The role of commercial agriculture in meeting sustainable development goals in South Africa: Evidence from municipal-level total factor productivity analysis

被引:3
作者
Temoso, Omphile [1 ]
Myeki, Lindikaya W. [2 ]
Motlhabane, Comfort [3 ]
Asante, Bright O. [4 ]
Villano, Renato A. [1 ]
机构
[1] Univ New England, UNE Business Sch, Armidale, NSW, Australia
[2] North West Univ, Sch Agr Sci Agr Econ & Extens, Mafikeng, South Africa
[3] Minist Finance & Econ Dev, Dept Econ, Gaborone, Botswana
[4] Kwame Nkrumah Univ Sci & Technol, Dept Agr Econ Agribusiness & Extens, Kumasi, Ghana
关键词
Commercial agriculture; Sustainable development goals; Municipality total factor productivity; Cluster analysis; National development plan; EFFICIENCY; GROWTH; SYSTEMS; MODELS; DEA;
D O I
10.1016/j.jclepro.2024.142723
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Improving agricultural productivity is critical, both locally and globally, particularly in the pursuit of the Sustainable Development Goals (SDGs) of eradicating poverty (SDG 1), increasing food production for food security (SDG 2), and promoting efficient use of agricultural resources and sustainable farming practices (SDG 12). This study examines and compares total factor productivity efficiency (TFPE) in the South African commercial agricultural sector, along with its drivers, using local municipal-level data. We used the Fa<spacing diaeresis>re-Primont index to assess municipalities' TFPE levels, considering both traditional (economic) factors (labour, land, and operating expenses) and environmental variables (temperature, rainfall, and soil moisture index). Our TFPE index results are not only lower, but they show more variation across municipalities than the economic TFPE index, which is commonly used in agricultural productivity research. This implies that ignoring environmental variables may bias analysis; therefore, future studies should consider including environmental factors in their analyses. We then used hierarchical clustering to group municipalities with similar TFPE levels and components, followed by fractional regression to identify the drivers of efficiency levels. The cluster analysis results reveal that the bestperforming municipalities are in cluster 4, comprising municipalities from the Western Cape Winelands specialising in horticulture production, municipalities near urban areas with better market proximity, those engaged in the global value chain, and those with a high proportion of farmers who own most of their farmland. Furthermore, the fractional regression results show that age, gender, race, market proximity, land use types, and production diversification are significant drivers of TFPE and its components. Our study offers insights into the divergent agricultural TFPE performance among municipalities and the underlying factors causing these disparities. The findings can inform the development of targeted strategies, particularly at the local level, aimed at enhancing agricultural productivity and making significant contributions to achieving the SDGs.
引用
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页数:14
相关论文
共 68 条
[1]  
[Anonymous], 2022, Food Security Update- 2022
[2]  
[Anonymous], 2023, The status of women in agrifood systems, DOI [DOI 10.4060/CC5343EN, 10.4060/cc5343en]
[3]  
[Anonymous], 2019, Sustainable Development Goals: Country report 2019
[4]  
Arndt C., 2020, SA-TIED Working Paper #96
[5]   Drivers of integrated crop-livestock farming system's efficiency for smallholder farmers in the forest-savanna transition agro-ecological zone of Ghana [J].
Asante, Bright O. ;
Villano, Renato A. ;
Temoso, Omphile .
ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY, 2024, 26 (11) :29429-29451
[6]  
Banerjee AV, 1999, ANN WB CONF DEV ECON, P253
[7]  
Bureau J-C., 2022, Agricultural Total Factor Productivity and the Environment: A Guide to Emerging Best Practices in Measurement
[8]  
Calinski T., 1974, COMMUN STAT, V3, P1, DOI [10.1080/03610927408827101, DOI 10.1080/03610927408827101]
[9]   Evaluation of soil moisture extremes for agricultural productivity in the Canadian prairies [J].
Champagne, C. ;
Berg, A. A. ;
McNairn, H. ;
Drewitt, G. ;
Huffman, T. .
AGRICULTURAL AND FOREST METEOROLOGY, 2012, 165 :1-11
[10]   Technology heterogeneity and policy change in farm-level efficiency analysis: an application to the Irish beef sector [J].
Cillero, Maria Martinez ;
Thorne, Fiona ;
Wallace, Michael ;
Breen, James .
EUROPEAN REVIEW OF AGRICULTURAL ECONOMICS, 2019, 46 (02) :193-214