Green Productivity Growth Research Articles

Marketization, environmental regulation, and eco-friendly productivity: A Malmquist–Luenberger index for pollution emissions of large Chinese firms

Marketization requires individuals and firms to increase energy efficiency and improve environmental quality, and various levels of governments interested in environmental protection have adopted tough environmental regulations. This paper develops data envelopment analysis (DEA) to measure unified efficiency at the firm level by introducing energy utilization and pollution emissions. A Malmquist–Luenberger efficiency model with undesirable output follows radial measurement by directional distance function type. We analyze green productive efficiency in relation to polluting emissions using a large dynamic panel dataset of 229,491 Chinese manufacturing firms from 1998 to 2012. We identify that marketization and environmental regulation both significantly facilitate green productivity. Further, our findings imply that both marketization and regulatory effects weakened from the tenth to the twelfth Five-Year Plans. Regarding effects across ownership type, green total factor productivity (TFP) growth of state-owned enterprises is significantly affected by regulation but not marketization. Private and foreign-owned firms are both significantly affected by marketization and regulation. Regionally, green TFP growth is positively associated with marketization and regulation in central China. East China’s green TFP growth is motivated by marketization, and West China’s green TFP growth is strongly driven by regulation.

Environmental regulation induces technological change and green transformation in Chinese cities

Improving green total factor productivity is an important step for China’s green transformation. By proposing a meta-frontier Malmquist Luenberger productivity indicator, this paper attempts to investigate China’s green productivity evolution and its determinants at the city level during the period of 2003–2016. Our results reveal that China has improved green productivity, and that exogenous technological change acts as the dominant force to drive the change of green productivity. Overall, the effects of technological change induced by environmental regulation (TCIER) have not been fully manifested. Further, we find significant spatial heterogeneities in TCIER: western China shows the highest contribution of TCIER to changes in green productivity, followed by central China, and the contribution is negative in eastern China, due to the region’s relatively lower growth rate in environmental regulation intensity. Nevertheless, from the perspective of evolutionary trends, the TCIER scores of all three regions exhibit upward trends during the review period, ultimately contributing positively to green productivity growth during the 12th Five-Year Plan period (2011–2015).

How do environmental regulation and foreign investment behavior affect green productivity growth in the industrial sector? An empirical test based on Chinese provincial panel data

This study investigates the impact of environmental regulations (ERs) and foreign direct investment (FDI) on the green total factor productivity (GTFP) of the industrial sectors in 30 provinces in China by controlling human capital, technological innovation, energy structure, degree of opening up, and ownership structure for the period of 2004–2017. This not only helps to explain the influence path of ERs and FDI on green economic growth, but also effectively measures the moderating effect of ERs on technology spillover from FDI. The purpose of this paper is to explore the relationship between ERs, FDI and industrial GTFP from the perspective of regional heterogeneity, focusing on studying how ERs regulate the impact of FDI on GTFP. By constructing an influence mechanism of ERs and FDI on industrial GTFP, this study employs the feasible generalized least squares (FGLS) model and dynamic generalized method of moments (GMM) model to analyze the effects of ERs, FDI and their cross-terms on GTFP. The empirical results show that (1) the relationship between ERs and GTFP is not linear, but “U”-shaped and China is still in the left half of the “U”-shaped curve; (2) FDI flowing into China has a “pollution heaven” effect on the GTFP in the eastern and central regions while a “pollution halo” effect on the GTFP in the western region; (3) the strengthening of ERs weakens the negative effect of FDI on GTFP and plays a role in “screening” foreign investment; and (4) the spatial heterogeneity could affect the synergistic effect between ERs and FDI. Therefore, it is necessary for China to consider a series of environmental policies to “screen” inward FDI to ensure its move to a green economy benefits its own sustainable development by contributing to the increase in GTFP.

Green credit regulation, induced R&D and green productivity: Revisiting the Porter Hypothesis

This paper investigates the causal effect of green credit regulation policy on green productivity and revisits the Porter hypothesis. By separating R&D into environmentally induced R&D and production R&D, we find that green credit regulation policy significantly improves green total factor productivity (GTFP) growth rather than input-output TFP. We further show that environmentally induced R&D is the driver of GTFP, while production R&D significantly improves the input-output TFP. Finally, our estimations indicate that internal financing intermediation is used to finance environmental R&D projects due to the high cost of environmental innovation.

Green productivity growth and competition analysis of road transportation at the provincial level employing Global Malmquist-Luenberger Index approach

Road transportation has been playing an irreplaceable role in the process of pursuing sustainable development. This study employs a Global Malmquist-Luenberger Index approach to evaluate the green productivity growth of this industry at the provincial level based on the Data Envelopment Analysis and Directional Distance Function. Further, it decomposes green productivity growth into changes in various types of efficiency and technological progress. Finally, this study structures a novel quadrant matrix analysis framework based on the green productivity growth rate and stability, using the matrix to analyze the performance of provincial road transportation industries. This analysis results show that: (1) a fluctuating and slowly upward trend of green productivity over time exists; (2) at the regional level, the road transportation industries in Western and Central China achieved green productivity growth because of the catch-up effect and the economies of scale, respectively; (3) the green productivity in China’s Eastern area (the most developed area) declined, giving opportunities for improvement in both technology and efficiency; and (4) the southeast coast and border provinces showed large fluctuations in terms of green productivity of road transportation because of the impact of foreign trade environment. Implications for transportation system planning are provided based on the results.

Do renewable energy technology innovations promote China's green productivity growth? Fresh evidence from partially linear functional-coefficient models

Abstract Renewable energy technology innovation can benefit the environment by promoting green productivity, as proposed by existing theoretical studies. However, recent uneven developments of both environmental performance and renewable energy technology among regions in China remind us to revisit the above theoretical link. In this paper, we relax the hypothesized homogeneity and linearity in traditional empirical models to investigate the effects of renewable energy technology innovation on China's green productivity. The results of the partially linear functional-coefficient models show that the effect of renewable energy technological innovation on green productivity is significant only when the relative income level of a province passes a critical turning point. Beyond the turning point, such an effect increases with the growth of relative income levels. Finally, we provide provincial specific policy implications based on the estimated nonparametric relationship between renewable energy technology innovation and green productivity.

Technical Change and Green Productivity

When technologies could be “dirty” and “clean” in the context of green development, technical change does not necessarily mean (green) productivity growth. This paper studies the nonlinear impact of technical change on green productivity in China by applying a panel smooth transition regression approach with a panel data set of 284 prefecture-level cities from 2004 to 2015. Green productivity is measured by the meta-frontier Malmquist–Luenberger productivity growth (MML) index. Technical change is considered in three dimensions: indigenous technical change indicated by the stock of knowledge based on patents, technology transfers from foreign direct investment (FDI), and absorptive capacity. We find a non-linear relationship between technical change and green productivity contingent on specific economic situations and the city’s endowment of natural resources. In general, indigenous technical change shows an adverse effect on green productivity in China, which is much more prominent in the resource-dependent cities than in the non-resource-dependent cities. Technology transfers from FDI may either improve or hinder green productivity growth as economic situations change, while absorptive capacity has a small but positive effect. Also, these two effects are affected by the city’s endowment of natural resources. Accordingly, we discuss some policy implications.

Strategic interaction of environmental regulation and green productivity growth in China: Green innovation or pollution refuge?

The strategic interaction of inter-regional environmental regulation is a typical feature of local government behavior in China, which can affect the green productivity growth in the local region through the Porter effect and the pollution refuge effect. Based on the panel data of 274 prefecture-level cities from 2005 to 2015 in China, this thesis constructs a comprehensive indicator of environmental regulation, accurately identifies the mode of China's inter-regional strategic interaction of environmental regulation and calculates the green total factor productivity, green technology efficiency and green technology progress in 274 cities. In addition, this thesis also conducts an empirical analysis on the effect of the strategic interaction of environmental regulation on the green productivity in China. The author of this thesis finds that: (1) the mode of strategic interaction of environmental regulation in China is complementary “race to the top”, that is, the local region will strengthen its environmental regulation, if the environmental regulations in its adjacent regions are strengthened; (2) the environmental regulation in the local region promotes the green productivity in China, while the weighted environmental regulation in the adjacent regions inhibits the green productivity. What's more, environmental regulations in economic-proximity regions have greater negative spatial spillover effects on green productivity in the local region, compared with those in geographic-proximity regions; (3) environmental regulation in the local region and its adjacent regions can affect the green productivity growth in China through the channels of green innovation and pollution transfer, that is, the Porter effect and pollution refuge effect coexist in China. They mean that in the process of China's regional environmental governance, it is necessary to reduce pollution transfer, and promote green innovation so as to achieve sustainable and high-quality economic development.

Spatial-Temporal Characteristics of Agriculture Green Total Factor Productivity in China, 1998-2016: Based on More Sophisticated Calculations of Carbon Emissions.

Environmental costs should be taken into account when measuring the achievements of China’s agricultural development, since the long-term extensive development of agriculture has caused huge environmental pollution. This study took agricultural carbon emissions as an undesired output to estimate the agricultural development efficiency in 31 provinces of China from 1998 to 2016, based on the green total factor productivity, as assessed by the slacks-based measure directional distance function and constructing the global Malmquist–Luenberger index. We measured agricultural carbon emissions in terms of five aspects: agricultural materials, rice planting, soil, livestock and poultry farming, and straw burning, and then compared the green total factor productivity index and the total factor productivity index. The study came to the following conclusions: (1) the green technology efficiency change was smaller than the technology efficiency change at first, but the gap between them is narrowing with time, such that the former is now larger than the latter; (2) the green technology efficiency was in a declining state and the green technology progress was increasing, promoting the green total factor productivity growth, from 1998 to 2016; and (3) China’s agricultural green total factor productivity increased by 4.2% annually in the east, 3.4% annually in the central region, and 2.5% annually in the west.

Environmental regulation and green productivity growth: Empirical evidence on the Porter Hypothesis from OECD industrial sectors

Green growth has become an important development strategy for OECD countries and governments have correspondingly implemented various environmental regulation policies, whereas few studies have discussed the impacts of environmental regulation on green productivity growth in OECD countries. Based on a panel data of OECD countries' industrial sectors, this study analyzes the stringency of environmental regulation policies and measures green productivity growth using an extended SBM-DDF approach. The dynamic panel regression investigates the impacts and mechanism of environmental policy stringency on green productivity growth in OECD countries’ industrial sectors. The main results are: (i) Porter hypothesis is validated that the environmental policy has a positive impact on green productivity growth within a certain level of stringency (lower than 3.08); (ii) The impact turns to be adverse when the environmental regulation policy is stringent over a certain level, as the compliance cost effect is higher than innovation offset effect. The findings provide new empirical evidence for the strong version of the Porter Hypothesis and some implications for OECD countries to further promote green growth.

Which factors stimulate industrial green total factor productivity growth rate in China? An industrial aspect

AbstractAs an important evaluation transformation index, exploring green total factor productivity (GTFP) trend and related key factors is significant for China's economy entering into high‐quality development and green transformation. In this study, stochastic frontier analysis (SFA) and kernel density function are used to evaluate GTFP growth trend for 36 China's industrial sectors during 2000–2016, and system generalized method of moment is used to explore their key driving factors. The results are as follows: First, SFA supplies efficient estimation for GTFP growth information. The 36 industrial sectors are classified into three emission types, that is, high‐, moderate‐, and low emission. Second, GTFP growth differs significantly in three types of sectors. With kernel density results for 36 sectors, the curve of GTFP growth has shifted upward and toward the left since 2010. For high‐emission type sectors, their kernel curve has also moved upward and toward the left. The curve of moderate‐emission type sectors significantly shifted toward the left, whereas the curve of low‐emission type moved upward. Third, based on regression estimation results, environmental regulatory policy, resource input structure, foreign direct investment, and energy‐type structure significantly influence GTFP growth. Technology innovation makes insignificant impact on GTFP for industrial sectors. In conclusion, sectorial heterogeneity should be paid more focus in order to improve their growth, especially for high‐emission type sectors. Green technology innovation is the most potential factor in the future to stimulate GTFP growth in China. © 2019 Society of Chemical Industry and John Wiley & Sons, Ltd.

Decentralized environmental regulations and plant‐level productivity

AbstractUsing the framework provided by the Porter hypothesis, we study the impact of environmental regulations and enforcement policies on plant‐level green total factor productivity (TFP) growth and its components related to efficiency change and technical change. The detailed microdata we use are from Sweden and for the pulp and paper industry. This industry is the source of significant amounts of water and air pollution and is one of the most heavily environmentally regulated manufacturing industries. Sweden has a unique decentralized regulatory structure where the manufacturing plants have to comply with plant‐specific regulatory standards stipulated at the national level, as well as decentralized local supervision and enforcement. Our empirical results point to beneficial impacts of the environmental policies on plants' green TFP growth and sustainable production practices. We also find that political economy considerations are important, as the presence of the Green Party and aspects like plant size (with corresponding local and regional economic effects) matter in enforcement of the standards.

Green manufacturing and environmental productivity growth

PurposeDue to stringent regulations on carbon emissions, green manufacturing has become a critical issue in manufacturers’ strategic planning. Manufacturers are greening production through carbon abatement activities. The purpose of this paper is to investigate the factors that influence the effects of carbon abatement on environmental productivity growth.Design/methodology/approachUsing data envelopment analysis with directional distance function, this study examines productivity growth associated with carbon abatement under regulated and unregulated production technologies. A pollution abatement index (PAI) is constructed for determining the effects of carbon abatement on environmental productivity growth. Panel data of 18 European countries in paper and pulp and coke sectors are collected for the analysis.FindingsThe empirical findings reveal that carbon abatement may positively or negatively affect environmental productivity growth which is dependent on the nature of technology in a sector, the innovation capabilities of a country and environmental regulations.Originality/valueConventional approaches in measuring productivity changes do not normally take undesired outputs (e.g. carbon emissions) into consideration. This study contributes to literature by constructing a PAI that considers productivity changes under a joint production technology (where both desired and undesired outputs are considered). The findings enhance current understandings on the effectiveness of carbon abatement activities and help managers establish corporate environmental strategies to adopt green manufacturing.

Characterizing the Difference between Indirect and Direct CO2 Emissions: Evidence from Korean Manufacturing Industries, 2004–2010

This study measures and decomposes green productivity growth of Korean manufacturing industries between 2004 and 2010 using the Malmquist-Luenberger productivity index. We focus on differences in the measures of productivity growth by distinguishing carbon emissions from either end-user industries or the electricity generation industry. Empirical results suggest three main findings. First, the efficiency of total emissions is higher than that of direct emissions except for the shipbuilding industry. Second, green productivity in the manufacturing sector increased during the study period. Finally, green productivity depends on the indirect emissions of each industry. These results indicate that policymakers need to deliberately develop policy tools for mitigating carbon emissions of the manufacturing industrial sectors based on our empirical findings.

Green Total Factor Productivity Growth and Its Determinants in China’s Industrial Economy

This paper employs directional distance function (DDF) and the global Malmquist–Luenberger (GML) productivity index to measure the green total factor productivity (GTFP) growth of China’s 36 industrial sectors from 2000 to 2014. Based on this, this paper ascertains the determinants of GTFP from the perspectives of institution, technology, and structure, and the determinant factors that affect GTFP are empirically tested by a dynamic panel data (DPD) model. The research shows that, considering energy consumption and environmental undesirable outputs, the industrial GTFP goes backwards by 0.02% per year on average, and the contributions of GTFP to output growth are far from the target value of 50% in all industrial sectors, which indicates that the growth of industrial economy sacrifices resources and environment to a certain degree. In terms of the determinant factors of GTFP, environmental regulation does improve the GTFP, while environmental regulation is difficult to promote GTFP by the route of technological innovation. Compared with technology importation, the driving effect of independent research and development on GTFP is obvious, especially promoting the GTFP of moderately and lightly polluting industries, while the driving effect in heavily polluting industries is poor. Endowment structure and property right structure play a positive role in improving GTFP, but the impacts of capital structure and energy structure on GTFP are poor.

A Dynamic Analysis of Green Productivity Growth for Cities in Xinjiang

Improving green productivity is an important way to achieve sustainable development. In this paper, we use the Global Malmquist-Luenberger (GML) index to measure and decompose the green productivity growth of 18 cities in Xinjiang over 2000–2015. Furthermore, this study also explores factors influencing urban green productivity growth. Our results reveal that the urban green productivity in Xinjiang has slowly declined during the sample period. Technological progress is the main factor contributing to green productivity growth, while improvements in efficiency lag behind. Implementing stricter environmental regulation, improving infrastructure, and appropriately enhancing the spatial agglomeration of economic activities may improve green productivity, while the increase in the size of the industrial base in the near future will likely hinder green productivity growth. Based on these results, this paper puts forward corresponding policy suggestions for the sustainable development of the urban economy in Xinjiang.

Promoting green productivity growth for China's industrial exports: Evidence from a hybrid input-output model

Stimulated by low labor cost and loose environmental regulations, China's industrial exports have benefited significantly since joining the World Trade Organization (WTO). However, the extensive growth model in the past several decades has led to environmental degradation. China is now shifting her development pattern to a more sustainable model. Using a hybrid input-output model, this paper found that total energy coefficients fell sharply between 1997 and 2002, and 2007 and 2012. The total energy consumption and CO2 emission embodied in China's industrial exports grew by more than 100% from 2002 to 2007, with little variation from 2007 to 2012. Subsequently, Malmquist-Luenberger productivity index (MLPI) is employed to assess the green productivity growth in the sector. The decomposition of the MLPI is further conducted. This suggests that efficiency changes from 2002 to 2007 and 2007 to 2012 are lower than 1, indicating that technical change is the main contributor to MLPI. Finally, policy implications are provided with emphasis on dissemination of new conservation technologies.

Term Limits of Public Officials, Environmental Regulations, and Sustainable Development: An Analysis Based on Empirical Spatial Econometrics

ABSTRACTThis study investigates the impact of public officials’ term limits and environmental regulations on sustainable development using provincial panel data in China for the period 1986–2013. Applying empirical spatial econometrics, the spatial dependence of green productivity growth, calculated by the global Malmquist–Luenberger (ML) index, across provinces has been supported. There appears to be a U relationship between the term limits of provincial governors and the green productivity growth. The Porter hypothesis does not exist in this sample. Finally, the study provides some policy implications.

Growth of Green Total Factor Productivity and Its Determinants of Cities in China: A Spatial Econometric Approach

ABSTRACTAs pollution in Chinese cities worsens, there is renewed interest in promoting sustainable development across the country. This article introduces the global Malmquist–Luenberger productivity index (ML) to measure green total factor productivity (TFP) growth of 270 Chinese cities over the period 2003–2013. Empirical spatial econometrics is applied to analyze the spatial spillovers and the determinants of green TFP growth. Our results show that green TFP is a useful metric for measuring development, and that spatial spillover effects do exist among neighboring cities of similar development. Finally, the study provides some policy implications.

Aggregate green productivity growth in OECD’s countries

Most of previous research about Total Factor Productivity (TFP) at the macro level only emphasizes technical effect and technological progress at the country level, but it ignores structural effect for a group of countries at the aggregate level. This paper attempts to measure the green productivity evolution incorporating carbon dioxide emissions based on the Luenberger productivity indicator for a group of 30 OECD countries over the period of 1971−2011. We propose a novel decomposition for green productivity growth at the aggregate level which separates productivity changes into three components: technological progress, technical efficiency change, and structural efficiency change. The structural effect captures the heterogeneity in the combination of input and output mixes among countries that can impact productivity growth at a more aggregate level. In the literature, this effect has not been quantified for a group of nations such as the OECD countries. Our results indicate that the traditional TFP index underestimates green growth which is motivated by the effective and efficient environmental policies of the OECD. For the last two decades, the green productivity growth has been mainly driven by technology progress.