Green Total Factor Productivity Research Articles

Impact of Low-Carbon City Pilot Policies on Regional Green Total Factor Productivity: A Study

Based on data from 246 prefecture-level cities in China spanning the years 2006 to 2019, this paper employs a multi-temporal double-difference model to empirically examine the effects of low-carbon pilot policies implemented since 2010 on green total factor productivity. Furthermore, the paper conducts a mechanism analysis and heterogeneity analysis to explore the policys impact mechanisms and effects on different regions. The study reveals that low-carbon pilot policies have enhanced Chinas green total factor productivity. Results from the mechanism analysis indicate that these policies increase green total factor productivity by promoting the agglomeration of productive service industries and the innovation of green technologies, with the mechanism test for manufacturing industry agglomeration showing non-significant effects. Heterogeneity analysis results suggest that the impact of low-carbon pilot policies on the improvement of green total factor productivity is significant in Chinas eastern and western regions as well as in non-resource-based cities.

Assessing the impact of digital financial inclusion on green total factor productivity of grain in China: promotion or inhibition?

Abstract This study investigates the influence of digital financial inclusion on green total factor productivity of grain in China, using data from 30 provinces (excluding Tibet) from 2011 to 2020. Our findings reveal a dual role of digital finance: it significantly enhances green productivity of grain in central and eastern China but has a contrasting effect in the western regions. The research also uncovers a unique pattern where the benefits of digital finance in one area can negatively affect nearby regions. This research contributes significantly to the discourse on finance and agriculture, providing nuanced perspectives on the regional implications of digital financial inclusion for grain productivity, and thereby enriching the understanding of its role in agrarian economies.

Can carbon reduction policies promote sustainable construction development? Evidence from China’s green building market

Carbon emissions have become a global challenge, and China, as the world’s largest developing country, has a serious emissions problem. Developing green buildings is an important way of reducing carbon emissions. China’s low-carbon city pilot policy may be an effective way of promoting green building development and reducing these emissions. This study uses the low carbon city pilot policy as a quasi-natural experiment and employs the staggered difference-in-differences method to investigate its impact on green building development. The results show that the low-carbon city pilot policy promotes green building development, and this policy promotes it by enhancing regional green innovation capacity, improving green total factor productivity at the firm and regional levels, and reducing the financing constraints of firms in the construction and real estate sectors. In addition, the promotion effect of the policy on green building development is stronger in western and non-resource-based regions and large-scale cities in China. This study contributes to the literature related to environmental policy, green building, and carbon emissions and supports the promotion of green building development and the reduction of carbon emissions.

Industrial structure optimization and green growth in China based on a population heterogeneity perspective

AbstractPopulation and industrial structure, as foundational characteristics of economic and social systems, exhibit significant spatial heterogeneity and dynamic evolutionary trends in their impact on sustainable economic and social development. However, existing research often employs subjective spatial categorization of samples and overlooks the dynamic transitions of influencing patterns, potentially leading to biases in empirical results. To address this, the current study, based on the calculation of green total factor productivity (GTFP) for 30 provinces in China from 2000 to 2018, incorporates a finite mixture model. This model examines the objective heterogeneity and dynamic transition patterns of industrial structure's impact on GTFP, both from the perspectives of industrial structure advancement (ISA) and rationalization (ISR), and reveals the mechanisms of heterogeneity and dynamic changes from a population standpoint. The findings indicate that there are three patterns in the impact of industrial structure on GTFP, with nearly half of the provinces undergoing pattern transitions during the observation period. The key factors for these transitions are identified as the improvement in human capital levels and urbanization rates. In provinces like Beijing, Guangdong, and Shanghai, ISA and ISR significantly promote GTFP, with their effects further enhanced by increased urbanization and human capital levels. Conversely, in regions such as Shanxi and Hebei, ISA does not favor GTFP improvement, and while ISR can enhance GTFP, this positive effect diminishes with increasing urbanization and labor force numbers. This research not only enriches the literature on the positive interaction patterns between industrial and population structures but also provides a comprehensive analytical framework for governments to adopt differentiated policy measures for sustainable economic development.

Can Digital Innovation Improve Green Total Factor Productivity: Evidence from Digital Patents of China

Amid intensifying global economic rivalries, China has pinpointed the digital economy and sustainable growth as key accelerators for societal and economic progress. Digital innovation (DI) plays a crucial role in propelling China’s economy towards sustainable growth, by serving as the technological backbone of the digital economy. This study explores how DI influences China’s GTFP through an analysis of panel data covering 30 provinces, municipalities, and autonomous regions from 2005 to 2021. The results indicate that DI greatly contributes to the enhancement of GTFP. DI can also indirectly promote GTFP by increasing the effectiveness of factor allocation efficiency including capital, labor, and technology. Heterogeneity analysis results indicate that the influence of DI on GTFP differs depending on the degree of intellectual property protection (IPP), the development of digital infrastructure construction (DIC), and the geographical location. A higher degree of IPP and developed DIC make areas better suited for the role of DI in advancing GTFP. Furthermore, in the central and eastern areas, the impact of the digital economy on the promotion of GTFP is particularly noticeable. This study offers reliable empirical evidence for the effect of DI on GTFP and contributes to China’s digital economy and sustainable development.

Impact of green technology innovation on the quality of regional economic development

This study examines the effects of green technology innovation on regional economic development and its heterogeneity by using Chinese interprovincial panel data (2010–2020), and analyses the impacts of spatial effect and mediating effect. Green technology innovation can significantly contribute to regional economic development. From a spatial perspective, green technology innovation in surrounding provinces can inhibit regional economic development. Based on intermediary effects, green technology innovation can aid regional economic development by promoting industrial structural transformation, optimizing the energy consumption structure, and enhancing green total factor productivity.

Can low-carbon cities pilot policy promote enterprise sustainable development? Quasi-experimental evidence from China.

With the predicament of sustainable improvement in traditional cities, the low-carbon city pilot policy (LCCPP), as a novel development mode, provides thinking for resolving the tensions of green development, resource conservation and environmental protection among firms. Using Chinese A-share listed companies panel data during 2007-2019, this study adopts the difference-in-differences model to explore the impact of LCCPP on firm green innovation. Based on theoretical analysis, LCCPP-driven environmental rules have the impact of encouraging business green innovation. The relationship between LCCPP and green innovation is strengthened by external media attention and organizational redundancy resources. The mechanism study shows that the incentive effect of LCCPP on firm green innovation is mainly due to the improvement of enterprises' green total factor productivity and financial stability. In addition, the heterogeneity analysis shows that the LCCPP has significantly positive effects in promoting green innovation in high-carbon industries and state-owned enterprises. This research contributes to the understanding of city-level low-carbon policies as a driving force for corporate green innovation, offering practical implications for policymakers and businesses striving for sustainability.

Labor Mobility Networks and Green Total Factor Productivity

Population migration continues to reshape the spatial pattern of China’s population and regional economic development. During this internal migration process, production and consumption patterns often change, ultimately leading to changes in green total factor productivity. This paper, based on the Chinese population census data and 1% sampling survey data from 2005 to 2015, utilizes social network analysis methods to measure the labor mobility network indicators of 284 prefecture-level cities. Further, this paper analyzes the impact and mechanisms of regional network status on green total factor productivity using a panel fixed effects model. We find that as network density increases, the interpersonal connections between regions become closer, and the network exhibits a clear pattern of “concentrated inflows” and “dispersed outflows”, with the trend of forming strong alliances becoming increasingly apparent. Regions positioned centrally either in terms of network in-degree or out-degree exhibit higher green total factor productivity. Among these, the labor mobility network plays a crucial role in enhancing green total factor productivity through the channel of technology diffusion effects, which improve investment efficiency via knowledge exchange and material capital accumulation. The promotive effect of labor network status on green total factor productivity is more pronounced in the eastern regions, where talent quality is higher, and in areas with fewer restrictions from the household registration system.

Effects of carbon emission trading system on corporate green total factor productivity: Does environmental regulation play a role of green blessing?

Extant studies focus on the impact of environmental regulation on regional economic growth or environmental pollution, and a lot of research outcomes have been made. However, from the perspective of corporate green sustainable development, the question of whether carbon emission trading represents a “green blessing” remains unclear. To address this issue, we employ a staggered difference-in-differences model to investigate the effects and mechanisms of the carbon emissions trading pilot policy (CETPP) on the green total factor productivity (GTFP) of listed manufacturing companies in China. Our results demonstrate that: a) CETPP can effectively promote corporate GTFP, and the robustness of this result is verified through a series of checks; b) the mediating role of environmental, social, and governance (ESG) performance is critical in the relationship between CETPP and corporate GTFP, with environmental and governance performance serving as two key transmission channels; and c) CEO green experience and public environmental concern both play the moderating roles on the relationship between CETPP and GTFP; d) CETPP has a stronger positive impact on GTFP of private enterprises and enterprises in the maturity life cycle; and e) CETPP has a spatial spillover effect on GTFP, and the effect will decay as spatial distance increases. Our study offers both theoretical and practical implications for enterprises to achieve their green economic development objectives, so as to promote China's high-quality development.

How does market-incentive environmental regulation affect enterprises green growth? The mediating role of R&D investment and innovation output

Manufacturing enterprises is a country's economic mainstay. However, their longtime extensive growth pattern of “high growth and high emission” has brought huge environment pollution and restricted sustainable development. Under the circumstance of carbon reduction and global green development, market-incentive environmental regulation (MER) has attracted the attention of scholars and become a kind of important methods of encouraging manufacturing enterprises green growth. Presently, two fairly distinct viewpoints of “Follow Cost” and “Porter Hypothesis” both have their own supportive research results, and the explanation for the role of MER is completely opposite. What's more, empirical research at the enterprise level is scarce. Therefore, this study makes a further analysis from the perspective of enterprises heterogeneous innovation ability. Guided by the classic theory of “Follow Cost” and “Porter Hypothesis”, this study aims to evaluate the applicable conditions of MER's environmental improvement effect, and testing the differential impact mechanism of MER on enterprise Green Total Factor Productivity (GTFP), enterprise Green Technological Change (GTC) and enterprise Green Efficiency Change (GEC). All these give theoretical and empirical supplementation for the rationality of related theories. This study examines the hypotheses and mechanism according to 1220 Chinese manufacturing listed companies data 2011–2020. The empirical results indicate that: (1) In short term, MER has a significant positive impact on GTC, and a significant negative impact on GTFP and GEC. (2) As innovation driven factors, both enterprise R&D investment and innovation output play the mediating role. (3) Heterogeneity analysis indicates that the impact mechanism varies depending on enterprise industry-type, location and digital level. Thus, policymakers should develop appropriate MER policies, and manufacturing enterprises should strengthen technological innovation to help achieve environmental sustainability and profit performance.

Exploring the effect of green finance on green development of China’s energy-intensive industry—A spatial econometric analysis

An indispensable part of the green revolution is the green development of the Energy-intensive Industry (EII), which is crucial for China to achieve its “double carbon” target. EII is one of the key sectors bound by the green finance policy, whose development level is susceptible to regional conditions. Therefore, this research constructs a spatial Durbin model using provincial panel data (2001-2019) to empirically examine the impact of green finance on EII’s green total factor productivity (GTFP). Evidence shows that green finance boosts EII’s GTFP significantly and there is a spatial spillover effect. Specifically, the results demonstrate the spatial spillover effect’s regional heterogeneity which in contrast to the western region, is positive in the eastern, central and northeastern regions. Furthermore, there is a spatial inhibitory effect on two subindustries of EII, i.e., Manufacture of Non-metallic Mineral Products industry and Smelting and Pressing of Non-ferrous Metals industry, proving the spatial spillover effect’s sectoral heterogeneity for green finance. This research provides experimental evidence and policy suggestions for enhancing the promotion impact of green finance on EII’s GTFP.

Advancing Green TFP Calculation: A Novel Spatiotemporal Econometric Solow Residual Method and Its Application to China’s Urban Industrial Sectors

The Solow residual method, traditionally pivotal for calculating total factor productivity (TFP), is typically not applied to green TFP calculations due to its exclusion of undesired outputs. Diverging from traditional approaches and other frontier methodologies such as Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA), this paper integrates undesired outputs and three types of spatial spillover effects into the conventional Solow framework, thereby creating a new spatiotemporal econometric Solow residual method (STE-SRM). Utilizing this novel method, the study computes the industrial green TFPs for 280 Chinese cities from 2003 to 2019, recalculates these TFPs using DEA-SBM and Bayesian SFA for the same cities and periods, and assesses the accuracy of the STE-SRM-derived TFPs through comparative analysis. Additionally, the paper explores the statistical properties of China’s urban industrial green TFPs as derived from the STE-SRM, employing Dagum’s Gini coefficient and spatial convergence analyses. The findings first indicate that by incorporating undesired outputs and spatial spillover into the Solow residual method, green TFPs are computable in alignment with the traditional Solow logic, although the allocation of per capita inputs and undesired outputs hinges on selecting the optimal empirical production function. Second, China’s urban industrial green TFPs, calculated using the STE-SRM with the spatial Durbin model with mixed effects as the optimal model, show that cities like Huangshan, Fangchenggang, and Sanya have notably higher TFPs, whereas Jincheng, Datong, and Taiyuan display lower TFPs. Third, comparisons of China’s urban industrial green TFP calculations reveal that those derived from the STE-SRM demonstrate broader but more concentrated results, while Bayesian SFA results are narrower and less concentrated, and DEA-SBM findings sit between these extremes. Fourth, the study highlights significant spatial heterogeneity in China’s urban industrial green TFPs across different regions—eastern, central, western, and northeast China—with evident sigma convergence across the urban landscape, though absolute beta convergence is significant only in a limited subset of cities and time periods.

Research on the Impact of China’s Foreign Trade Technology Spillover on Green Total Factor Productivity of Countries Along the “Belt and Road”: Based on the Institutional Quality Threshold Effect

China’s growing trade with countries along the “Belt and Road” Initiative is accompanied by a focus on green development. Based on the panel data from 2007 to 2018, this paper establishes a threshold regression model to empirically analyze the institutional quality threshold effect of China’s foreign trade technology spillover on the GTFP of countries along the “Belt and Road.” The results show that China’s foreign trade technology spillover has a significant institutional quality double threshold effect on the green total factor productivity of the countries along the “Belt and Road.” As the institutional quality of the countries along the “Belt and Road” crosses a specific threshold value, the impact of China’s foreign trade technology spillover on the green total factor productivity of the countries along the “Belt and Road” has a significant positive promoting effect, and corresponding suggestions are put forward.

Does Free Compulsory Education Matter for the Green Transformation of Agriculture? Evidence from Rural China

Education plays a crucial role in promoting green development by shaping environmentally friendly production behaviors and fostering low-carbon lifestyles. This research examines the impact of China’s free compulsory education (FCE) policy on agricultural green total factor productivity (AGTFP) using provincial panel data from 2002 to 2015. Additionally, it explores the impact mechanisms and regional heterogeneity. The results indicate that first, the FCE policy has a significantly positive effect on AGTFP, as confirmed through a series of robustness tests. Second, the FCE policy primarily influences AGTFP by increasing farmers’ awareness of green production and promoting the development of green technologies in agriculture. Third, the impact of the FCE policy varies across regions. It promotes green technologies in agriculture in developed provinces and fosters ecological awareness among farmers in less developed provinces. These findings offer valuable empirical evidence and policy implications for implementing education popularization projects and reducing agricultural carbon emissions in developing countries.

Toward a Green Energy System: How Does Carbon Capture,  Utilization,  and Storage Technology Innovation Promote Green Total Factor Productivity?

Abstract Using a panel data set from 2007 to 2019, we empirically evaluate the impact of carbon capture, utilization, and storage (CCUS) technology innovation on green total factor productivity (GTFP). The findings show that (1) CCUS technology innovation significantly improves GTFP. (2) CCUS technology innovation significantly contributes to GTFP by promoting industrial structure upgrading and carbon emissions efficiency. (3) Environmental regulation plays a positive moderating role in the nexus between CCUS technology innovation and GTFP. The findings of this paper provide guidance for China to achieve green energy transition and build a green energy system.

Comments by Chia Wai Mun,  on  Toward a Green Energy System: How Does Carbon Capture, Utilization,  and Storage Technology Innovation Promote Green Total Factor Productivity?

Comments by Chia Wai Mun,  on  Toward a Green Energy System: How Does Carbon Capture, Utilization,  and Storage Technology Innovation Promote Green Total Factor Productivity?

Urban industrial land misallocation and green total factor productivity: Evidence from China's Yellow River Basin regions

AbstractThis study aims to investigate the repercussions of urban industrial land misallocation on green total factor productivity (GTFP) within the context of China's Yellow River Basin regions. Utilising data from 99 prefecture‐level cities over the period from 2007 to 2020, the analysis reveals that the misallocation of urban industrial land exhibits regional variations and exerts a significant and persistent negative influence on GTFP, with notable regional disparities. Further analysis shows the mechanism of this effect is the obstacle to urban innovation due to industrial land misallocation. In addition, education expenditure plays a moderating role both directly and indirectly. These findings imply the need to continuously improve the performance evaluation and financial system of local governments, reduce government intervention, and make use of the market mechanism in the allocation of urban industrial land.

Does ecological economic zone policy affect pollutant emission: Evidence from a case study of Dongting Lake

Environmental pollution affects human health, reduces work motivation, and addressing environmental pollution is a common challenge faced by the world. The Chinese government has recently implemented a new environmental policy - the national-level ecological economic zone - to develop a green economy and reduce environmental pollution. This study utilizes the difference-in-difference method to analyze the impact of the Dongting Lake ecological economic zone on environmental pollution. The results show that: policy led to a 68 % reduction in sulfur dioxide emissions. This impact was more pronounced in economically developed areas, regions with a high concentration of foreign-invested, and areas with greater economic openness. Mechanism tests indicate that the policy reduces environmental pollution by promoting technological progress. Robustness checks show that the policy also resulted in a 37 % reduction in industrial wastewater emissions. The results offer new insights to advance the development of the ecological economic zone more effectively. The ecological economic zone should focus on enhancing technological advancement and green total factor productivity to amplify the policy's positive effects.

How does emission trade scheme affect green total factor productivity: perspectives of efficiency decomposition and mediating effects

How does emission trade scheme affect green total factor productivity: perspectives of efficiency decomposition and mediating effects

Research on Green Production of the Iron and Steel Industry Based on DDF-BML Model

Although the iron and steel industry serves as the pillar industry of national economic development, the negative effects of its high emission and high pollution characteristics on the environment cannot be ignored. In order to achieve the carbon peaking and carbon neutrality goals at an early time and implement five priority tasks, including cutting overcapacity, reducing excess inventory, deleveraging, lowering costs and strengthening areas of weakness, it is urgent to realize the green production of the iron and steel industry. This paper takes listed iron and steel companies from 2016 to 2019 as research samples, and applies the two-stage Malmquist index based on the directional distance function (DDF) to measure the green total factor productivity (GTFP) of iron and steel enterprises. From macro and micro perspectives, the empirical model is used to explore the main influential factors of gtfp. The empirical results show that the overall gtfp growth rate of iron and steel enterprises is not ideal, falling behind at the end of the manufacturing industry. The promotion effect of R&D investment is limited, and the environmental carrying capacity of the production cluster area is approaching the limit. Based on the above empirical results, this paper proposes the following workable implementation path to the realization of the green production of iron and steel industry: On the one hand, the iron and steel enterprises should pay attention to improve technical efficiency, constantly improve low-carbon production process, optimize industrial layout. On the other hand, the government should guide the digital and intelligent development of the iron and steel industry and strengthen supervision to ensure the safety and stability of the supply of resources in the iron and steel industry.