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Examining the Regional Disparity of Agricultural Development: A Distribution Dynamics Approach
Many scholars have argued that the increased disparity in agricultural development among countries is the crux of the regional inequality problem and exerts adverse effects on individuals’ well-being. This study thus aims to examine the distribution dynamics of global agricultural development. Specifically, it examines whether the disparity in agricultural development among countries vanishes over time and whether convergence can be achieved. On that account, a new distribution dynamics analysis method based on the stochastic kernel approach is employed at the country level. The proposed model can address the inadequacies of traditional econometric modelling methods and visualisation tools in the distribution dynamics literature. The research outcomes are as follows. Firstly, the global agricultural income disparity is primarily due to the Global South countries’ low productivity level, which lowers the world average, indicating that these countries need more fiscal and financial aid from Global North countries to boost their agricultural sector productivity levels. Secondly, regarding income division, upper-middle-income countries have been above the average output levels, indicating the invalidity of the middle-income trap for these countries’ agricultural sectors. This finding suggests that increased investment in agricultural productivity can overcome the middle-income trap. Thirdly, from a geographical perspective, Europe, Central Asia, and North America have a technological edge in the agricultural sector. In contrast, East Asia and Pacific countries have the potential to boost agricultural sector productivity. As a result, this study helps policymakers to design better schemes to improve the development of agriculture for each group and country type to improve the development of agriculture for each group and country type.
Examining the Regional Disparity of Agricultural Development: A Distribution Dynamics Approach
Many scholars have argued that the increased disparity in agricultural development among countries is the crux of the regional inequality problem and exerts adverse effects on individuals’ well-being. This study thus aims to examine the distribution dynamics of global agricultural development. Specifically, it examines whether the disparity in agricultural development among countries vanishes over time and whether convergence can be achieved. On that account, a new distribution dynamics analysis method based on the stochastic kernel approach is employed at the country level. The proposed model can address the inadequacies of traditional econometric modelling methods and visualisation tools in the distribution dynamics literature. The research outcomes are as follows. Firstly, the global agricultural income disparity is primarily due to the Global South countries’ low productivity level, which lowers the world average, indicating that these countries need more fiscal and financial aid from Global North countries to boost their agricultural sector productivity levels. Secondly, regarding income division, upper-middle-income countries have been above the average output levels, indicating the invalidity of the middle-income trap for these countries’ agricultural sectors. This finding suggests that increased investment in agricultural productivity can overcome the middle-income trap. Thirdly, from a geographical perspective, Europe, Central Asia, and North America have a technological edge in the agricultural sector. In contrast, East Asia and Pacific countries have the potential to boost agricultural sector productivity. As a result, this study helps policymakers to design better schemes to improve the development of agriculture for each group and country type to improve the development of agriculture for each group and country type.
Examining the Regional Disparity of Agricultural Development: A Distribution Dynamics Approach
Jing Li (Autor:in) / Tsun Se Cheong (Autor:in) / Wenyang Huang (Autor:in) / Wai Yan Shum (Autor:in)
2022
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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