Productivity, Efficiency and Sustainability Challenges in Developing High Value and/or High Quality Agriculture in Developing Economies

A special issue of Agriculture (ISSN 2077-0472). This special issue belongs to the section "Agricultural Economics, Policies and Rural Management".

Deadline for manuscript submissions: closed (28 February 2023) | Viewed by 20992

Special Issue Editors


E-Mail Website
Guest Editor
School of Agriculture, Policy and Development (SAPD), University of Reading, Reading RG6 6UR, UK
Interests: agricultural and resources economics; productivity and efficiency; technological progress in agriculture; sustainable agriculture; poverty, inequality and sustainable livelihoods; international development
Special Issues, Collections and Topics in MDPI journals
1. School of Economics, Shandong University of Finance and Economics, Jinan, China
2. China-ASEAN High-Quality Development Research Center, Shandong University of Finance and Economics, Jinan, China
3. Centre of Excellence in Econometrics, Chiang Mai University, Chiang Mai, Thailand
Interests: agricultural economics; high-quality development; TFP; economic modelling

Special Issue Information

Dear Colleagues,

Improving the productivity and efficiency of agriculture is a priority concern for governments, policy makers, nongovernmental organizations (NGOs), relevant stakeholders and farming communities worldwide to meet the demand for food, food products and services from a closing land frontier and degrading land base. Concern is also centered on developing high-value and/or high-quality agriculture industry and food system to ensure the commercialization, growth, revenue and sustainable development of the agricultural sector. These concerns are particularly high for countries grappling with a lack of innovation, low levels of technical progress, subsistence farming, adverse production environments and a changing climate. High-quality agriculture here refers to the growth mode of innovation-driven agriculture, which is efficient, energy-saving and contributes towards environmental protection and is characterized by high added value. It is an agricultural system dominated by smart technologies with high added value as the core emphasizing quality in addition to the quantity of production and services from the sector.

This Special Issue aims to solicit original contributions from academics, researchers, practitioners, NGOs and other stakeholders providing theoretical insights and/or empirical analysis focusing on examining productivity, efficiency and the multiple challenges encountered in pursuing a path of high-value and/or high-quality agriculture development in developing economies. The editors encourage submissions with applications of innovative and/or novel methodologies ranging from parametric, semi-parametric and non-parametric approaches to address any aspects of the theme of this Special Issue. The scope of submission includes original research and review articles on the theme. 

Dr. Sanzidur Rahman
Dr. Jianxu Liu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Agriculture is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • high value and/or high quality agriculture
  • productivity and efficiency of high value and/or high quality agriculture
  • economic sustainability of high value and/or high quality agriculture
  • challenges in developing high value and/or high quality agriculture
  • environment, climate change and high value and/or high quality agriculture interaction
  • high value and/or high quality agriculture and international trade
  • high value and/or high quality agriculture and rural development
  • digital transformation of agriculture towards high value and/or high quality development path

Published Papers (10 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

23 pages, 3107 KiB  
Article
A Copula-Based Meta-Stochastic Frontier Analysis for Comparing Traditional and HDPE Geomembranes Technology in Sea Salt Farming among Farmers in Phetchaburi, Thailand
by Roengchai Tansuchat
Agriculture 2023, 13(4), 802; https://doi.org/10.3390/agriculture13040802 - 30 Mar 2023
Cited by 4 | Viewed by 1611
Abstract
This study analyzed sea salt production and compared the technical efficiency level and the technology gap between traditional technology and High-Density Polyethylene Geomembranes (HDPE GMB) technology in the Phetchaburi province using a copula-based meta-stochastic frontier technique. A total sample size of 250 was [...] Read more.
This study analyzed sea salt production and compared the technical efficiency level and the technology gap between traditional technology and High-Density Polyethylene Geomembranes (HDPE GMB) technology in the Phetchaburi province using a copula-based meta-stochastic frontier technique. A total sample size of 250 was chosen, comprising 195 traditional farmers and 55 HDPE GMBs farmers. Several copula families were used to analyze the dependence structure of the two error components and the best-fit copula-based meta-frontier model used Gaussian copulas. Land, labor, and fuel energy are the most significant input variables in the Gaussian copula-based meta-frontier model with a translog production function. Compared to meta-frontier production, the average technological gap between traditional technology production and HDPE GMB technology production was 0.69 and 0.77, respectively, meaning HDPE GMB technology is more technically efficient than traditional technology. The study identified that land, market price, sex, and experience were the contributing technical inefficiency factors for traditional technology production. For HDPE GMB technology production, land, sex, and experience were found to be contributing factors. The performance of HDPE GMB technology in salt farming in the Phetchaburi province suggests that public and private sector agencies should promote greater access to this technology for salt farmers. Full article
Show Figures

Figure 1

21 pages, 1672 KiB  
Article
The Effects of Agricultural Technology Progress on Agricultural Carbon Emission and Carbon Sink in China
by Shulong Li and Zhizhang Wang
Agriculture 2023, 13(4), 793; https://doi.org/10.3390/agriculture13040793 - 30 Mar 2023
Cited by 9 | Viewed by 1950
Abstract
The development mode of expanding agricultural scale will inevitably lead to an increase in agricultural carbon emissions but the impacts of agricultural technology progress on agricultural carbon emission and carbon sink are still not quite clear. This paper firstly discuss the definition of [...] Read more.
The development mode of expanding agricultural scale will inevitably lead to an increase in agricultural carbon emissions but the impacts of agricultural technology progress on agricultural carbon emission and carbon sink are still not quite clear. This paper firstly discuss the definition of agricultural technology level. Then the estimating methods of agricultural technology, agricultural carbon emission and carbon sink are introduced. Based on the China’s provincial panel data with 31 province from 2000 to 2019, the indicators are calculated and statistically analysed. After that, the representativeness of the three secondary classifications of the agricultural technology is empirically checked. Panel data regression models especially the fixed effect model is employed to estimate the effects of agricultural technology level as well as its components on agricultural carbon emission and carbon sink. Results show that the agricultural carbon sink is approximately 10 times higher than agricultural carbon emission. Agricultural technology level in general has significant effect on the carbon emission rather than the carbon sink. Our suggestion is that (1) it is not necessary to worry about the agricultural carbon emission since the net effect of agriculture is carbon neutrality; (2) the development of agricultural production technology and agricultural management technology needs strong support, and the two need to develop coordinated. Full article
Show Figures

Figure 1

19 pages, 5905 KiB  
Article
Study on the Coupling Effect of Agricultural Production, Road Construction, and Ecology: The Case for Cambodia
by Lingfei Weng, Wentao Dou and Yejing Chen
Agriculture 2023, 13(4), 780; https://doi.org/10.3390/agriculture13040780 - 28 Mar 2023
Cited by 3 | Viewed by 1844
Abstract
Agricultural development is a necessary component of national development efforts to fight food crises and promote poverty reduction in many developing countries. However, many developing countries have fallen into a stalemate between modernization and development—modernized areas are less capable of driving regional development [...] Read more.
Agricultural development is a necessary component of national development efforts to fight food crises and promote poverty reduction in many developing countries. However, many developing countries have fallen into a stalemate between modernization and development—modernized areas are less capable of driving regional development despite their abundant land and rich population. Striking a balance between agricultural technology and environmental protection is a key feature of sustainable land development. Based on the social–ecological resilience theory, this study takes Cambodia as an example and aims to establish a comprehensive evaluation index system to measure the agricultural production, regional road construction, and agricultural eco-environment in Cambodia. The coupled coordination model and gray relation analysis model are utilized to explore the interaction between agriculture, roads, and the agricultural eco-environment. The results show that (1) Cambodia has road environmental risks, and there is a need for rural labor migration in areas with higher levels of economic development. (2) The main agricultural production areas are faced with the dilemma of lagging infrastructure development, such as roads, and a huge potential for agricultural development. (3) In the plains areas, the growing population has caused tension between food security, fertilizer abuse, and deforestation, which intensified the disturbance of the agricultural ecological environment. In summary, based on their own developmental needs, developing countries at different stages of development can explore the interaction between agricultural production, infrastructure development, and the agricultural eco-environment in the process of agricultural development. This study attempts to provide a set of practical development policy implications for developing countries that are seeking to enhance the coupling relationship between agricultural production, infrastructure, and the agricultural eco-environment. Full article
Show Figures

Figure 1

14 pages, 673 KiB  
Article
The Impact of Migration on Farm Performance: Evidence from Rice Farmers in China
by Guangcheng Ren, Xueqin Zhu and Shuyi Feng
Agriculture 2023, 13(3), 708; https://doi.org/10.3390/agriculture13030708 - 18 Mar 2023
Cited by 1 | Viewed by 3470
Abstract
Developing economies face challenges in improving the overall performance of farms. An essential challenge could be a substantial shift in the agricultural labor force to off-farm sectors during the process of economic transition. This paper estimates the causal impact of migration on the [...] Read more.
Developing economies face challenges in improving the overall performance of farms. An essential challenge could be a substantial shift in the agricultural labor force to off-farm sectors during the process of economic transition. This paper estimates the causal impact of migration on the economic and environmental performance of rice farms, measured using technical efficiency and fertilizer use efficiency. A stochastic frontier analysis, based on the survey data collected in four regions of China, is applied, finding an average technical efficiency of 0.92, while the average fertilizer use efficiency is only 0.22. The results of propensity score matching suggest that migration has a marginally negative impact on both technical efficiency and fertilizer use efficiency of their rice production, while the impact is amplified for farmers who participated in migration more intensively. This would imply that the government policy on the migration of rural households might also need to consider this impact. Full article
Show Figures

Figure 1

16 pages, 1291 KiB  
Article
Time, Spatial and Component Characteristics of Agricultural Carbon Emissions of China
by Shulong Li and Zhizhang Wang
Agriculture 2023, 13(1), 214; https://doi.org/10.3390/agriculture13010214 - 14 Jan 2023
Cited by 4 | Viewed by 1635
Abstract
In this study, the time trend, regional distribution and component characteristics of the agricultural carbon emissions (ACEs) of China are analyzed. The estimation methods of each component of the ACE are introduced. According to the annually provincial panel data set with the 31 [...] Read more.
In this study, the time trend, regional distribution and component characteristics of the agricultural carbon emissions (ACEs) of China are analyzed. The estimation methods of each component of the ACE are introduced. According to the annually provincial panel data set with the 31 provinces from 1996 to 2019, the time trend, regional distribution and component characteristics are empirically discussed. Meanwhile, since it is also worthwhile to explore the effect of the ACE on economic growth, econometric models such as the pooled ordinary least squares (OLS) and fixed effect (FE) models are employed to examine the inverted “U”-shape effect of ACE on both of the agricultural GDP and GDP under the control of other variables. The results show that (1) the carbon emission started to fall after 2015; (2) the majority source of the agricultural carbon emission is caused by chemical fertilizer, which is approximately half of the total; (3) the current provincial ACE levels (0.287 ×1010 kg in 2019) are significantly smaller than the estimated optimal level for agricultural GDP as well as GDP (respectively, 1.003×1010 kg and 1.256×1010 kg). In light of this, environmental protection and agricultural development are currently conflicted. Therefore, we suggest that the government should accept a trade-off between economic growth and the quality of the environment. Full article
Show Figures

Figure 1

14 pages, 1218 KiB  
Article
Effect of Relationship Quality in Collaboration and Innovation of Agricultural Service Supply Chain under Omni-Channel Model
by Baojun Yang, Bo Yuan, Ning Yang, Yan Liu, Ruiqi Jia, Yongyan Wang, Ting Miao, Jianxu Liu and Songsak Sriboonchitta
Agriculture 2022, 12(11), 1932; https://doi.org/10.3390/agriculture12111932 - 17 Nov 2022
Viewed by 1789
Abstract
The goal of this study is to investigate the regulation effect of relationship quality in the process of the omni-channel (OC) model on service supply chain (SSC) collaboration of agricultural products. Furthermore, it is also to explore the intermediary effect of SSC collaboration [...] Read more.
The goal of this study is to investigate the regulation effect of relationship quality in the process of the omni-channel (OC) model on service supply chain (SSC) collaboration of agricultural products. Furthermore, it is also to explore the intermediary effect of SSC collaboration in the process of service innovation and OC. A questionnaire was developed, research data were gathered from businesses in the agricultural SSC in western China, and an empirical study was carried out by using the AMOS multivariate statistical analysis approach after a thorough review of the literature in recent years. The study demonstrates that the OC model has a considerable impact on service innovation, SSC collaboration has an intermediary effect, and the quality of supply chain (SC) relationships has a regulation effect in the model. The results inspire academics and industry professionals to focus on SSC collaboration, improve the OC model’s administration, and promote service innovation in agricultural SC. Finally, the paper proposes suggestions to promote agricultural product development in western China in terms of enhancing SSC collaboration, OC model, and service innovation. Full article
Show Figures

Figure 1

23 pages, 1040 KiB  
Article
Addressing Rural–Urban Income Gap in China through Farmers’ Education and Agricultural Productivity Growth via Mediation and Interaction Effects
by Jianxu Liu, Xiaoqing Li, Shutong Liu, Sanzidur Rahman and Songsak Sriboonchitta
Agriculture 2022, 12(11), 1920; https://doi.org/10.3390/agriculture12111920 - 15 Nov 2022
Cited by 4 | Viewed by 1894
Abstract
Narrowing the rural–urban income gap is an important challenge in achieving sustained and stable economic and social development in China. The present study investigates the role of farmers’ education and agricultural productivity growth in influencing the rural–urban income gap by applying mediation, interaction, [...] Read more.
Narrowing the rural–urban income gap is an important challenge in achieving sustained and stable economic and social development in China. The present study investigates the role of farmers’ education and agricultural productivity growth in influencing the rural–urban income gap by applying mediation, interaction, and quantile regression models to provincial panel data of China from 2003 to 2017. Results show that, first of all, China’s agricultural productivity (TFP) continues to improve, and it is mainly driven by technical change (TC), with no significant role of technical efficiency change (TEC) or stable scale change (SC). Improving farmers’ education not only directly narrows the rural–urban income gap but also indirectly improves agricultural productivity to further narrow the rural–urban income gap. Due to differences in income sources of farmers, the corresponding impacts of farmers’ education and agricultural productivity growth on the rural–urban income gap also differ. Policy recommendations include continued investments in farmers’ education and training as well as modernization of agricultural for higher productivity growth. Full article
Show Figures

Figure 1

22 pages, 1006 KiB  
Article
The Technical Efficiency of Beef Calf Production Systems: Evidence from a Survey in Hebei, China
by Yongjie Xue, Jinling Yan, Yongfu Cui, Huifeng Zhao, Ya’nan Zhang, Changhai Ma and Haijing Zheng
Agriculture 2022, 12(10), 1604; https://doi.org/10.3390/agriculture12101604 - 03 Oct 2022
Cited by 2 | Viewed by 1587
Abstract
Beef calf production is a source of sustainable development for the beef cattle industry. However, no comparative studies have reported on the technical efficiency of different beef calf production systems and their influencing factors. Based on data from 218 Chinese farmers and 12 [...] Read more.
Beef calf production is a source of sustainable development for the beef cattle industry. However, no comparative studies have reported on the technical efficiency of different beef calf production systems and their influencing factors. Based on data from 218 Chinese farmers and 12 governments, in the present study, we constructed data envelopment analysis (DEA) models and conducted a comparative analysis of the technical efficiency of the main three beef calf production systems: the Simmental calf intensive production system (CIPS), Simmental calf semi-intensive production system (SCIPS) and Holstein bull calf intensive production system (BCIPS). Using Tobit models, we analyzed the effects of various factors. The results show that: (1) The technical efficiency of the production system of Simmental calf is higher than that of Holstein bull calf, and the efficiency of SCIPS is higher than that of CIPS. The technical efficiency (TE), pure technical efficiency (PTE) and scale efficiency (SE) of different systems are significantly different. (2) Policy on the environment positively affected (p < 0.01) the TE, TPE and SE of CIPS, but negatively affected the PTE of SCIPS. Therefore, appropriate environmental regulations have a positive effect on production efficiency, which means that measures should be taken according to the reality and characteristics of the production system, and policies applicable to other systems or regions may not be applicable in a given case. (3) The management level and technology training had positive effects on the TE, TPE and SE of the three systems, while the number of years of production had a negative or no significant effect. Producers are not the “perfectly rational economic man”, and the more knowledge they have, the more productive they will be. However, the “knowledge” referred to here is that which is adapted to production, not that which is traditional. The knowledge possessed by the producer should be updated continuously with the changes over time and the development of the industry, while outdated information is not considered as “knowledge” here. Therefore, to achieve sustainability, the government should fully consider the characteristics of the local breeding mode and, more importantly, the expected effects of policies to be implemented. Full article
Show Figures

Figure 1

13 pages, 569 KiB  
Article
Technical Efficiency of Rice Production in the Upper North of Thailand: Clustering Copula-Based Stochastic Frontier Analysis
by Yaovarate Chaovanapoonphol, Jittima Singvejsakul and Songsak Sriboonchitta
Agriculture 2022, 12(10), 1585; https://doi.org/10.3390/agriculture12101585 - 01 Oct 2022
Cited by 4 | Viewed by 2175
Abstract
This study examines the efficiency of rice production in Thailand, especially major rice, which is the main crop of farmers in all regions of Thailand and is still a pressing issue. Analyzing technical efficiency by using the appropriate analytical tools inevitably brings about [...] Read more.
This study examines the efficiency of rice production in Thailand, especially major rice, which is the main crop of farmers in all regions of Thailand and is still a pressing issue. Analyzing technical efficiency by using the appropriate analytical tools inevitably brings about determining the correct production efficiency measures. In this study, we applied the K-Means algorithm and copula-based stochastic frontier model to cluster farmer groups in order to find the different factors that impact the group, and to relax the assumption of the two components of random error, which is that they are independent to each other; the correlation of the two components of random error is also represented by the estimation of copula. The findings from the K-Means clustering algorithms applied in this study indicate that the production frontiers can be divided into two frontiers, with the number of farmers under the frontiers of such production differing from the number of farmers collected in each area. The production frontiers were obtained with 591 farmers under the first production frontier and 65 farmers under the second. In addition, the results reflected a correlation between the two error components U and V. This suggests inefficiencies and zero-mean, and that the symmetric error is not independent of each other. The findings from the application of the copula-based stochastic frontier production function models indicate that land, cost of chemicals, and labor inputs have significant positive effects on the mean output of major rice in both groups of farmers. Therefore, the results of this study indicate that the financial services in rural areas should be continuously promoted by governmental policy, particularly via agricultural loans, to rural people since the utilization of inputs affects the quantity of rice produced. Timely loans should be encouraged. Full article
Show Figures

Figure 1

19 pages, 2158 KiB  
Article
Measurement and Analysis of Contribution Rate for China Rice Input Factors via a Varying-Coefficient Production Function Model
by Zehua Li, Xiaola Wu, Xicheng Wang, Haimin Zhong, Jiongtao Chen and Xu Ma
Agriculture 2022, 12(9), 1431; https://doi.org/10.3390/agriculture12091431 - 09 Sep 2022
Cited by 2 | Viewed by 1401
Abstract
To explore the internal driving force of the growth of rice yield per unit area in China, a model based on varying-coefficient production function is proposed in this study, which comes from the idea that the constant elasticity parameters in the Cobb-Douglas production [...] Read more.
To explore the internal driving force of the growth of rice yield per unit area in China, a model based on varying-coefficient production function is proposed in this study, which comes from the idea that the constant elasticity parameters in the Cobb-Douglas production function can be extended to functional forms. Applying such model to economic growth analysis, on the one hand, the dynamic contribution rate of each input factor can be measured, and, on the other hand, the contribution rate of the input factor can be decomposed into net factor contribution rate and interaction factor contribution rate, thus expanding the explanatory ability of growth rate equation. Using such model, the output elasticity of capital and labor in China’s rice yield growth are calculated from 1978 to 2020, and the dynamic characteristics of the contribution rate of capital, labor and generalized technological progress are analyzed. Next, the capital contribution rate is decomposed according to the composition of the total capital. The results show that: (1) The capital elasticity and labor elasticity are indeed not constant in different years. In China, from 1978 to 2020 the value of capital elasticity was between 0.3209 to 0.3589, with a mean of 0.3437, and the value of labor elasticity was between −0.1759 to −0.1640, with a mean of −0.1730. (2) Natural disasters do affect capital elasticity and labor elasticity in rice production. (3) When the annual proportion of crop disasters increases, the contribution rate of interaction between capital and natural disaster (KDR) value is negative, whereas the contribution rate of interaction between labor and natural disaster (LDR) value is positive. (4) Compared with 1978, the generalized technological progress contribution rate (GTPR) of the rice yield growth in China from 1979 to 2020 shows a declining trend in fluctuations, whereas the total capital contribution rate (TKR) shows a rising trend in fluctuations and the total labor contribution rate (TLR) is relatively stable in the same period. Since 2000, capital investment has become the main factor for the rice yield growth per unit area in China, of which machinery, chemical fertilizer, seed and pesticide are the four most important input factors. Full article
Show Figures

Figure 1

Back to TopTop