Environmental Total Factor Productivity Research Articles

Lessons from the Pilot Project of Korean ETS on the Local Landscape of Economy

For a sustainable landscape of local economies, many researchers have emphasized the importance of field-oriented differentiation in government policies. In particular, the Paris Agreement, based on the bottom-up approach, aims to maximize the participation of all economic agents, in contrast to the top-down approach of the Tokyo Protocol. In response to these global paradigm shifts in the local landscape, local governments in Korea have made significant efforts to adapt to sustainable development during the pilot phase of emission trading scheme (ETS), during the period from 2015 to 2020. This study evaluates the performance of these local government policies in the transition to a carbon-zero economy. Using the general non-radial directional distance function (GNDDF), we found that Gyeongsang Province demonstrated enhanced environmental total factor productivity (TFP) during the pilot project, whereas the Seoul metropolitan area lagged behind due to a lack of governance. As the economic center of Korea, Seoul showed poor environmental performance because of the arbitrary elimination of green belt areas and unchecked land development, resulting in environmental degradation, a trend common in many developing countries facing climate adaptation challenges. To address these urbanization issues, this study concludes that a balanced approach combining stricter regulations with market-oriented promotional incentives is essential for optimizing the transition of local economies to a sustainable landscape.

Economic and Environmental Decomposition of Luenberger-Hicks-Moorsteen Total Factor Productivity Indicator: Empirical Analysis of Chinese Textile Firms With a Focus on Reporting Infeasibilities and Questioning Convexity

We discuss an environmental Luenberger–Hicks–Moorsteen (LHM) total factor productivity (TFP) indicator and its decomposition that incorporates a negative externality into the measurement of economic performance. Special cases of a generalized environmental directional distance function are involved in the definition of this LHM indicator and its proposed decomposition. We also seek to test whether changes in the convexity assumption provoke differences in the TFP measures. We apply two specifications of the by-production nonparametric environmental technology to implement this LHM TFP. This LHM TFP indicator decomposes into three terms representing technical change, technical inefficiency change, and scale inefficiency change. The changes in the environmental TFP for China's textile industry is then estimated for the period from 2001 to 2010. We report infeasibilities and we show the differences of the proposed framework for the decomposition of the LHM indicator depending on the convexity assumption. The results suggest there has been an increase in the TFP of China's textile industry: the amount depends on the convexity or not of the technology. The environmental performance is poorer than the economic one. Moreover, contradictions between convex and nonconvex LHM indicators for individual observations appear for a substantial part of the sample.

Can Rural Industrial Convergence Improve the Total Factor Productivity of Agricultural Environments: Evidence from China

The convergence of rural industries has brought about significant changes in the traditional small-scale farmer management model, as well as new requirements for the quality and skills of agricultural practitioners in China. Meanwhile, it has inevitably affected the agricultural environmental total factor productivity (AETFP). This paper endeavors to assess the impact of industrial convergence on AETFP, striving to clarify their inherent connection and furnish insightful guidance for policymaking. Utilizing inter-provincial panel data from China spanning 2008 to 2021, this paper applies the SBM-GML model for measurement purposes and employs the entropy method to evaluate the extent of industrial convergence in rural areas. It delves into the mechanism through which industrial convergence influences AETFP, utilizing the intermediary effect model and incorporating two mediating variables: rural human capital and agricultural scale operations. The findings of this research reveal that industrial convergence exerts a direct positive influence on AETFP, while rural human capital and agricultural scale operations serve as partial mediators in this process. Additionally, the stability of the transmission mechanism receives further validation via the application of interaction terms. Consequently, it is possible to enhance AETFP via the expedited convergent development of industries, coupled with the strategic utilization of rural human capital and agricultural scale operations as catalysts for further improvements in AETFP.

Environmental taxes, enterprise innovation, and environmental total factor productivity-effect test based on Porter's hypothesis.

Under the increasingly severe environmental constraints, improving environmental total factor productivity (ETFP) is the fundamental way for the sustainable development of heavily polluting enterprises. Based on 3463 panel data of A-share listed companies in China from 2011 to 2019, this paper employs Porter's hypothesis (PH) framework to explore the impact of environmental tax (EN_T) on enterprise innovation and environmental total factor productivity for the heavily polluting manufacturing industry using the propensity score matching (PSM) method. The empirical results show the following. (i) Environmental taxes positively affect enterprise innovation (EI) and environmental total factor productivity (ETFP). (ii) Mechanism analysis verifies a partial mediating effect for EI between EN_T and ETFP. (iii) Regional heterogeneity analysis illustrates the differences in the impact of environmental taxes on innovation quality. (iv) Individual heterogeneity analysis shows that the "strong Porter hypothesis" is only valid for large-scale enterprises. The results are of great importance for both government and enterprises to improve the EN_T system and optimize the allocation of resources in realistic practice.

Political uncertainty and high-quality economic development: Evidence from China.

We manually collated data on the turnover of party secretaries and mayors in 285 Chinese cities from 2003 to 2016 and calculated the quality of city economic development represented by environmental total factor productivity growth. We find that the political uncertainty caused by official turnover could significantly promote the improvement of the quality of economic development, and this positive can explained by the progress of production technology and government intervention. Moreover, the political uncertainty caused by the turnover of more educated officials, those with local hukou, promoted officials, and experienced officials could better promote high-quality economic development.

Research on the Coordinated Relationship between China's Provincial Environment and Economy

<p>The aim of the paper is to study the coordinated relationship between environment and economy among provinces in China. The environmental total factor productivity of 30 provinces and cities in China from 2003 to 2017 are measured using sequential ML methods, and the influencing factors of environmental total factor productivity are analyzed in a panel. It is found that: environmental total factor productivity has no obvious regional distribution characteristics, and is highly consistent with the change pattern of environmental technological progress rate, with oscillating upward characteristics; foreign capital utilization, capital increase per capita, and long-term education and science investment all have positive effects on environmental total factor productivity.</p>

How does digital finance affect environmental total factor productivity: A comprehensive analysis based on econometric model

The promotion of environmental total factor productivity (ETFP) is the key to ensure the sustainable development. As an important way of resource allocation, digital finance plays a significant role in regional ETFP. This study employs global Malmquist-Luenberger productivity index, based on super SBM directional distance function, to estimate the China's regional ETFP from the perspective of sustainable development. Furthermore, this paper adopts dual-effect fixed regression model, spatial econometric model and threshold model to verify the impact of digital finance on provincial ETFP. Results show that: (1) ETFP in China presents a trend of improvement, and the driving force is technological progress. The spatial distribution is in accordance with the “East, middle and West” gradient distribution; (2) Digital finance inhibits the improvement of ETFP, which shows nonlinear characteristics. The impact of digital finance on restraining ETFP will gradually weaken with the development of digital finance. In terms of decomposition terms, the coverage breadth and usage depth of digital finance have inhibitory action on the betterment of ETFP; (3) Digital finance can promote the regional ETFP of the surrounding areas, and the potential reason may be the “siphon effect”. Therefore, it is essential to further guide financial resources to enterprises and industries with high environmental benefits. (4) There is also significant heterogeneity in the impact of digital finance on ETFP. This study explores from the two aspects of region and material capital, and finds that the more backward the economy is, the more significant the inhibition effect is.

Does improvement of environmental efficiency matter in reducing carbon emission intensity? Fresh evidence from 283 prefecture-level cities in China

While promoting environmental efficiency is widely perceived as one of the panaceas for solving environmental issues in China, little effort has been made to identify whether environmental efficiency improvement helps to reduce carbon emission intensity (CEI). Therefore, the work presented in this study remedies the inadequacies in the previous literature by investigating the linkages between environmental efficiency and CEI, by explicitly considering its spatiotemporal heterogeneous effect and dynamic measurement. We first measure the environmental efficiency (EE) and its growth (environmental total factor productivity) at prefecture level in China during 2003–2016 by incorporating a recently modified epsilon-based data envelopment analysis technique in the global Malmquist–Luenberger index. A spatial panel regression approach is then applied to reveal the impact mechanism of EE and its growth on the CEI. The empirical results confirm that promoting EE and environmental technology efficiency can help mitigate the urban CEI. However, the impact of economic scale efficiency on the CEI reduction has not been verified, indicating great room for CEI mitigation by optimizing the urban production scale and reducing production redundancy. Evidence from the spatiotemporal econometric analysis shows a spatially heterogeneous effect of EE on CEI, and the strength of influence tends to decrease over time. The findings also reveal that enhancing EE matters in reducing CEI for southern and western cities. Finally, several control variables have negative direct and indirect (spillover effect) effects on CEI reduction, including urbanization, industrial structure, and foreign direct investment. Our findings suggest that strengthening the synergistic effect between environmental pollution governance and carbon emission control by enhancing EE to promote low-carbon development in Chinese cities.

The spatial spillover effect of environmental regulation on the total factor productivity of pharmaceutical manufacturing industry in China

As an important embodiment of a country's economic strength and national health, pharmaceutical manufacturing industry has made rapid development in China in recent years. But at the same time, the pharmaceutical manufacturing industry is facing many environmental problems, such as large pollution emissions, complex pollution components, controlling difficulties and so on. This paper measures the total factor productivity of pharmaceutical manufacturing industry (HTFP) by using data envelopment analysis with unexpected output, which is more accurate and effective than the traditional model. It also studies the effect of environmental regulation on the total factor productivity of pharmaceutical manufacturing industry (HTFP) by establishing panel data regression model and spatial econometric model based on 30 provinces in China from 2004 to 2019, which enriches the research results in the field of cleaning in pharmaceutical manufacturing industry. The conclusions are as follows: (1) Environmental regulation and total factor productivity of pharmaceutical manufacturing industry have significant spatial autocorrelation, showing "high-high" or "low-low" spatial aggregation characteristics; (2) Environmental regulation has a significant promoting effect on improving pharmaceutical manufacturing total factor productivity in local and surrounding areas, and there are differences in the impact of eastern, central and western regions; (3) Green technology, production technology and industrial structure play an important role in the impact of environmental regulation on pharmaceutical manufacturing total factor productivity, which provides theoretical guidance and policy recommendations for improving the level of total factor productivity of pharmaceutical manufacturing industry in the environmental aspect.

The Effect of Innovation Investment on Environmental Total Factor Productivity

Based on the panel data of 30 provinces (except Tibet) in China from 2012 to 2019, this paper uses the ML index method and spatial econometric model to evaluate the impact and spillover effect of innovation investment on environmental total factor productivity. The study found the following conclusions. (1) Environmental total factor productivity showed a fluctuating upward trend as a whole, and the driving force of environmental total factor productivity growth mainly came from technological progress. (2) There is global spatial correlation and positive spatial spillover effect in regional environmental total factor productivity. There is a certain spatial correlation in provincial environmental total factor productivity, and the improvement of environmental total factor productivity in this region will promote the improvement of environmental total factor productivity in surrounding areas. (3) Innovation investment, economic development, and foreign investment level play a significant role in promoting the improvement of environmental total factor productivity, and energy structure and human capital level have a negative impact on the improvement of environmental total factor productivity. (4) Innovation investment, economic development, human capital, and foreign investment have positive spillover effects on the improvement of environmental total factor productivity in the surrounding areas, while the energy structure shows negative spillover effects.

Environmental total factor productivity of agriculture in South Asia: A generalized decomposition of Luenberger-Hicks-Moorsteen productivity indicator

The agricultural total factor productivity (TFP) assessment is essential for providing intuition regarding factors involving productivity change. Integration of environmental aspects together with productive efficiency provides identification of factors for agricultural growth and environmental performance which anticipates foundation for the sustainable agricultural development. In a non-parametric framework, this paper establishes a modified directional by-production model to ensure the link between production and pollution-generating sub-technologies which offers more refined economic interpretations thereby proposing a unique shadow value of the pollution-generating inputs for the two sub-technologies. Further, a non-oriented generalized Luenberger-Hicks-Moorsteen (LHM) productivity indicator is adapted for the refined by-production model to measure the environmental TFP of agriculture sector in South Asia during 2000–2019. The environmental LHM-TFP decomposition accumulates both input and output changes yielding three mutually exclusive components, i.e. technical efficiency change, technological progress, and scale efficiency change. Moreover, the spatial evolution of agricultural carbon shadow price has been accessed during the study period. The policy implications suggest effective ways to improve the environmental TFP of agriculture in South Asia by strengthening technical efficiency advancements and optimizing economies of scale, promoting the coordinated development among countries for sustainable agricultural practices, and encouraging cleaner agricultural production for emissions reduction.

A generalization of environmental productivity analysis

This paper aims to analyze environmental Total Factor Productivity (TFP) change. Indeed, innovative environmental TFP measures are introduced through convex and non convex environmental production processes. Hence, the impacts of input and output quality change on environmental productivity variation are underscored. In addition, general decomposition of the new ratio- and difference-based environmental TFP measures is proposed. Finally, an empirical example is provided to illustrate these propositions.

Effect evaluation of the main grain producing area policy on agricultural environmental total factor productivity

Effect evaluation of the main grain producing area policy on agricultural environmental total factor productivity

A Multi-stage Malmquist-Luenberger Index to Measure Environmental Productivity in China's Iron and Steel Industry

This paper develops a multi-stage Malmquist-Luenberger index (MLPI) model by considering the joint production of desirable and undesirable outputs in multiple production processes. The proposed approach not only evaluates the environmental total factor productivity (ETFP) growth of the whole system but also investigate the progress and regress of each sub-process, i.e., the iron-making sub-process and the steel-making sub-process. Driving factors of ETFP change are identified through multi-stage MLPI decomposition. With an application of the proposed model in China's 48 iron and steel enterprises over the period of 2009–2013, the validity of the proposed models has been demonstrated. Moreover, this study explores the regional difference analysis of system and multi-stage ETFP among 31 provinces in eastern, central and western regions. Results show that the ETFP of system, iron-making sub-process and steel-making sub-process experienced increase annually, the most important finding is that the environmental efficiency increase is the most critical driving factor in promoting ETFP growth. Technical regression of steel-making sub-process is the main source of restricting system ETFP growth. In addition, the change of system ETFP varies greatly in different regions, being highest in the eastern region, and lowest in the western region. Compared with the single-stage conventional MLPI, the multi-stage MLPI is smaller and has more discriminatory power.

Can Industrial Agglomeration Facilitate Green Development? Evidence From China

Industrial agglomeration can promote economic growth through knowledge spillover and cooperation, while it may also bring serious pollution problems. Therefore, clarifying the relationship between industrial agglomeration and green development is of great significance to the realization of China’s sustainable development. In order to study the causal relationship between industrial agglomeration and green development, this paper first adopts the Overall Malquist Index method to more accurately measure the green development of Chinese cities characterized by environmental total factor productivity (ETFP). Subsequently, this paper uses the panel data of prefecture-level cities from 2003 to 2016 to study the causal relationship between industrial agglomeration and green development. We found that China’s current industrial agglomeration can promote green development. Mechanism analysis shows that industrial agglomeration can promote green development through improving the technological innovation, strengthening government intervention and optimizing the industrial structure. Finally, heterogeneity analysis shows that industrial agglomeration has a stronger role in promoting green development in areas where the economy is more developed, the degree of resource dependence is lower, and the degree of industrial agglomeration is higher. This paper not only provides theoretical and policy references for the research on industrial agglomeration and green development, but also provides experience reference for other developing countries.

The Evolution and Influencing Factors of Total Factor Productivity of Grain Production Environment: Evidence from Poyang Lake Basin, China

The total factor productivity (hereafter TFP) of grain production is important to achieve balanced development, while environmental factors are an important part of TEP. In order to explore the characteristics and patterns of the temporal and spatial evolution of the environmental total factor productivity (hereafter ETFP), the Malmquist-Luerberger index, and the spatial autoregressive panel (SAR panel) model were adopted to analyze the evolutionary rules and the influencing factors of ETFP. In this study, we took Poyang Lake, one of China’s main grain production areas, as a study area, and carried out empirical research based on grain production statistical data. The results show that: (1) ETFP shows a growth trend with the increase of grain production from 2001 to 2017, and a great potential for improvement exists. Moreover, from the perspective of time sequence evolution and decomposition of ETFP, which belongs to the dual-track driver of environmental technical efficiency and environmental technological progress, relevant technologies play an important role in promoting the improvement of TEFP; (2) Given that the objective conditions of gain production remain unchanged, the fact that the urbanization rate and average annual rainfall have a negative effect on ETFP, the explanatory variables such as the business scale per worker, the proportion of grain growing population, industrial agglomeration, the proportion of grain sown area and the average annual temperature all play a positive role. Among the variables, the business scale per worker and the proportion of grain growing population significantly affect ETFP at the 1% level. The average annual rainfall, industrial agglomeration and the proportion of grain sown area significantly affect the ETFP at the 5% level. The average annual temperature significantly affects the ETFP at the 10% level.

Impact of Regional Green Development Strategy on Environmental Total Factor Productivity: Evidence from the Yangtze River Economic Belt, China.

Chinese government policy officially identify the Yangtze River Economic Belt (YREB) as one of regional green development strategies firstly in 2014. This strategy can be regarded as quasi-natural experiment, this paper aims to test its impact on regional environmental total factor productivity (TFP). First, slack-based measure model is used to calculate the environmental TFP from 2005 to 2017 at provincial level. Second, based on Chinese official statistics, differences-in-differences (DID) method is applied to construct an evaluation model of policy effect, combining with the kernel matching in propensity score matching (PSM) method. The results show that environmental TFP of YREB has significant spatial differences, with characteristic of high-east and low-west, its average level is 11.69 percentage points higher than the national average. YREB strategy promotes regional economic growth, but it does no effect on the regional environmental TFP yet. Modelling suggests that YREB strategy may play a role in the short term. From the significance of the control variables, infrastructure construction level is positively correlated with environmental TFP, while per capita GDP, financial development and energy consumption intensity have negative effect on environmental TFP. Based on this, policymakers should focus on green development, promoting industrial transformation, and enhancing environmental protection.

Innovation and environmental total factor productivity in China: the moderating roles of economic policy uncertainty and marketization process.

China's economic development practices are facing strict energy constraints and severe environmental pollution. Improvement of China's environmental total factor productivity (ETFP) through innovation is a major scientific focus of both policy-makers and academia. However, the boundary conditions where innovation affects ETFP are yet to be clarified. On this basis, the present study starts from two dimensions-policy context and market context, introduces economic policy uncertainty (EPU) and marketization process as moderating variables, and examines the impact mechanism of innovation on ETFP. The results show the following: (1) Innovation promotes ETFP. (2) Although EPU inhibits ETFP, it positively moderates the impact of innovation on ETFP. (3) The marketization process has an insignificant inhibitory effect on ETFP. Specifically, the development of product markets, the development of market intermediary organizations, and the legal system environment have a significant inhibitory effect on ETFP. In contrast, the marketization process positively moderates the impact of innovation on ETFP. (4) The impact of innovation on ETFP exhibits obvious regional heterogeneity. In regions with low pollution intensity, innovation and EPU promotes ETFP. The marketization process inhibits ETFP and shows a positive moderating effect. In regions with high pollution intensity, both innovation and EPU inhibits ETFP. Based on these conclusions, policy-makers should guide companies to increase investment in research and development, improve innovation capabilities, and focus on strengthening energy-saving and environmental protection technologies and process innovations. When formulating and adjusting economic policies, policy-makers should aim promote enterprise innovation and reduce the negative impact of economic policy uncertainty. Policies should fully utilize the decisive role of the market in the allocation of innovative factors and rely on market mechanisms to enhance the positive effect of innovation on regional ETFP.

Impact of Nanotechnology Patents on Green Development of China's Building Industry

The sustainable development of the building industry has drawn increasing attention around the world. Nanomaterials and nanotechnology play an important role in the processes of energy saving and reducing consumption in the building industry. Nanotechnology patents provide key technological support for the green development of the building industry. Based on patent data in China, this paper quantitatively analyzed the application of nanotechnology patents in the building industry and the time trend, regional differences, and evolution of China's nano-patent applications in the building field. In this study, the environmental total factor productivity of the building industry considering carbon constraints was determined and then used as the dependent variable to measure the green development of the building industry. On this basis, a panel data regression model was constructed to determine the impact of nano-patents on the green development of the building industry. Nanotechnology patents in the building industry can significantly improve total factor productivity. From the perspective of patent composition, technology-based patents that focus on substantial innovation can significantly promote the green development of the building industry, whereas strategic patents show a significant inhibitory effect. Regionally, the western region of China has the advantage of being less developed and thus more efficient than the central and eastern regions in the application of new nano-products. Finally, the research also showed a significant lag in the application of China's nanotechnology patents and low implementation efficiency. Nano patents can promote green development in the building industry, but there is room for improvement in the speed with which laboratory inventions are transformed into building engineering applications.

The influence of environmental efficiency on PM2.5 pollution: Evidence from 283 Chinese prefecture-level cities

Environmental inefficiency caused by the extensive economic growth pattern is considered a critical driver of the unprecedented PM2.5 (fine particulate matter) pollution in China. However, the nexus between environmental efficiency and PM2.5 concentrations has rarely been examined. We used a recently developed data envelopment analysis method to measure environmental efficiency, environmental total factor productivity, and their compositions in China at the prefecture level from 2003 to 2013 and examined the effects of environmental efficiency on PM2.5 pollution. The results indicated that improvements in environmental efficiency significantly ameliorated PM2.5 pollution. The effect of technological progress on PM2.5 reduction is limited, but the pure efficiency and scale efficiency promoted by enhanced management level and optimized production scale strongly contribute to PM2.5 mitigation. The significant spatial spillover of environmental efficiency and PM2.5 pollution introduces challenges and opportunities for lowering PM2.5 emissions. The impact of environmental efficiency on PM2.5 pollution exhibits significant spatiotemporal heterogeneity, and the strength of influence tends to increase with PM2.5 concentration and become more pronounced over time. Furthermore, several socioeconomic factors are related to PM2.5 pollution, which implies that PM2.5 control is a complex system and requires a comprehensive policy mix.