Pub Date : 2022-08-12DOI: 10.1108/caer-09-2021-0188
Dingqiang Sun, Xinyue Yang, H. Qiu
PurposeThis paper aims to examine the role of off-farm work in the rural residential energy transition in China.Design/methodology/approachTo guide this empirical work, the authors present a simple farm-household model to explain rural energy consumption. The authors then empirically assess three main mechanisms through which off-farm work can speed up energy transition in rural China using panel data methods.FindingsThe study shows that income growth from off-farm work can reduce the consumption of traditional biomass energy and facilitate a shift to commercial energy. The losses of labor available for on-farm production raise the shadow price of non-tradable biomass energy and further dampen the demand for traditional biomass energy. More importantly, the authors find that working in service sectors can significantly promote the consumption of commercial energy by rural households. The sectoral exposure effect indicates that a new working environment may influence rural households' energy preferences and thus accelerate the transition away from traditional biomass energy.Originality/valuePrevious studies focus mainly on the income effect of off-farm work on rural energy consumption. The authors first identify three related but essentially different effects of off-farm work on rural energy transition in China. This study provides new insights into the process of energy consumption transition in rural China.
{"title":"Off-farm work and rural residential energy transition: a farm-household model and empirical evidence from China","authors":"Dingqiang Sun, Xinyue Yang, H. Qiu","doi":"10.1108/caer-09-2021-0188","DOIUrl":"https://doi.org/10.1108/caer-09-2021-0188","url":null,"abstract":"PurposeThis paper aims to examine the role of off-farm work in the rural residential energy transition in China.Design/methodology/approachTo guide this empirical work, the authors present a simple farm-household model to explain rural energy consumption. The authors then empirically assess three main mechanisms through which off-farm work can speed up energy transition in rural China using panel data methods.FindingsThe study shows that income growth from off-farm work can reduce the consumption of traditional biomass energy and facilitate a shift to commercial energy. The losses of labor available for on-farm production raise the shadow price of non-tradable biomass energy and further dampen the demand for traditional biomass energy. More importantly, the authors find that working in service sectors can significantly promote the consumption of commercial energy by rural households. The sectoral exposure effect indicates that a new working environment may influence rural households' energy preferences and thus accelerate the transition away from traditional biomass energy.Originality/valuePrevious studies focus mainly on the income effect of off-farm work on rural energy consumption. The authors first identify three related but essentially different effects of off-farm work on rural energy transition in China. This study provides new insights into the process of energy consumption transition in rural China.","PeriodicalId":10095,"journal":{"name":"China Agricultural Economic Review","volume":null,"pages":null},"PeriodicalIF":5.1,"publicationDate":"2022-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46320125","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-09DOI: 10.1108/caer-02-2022-0036
Hua Zhang, Fang Zhao, Kexuan Han
PurposeThe purpose of this paper is to reduce the carbon footprint of food by adjusting the international trade and planting structure and to provide possible ideas for the improvement of the world's food green production and green trade.Design/methodology/approachUsing the literature analysis method to collect carbon footprint data calculated based on the life cycle assessment (LCA) method, and establishing an optimization model and an ARIMA prediction model for empirical analysis, this paper explores the possibility to reduce carbon emissions by adjusting import structure and self-production structure.FindingsThe results show that only through the adjustment of the import structure, carbon emissions can be reduced by 3.29 million tons at the source of imports. When domestic self-production is included, a total of 4.51 million tons of carbon emissions can be reduced, this provides ideas for low-carbon emission reduction in agriculture and animal husbandry.Originality/valueThis article is the first to use the carbon footprint data obtained by other scholars using LCA to optimize and analyze the grain trade structure and planting structure from a low-carbon perspective, and obtain specific emission reductions.
{"title":"Optimization analysis of grain self-production and import structure based on carbon footprint","authors":"Hua Zhang, Fang Zhao, Kexuan Han","doi":"10.1108/caer-02-2022-0036","DOIUrl":"https://doi.org/10.1108/caer-02-2022-0036","url":null,"abstract":"PurposeThe purpose of this paper is to reduce the carbon footprint of food by adjusting the international trade and planting structure and to provide possible ideas for the improvement of the world's food green production and green trade.Design/methodology/approachUsing the literature analysis method to collect carbon footprint data calculated based on the life cycle assessment (LCA) method, and establishing an optimization model and an ARIMA prediction model for empirical analysis, this paper explores the possibility to reduce carbon emissions by adjusting import structure and self-production structure.FindingsThe results show that only through the adjustment of the import structure, carbon emissions can be reduced by 3.29 million tons at the source of imports. When domestic self-production is included, a total of 4.51 million tons of carbon emissions can be reduced, this provides ideas for low-carbon emission reduction in agriculture and animal husbandry.Originality/valueThis article is the first to use the carbon footprint data obtained by other scholars using LCA to optimize and analyze the grain trade structure and planting structure from a low-carbon perspective, and obtain specific emission reductions.","PeriodicalId":10095,"journal":{"name":"China Agricultural Economic Review","volume":null,"pages":null},"PeriodicalIF":5.1,"publicationDate":"2022-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47646476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-09DOI: 10.1108/caer-02-2022-0038
Huaiyu Wang, Xi Hu, Shuangquan Yang, Guoquan Xu
PurposeThe study aims to examine the impact of farmers’ actual adaptations on rice yields in the upland areas of Yunnan province, China.Design/methodology/approachThe paper employs the simultaneous equations model with endogenous switching to investigate the different effects of adaptation strategies on rice yields achieved by adopters and nonadopters based on the cross-sectional data at farm level.FindingsThe results show that farmers’ access to government agricultural extension services significantly encourages rice farmers to make the adjustments in farm managements. The authors find that the adaptation strategies employed by farmers significantly increase rice yields. Adaptations adopted by upland farmers increase rice yields for both adopters and nonadopters, particularly for the nonadopters.Originality/valueThis paper contributes to the existing literature by focusing on farmers’ adaptation strategies to climate change in uplands of Yunnan using the primary household survey data. The results show the effectiveness of farmers’ adaptation adoptions on rice yields in uplands of Yunnan province.
{"title":"Climate change adaptation and upland rice yield: evidence from a farm survey in Yunnan, China","authors":"Huaiyu Wang, Xi Hu, Shuangquan Yang, Guoquan Xu","doi":"10.1108/caer-02-2022-0038","DOIUrl":"https://doi.org/10.1108/caer-02-2022-0038","url":null,"abstract":"PurposeThe study aims to examine the impact of farmers’ actual adaptations on rice yields in the upland areas of Yunnan province, China.Design/methodology/approachThe paper employs the simultaneous equations model with endogenous switching to investigate the different effects of adaptation strategies on rice yields achieved by adopters and nonadopters based on the cross-sectional data at farm level.FindingsThe results show that farmers’ access to government agricultural extension services significantly encourages rice farmers to make the adjustments in farm managements. The authors find that the adaptation strategies employed by farmers significantly increase rice yields. Adaptations adopted by upland farmers increase rice yields for both adopters and nonadopters, particularly for the nonadopters.Originality/valueThis paper contributes to the existing literature by focusing on farmers’ adaptation strategies to climate change in uplands of Yunnan using the primary household survey data. The results show the effectiveness of farmers’ adaptation adoptions on rice yields in uplands of Yunnan province.","PeriodicalId":10095,"journal":{"name":"China Agricultural Economic Review","volume":null,"pages":null},"PeriodicalIF":5.1,"publicationDate":"2022-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41957132","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-09DOI: 10.1108/caer-02-2022-0020
Wei Wei, Qi Cui, Yu Sheng
PurposeThis paper aims to explore the future path of agricultural development in China toward 2060 under the dual carbon goals, so as to inform better policy choices for facilitating agricultural and rural transformation toward the goal of maintaining food security, sustainable income growth and low carbon emission.Design/methodology/approachThis study employs a single-country, multi-sectoral computable general equilibrium model, CHINAGEM model and develops eight illustrative scenarios to simulate the impacts of attaining dual carbon goals on agricultural development in China. Additional two scenarios have also been designed to inform better policy making with the aim to offset the negative impact of the decarbonization schemes through facilitating agricultural technology progress.FindingsDual carbon goals are projected to impose substantial negative impact on agricultural productions and consumptions in China in the coming four decades. Under the assumption of business as usual, agricultural production will reduce by 0.49–8.94% along with the attainment of carbon neutrality goal by 2060, with the production of cereals and high-value being more severely damaged. To mitigate the adverse impact of the decarbonization schemes, it is believed that fastening technology progress in agriculture is one of the most efficient ways for maintaining domestic food security without harming the dual carbon goals. In particular, if agricultural productivity (particularly, for cereals and high-value products) can be increased by another 1% per year, the production losses caused by carbon emission mitigation will be fully offset. This implies that promoting technology progress is still the best way to facilitate agricultural development and rural transformation in future China.Originality/valueThe paper contributes to the literature in better informing the impact of dual carbon goals on China's agriculture and the effectiveness of technology progress in agriculture on buffering the adverse impact of the decarbonization schemes and promoting agricultural development.
{"title":"Dual carbon goals and the impact on future agricultural development in China: a general equilibrium analysis","authors":"Wei Wei, Qi Cui, Yu Sheng","doi":"10.1108/caer-02-2022-0020","DOIUrl":"https://doi.org/10.1108/caer-02-2022-0020","url":null,"abstract":"PurposeThis paper aims to explore the future path of agricultural development in China toward 2060 under the dual carbon goals, so as to inform better policy choices for facilitating agricultural and rural transformation toward the goal of maintaining food security, sustainable income growth and low carbon emission.Design/methodology/approachThis study employs a single-country, multi-sectoral computable general equilibrium model, CHINAGEM model and develops eight illustrative scenarios to simulate the impacts of attaining dual carbon goals on agricultural development in China. Additional two scenarios have also been designed to inform better policy making with the aim to offset the negative impact of the decarbonization schemes through facilitating agricultural technology progress.FindingsDual carbon goals are projected to impose substantial negative impact on agricultural productions and consumptions in China in the coming four decades. Under the assumption of business as usual, agricultural production will reduce by 0.49–8.94% along with the attainment of carbon neutrality goal by 2060, with the production of cereals and high-value being more severely damaged. To mitigate the adverse impact of the decarbonization schemes, it is believed that fastening technology progress in agriculture is one of the most efficient ways for maintaining domestic food security without harming the dual carbon goals. In particular, if agricultural productivity (particularly, for cereals and high-value products) can be increased by another 1% per year, the production losses caused by carbon emission mitigation will be fully offset. This implies that promoting technology progress is still the best way to facilitate agricultural development and rural transformation in future China.Originality/valueThe paper contributes to the literature in better informing the impact of dual carbon goals on China's agriculture and the effectiveness of technology progress in agriculture on buffering the adverse impact of the decarbonization schemes and promoting agricultural development.","PeriodicalId":10095,"journal":{"name":"China Agricultural Economic Review","volume":null,"pages":null},"PeriodicalIF":5.1,"publicationDate":"2022-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47107272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-08DOI: 10.1108/caer-04-2022-0069
Haiyue Fu, Shuchang Zhao, Chuan Liao
PurposeThis paper aims to promote urban–rural synergy in carbon reduction and achieve the dual carbon goal, reconstruct the low-carbon urban–rural spatial pattern and explore planning strategies for carbon mitigation in urban agglomerations.Design/methodology/approachThe authors propose the idea of land governance zoning based on low-carbon scenario simulation, using the Beijing–Tianjin–Hebei (BTH) urban agglomeration as the empirical research area. Specifically, the authors analyze its spatiotemporal evolution characteristics of carbon balance over the past two decades and simulate the land use pattern under the scenario of low-carbon emission in 2030. Furthermore, the authors create spatial zoning rules combined with land use transition characteristics to classify the urban agglomeration into carbon sink restoration zone, carbon sink protection zone, carbon control development zone and carbon transition agriculture zone and put forward corresponding targeted governance principals.FindingsThe study findings classify the BTH urban agglomeration into carbon sink restoration zone, carbon sink protection zone, carbon control development zone and carbon transition agriculture zone, which account for 28.1%, 17.2%, 20.1% and 34.6% of the total area, respectively. The carbon sink restoration zone and carbon sink protection zone are mainly distributed in the northern and western parts and Bohai Rim region. The carbon transition agriculture zone and carbon control development zone are mainly distributed in the southeastern plain and Zhangjiakou.Research limitations/implicationsThe authors suggest restoring and rebuilding ecosystems mainly in the northwest and east parts to increase the number of carbon sinks and the stability of the ecosystem. Besides, measures should be taken to promote collaborative emission reduction work between cities and optimize industrial and energy structures within cities such as Beijing, Langfang, Tianjin and Baoding. Furthermore, the authors recommend promoting sustainable intensification of agriculture and carefully balance between both economic development and ecological protection in Zhangjiakou and plain area.Originality/valueThe authors propose a zoning method based on the optimization of land use towards low-carbon development by combining “top-down” and “bottom-up” strategies and provide targeted governance suggestions for each region. This study provides policy implications to implement the regional low-carbon economic transition under the “double carbon” target in urban agglomerations in China.
{"title":"Spatial governance of Beijing-Tianjin-Hebei urban agglomeration towards low-carbon transition","authors":"Haiyue Fu, Shuchang Zhao, Chuan Liao","doi":"10.1108/caer-04-2022-0069","DOIUrl":"https://doi.org/10.1108/caer-04-2022-0069","url":null,"abstract":"PurposeThis paper aims to promote urban–rural synergy in carbon reduction and achieve the dual carbon goal, reconstruct the low-carbon urban–rural spatial pattern and explore planning strategies for carbon mitigation in urban agglomerations.Design/methodology/approachThe authors propose the idea of land governance zoning based on low-carbon scenario simulation, using the Beijing–Tianjin–Hebei (BTH) urban agglomeration as the empirical research area. Specifically, the authors analyze its spatiotemporal evolution characteristics of carbon balance over the past two decades and simulate the land use pattern under the scenario of low-carbon emission in 2030. Furthermore, the authors create spatial zoning rules combined with land use transition characteristics to classify the urban agglomeration into carbon sink restoration zone, carbon sink protection zone, carbon control development zone and carbon transition agriculture zone and put forward corresponding targeted governance principals.FindingsThe study findings classify the BTH urban agglomeration into carbon sink restoration zone, carbon sink protection zone, carbon control development zone and carbon transition agriculture zone, which account for 28.1%, 17.2%, 20.1% and 34.6% of the total area, respectively. The carbon sink restoration zone and carbon sink protection zone are mainly distributed in the northern and western parts and Bohai Rim region. The carbon transition agriculture zone and carbon control development zone are mainly distributed in the southeastern plain and Zhangjiakou.Research limitations/implicationsThe authors suggest restoring and rebuilding ecosystems mainly in the northwest and east parts to increase the number of carbon sinks and the stability of the ecosystem. Besides, measures should be taken to promote collaborative emission reduction work between cities and optimize industrial and energy structures within cities such as Beijing, Langfang, Tianjin and Baoding. Furthermore, the authors recommend promoting sustainable intensification of agriculture and carefully balance between both economic development and ecological protection in Zhangjiakou and plain area.Originality/valueThe authors propose a zoning method based on the optimization of land use towards low-carbon development by combining “top-down” and “bottom-up” strategies and provide targeted governance suggestions for each region. This study provides policy implications to implement the regional low-carbon economic transition under the “double carbon” target in urban agglomerations in China.","PeriodicalId":10095,"journal":{"name":"China Agricultural Economic Review","volume":null,"pages":null},"PeriodicalIF":5.1,"publicationDate":"2022-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49615476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-05DOI: 10.1108/caer-01-2022-0011
R. Mao
PurposeThe author attempts to examine the existence and pattern of coalitions in international relations across countries, and investigates whether international relations of coalition partners influence a country's enaction of agricultural non-tariff measures (NTMs).Design/methodology/approachThe author adopts a machine learning technique to identify international relation coalition partnerships and use network analysis to characterize the clustering pattern of coalitions with high-frequent records of global event data. The author then constructs a monthly dataset of agricultural NTMs against China and international relations with China of each importer and its coalition partners, and designs a panel structural vector autoregressive (PSVAR) model to estimate impulse response functions of agricultural NTMs with regard to international relation shocks.FindingsThe author finds countries to establish coalition partnerships. Two major clusters of coalitions are noted, with one composed of coalitions primarily among “North” countries and the other of coalitions among “South” countries. The United States is found to play a pivotal role by connecting the two clusters. The PSVAR estimation reveals reductions of NTMs against China following improved international relations with China of both the importer and its coalition partners. NTM responses are more substantial for measures that are trade restrictive. These results confirm that coalitions in international relations lead to coordination of agricultural NTMs.Originality/valueThe author provides international political insights into agricultural trade policymaking by showing interactions of NTM enaction across countries in the same coalition of international relations. These insights offer useful policy implications to predict and cope with hidden barriers to agricultural trade.
{"title":"Coalitions in international relations and coordination of agricultural trade policies","authors":"R. Mao","doi":"10.1108/caer-01-2022-0011","DOIUrl":"https://doi.org/10.1108/caer-01-2022-0011","url":null,"abstract":"PurposeThe author attempts to examine the existence and pattern of coalitions in international relations across countries, and investigates whether international relations of coalition partners influence a country's enaction of agricultural non-tariff measures (NTMs).Design/methodology/approachThe author adopts a machine learning technique to identify international relation coalition partnerships and use network analysis to characterize the clustering pattern of coalitions with high-frequent records of global event data. The author then constructs a monthly dataset of agricultural NTMs against China and international relations with China of each importer and its coalition partners, and designs a panel structural vector autoregressive (PSVAR) model to estimate impulse response functions of agricultural NTMs with regard to international relation shocks.FindingsThe author finds countries to establish coalition partnerships. Two major clusters of coalitions are noted, with one composed of coalitions primarily among “North” countries and the other of coalitions among “South” countries. The United States is found to play a pivotal role by connecting the two clusters. The PSVAR estimation reveals reductions of NTMs against China following improved international relations with China of both the importer and its coalition partners. NTM responses are more substantial for measures that are trade restrictive. These results confirm that coalitions in international relations lead to coordination of agricultural NTMs.Originality/valueThe author provides international political insights into agricultural trade policymaking by showing interactions of NTM enaction across countries in the same coalition of international relations. These insights offer useful policy implications to predict and cope with hidden barriers to agricultural trade.","PeriodicalId":10095,"journal":{"name":"China Agricultural Economic Review","volume":null,"pages":null},"PeriodicalIF":5.1,"publicationDate":"2022-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42665486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-03DOI: 10.1108/caer-02-2022-0034
Xiangwen Kong, Liufang Su, Heng Wang, H. Qiu
PurposeTo achieve the dual goals of decarbonization and food security, this paper examines China's carbon footprint reduction in 2050 based on current mitigation strategies.Design/methodology/approachConsidering publications as featured evidence, this study develops an investigation of agricultural decarbonization in China. First, the authors summarize the mitigation strategies for agricultural greenhouse gas (GHG) emissions in the existing literature. Second, the authors demonstrate the domestic food production target in 2050 and the projection target's projected life-cycle-based GHG emissions at the commodity level. Lastly, the authors forecast China's emission removal in the agri-food sector in 2050 concerning current mitigation strategies and commodity productions. The authors highlight the extent to which each mitigation strategy contributes to decarbonization in China.FindingsPractices promoting sustainable development in the agri-food sector significantly contribute to GHG emission removal. The authors find mitigation strategies inhibiting future GHG emissions in the agri-food sector comprise improving nitrogen use efficiency in fertilizers, changing food consumption structure, manure management, cover crops, food waste reduction, dietary change of livestock and covered manure. A 10% improvement in nitrogen use efficiency contributes to 5.03% of GHG emission removal in the agri-food sector by 2050. Reducing food waste and food processing from 30% to 20% would inhibit 1.59% of the total GHG emissions in the agri-food sector.Originality/valueThis study contributes to policy discussions by accounting for agricultural direct and indirect emission components and assessing the dynamic changes in those related components. This study also extends existing research by forecasting to which extent the decarbonization effects implemented by current mitigation strategies can be achieved while meeting 2050 food security in China.
{"title":"Agricultural carbon footprint and food security: an assessment of multiple carbon mitigation strategies in China","authors":"Xiangwen Kong, Liufang Su, Heng Wang, H. Qiu","doi":"10.1108/caer-02-2022-0034","DOIUrl":"https://doi.org/10.1108/caer-02-2022-0034","url":null,"abstract":"PurposeTo achieve the dual goals of decarbonization and food security, this paper examines China's carbon footprint reduction in 2050 based on current mitigation strategies.Design/methodology/approachConsidering publications as featured evidence, this study develops an investigation of agricultural decarbonization in China. First, the authors summarize the mitigation strategies for agricultural greenhouse gas (GHG) emissions in the existing literature. Second, the authors demonstrate the domestic food production target in 2050 and the projection target's projected life-cycle-based GHG emissions at the commodity level. Lastly, the authors forecast China's emission removal in the agri-food sector in 2050 concerning current mitigation strategies and commodity productions. The authors highlight the extent to which each mitigation strategy contributes to decarbonization in China.FindingsPractices promoting sustainable development in the agri-food sector significantly contribute to GHG emission removal. The authors find mitigation strategies inhibiting future GHG emissions in the agri-food sector comprise improving nitrogen use efficiency in fertilizers, changing food consumption structure, manure management, cover crops, food waste reduction, dietary change of livestock and covered manure. A 10% improvement in nitrogen use efficiency contributes to 5.03% of GHG emission removal in the agri-food sector by 2050. Reducing food waste and food processing from 30% to 20% would inhibit 1.59% of the total GHG emissions in the agri-food sector.Originality/valueThis study contributes to policy discussions by accounting for agricultural direct and indirect emission components and assessing the dynamic changes in those related components. This study also extends existing research by forecasting to which extent the decarbonization effects implemented by current mitigation strategies can be achieved while meeting 2050 food security in China.","PeriodicalId":10095,"journal":{"name":"China Agricultural Economic Review","volume":null,"pages":null},"PeriodicalIF":5.1,"publicationDate":"2022-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41587192","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-20DOI: 10.1108/caer-02-2022-0035
Hongman Liu, Shibin Wen, Zhuang Wang
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 ag
{"title":"Agricultural production agglomeration and total factor carbon productivity: based on NDDF–MML index analysis","authors":"Hongman Liu, Shibin Wen, Zhuang Wang","doi":"10.1108/caer-02-2022-0035","DOIUrl":"https://doi.org/10.1108/caer-02-2022-0035","url":null,"abstract":"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 ag","PeriodicalId":10095,"journal":{"name":"China Agricultural Economic Review","volume":null,"pages":null},"PeriodicalIF":5.1,"publicationDate":"2022-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47416580","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-28DOI: 10.1108/caer-01-2022-0008
Kai-Ning Tang, Chunbo Ma
PurposeMitigating agricultural greenhouse gas (GHG) emissions is an essential part of China's effort to achieve net-zero emissions. This study assesses the cost-effectiveness of China's agricultural GHG reduction under diverse carbon policies.Design/methodology/approachThe study employs a parametric non-radial distance function approach and estimates the technical abatement potential and marginal abatement cost (MAC) of GHG in China's agricultural sector for the 2008–2017 period.FindingsAgriculture is expected to make a great contribution to China's net-zero emissions progress. This study empirically analyses the cost-effectiveness of China's agricultural GHG reduction under diverse carbon policies. A parametric non-radial distance function approach is used to derive technical abatement potential and MAC of GHG for the 2008–2017 period. The results indicate that no significant improvement had been achieved in terms of agricultural GHG reduction in China during 2008–2017. The country's agricultural sector could reduce 20–40% GHG emissions with a mean value of 31%. In general, western provinces have larger reduction potential than eastern ones. The average MAC for the whole country is 4,656 yuan/ton CO2e during 2008–2017. For most western provinces, their MAC values are considerably higher than those for most eastern provinces. Compared with previous sectoral estimates of GHG mitigation cost, this study’s estimates indicate that reducing agricultural GHG emissions in some provinces is likely to be cost-effective. The Chinese government should consider expanding its national carbon market to cover agricultural sector.Practical implicationsThe Chinese government should consider expanding its national carbon market to cover agricultural sector.Originality/valueExisting studies in the field mostly ignore input constraints, which is inconsistent with carbon mitigation policy practice, especially in the agricultural sector. This study’s approach integrates both input and output constraints reflecting differing policy practice.
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Pub Date : 2022-06-27DOI: 10.1108/caer-01-2022-0009
Xiaoxue Du, Xuejian Wang, Patrick L. Hatzenbuehler
PurposeThe purpose of this paper is to show the impact of digital agriculture on food supply chain, research trend, emphasis and implications for future research.Design/methodology/approachThe paper analyzes how the digital technology reshapes the production, assembly, transaction, retail and logistics. Impact from each main technological progress is discussed.FindingsFirst, digital agriculture develops quickly and changes all parts of the food supply chain. Second, while many technological progresses show their impacts in agriculture and food sector, e-commerce and progress of artificial intelligence show its comprehensive impact on the argi-food sector.Originality/valueThe paper shows the technological trend and progress in food and agriculture sector. Researchers focusing on agricultural economics and agribusiness should pay attention to recent developments in the real world, know the recent developments from other disciplines, get more data for empirical research and show the impact of digital agriculture on consumer's preference and social welfare.
{"title":"Digital technology in agriculture: a review of issues, applications and methodologies","authors":"Xiaoxue Du, Xuejian Wang, Patrick L. Hatzenbuehler","doi":"10.1108/caer-01-2022-0009","DOIUrl":"https://doi.org/10.1108/caer-01-2022-0009","url":null,"abstract":"PurposeThe purpose of this paper is to show the impact of digital agriculture on food supply chain, research trend, emphasis and implications for future research.Design/methodology/approachThe paper analyzes how the digital technology reshapes the production, assembly, transaction, retail and logistics. Impact from each main technological progress is discussed.FindingsFirst, digital agriculture develops quickly and changes all parts of the food supply chain. Second, while many technological progresses show their impacts in agriculture and food sector, e-commerce and progress of artificial intelligence show its comprehensive impact on the argi-food sector.Originality/valueThe paper shows the technological trend and progress in food and agriculture sector. Researchers focusing on agricultural economics and agribusiness should pay attention to recent developments in the real world, know the recent developments from other disciplines, get more data for empirical research and show the impact of digital agriculture on consumer's preference and social welfare.","PeriodicalId":10095,"journal":{"name":"China Agricultural Economic Review","volume":null,"pages":null},"PeriodicalIF":5.1,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44142586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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