Pub Date : 2022-08-30DOI: 10.1108/caer-03-2022-0046
Qingxin Xie, F. Yi, Xu Tian
PurposeThis paper aims to investigate the changes in living standard among families with different socio-economic status in China with the use of Engel's Coefficient. The authors develop a decomposition methodology to figure out the driving forces behind changes in Engel's Coefficient, and investigate how dramatic economic growth, volatile food price and rapid nutrition transition affect living standard among different families.Design/methodology/approachThe authors propose a statistical method to decompose the changes in living standard measured by Engel's Coefficient into structure effect, price effect, quantity effect and income effect. Using the China Health and Nutrition Survey data between 2000 and 2011, the authors estimate these four effects by employing a decomposition method.FindingsResults show that Engel's Coefficient in China decreased by 8.7 percentage points (hereafter “pp”) during 2000–2011, where structure effect leads to 0.2 pp increase, price effect results in 17.7 pp increase, quantity effect brings about 12.4 pp decline and income effect contributes to 14.2 pp decline. Results indicate that rising food prices are the main obstacle to improve households' living standard. Typically, poor and rural families' living standard is more vulnerable to the rise in food prices, and they benefit less from income growth.Originality/valueThis study proposes a decomposition method to investigate the determinants of change in Engel's Coefficient, which provides a deeper understanding of how economic growth, food price change and nutrition transition affect people's living standard in different socio-economic groups in developing countries. This study also provides valuable insights on how to achieve common prosperity from the perspective of consumption upgrading.
{"title":"Disparate changes of living standard in China: perspective from Engel's coefficient","authors":"Qingxin Xie, F. Yi, Xu Tian","doi":"10.1108/caer-03-2022-0046","DOIUrl":"https://doi.org/10.1108/caer-03-2022-0046","url":null,"abstract":"PurposeThis paper aims to investigate the changes in living standard among families with different socio-economic status in China with the use of Engel's Coefficient. The authors develop a decomposition methodology to figure out the driving forces behind changes in Engel's Coefficient, and investigate how dramatic economic growth, volatile food price and rapid nutrition transition affect living standard among different families.Design/methodology/approachThe authors propose a statistical method to decompose the changes in living standard measured by Engel's Coefficient into structure effect, price effect, quantity effect and income effect. Using the China Health and Nutrition Survey data between 2000 and 2011, the authors estimate these four effects by employing a decomposition method.FindingsResults show that Engel's Coefficient in China decreased by 8.7 percentage points (hereafter “pp”) during 2000–2011, where structure effect leads to 0.2 pp increase, price effect results in 17.7 pp increase, quantity effect brings about 12.4 pp decline and income effect contributes to 14.2 pp decline. Results indicate that rising food prices are the main obstacle to improve households' living standard. Typically, poor and rural families' living standard is more vulnerable to the rise in food prices, and they benefit less from income growth.Originality/valueThis study proposes a decomposition method to investigate the determinants of change in Engel's Coefficient, which provides a deeper understanding of how economic growth, food price change and nutrition transition affect people's living standard in different socio-economic groups in developing countries. This study also provides valuable insights on how to achieve common prosperity from the perspective of consumption upgrading.","PeriodicalId":10095,"journal":{"name":"China Agricultural Economic Review","volume":" ","pages":""},"PeriodicalIF":5.1,"publicationDate":"2022-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49340133","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 : 2022-08-16DOI: 10.1108/caer-12-2021-0239
Nan Li, Muzi Chen, Haoyu Gao, Difang Huang, Xiaoguang Yang
PurposeGiven the scarcity of data during the early stages of the COVID-19 pandemic in China, the decision-making for non-pharmaceutical policies was mostly based on insufficient evidence. The purpose of this study is to assess the effectiveness of these policies, such as lockdown and government subsidies, on rural households and identify policy implications for China and other countries in dealing with pandemics.Design/methodology/approachThe authors survey 2,408 rural households by telephone from 101 counties across 17 provinces in China during the first stage of the pandemic (March 2020). The authors use the ordered probit model and linear regression model to study the overall impact of policies and then use the quantile regression model and sub-sample regression method to study the heterogeneity of the effects of government policies.FindingsThe authors find that logistics disruption due to lockdown negatively affected rural households. Obstructed logistics is associated with a more significant loss for high-income households, while its impact on the loss expectation of low-income households is more severe. Breeding and other industries such as transport and sales suffer more from logistics than cultivation. The impact of logistics on intensive agricultural entities is more serious than that on professional farms. The government subsidy is more effective at reducing loss for low-income households. Lockdown and government subsidies have shown heterogeneous impacts on rural households.Practical implicationsThe overall economic losses experienced by rural households in the early stages of the pandemic are controllable. The government policies of logistics and subsidies should target specific groups.Originality/valueThe authors evaluate the economic impacts of lockdown and government subsidies on rural households and show their heterogeneity among different groups. The authors further demonstrate the policy effectiveness in supporting rural households during the early stages of the pandemic and provide future policy guidance on major public health event.
{"title":"Impact of lockdown and government subsidies on rural households at early COVID-19 pandemic in China","authors":"Nan Li, Muzi Chen, Haoyu Gao, Difang Huang, Xiaoguang Yang","doi":"10.1108/caer-12-2021-0239","DOIUrl":"https://doi.org/10.1108/caer-12-2021-0239","url":null,"abstract":"PurposeGiven the scarcity of data during the early stages of the COVID-19 pandemic in China, the decision-making for non-pharmaceutical policies was mostly based on insufficient evidence. The purpose of this study is to assess the effectiveness of these policies, such as lockdown and government subsidies, on rural households and identify policy implications for China and other countries in dealing with pandemics.Design/methodology/approachThe authors survey 2,408 rural households by telephone from 101 counties across 17 provinces in China during the first stage of the pandemic (March 2020). The authors use the ordered probit model and linear regression model to study the overall impact of policies and then use the quantile regression model and sub-sample regression method to study the heterogeneity of the effects of government policies.FindingsThe authors find that logistics disruption due to lockdown negatively affected rural households. Obstructed logistics is associated with a more significant loss for high-income households, while its impact on the loss expectation of low-income households is more severe. Breeding and other industries such as transport and sales suffer more from logistics than cultivation. The impact of logistics on intensive agricultural entities is more serious than that on professional farms. The government subsidy is more effective at reducing loss for low-income households. Lockdown and government subsidies have shown heterogeneous impacts on rural households.Practical implicationsThe overall economic losses experienced by rural households in the early stages of the pandemic are controllable. The government policies of logistics and subsidies should target specific groups.Originality/valueThe authors evaluate the economic impacts of lockdown and government subsidies on rural households and show their heterogeneity among different groups. The authors further demonstrate the policy effectiveness in supporting rural households during the early stages of the pandemic and provide future policy guidance on major public health event.","PeriodicalId":10095,"journal":{"name":"China Agricultural Economic Review","volume":" ","pages":""},"PeriodicalIF":5.1,"publicationDate":"2022-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45986576","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 : 2022-08-12DOI: 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":" ","pages":""},"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":" ","pages":""},"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":" ","pages":""},"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":" ","pages":""},"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":" ","pages":""},"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":" ","pages":""},"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":"1 1","pages":""},"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":" ","pages":""},"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}
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