be better suited for attaining dual-carbon goals in the industrial sector. [ABSTRACT FROM AUTHOR]

It has become a new trend for the future development of Chinese agriculture to accelerate the transformation from increasing production to improving quality and realizing green growth. This paper uses the sequential DEA to measure the agricultural green total factor productivity (GTFP) of 306 Chinese cities from 1996 to 2017, then tests its convergence. The results show that the average growth rate of Chinese agricultural GTFP is 0.58%; the main driving force coming from technical progress. The convergence of agricultural GTFP has dual characteristics of stages and regions, and the significant σ convergence only exists in the central region during 1996–2003. There is significant β convergence at the national level, in the eastern and central regions, and neither convergence nor divergence in the western region. However, during 2004–2017, only the eastern region had β convergence. Finally, the conditional convergence speed is higher than the absolute convergence, and the eastern region is higher than the central. [ABSTRACT FROM AUTHOR]

In the study of urban development, it is very important to evaluate the influence of production factors reasonably and efficiently for the region to achieve efficient development. The principal aim of this investigation is to amalgamate the conventional measurement model characterized by robust interpretability with the non-parametric model characterized by limited interpretability, thereby enhancing the precision of research outcomes. Towards this objective, the study employs an optimized directional distance function integrated with a global Malmquist–Luenberger index to formulate a comprehensive total factor productivity measurement framework. In elucidating the homogeneous attributes of regions, departing from prior methodologies reliant on manual or direct algorithmic partitioning, this paper employs the K-means clustering algorithm for index discernment, abstracting the concept of K-means clustering centroids to encapsulate regional homogeneity, thereby delineating results through the visualization of regional development potential maps and the evolution of centroid-based clustering trend maps. The findings of the investigation illuminate common patterns of change across disparate regions, proposing a strategy for leveraging regional resource endowments towards a cohesive framework, thereby transcending constraints imposed by production efficiency limitations. Amidst the backdrop of the COVID-19 pandemic, this study draws upon provincial-level data spanning from 2000 to 2018 in China. The conclusive analytical outcomes underscore the pivotal role of energy factors in regional development efficiency, particularly within high-potential development regions, followed by the capital and labor factors. Concurrently, the study discerns a discernible hierarchical pattern among areas of development potential, which exhibits correlation with factor mobility dynamics. [ABSTRACT FROM AUTHOR]

This paper investigates the impact on polluting emissions as a result of manufacturing industries in China offering services as well as products. We merge detailed firm-level statistics covering 2000 to 2011, and use two-way linear fixed effects regression to control for firm and year heterogeneities and a host of control variables. The empirical results show that manufacturing servitization significantly reduces the emission intensity of firms. This effect is achieved by improving the total factor productivity of firms, optimizing the efficiency of energy use, and increasing the share of the highly-skilled labour force. Moreover, the emission reduction effect of manufacturing servitization is more profound in the eastern and central regions, pollution-intensive industries, non-state-owned firms, and processing trade firms. In addition, our extended analysis shows that the emission reduction effects of manufacturing servitization can be strengthened through trade liberalization and cohort study. The major policy implication is that governments should undertake industrial policies that reinforce the positive effects of manufacturing servitization in order to achieve win-win outcomes in manufacturing upgrading and environmental protection. [ABSTRACT FROM AUTHOR]

Labour productivity growth in the construction sector has been very weak in recent decades in most OECD countries. This paper addresses this issue based on a panel of 23 countries over the period 1995–2015. First, we use the Ackerberg, Caves, and Frazer (2015) method to propose a multifactor explanation for this lack of productivity growth: (i) average TFP growth is close to zero and even negative for most countries; (ii) average contributions to growth of capital and intermediate inputs are positive but weak, respectively of 0.05% and 0.90% per year, and much smaller than in the manufacturing sector over the same period (respectively of 0.40% and 3.10% per year). Then, we investigate whether reforms of regulations specific to the construction sector might boost productivity there. Using regulation indicators from the 'Doing Business Report', we find a negative impact of these regulations on TFP, but not on the intensities of capital and intermediate inputs. Our results suggest that reducing the construction sector regulations might bolster productivity: a switch to the lightest regulations would lead to a long-term TFP increase of 6% on average. [ABSTRACT FROM AUTHOR]

This study constructs an economic growth model that includes natural resource endowments to theoretically explore the paradox of “resource gospel” and “resource curse.” Based on the theoretical analysis, the influence of natural resources on green total factor productivity is analyzed empirically through an econometric model using Chinese urban panel data from 2010 to 2019. The theoretical analysis shows that the impact of natural resource endowment on green total factor productivity is indecisive. The empirical results show that natural resource endowments significantly lessen urban green total factor efficiency, and the results remain robust after addressing for endogeneity issues and robustness tests. However, this effect is significantly heterogeneous depending on the city level and science and education level; for example, the “resource curse” effect is more pronounced in non‐central cities and cities with average education and science level. Simultaneously, the mechanism analysis shows that natural resource endowment reduces urban total factor productivity by inhibiting innovation and introducing choices in the technological progress approach. Therefore, the research findings bring empirical evidence to promote reforms in natural resource allocation and provide theoretical support for encouraging green total factor productivity in resource‐based cities. [ABSTRACT FROM AUTHOR]

As environmental challenges escalate, green development is crucial for sustainability. This study analyzes China's county-level agricultural green total factor productivity using SBM and ML index, introducing a comprehensive index to quantify the impact of different types of environmental regulations on productivity. The findings reveal the following: baseline analysis reveals that comprehensive environmental regulation notably boosts agricultural green total factor productivity (AGTFP), with regulatory intensity positively linked to productivity growth. Other factors like policy intervention, industrial structure, savings levels, and per capita GDP also favorably impact productivity. All three types of regulations, command, incentive, and voluntary type, substantially enhance AGTFP. The mediating effect test results show that all three types of regulations directly and positively impact AGTFP. Indirect effects vary: command-type regulation's mediating effect through independent R&D is significant, accounting for 39% of the impact. For incentive type, both industry structure upgrading (23.79%) and independent R&D (3.1%) mediate the effect. For voluntary type, technological advancement via independent R&D mediates about 13.0% of the impact. Heterogeneity analysis reveals distinct impacts of different environmental regulations on AGTFP across regions. Command-type regulation is most effective in the west, while in the central region, both command- and incentive-type regulations have similar promotional effects. In the east, incentive- and voluntary-type regulations show stronger impacts. Robustness tests, including endogeneity testing, dependent variable substitution, sample winsorizing, and model substitution, consistently confirm the baseline finding that environmental regulation significantly boosts AGTFP. [ABSTRACT FROM AUTHOR]

Furniture production is one of the activities that has the potential to generate income for educational institutions. The furniture production process is generally carried out by experienced students utilizing industry-standard facilities, namely the Wood Construction workshop along with its machinery equipment. Therefore, the implementation of Quality Control in the production process is necessary. This study aims to determine the impact of Quality Control implementation on improving the productivity and quality of furniture products. The method used is quantitative with 4 stages of Quality Control, including product design, process planning, Incoming Quality Control (IQC), and In-Process Quality Control (IPQC). Productivity measurement is divided into 3 parts: partial productivity, total factor productivity, and total productivity, which includes labor productivity, time, and production output. Meanwhile, product quality measurement is obtained from assessments by practitioners and product quality testing according to ISO 19682. Data is processed using the path analysis method with the help of a smart PLS application. The research results show that the productivity of production output is 87.5%, categorized as good, with labor productivity of 0.125 pieces/person/day and work hour productivity of 0.25 pieces/hour/day. Product quality based on production processes is categorized as good at 83%. Meanwhile, product quality testing, including visual aspects is good (82.3%), product stability (normal), strength (normal), durability (normal), stiffness (normal 34mm/m), and drop test (normal). Based on path analysis, it is known that quality control including product design, process planning, Incoming Quality Control (IQC), and In-Process Quality Control (IPQC) has an impact on improving the productivity and quality of furniture products. the quality control carried out to increase productivity and product quality can be said to be good with the validation of the final result of 0.188 including in the good category. [ABSTRACT FROM AUTHOR]

This paper focused on the decision and regulation for the production-warehousing-selling (P-W-S) model. A novel event-triggered mechanism (ETM) was meticulously developed to determine when to impose control, alongside the development of the corresponding impulsive strategy. By applying the input-to-state stability (ISS) theory, some quantitative relationships between system parameters and ETM were integrated into the estimation of the state of the P-W-S model. It was shown that under the designed ETM and impulsive strategy, the warehouse was able to autonomously adjust inventory levels based on factory production efficiency and market selling trends, and hence the quantity of goods could be maintained within a reasonable range, avoiding excessive inventory while adequately meeting market requirements. At last, an example with numerical simulations was presented to validate our results. [ABSTRACT FROM AUTHOR]

This article investigates the causes of structural change in Brazil, through the rise and the fall of the manufacturing industry, and the consequences for total factor productivity and manufacturing labour productivity, from 1947 to 2021. Our results show that the industrialization of the Brazilian productive structure is positively associated with expansions in infrastructure investments and with the pursuit of a competitive real exchange rate, that is, with policies oriented towards economic development. Our findings also indicate that such variables exert a direct influence on total factor productivity and manufacturing labour productivity and an indirect influence through their impacts on the Brazilian productive structure. Our conclusions suggest that an important cause of the Brazilian premature deindustrialization, and then of its poor performance in terms of total factor productivity and manufacturing labour productivity, is the adoption of policies not oriented towards economic development adopted since the neoliberal reforms of the 1980s and 1990s. [ABSTRACT FROM AUTHOR]

Background: With Primary Health Care (PHC) being a cornerstone of accessible, affordable, and effective healthcare worldwide, its efficiency, especially in developing countries like China, is crucial for achieving Universal Health Coverage (UHC). This study evaluates the efficiency of PHC systems in a southwest China municipality post-healthcare reform, identifying factors influencing efficiency and proposing strategies for improvement. Methods: Utilising a 10-year provincial panel dataset, this study employs an enhanced Data Envelopment Analysis (DEA) model integrating Slack-Based Measure (SBM) and Directional Distance Function (DDF) with the Global Malmquist-Luenberger (GML) index for efficiency evaluation. Tobit regression analysis identifies efficiency determinants within the context of China's healthcare reforms, focusing on horizontal integration, fiscal spending, urbanisation rates, and workforce optimisation. Results: The study reveals a slight decline in PHC system efficiency across the municipality from 2009 to 2018. However, the highest-performing county achieved a 2.36% increase in Total Factor Productivity (TFP), demonstrating the potential of horizontal integration reforms and strategic fiscal investments in enhancing PHC efficiency. However, an increase in nurse density per 1,000 population negatively correlated with efficiency, indicating the need for a balanced approach to workforce expansion. Conclusions: Horizontal integration reforms, along with targeted fiscal inputs and urbanisation, are key to improving PHC efficiency in underdeveloped regions. The study underscores the importance of optimising workforce allocation and skillsets over mere expansion, providing valuable insights for policymakers aiming to strengthen PHC systems toward achieving UHC in China and similar contexts. [ABSTRACT FROM AUTHOR]

The carbon emissions trading system (CETS) is a crucial market-based tool aimed at achieving the goals of “carbon peaking” and “carbon neutrality”, and plays a pivotal role in promoting the green development of the logistics industry. The green total factor productivity (GTFP) of the logistics industry is a key indicator used to measure the green development level of the logistics industry. The research on the CETS and the GTFP in the logistics industry(LGTFP) is currently lacking. Accurately assessing the impact of CETS on LGFP is crucial for improving the construction of the CETS and promoting the green transformation of the logistics industry. Utilizing a combined approach of system dynamics and econometrics, this study examines the effects of CETS on the LGFTP. In this study, the impact mechanism of CETS on the LGTFP is analyzed by constructing a causal relationship diagram using system dynamics theory. And then, we construct a multi-period differencein- difference (DID) model using panel data from 30 Chinese provinces spanning from 2010 to 2020 to verify the impact of CETS on LGTFP. The findings reveal that: (1) CETS significantly promotes LGTFP, and this conclusion is consistent even after conducting robustness tests. (2) Green technological innovation is identified as the primary influencing mechanism of CETS in enhancing LGTFP, while industrial upgrading does not play a positive mediating role, contrary to established studies. (3) Heterogeneity analysis reveals that CETS has a significant promotion effect on LGTFP in central and western regions, and resource-based provinces, but not yet in eastern regions and non-resource-based provinces. Based on the empirical analysis, we propose relevant policy recommendations to improve China’s CETS and promote the improvement of LGTFP. [ABSTRACT FROM AUTHOR]

In this article, we analyse India's transport sector policy. The study examines the two important modes of transport, viz., road and rail, and analyses the efficiency of transport infrastructure from 2011 to 2019. Through Data Envelopment Analysis (DEA), we evaluate modes in terms of the capacity of registered road goods vehicles and railway goods wagons, truck km/train km and energy consumption and corresponding freight traffic. The analysis gives valuable insight into the fact that rail infrastructure is more efficient than road infrastructure. Still, current transport sector policies promote energy-intensive carbon-fuel road vehicles rather than energy-efficient alternative transport modes. The study suggests the changes that may be incorporated in inputs to improve the efficiency of the road infrastructure. The Data Envelopment Analysis (DEA)-Malmquist Index analysis reports the need for total factor productivity improvement in rail transport and the introduction of technological innovations in road and rail transport sector management. The study employs a well-to-wheel (WTW) based index to ascertain the energy consumed and pollutants emitted by freight-carrying road and rail modes between two leading business hubs of India, i.e., Ludhiana and Mumbai. The paper identifies policy gaps and suggests a holistic approach for need-based roadway investment and a time-bound development of railway infrastructure in India. Our study generates valuable implications for India's policy planners and government authorities and provides new insights to other countries. • The study examines road and rail transport, and analyses the efficiency and energy consumption of these modes. • The study suggests the changes to improve the efficiency of the road infrastructure. • The Data Envelopment Analysis (DEA)-Malmquist Index analysis and well-to-wheel (WTW) based index have been employed for the analysis. • The paper suggests a need-based roadway investment approach and a time-bound development of railway infrastructure. [ABSTRACT FROM AUTHOR]

Increasing agricultural productivity and reducing carbon emissions are two major challenges that China faces. This paper explores how agricultural insurance affects agricultural green total factor productivity (AGTFP) that addresses these two challenges. First, we adopt DDF-GML to measure AGTFP, and the Dagum's Gini decompositions results show the large differences in AGTFP, with transvariation between subregions contributing the most. Second, we find the U-shaped effect of agricultural insurance on AGTFP in a large country context. The result remains robust after adjusting for time, sample and estimation method of AGTFP. We also construct instrumental variables from the minimum distance from the centroid of counties within a province to the 45 ports in China and two-stage lagged agricultural insurance penetration (AIP) for AIP, and their squares as instrumental variables for AIP2. The conclusion remains robust in 2SLS model. Third, the findings confirm three channels for agricultural insurance to influence the AGTFP: environmentally friendly production, labor inputs and operation scale. We further propose policy advice to promote China's agricultural modernization and point out further research directions in this field. [ABSTRACT FROM AUTHOR]

Objective: An organization demands its employees to possess the maximum potential benefits and expects them to meet organizational needs. Therefore, in a new perspective, the creation of an appropriate environment for the retention and maintenance of human capital and its connection to increased organizational productivity has been introduced as an important step towards the realization and achievement of objectives, including organizational productivity. The aim of this paper is to explain the structural model of factors effective in retaining and maintaining human capital based on organizational productivity in the National Iranian Oil Company. Methodology: The research method was descriptive-survey, and the statistical population consisted of senior managers and deputies in the human resources domain from the National Iranian Oil Company in headquarters and field staff (582 individuals), of whom 235 were selected as the sample using Cochran's formula. Interviews and questionnaires were used as data collection tools, validated through content and construct validity, and reliability was established using Cronbach's alpha coefficient. For data analysis, statistical methods and tests such as Pearson correlation coefficient, single variable t-test, Kolmogorov-Smirnov test, exploratory and confirmatory factor analysis were used, employing SPSS and LISREL software. Findings: The results indicate that the investigation into creating an appropriate environment for retaining and maintaining human capital and increasing organizational productivity involves individual factors, organizational factors, and group factors, each including components that significantly impact the productivity of the organization at the National Iranian Oil Company. The research also showed that retaining and maintaining human capital is key to improving and increasing organizational productivity, with the most influential components on productivity in the National Iranian Oil Company being organizational factors--performance management (efficiency and effectiveness) with an impact of 0.85, merit selection with an impact of 0.83, intellectual capital smartization with an impact of 0.80, talent management with an impact of 0.80, and individual factors--ability and knowledge with an impact of 0.79. Conclusion: A comprehensive human resource retention program can play a vital role both in attracting and retaining key employees and in financial turnover and other human resource costs. These factors significantly aid organizational productivity and overall business performance. It is far more efficient to retain a competent employee than to hire, train, and guide a replacement with similar capabilities. [ABSTRACT FROM AUTHOR]

In Older to improve the operational efficiency of Chinese textile and clothing enterprises, 54 textile and clothing listed enterprises in China from 2018 to 20 were suspected as the research objects. Based on the data envelopment analysis ( DEA ) theory, the etteuation index system of operational efficiency in the digital transformation context was constructed, and DEA related models were used to analyze the operational efficiency of enterprises from both static and dynamic perspectives. The static analysis results show that the average comprehensive efficiency of the sample enterprises from 2018 to 2022 is between 0. 700 and 0. 800, and there is still a large room for improvement in the future; The number of enterprises with comprehensive efficiency is 8-14, indicating that the operational efficiency of most enterprises is in an invalid state of DEA. The number of companies with increasing returns to scale increased from 4 to 11, indicating that the number of enterprises with decreasing input-output ratio increased. The results of dynamic analysis show that the average value of total factor productivity index is greater than 1. The number of enterprises with total factor productivity index greater than 1 accounted for 61. 1%, indicating that the operation efficiency of most enterprises was in a state of progress. The technical progress decreased continuously from 1. 019 to 0. 968, indicating that the technological progress rate of enterprises decreased. In the future, enterprises should pay attention to the investment of digital talents and technologies, improve the operation system and improve the operation efficiency. [ABSTRACT FROM AUTHOR]

Green development has become one of the important concepts leading China's economic developments, and it is extremely meaningful to boost the continuous growth of agricultural green total factor productivity (AGTFP) to achieve the construction of a powerful agricultural country. Using China's provincial data from 2011 to 2020, this manuscript calculates AGTFP through the SBM–GML model, and the digital green finance (DGF) through a comprehensive indicator system. The double fixed-effect model, quantile model and spatial Durbin model are used for in-depth study of the benchmark influence, the nonlinear effect and spatial spillover effect of DGF on AGTFP. The main research conclusions of the article are as follows: (1) DGF is significantly conducive to the improvement of AGTFP. Along with the continuous growth of AGTFP, the promoting effect of DGF has gradually increased. (2) In terms of impact path, green finance can properly promote the growth of AGTFP, while the role of the degree of digitization is not very significant. Meanwhile, the main channel for DGF to promote AGTFP is through green technology efficiency. (3) The impact of DGF on AGTFP varies spatially, while the role is more effective in regions with a higher degree of economic development and well-developed modernization. (4) There is a spatial spillover effect of DGF's impact on AGTFP, which means that DGF can simultaneously promote the growth of AGTFP in local regions and neighboring regions. [ABSTRACT FROM AUTHOR]

Hog insurance and rural environmental protection are complementary to each other. Studying the environmental effects of hog insurance is imperative for safeguarding food safety and promoting the long-term development of the agricultural insurance industry. Informed by the risk management theory and sustainable development theory, this paper constructs a theoretical framework for the impact of policy-supported hog insurance on the green total factor productivity (GTFP) of hog farming. Utilizing panel data from China's hog-dominant production areas spanning from 2005 to 2021, the slacks-based measures of directional distance functions (SBM-DDF) model and multiple-time-point difference-in-differences (DID) approach were used to measure GTFP and explore the effects of hog insurance on GTFP and the underlying mechanisms. The findings indicate a substantial enhancement in GTFP due to hog insurance. The conclusion drawn was robust to various tests. The mechanism is that hog insurance fosters GTFP by expanding the breeding scale, adjusting the planting–breeding structure, and promoting technological progress. Furthermore, the environmental effects of hog insurance policy are more pronounced in economically developed regions, with significant effects observed on the GTFP of free-range, small-scale, and medium-scale hog-farming households. This study contributes new evidence to the field of assessing the environmental impact of agricultural insurance policies and provides valuable insights for furthering green transformation and development in the hog insurance-supported breeding industry. [ABSTRACT FROM AUTHOR]

Improving agricultural green total factor productivity (AGTFP) is the key to achieving sustainable agricultural development and empowering agricultural modernization. Based on the panel data of 30 provincial levels in China from 2011 to 2021, AGTFP is measured using the non-expected MinDS super-efficiency—MetaFrontier Malmquist model, and the impact of environmental regulation (ER) and digital finance on AGTFP is analyzed using the spatial Durbin model (SDM). The results show the following: (1) ER can increase local AGTFP and has a positive spatial spillover effect. Command-based ER has the highest impact on AGTFP, followed by market-incentive and public-voluntary ER. (2) Digital finance has a direct promotional effect on local AGTFP, while it has an inhibitory effect on AGTFP in neighboring regions due to the siphon effect. (3) Digital finance is an important regulatory variable affecting AGTFP concerning command-based, market-incentive and public-voluntary ER. Digital finance plays a significantly moderating role in the effectiveness of the three ERs on AGTFP, with the market-incentive ER being the highest in eastern China. Nonetheless, digital finance has a significantly moderating effect on the effectiveness of command-based and public-voluntary ER on AGTFP, with command-based ER being higher in central China. Meanwhile, digital finance only plays a significantly moderating role in the effectiveness of command-based environment regulation on AGTFP in western China. This study provides valuable reference for policymakers concerning agriculture green production in varied regions. [ABSTRACT FROM AUTHOR]