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Keywords = Malmquist–Luenberger (M-L) productivity index

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17 pages, 1823 KiB  
Article
Can Environmental Protection Tax Promote Urban Green Transformation? Experimental Evidence from China
by Zhankun Qi, Feng Long, Fenfen Bi, Xue Tian, Ziwei Qian, Xianming Duan and Chazhong Ge
Sustainability 2024, 16(20), 9011; https://doi.org/10.3390/su16209011 - 17 Oct 2024
Cited by 1 | Viewed by 1644
Abstract
As one of China’s important environmental and economic policies, the environmental protection tax (EPT) is important in promoting economic and social green transformation. In this study, the green total factor productivity (GTFP) of 283 prefecture-level cities in China from 2013 to 2022 was [...] Read more.
As one of China’s important environmental and economic policies, the environmental protection tax (EPT) is important in promoting economic and social green transformation. In this study, the green total factor productivity (GTFP) of 283 prefecture-level cities in China from 2013 to 2022 was calculated using a Super Slack-Based Model (Super-SBM) and the Malmquist-Luenberger (ML) index, which includes undesirable outputs. Moreover, the implementation effect of environmental tax on promoting urban green transformation is identified through the difference-in-differences (DID) model. This study revealed that (1) an EPT can significantly increase the GTFP of a city and promote its green transformation. (2) Industrial structure optimization and technological innovation are important mechanisms through which EPT drives urban green transformation. (3) The implementation effect of EPT in promoting urban green transformation presents significant policy differences across geographic locations, whether cities are key environmental protection cities or types of resource-based cities. EPT can significantly promote the green transformation of local cities, which in turn can positively affect the green transformation of neighboring cities. Based on this study’s conclusions, suggestions are put forward to improve the EPT system to promote urban green transformation. Full article
(This article belongs to the Special Issue Environmental Governance and Environmental Responsibility Research)
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26 pages, 8036 KiB  
Article
Dynamic Analysis of Urban Land Use Efficiency in the Western Taiwan Strait Economic Zone
by Haixiang Xu and Rui Zhang
Land 2024, 13(8), 1298; https://doi.org/10.3390/land13081298 - 16 Aug 2024
Cited by 1 | Viewed by 1456
Abstract
The Western Taiwan Strait (WTS) Economic Zone connects the Yangtze River Delta and the Pearl River Delta, playing a significant role in China’s coastal economy and forming part of the East Asian economic structure. This study used panel data from 20 cities in [...] Read more.
The Western Taiwan Strait (WTS) Economic Zone connects the Yangtze River Delta and the Pearl River Delta, playing a significant role in China’s coastal economy and forming part of the East Asian economic structure. This study used panel data from 20 cities in the WTS Economic Zone, spanning 2011 to 2020, to investigate urban land use efficiency and its dynamic evolution characteristics. The study used a super-efficiency EBM model, which accounts for undesirable outputs, combined with kernel density estimation and Malmquist–Luenberger (ML) index analysis, to thoroughly examine the changes in total factor productivity (TFP) of urban land use and the factors driving these changes within the WTS Economic Zone. The findings are as follows: (1) From 2011 to 2020, the overall trend of urban land use efficiency in the WTS Economic Zone was upward, with coastal areas generally exhibiting higher urban land use efficiency compared to inland areas. (2) The urban land use efficiency of cities in the WTS Economic Zone displayed four types of changes: rising, stable, “U”-shaped, and inverted “U”-shaped. (3) The TEP index of the WTS Economic Zone exhibited a right-leaning “M” trend. Technological change was the primary driver of enhanced urban land use efficiency, although there is still room for improvement in technical efficiency. Based on these findings, this study proposes policy insights to foster high-quality development of urban land use efficiency in the WTS Economic Zone. Full article
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27 pages, 1030 KiB  
Article
The Influence Mechanism of Bidirectional Foreign Direct Investment on Green Total Factor Productivity in China’s Manufacturing Industry
by Zongxian Feng, Huiting Hua and Lingle Wang
Sustainability 2024, 16(15), 6386; https://doi.org/10.3390/su16156386 - 25 Jul 2024
Viewed by 1295
Abstract
Recently, China has actively advocated green transformation in manufacturing. This paper applies the Malmquist–Luenberger (ML) index method to measure the green total factor productivity (GTFP) and its decomposition of 28 segments of China’s manufacturing industry from 2004 to 2020; then, it empirically investigates [...] Read more.
Recently, China has actively advocated green transformation in manufacturing. This paper applies the Malmquist–Luenberger (ML) index method to measure the green total factor productivity (GTFP) and its decomposition of 28 segments of China’s manufacturing industry from 2004 to 2020; then, it empirically investigates their causal relationship and impact mechanism on bidirectional foreign direct investment (FDI). The results show that inward foreign direct investment (IFDI) and outward foreign direct investment (OFDI) significantly inhibit GTFP, whereas the interactive development level between the two (DFDI) significantly promotes GTFP during the sample period. After decomposing GTFP, it is found that IFDI or OFDI has a significant promotional effect on green technical change (GTC) but an inhibitory effect on green technical efficiency change (GEC), while DFDI has a promotional effect on GTC or GEC. Further research also finds that OFDI can effectively weaken the inhibitory effects in the long run; IFDI, OFDI, and DFDI have the same direction of impact on GTFP or GEC, only showing heterogeneity at the significant level, while their impact on GTC has uncertainty in different types of manufacturing industries. The more rational the manufacturing industry structure, the more significant the promotional effect of IFDI, OFDI, and DFDI on GTFP. Full article
(This article belongs to the Special Issue Resource Price Fluctuations and Sustainable Growth)
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18 pages, 4232 KiB  
Article
Environmental Regulation Effect on Green Total Factor Productivity: Mediating Role of Foreign Direct Investment Quantity and Quality
by Yusen Luo, Zhengnan Lu, Chao Wu and Claudia Nyarko Mensah
Int. J. Environ. Res. Public Health 2023, 20(4), 3150; https://doi.org/10.3390/ijerph20043150 - 10 Feb 2023
Cited by 9 | Viewed by 2641
Abstract
Green total factor productivity (GTFP) is an excellent index for green development. The objective of this study was to check whether environmental regulation (ER) can affect GTFP through the mediating role of foreign direct investment (FDI) quantity and quality. Using the super-efficiency Epsilon-based [...] Read more.
Green total factor productivity (GTFP) is an excellent index for green development. The objective of this study was to check whether environmental regulation (ER) can affect GTFP through the mediating role of foreign direct investment (FDI) quantity and quality. Using the super-efficiency Epsilon-based measure (EBM) model and a Malmquist–Luenberger (ML) index, China’s GTFP growth was measured during 1998–2018. On this basis, we adopted a Systematic Generalized Method of Moments (SYS-GMM) to analyze the effect of ER on GTFP. The findings show that China’s GTFP declined first and rose again during the sample period. GTFP in the coastland was greater than that in the inland region. ER positively affected China’s GTFP growth. FDI quantity and quality mediated the nexus between ER and GTFP growth in the whole nation. Specifically, this mediation role of FDI quantity and quality was only significant in coastal China. Additionally, financial development can also boost GTFP growth in China. Given the importance of developing a green economy, the government should improve the FDI quality and attract green FDI. Full article
(This article belongs to the Special Issue The Impact of Environmental Regulation on Green Economic Development)
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19 pages, 2380 KiB  
Article
Research on the Spatial-Temporal Distribution Characteristics and Influencing Factors of Carbon Emission Efficiency in China’s Metal Smelting Industry—Based on the Three-Stage DEA Method
by Linan Gao, Xiaofei Liu, Xinyi Mei, Guangwei Rui and Jingcheng Li
Sustainability 2022, 14(24), 16903; https://doi.org/10.3390/su142416903 - 16 Dec 2022
Cited by 4 | Viewed by 2211
Abstract
The threat of global climate change has encouraged the international community to pay close attention to the levels of greenhouse gases, such as carbon dioxide, in the atmosphere. China has the world’s largest metal smelting industry, which is a major energy-consuming and carbon-emitting [...] Read more.
The threat of global climate change has encouraged the international community to pay close attention to the levels of greenhouse gases, such as carbon dioxide, in the atmosphere. China has the world’s largest metal smelting industry, which is a major energy-consuming and carbon-emitting industry. Thus, this industry’s low-carbon transition is of great significance. Carbon emission efficiency (CEE) is a key indicator for the metal smelting industry to prioritize sustainable development. This paper applies a three-stage data envelopment analysis model with undesirable outputs to estimate CEE for 30 provinces from 2005 to 2020 in China, and analyzes the influencing factors using a spatial Durbin model. The results show that the CEE level generally improved in all Chinese provinces during the sample period, but the average CEE in the eastern region was 1.05 compared to 1.07 in the western and central regions, with the latter two regions progressing faster in terms of low carbon production capacity. The national average Malmquist–Luenberger (ML) index demonstrates a significant increase in technical efficiency across regions in 2010 and 2017, peaking in 2017. The study also suggests that current green credit and environmental regulations are not effective in promoting CEE improvements in the metal smelting industry, and that existing policies should be modified. Moreover, the spatial regression results indicate that the cross-regional transfer of low-carbon production technologies in China is largely complete. This study provides a more objective evaluation of the CEE levels of metal smelting across China, providing the government with a new perspective to guide the green transformation of energy-intensive industries. Full article
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19 pages, 4598 KiB  
Article
Measurement of Green Total Factor Productivity and Its Spatial Convergence Test on the Pig-Breeding Industry in China
by Ning Geng, Zengjin Liu, Xuejiao Wang, Lin Meng and Jiayan Pan
Sustainability 2022, 14(21), 13902; https://doi.org/10.3390/su142113902 - 26 Oct 2022
Cited by 7 | Viewed by 2093
Abstract
The pig-breeding industry is one of the pillar industries of China’s agriculture. Improving the green total factor productivity of pig breeding is the basis for ensuring the stable supply of pork, and is also the key to the green transformation of the pig [...] Read more.
The pig-breeding industry is one of the pillar industries of China’s agriculture. Improving the green total factor productivity of pig breeding is the basis for ensuring the stable supply of pork, and is also the key to the green transformation of the pig industry. The existing studies about the green total factor productivity of pig breeding lack an analysis of regional coordination and the spillover of spatial technology efficiency at the macro level, and most studies focus on the impact of agricultural production’s environment pollution and other undesirable outputs. Based on the input–output index system of the pig-breeding industry’s green production, the DDF directional distance function model and the Malmquist–Luenberger (ML) productivity index were combined to measure the green total factor productivity of the pig-breeding industry. Moran’s I-Theil index model was used to measure and reveal the technical efficiency differences among the dominant regions of the pig-breeding industry in China and the σ-convergence test was adopted to reveal the convergence trend of green total factor productivity. The results showed that: (1) The growth level of green total factor productivity of pig breeding in China was generally low from 2006 to 2018, and there were obvious regional and scale differences. (2) The green total factor productivity of pig breeding in each province had spatial autocorrelation; that is, there was technology spillover. From 2006 to 2018, with the advance of time, a pattern of gradual evolution from low-level equilibrium to high-level imbalance was formed. (3) Through the convergence test, the convergence trend of large and medium-scale development between different regions fluctuated, while the convergence trend of small-scale development between different regions was not obvious. Therefore, it is necessary to increase investment in technological innovation, promote the large-scale and standardized development of the pig-breeding industry, and strengthen the promotion of technology in producing areas with advantages in pig breeding. Full article
(This article belongs to the Section Environmental Sustainability and Applications)
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17 pages, 343 KiB  
Article
Impact of Environmental Regulation on the Green Total Factor Productivity of Dairy Farming: Evidence from China
by Chenyang Liu, Lihang Cui and Cuixia Li
Sustainability 2022, 14(12), 7274; https://doi.org/10.3390/su14127274 - 14 Jun 2022
Cited by 19 | Viewed by 3104
Abstract
Environmental regulation is essential to promote green and sustainable development in dairy farming. Nevertheless, limited studies have focused on the impact of environmental regulation on the green total factor productivity (GTFP) of dairy farming. This study measures the GTFP of dairy farming in [...] Read more.
Environmental regulation is essential to promote green and sustainable development in dairy farming. Nevertheless, limited studies have focused on the impact of environmental regulation on the green total factor productivity (GTFP) of dairy farming. This study measures the GTFP of dairy farming in 27 provinces in China during 2009–2020 using the Slack Based Measure (SBM) model and the Malmquist–Luenberger (ML) productivity index. In addition, random effects and threshold regression models are used to measure the impact of environmental regulations on the GTFP of dairy farming. The results demonstrate the fluctuating growth of the GTFP of dairy farming and that technical efficiency is the primary driver of the GTFP growth. The annual growth rate of GTFP is the highest in large-scale dairy farming (3.27%), followed by medium-scale dairy farming (2.73%) and small-scale dairy farming (1.98%). Furthermore, environmental regulation positively affects the GTFP and has a threshold effect on the GTFP, with the urban–rural income gap as the threshold variable in medium-scale dairy farming and small-scale dairy farming. The impact on the GTFP can be significantly negative if the urban–rural income gap crosses the threshold value. Overall, this study provides some policy recommendations for attaining green and sustainable dairy farming development in China. Full article
19 pages, 3293 KiB  
Article
Evaluation and Dynamic Evolution of the Total Factor Environmental Efficiency in China’s Mining Industry
by Xiangqian Wang, Shudong Wang and Yongqiu Xia
Energies 2022, 15(3), 1232; https://doi.org/10.3390/en15031232 - 8 Feb 2022
Cited by 9 | Viewed by 2301
Abstract
The mining industry plays an extremely important strategic role in China’s economic and social development. In the new era of pursuing circular/green/efficient development, the evaluation of the total factor environmental efficiency (TFEE) of China’s mining industry is essential for alleviating resource waste and [...] Read more.
The mining industry plays an extremely important strategic role in China’s economic and social development. In the new era of pursuing circular/green/efficient development, the evaluation of the total factor environmental efficiency (TFEE) of China’s mining industry is essential for alleviating resource waste and environmental pollution. The Epsilon-Based Measure (EBM) model effectively solves the shortcomings of radial and non-radial DEA models. In addition, the Malmquist–Luenberger (ML) index can measure the dynamic change of efficiency value. Combining the EBM model and the ML productivity index, this paper evaluates the TFEE from the static and dynamic perspective in China’s 31 provincial mining industries over the period 2007–2016. The Theil index is employed to reveal the root of the overall provincial TFEE gap (OGTFEE) in China’s mining industry. The results show that the average total factor static environmental efficiency (TFSEE) of China’s provincial mining industry exhibits a low score of 0.6589 and with significant spatio-temporal differences. The provincial TFEE gap within four major areas (WGTFEE), especially that in east and west areas, is the main cause of the OGTFEE in China’s mining industry. Technical change contributes more to the TFEE decline in China’s mining industry. There are differences in improving the TFEE among China’s 31 provincial mining industries, and corresponding countermeasures can be formulated accordingly. This study provides theoretical and practical basis for the clean and green development of China’s mining industry. Full article
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16 pages, 1682 KiB  
Article
Analysis of Green Total Factor Productivity of Grain and Its Dynamic Distribution: Evidence from Poyang Lake Basin, China
by Bingfei Bao, Shengtian Jin, Lilian Li, Kaifeng Duan and Xiaomei Gong
Agriculture 2022, 12(1), 8; https://doi.org/10.3390/agriculture12010008 - 22 Dec 2021
Cited by 15 | Viewed by 3294
Abstract
Based on the grain production data of the counties (cities, districts) in Poyang Lake Basin, this paper uses the productivity index of Epsilon Based Measure of Malmquist Luenberger (EBM-ML Index) to analyse the green total factor productivity (GTFP) of grain in Poyang Lake [...] Read more.
Based on the grain production data of the counties (cities, districts) in Poyang Lake Basin, this paper uses the productivity index of Epsilon Based Measure of Malmquist Luenberger (EBM-ML Index) to analyse the green total factor productivity (GTFP) of grain in Poyang Lake Basin. Kernel density function and Markov analysis are used to discuss the dynamic evolution process of the distribution of GTFP of grain. The results show the following: (1) From the time dimension, the GTFP of grain is on the rise and fluctuates more frequently from 2001 to 2017, and its trend of change is determined by the combination of technical efficiency and technological progress. Moreover, from a spatial dimension, the number of counties (cities, districts) with GTFP of grain greater than 1.0 has shown an overall increase, indicating that the overall level of GTFP of grain is increasing. (2) According to the kernel density estimation results, the crest of the main peak of the kernel density curve corresponding to the GTFP of grain in Poyang Lake Basin shifts to the right, and the area formed by the right part of the GTFP of grain corresponding to the crest of the main peak of its kernel density curve gradually increases. The peak of the kernel density curve changes from “multi-peak mode” to “single-peak mode,” and the height of the main peak of the kernel density curve of GTFP of grain shows an overall decrease. Meanwhile, the right tail of the kernel density curve shows an overall extending trend. (3) According to the estimation results of the Markov chain, the GTFP of grain in Poyang Lake Basin is highly mobile from 2001 to 2017, and the counties (cities, districts) have a certain degree of agglomeration in the low, medium-low, medium-high and high levels. In other words, the long-term equilibrium state of growth of GTFP of grain remains dispersed in the state space of four level types, indicating that the divergence state of GTFP of grain in counties (cities, districts) of Poyang Lake Basin will continue for a long time in the future. The study reveals the evolution and dynamic change of GTFP of grain in Poyang Lake Basin, which has important theoretical significance and practical value for optimizing the spatial pattern and realizing the balanced development of GTFP among counties (cities, districts) of Poyang Lake Basin and consolidating China’s food security strategy. Full article
(This article belongs to the Section Agricultural Economics, Policies and Rural Management)
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18 pages, 660 KiB  
Article
Research on the Impact Factors of Green Economy of China—From the Perspective of System and Foreign Direct Investment
by Bohan Chai, Junwei Gao, Lingying Pan and Yishu Chen
Sustainability 2021, 13(16), 8741; https://doi.org/10.3390/su13168741 - 5 Aug 2021
Cited by 20 | Viewed by 3332
Abstract
The outbreak of COVID-19 has had an immeasurable impact on the global economy. It has damaged parts of the real economy, but also provided new opportunities for China’s green development. Both the system and foreign direct investment (FDI) have an important impact on [...] Read more.
The outbreak of COVID-19 has had an immeasurable impact on the global economy. It has damaged parts of the real economy, but also provided new opportunities for China’s green development. Both the system and foreign direct investment (FDI) have an important impact on China’s green recovery path. Based on the provincial panel data of China from 2007 to 2016, this paper uses a slacks-based measure (SBM) model and Malmquist–Luenberger (ML) index to measure the green total factor productivity (GTFP), and empirically analyzes the regulatory role of system in the influencing mechanism of FDI on GTFP. The results show that the overall level of FDI significantly inhibits the improvement of GTFP, and the interaction between system and FDI makes it shift from inhibition to promotion, but the promotion would be weakened with the improvement of the system. FDI in the eastern region shows a positive effect on GTFP, which will be weakened with the improvement of the system. FDI in central and western regions shows a negative effect on GTFP, and the negative effect in western regions will be increased with the improvement of the system. Then this article puts forward targeted policy suggestions for further improving the level of regional systems and introducing FDI of high quality. Full article
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12 pages, 439 KiB  
Article
Empirical Study of the Spatial Spillover Effect of Transportation Infrastructure on Green Total Factor Productivity
by Xi Liang and Pingan Li
Sustainability 2021, 13(1), 326; https://doi.org/10.3390/su13010326 - 31 Dec 2020
Cited by 24 | Viewed by 3182
Abstract
Transportation infrastructure promotes the regional flow of production. The construction and use of transportation infrastructure have a crucial effect on climate change, the sustainable development of the economy, and Green Total Factor Productivity (GTFP). Based on the panel data of 30 provinces in [...] Read more.
Transportation infrastructure promotes the regional flow of production. The construction and use of transportation infrastructure have a crucial effect on climate change, the sustainable development of the economy, and Green Total Factor Productivity (GTFP). Based on the panel data of 30 provinces in China from 2005 to 2017, this study empirically analyses the spatial spillover effect of transportation infrastructure on the GTFP using the Malmquist–Luenberger (ML) index and the dynamic spatial Durbin model. We found that transportation infrastructure has direct and spatial spillover effects on the growth of GTFP; highway density and railway density have significant positive spatial spillover effects, and especially-obvious immediate and lagging spatial spillover effects in the short-term. We also note that the passenger density and freight density of transportation infrastructure account for a relatively small contribution to the regional GTFP. Considering environmental pollution, energy consumption, and the enriching of the traffic infrastructure index system, we used the dynamic spatial Durbin model to study the spatial spillover effects of transportation infrastructure on GTFP. Full article
(This article belongs to the Special Issue Sustainable Transportation and Regional Economic Development)
9 pages, 734 KiB  
Article
Assessing Productivity Development of Public Hospitals: A Case Study of Shanghai, China
by Juan Du, Shuhong Cui and Hong Gao
Int. J. Environ. Res. Public Health 2020, 17(18), 6763; https://doi.org/10.3390/ijerph17186763 - 16 Sep 2020
Cited by 10 | Viewed by 2719
Abstract
As the main provider of medical services for the general public, the productivity changes of public hospitals directly reflect the development of the healthcare system and the implementation effect of medical reform policies. Using the dataset of 126 public hospitals in China from [...] Read more.
As the main provider of medical services for the general public, the productivity changes of public hospitals directly reflect the development of the healthcare system and the implementation effect of medical reform policies. Using the dataset of 126 public hospitals in China from 2013 to 2018, this paper improves the existing literature in both index selection and model formulation, and examines public hospitals’ total factor productivity (TFP) growth. Empirical results not only demonstrate the trend of productivity development but also point out the directions in how to improve the current running status. Our study demonstrates that there were no obvious productivity fluctuations in public hospitals during the recent observing years, indicating that the performance of China’s public health system was generally acceptable in coping with fast-growing medical demand. However, the effect of public hospital reform has not been remarkably shown; thus, no significant productivity improvement was observed in most hospitals. Tertiary hospitals witnessed a slight declining trend in TFP, while secondary hospitals showed signs of rising TFP. To effectively enhance the overall performance of public hospitals in China, practical suggestions are proposed from the government and hospital levels to further promote the graded medical treatment system. Full article
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14 pages, 1933 KiB  
Article
Measurement and Spatial Variation of Green Total Factor Productivity of the Tourism Industry in China
by Xingming Li, Pengfei Shi, Yazhi Han, Aimin Deng and Duan Liu
Int. J. Environ. Res. Public Health 2020, 17(4), 1159; https://doi.org/10.3390/ijerph17041159 - 12 Feb 2020
Cited by 25 | Viewed by 3682
Abstract
Promoting tourism in China using sustainable practices has become a very important issue. In order to analyze temporal characteristics and spatial regularities of green total factor productivity (GTFP), carbon emissions and the consumption of energy related to tourism in China were estimated using [...] Read more.
Promoting tourism in China using sustainable practices has become a very important issue. In order to analyze temporal characteristics and spatial regularities of green total factor productivity (GTFP), carbon emissions and the consumption of energy related to tourism in China were estimated using a "bottom-up" method. The construction of a measurement framework (including carbon emissions and energy consumption) of GTFP for the tourism industry was also undertaken. The data envelopment analysis (DEA) model and the Malmquist–Luenberger (ML) index were used to measure and calculate tourism GTFP in China between 2007 and 2018, as well as analyze spatio-temporal differences. Results indicate that: (1) carbon emissions and the consumption of energy are increasing, and they have not yet peaked, with traffic associated with tourism accounting for the largest proportion among tourism sectors; the spatial distribution of carbon emissions and the consumption of energy is not balanced; (2) green development of tourism in China has achieved a good level of performance during the study period, driven by technical efficiency. Since 2014, pure technical efficiency (PE) has been >1, indicating that the tourism industry in China has entered a stage of change and promotion; (3) significant spatial differences exist in tourism GTFP in China. For example, the overall pattern of being strongest in the east and weakest in the west has not changed. Currently, eastern, central, and western regions in China rely on different dynamic mechanisms to promote tourism green development. In addition, some provinces have become the core or secondary growth poles of tourism green development in China. Full article
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18 pages, 574 KiB  
Article
Does China’s Pollution Levy Standards Reform Promote Green Growth?
by Zhengge Tu, Tao Zhou and Ning Zhang
Sustainability 2019, 11(21), 6186; https://doi.org/10.3390/su11216186 - 5 Nov 2019
Cited by 13 | Viewed by 3839
Abstract
Estimating the impact of environmental taxes on economic output is of great theoretical value for promoting green growth in China. Using a dataset of 232 cities from 2004 to 2014, this paper investigates the effect of pollution levy standards reform (PSR) on green [...] Read more.
Estimating the impact of environmental taxes on economic output is of great theoretical value for promoting green growth in China. Using a dataset of 232 cities from 2004 to 2014, this paper investigates the effect of pollution levy standards reform (PSR) on green total factor productivity (GTFP). We employ directional distance functions (DDF) computed by data envelopment analysis (DEA) to derive GTFP based on the Malmquist–Luenberger (ML) productivity index. Then, we investigate the impacts of PSR on China’s GTFP using Difference-in-Differences (DID) estimation. The results reveal that PSR has an inhibitory effect on GTFP, via the mechanism of technological change. Furthermore, PSR has heterogeneous impacts on different city types. The results indicate that PSR statistically significantly reduces GTFP in key environmental protection cities (KEPCs), large cities, and eastern cities, but that it has less impact on non-KEPCs, small/medium cities, megacities, and cities in central areas. Full article
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19 pages, 917 KiB  
Article
Does FDI Promote or Inhibit the High-Quality Development of Agriculture in China? An Agricultural GTFP Perspective
by Yafei Wang, Li Xie, Yi Zhang, Chunyun Wang and Ke Yu
Sustainability 2019, 11(17), 4620; https://doi.org/10.3390/su11174620 - 25 Aug 2019
Cited by 67 | Viewed by 6136
Abstract
This paper innovatively brings the undesirable output of agricultural carbon emission into the agricultural Total Factor Productivity (TFP) accounting framework as a measure of Green Total Factor Productivity (GTFP) and uses the Slack-based Measure and Malmquist-Luenberger (SBM-ML) index method to measure the agricultural [...] Read more.
This paper innovatively brings the undesirable output of agricultural carbon emission into the agricultural Total Factor Productivity (TFP) accounting framework as a measure of Green Total Factor Productivity (GTFP) and uses the Slack-based Measure and Malmquist-Luenberger (SBM-ML) index method to measure the agricultural GTFP of 24 provinces in China from 2004 to 2016. Further, the two-step system generalized moment method (GMM) is adopted to reveal the effect of agricultural (Foreign Direct Investment) FDI on the growth of agricultural GTFP and various subitems. We find that the average annual growth rate of agricultural GTFP is 3.1%, and its contribution rate to agricultural growth is 52%; the growth of agricultural GTFP shows that the progress of agricultural technology is accompanied by the deterioration of agricultural technical efficiency; the agricultural GTFP in the Eastern region, the Central region and the Western region increases in a stepped-up form, with an annual growth rate of 3.1%, 3.3% and 3.4%, respectively. Agricultural FDI has a significant promoting effect on agricultural GTFP and subitems, however, it has an inverted U-shaped feature in the long term. Full article
(This article belongs to the Special Issue Trade Policy and Macroeconomic Impacts on Agricultural Sustainability)
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