Measuring the Green Total Factor Productivity in Chinese Aquaculture: A Zofio Index Decomposition

Guo, Wei; Dong, Shuangshuang; Qian, Jiarong; Lyu, Kaiyu

doi:10.3390/fishes7050269

Cited by 7 publications

(7 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For example, Hu et al measured the sum of chemical oxygen demand, total nitrogen and total phosphorus emissions from agricultural production processes as non-desired output for AGTFP in 306 cities in China (Hu et al, 2022). Guo et al measured the AGTFP of Chinese aquaculture separately using equivalent emissions of agricultural surface pollution as non -desired output (Guo et al, 2022). Chen et al Measuring agricultural productivity from an environmental constraint perspective using agricultural surface source pollution as a non-desired output (Chen et al, 2022).…”

Section: Literature Reviewmentioning

confidence: 99%

Spatiotemporal Patterns and Convergence Analysis of Green Agricultural Development: A Case Study of Xinjiang in China

Xia,

Ma,

Gao

et al. 2024

Preprint

View full text Add to dashboard Cite

Under the dual historical responsibility of the double carbon target and the rural revitalisation strategy, effectively improving green agricultural development level in Xinjiang is an important means to break the dilemma of inclusive agricultural economic growth under the complex environmental regulations in the western region nowadays. Based on the panel data of Xinjiang from 2007 to 2019, this paper incorporates agricultural carbon emissions and agricultural non-point source pollution into the same framework. The SBM-Global-Malmquist-Luenberger(GML) productivity index including directional distance function is used to measure the agricultural green total factor productivity(AGTFP) in various regions of Xinjiang, and then the Dagum Gini coefficient decomposition and kernel density estimation are used to investigate the regional differences and dynamic evolution of agricultural green development level in Xinjiang. Finally, the classical and spatial β-convergence models are used to analyze the convergence characteristics and influencing factors of agricultural green development level in Xinjiang. The study found that: AGTFP in Xinjiang showed a "wave-like" development during the sample period, with an overall growth trend; There are significant non-equilibrium characteristics of AGTFP in the sample period, and the agglomeration phenomenon of AGTFP gradually strengthens over time; The overall variation in AGTFP shows a fluctuating upward trend, with intra-regional variation being greater in northern than in southern and eastern Xinjiang, and inter-regional variation making the highest contribution to the overall variation; Inter-regional differences AGTFP have gradually widened and are multi-polar. Polarisation has increased in the northern and southern Xinjiang regions, and the gap has decreased in the eastern Xinjiang region; There is significant absolute β convergence and conditional β convergence of AGTFP during the sample period, and the rate of conditional β convergence is significantly higher than that of absolute β convergence, and the inclusion of spatial factors further increases the rate of convergence. There is still much room for improvement in the level of green agricultural development in Xinjiang. We should speed up green agricultural technology innovation and improve AGTFP; formulate green agricultural development policies according to local conditions; pay attention to the convergence effect and promote coordinated growth in AGTFP in regional agriculture.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Spatiotemporal Patterns and Convergence Analysis of Green Agricultural Development: A Case Study of Xinjiang in China

Xia,

Ma,

Gao

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…The density functions, f (x) and f (y) of x and y, are the identities of marine green aquaculture efficiency, x and y, respectively. Equation (11) can be further written as Equation (12):…”

Section: Wolfson Index Der Index Egr Indexmentioning

confidence: 99%

“…One is Stochastic Frontier Analysis (SFA), which is based on the parametric method and uses the unexpected output to construct the translog production function to measure the efficiency of mariculture [9]. The other method, based on non-parametric Data Envelopment Analysis (DEA), is the Super-SBM model that uses the unexpected output to measure the efficiency of green seawater aquaculture [10,11] or the SBM-GML model that uses the unexpected output to measure green TFP [12,13].…”

Section: Introductionmentioning

confidence: 99%

Study on the Spatial Imbalance and Polarization of Marine Green Aquaculture Efficiency in China

Wang,

Mao,

et al. 2024

Water

View full text Add to dashboard Cite

In-depth analyses of the spatial imbalance and polarization of marine green aquaculture efficiency have a profound impact on the realization of high-quality development of fisheries. Based on the data on mariculture in nine coastal provinces of China from 2006 to 2019, this research analyzed the spatial imbalance and polarization of green mariculture efficiency using quantitative measurements and explored their causes. The results showed that (1) the efficiency of marine green aquaculture in China is relatively effective, but there is still room for improvement. The spatial imbalance of the whole country and the three marine economic circles shows an increasing trend, and the efficiency of marine green aquaculture in China has two levels of differentiation characteristics. Compared with the coastal provinces with low and high levels of marine green aquaculture efficiency, the degree of spatial imbalance in the medium-level coastal provinces is greater. In the long run, the efficiency of China’s marine green aquaculture will slowly evolve to a high-level state, and it is particularly important to break the “self-locking trap” of the low-level state. (2) The differences in mariculture yield among coastal provinces are the main factor affecting the spatial imbalance of green mariculture efficiency in China. Promoting the development of low-carbon, resource-saving and high-added-value mariculture products and achieving a win–win situation of economic and ecological benefits is an important means to alleviate the spatial imbalance of China’s mariculture efficiency. (3) There is a certain polarization trend in the efficiency of marine green aquaculture in China, and the polarization degree shows an overall upward trend. Compared with the northern and eastern marine economic circles, the spatial polarization of green aquaculture efficiency in the southern marine economic circle is the lowest. During the observation year, the change in green aquaculture efficiency in coastal provinces did not converge into minority groups, and the main reason for spatial polarization was that there was a large gap in green aquaculture efficiency among coastal provinces. The research results can provide a reference for accelerating the green transformation of mariculture and promoting the high-quality development of fisheries.

show abstract

“…The current research on GTFP is mainly carried out from the aspects of measurement of different industries, urban construction, environmental protection requirements and green innovation. In studies on measures in different industries: Jiang et al [49] used the Super-SBM model to measure the GTFP of China's mineral resources industry from 2004 to 2019, and believed that improving GTFP is the key for China's mineral resources industry to get out of the dilemma of resource depletion and environmental degradation; Liu et al [50] used the SBM model to measure the GTFP of dairy farming in 27 provinces in China from 2009 to 2020, and found that the GTFP of dairy farming showed fluctuating growth; Guo et al [51] used the SBM-ML method to measure China's GTFP and analyzed the dynamic evolution of China's fish farming industry; Hong et al [52] found that digital financial inclusion can significantly improve China's agricultural GTFP by measuring and testing agricultural GTFP. In the study on urban construction: Yang et al [53] used the SBM-Undesirable model to calculate the GTFP and found that the construction of new energy demonstration cities can significantly improve the GTFP of resource-based cities; Wang et al [54] used PSM-DID and spatial DID models to conduct quantitative research and found that low-carbon city pilot policies can promote the improvement of urban GTFP; Zhang et al [55] found that implementing urban environmental legislation can significantly improve the GTFP of enterprises.…”

Section: Green Total Factor Productivity Of Enterprisesmentioning

confidence: 99%

Analysis of Regional Social Capital, Enterprise Green Innovation and Green Total Factor Productivity—Based on Chinese A-Share Listed Companies from 2011 to 2019

et al. 2022

View full text Add to dashboard Cite

At present, social capital is considered to be one of the important reasons for promoting economic development and causing regional economic differences, but in the existing research, there is little literature on the impact of regional social capital on enterprises’ green innovation behavior and green total factor productivity (GTFP), so this paper aims to enrich the research in this area. This paper builds a regional social capital evaluation index system and uses the super-SBM model to measure the enterprise GTFP. Then, this paper brings regional social capital, enterprise green innovation and GTFP into a unified framework for the first time and further reveals the quantitative relationship between the three by using OLS and Tobit two-step methods based on the panel data of 30 provinces from 2011 to 2019. The results show that regional social capital has a positive effect on enterprise GTFP and green innovation (except for strategic green innovation output), enterprise green innovation output has a positive role in promoting GTFP, and enterprise green innovation capital investment has a masking effect between regional social capital and GTFP. Furthermore, the expansive study finds that there are differences in the impact of regional social capital on green innovation and the GTFP of heterogeneous enterprises, and financing constraints have a positive regulatory effect on the relationship between regional social capital and the GTFP of state-owned enterprises, while having an inhibitory effect on the GTFP of private enterprises. Fiscal decentralization has a partial mediating effect between regional social capital and enterprise GTFP, while urbanization and CO2 emissions have a masking effect. Additionally, this paper aims to provide a reference for the improvement of regional social capital theory, the strategic choice of green innovation of enterprises, and the high-quality development of the economy.

show abstract

Measuring the Green Total Factor Productivity in Chinese Aquaculture: A Zofio Index Decomposition

Cited by 7 publications

References 26 publications

Spatiotemporal Patterns and Convergence Analysis of Green Agricultural Development: A Case Study of Xinjiang in China

Spatiotemporal Patterns and Convergence Analysis of Green Agricultural Development: A Case Study of Xinjiang in China

Study on the Spatial Imbalance and Polarization of Marine Green Aquaculture Efficiency in China

Analysis of Regional Social Capital, Enterprise Green Innovation and Green Total Factor Productivity—Based on Chinese A-Share Listed Companies from 2011 to 2019

Contact Info

Product

Resources

About