Scale of Production, Agglomeration and Agricultural Pollutant Treatment: Evidence From a Survey in China

Liu, Yazhou; Ji, Yueqing; Shao, Shuai; Fang, Zhong; Zhang, Ning; Chen, Yishan

doi:10.1016/j.ecolecon.2017.04.016

Cited by 21 publications

(8 citation statements)

References 25 publications

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“…On the other hand, some researchers have found that agglomeration can alleviate agricultural environmental pollution. Among them, based on the survey data of pig supply bases in the Yangtze River Delta region, Liu et al (2017) found that a higher level of pig production agglomeration can significantly improve the rate of manure treatment and promote the green development of agriculture. Tian and Yin (2021) pointed out that agricultural industrial agglomeration can improve the utilization efficiency of agricultural materials and reduce carbon emissions.…”

Section: Introductionmentioning

confidence: 99%

Agricultural production agglomeration and total factor carbon productivity: based on NDDF–MML index analysis

Liu

Wen

Wang

2022

CAER

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PurposeAgricultural carbon productivity considers the dual goals of “agricultural economic growth” and “carbon emission reduction”. Improving agricultural carbon productivity is a requirement for promoting green and low-carbon development of agriculture. Agricultural production agglomeration is widespread worldwide, but the relationship between agricultural production agglomeration and agricultural carbon productivity is inconclusive. This paper aims to study the impact of agricultural production agglomeration on agricultural carbon productivity, which is conducive to a better understanding of the relationships among agglomeration, agricultural economic development and carbon emission, better planning of agricultural layout to build a modern agricultural industrial system and achieve the goal of carbon peaking and carbon neutrality.Design/methodology/approachBased on China's provincial data from 1991 to 2019, this paper uses non-radial directional distance function (NDDF) and Metafrontier Malmquist–Luenberger (MML) productivity index to measure total factor agricultural carbon productivity. Subsequently, using a panel two-way fixed effect model to study the effect and mechanism of agricultural production agglomeration on agricultural carbon productivity, and the two-stage least squares method (IV-2SLS) is used to solve endogeneity. Finally, this paper formulates a moderating effect model from the perspective of the efficiency of agricultural material capital inputs.FindingsThe empirical results identify that Chinese provincial agricultural carbon productivity has an overall growth trend and agricultural technological progress is the major source of growth. There is an inverted U-shaped relationship between agricultural production agglomeration and agricultural carbon productivity. The input efficiency of agricultural film, machine and water resources have moderating effects on the inverted U-shaped relationship. Agricultural production agglomeration also promotes agricultural carbon productivity by inhibiting agricultural carbon emissions in addition to affecting agricultural input factors and its internal mechanisms are agricultural green technology progress and rural human capital improvement.Originality/valueThis paper innovatively adopts the NDDF–MML method to measure the total factor agricultural carbon productivity more scientifically and accurately and solves the problems of ignoring group heterogeneity and the shortcomings of traditional productivity measurement in previous studies. This paper also explains the inverted U-shaped relationship between agricultural production agglomeration and agricultural carbon productivity theoretically and empirically. Furthermore, from the perspective of agricultural material capital input efficiency, this paper discusses the moderating effect of input efficiency of fertilizers, pesticides, agricultural film, agricultural machines and water resources on agricultural production agglomeration affecting agricultural carbon productivity and answers the mechanism of carbon emission reduction of agricultural production agglomeration.

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Section: Introductionmentioning

confidence: 99%

Agricultural production agglomeration and total factor carbon productivity: based on NDDF–MML index analysis

Liu

Wen

Wang

2022

CAER

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“…Firstly, referring to Lu and Feng [ 48 ] revealing the load of cropland to absorb manure waste, we constructed a basic ratio indicator (

) to reveal the gap of breeding and planting industries. The indicator of

was constructed using the ratio of meat yield to grain area, as shown in Equation (1) , where

is the output of meat in province

, and

is the grain area of province

.…”

Section: Methodsmentioning

confidence: 99%

“…Given the trend of scale operation of breeding industry, the spatial spillover of livestock and poultry pollution cannot be ignored. Prior studies mostly focused on the breeding agglomeration on pollution [ 48 ]. Moreover, livestock and poultry pollution may have a strong spatial correlation, and CPB co-agglomeration is based on the proximity of industrial positions.…”

Section: Introductionmentioning

confidence: 99%

Does the agricultural co-agglomeration help reduce livestock and poultry pollution? From the perspective of planting and breeding combination in China

Wang

Zhao

2023

Heliyon

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“…Serious environmental pollution has been extended from heavy industry to various industries. 42 The environmental problem has become an important factor for evaluating the performance of the production department. 43 Thus, environmental pollution is included in the production process of the production sector.…”

Section: The Modelmentioning

confidence: 99%

Dynamic effect of environmental tax on export trade: Based on DSGE mode

Gao

Yao

Wang

et al. 2019

Energy & Environment

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We develop a Dynamic Stochastic General Equilibrium (DSGE) model with four sectors, including households, production, government, and export. The model is used to assess the response of China’s export trade to environmental tax shocks. The model parameters are obtained through a combination of calibration and Bayesian estimation. Using the impulse response analysis and variance decomposition, we find that environmental tax shocks can drive the reduction of export volume in China. However, the effect of the environmental tax shocks is smaller than export price mark-up rate shocks. These findings yield important implications for reasonably designing and choosing environmental tax rate and export trade policies.

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Scale of Production, Agglomeration and Agricultural Pollutant Treatment: Evidence From a Survey in China

Cited by 21 publications

References 25 publications

Agricultural production agglomeration and total factor carbon productivity: based on NDDF–MML index analysis

Agricultural production agglomeration and total factor carbon productivity: based on NDDF–MML index analysis

Does the agricultural co-agglomeration help reduce livestock and poultry pollution? From the perspective of planting and breeding combination in China

Dynamic effect of environmental tax on export trade: Based on DSGE mode

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