Impact of artificial intelligence on the total productivity of agricultural factors in Africa

被引:0
|
作者
Donfouet, Olivier [1 ]
Ngouhouo, Ibrahim [1 ]
机构
[1] Univ Dschang Cameroon, Fac Econ & Management, Grp Rech Econ Appl & Dev GREAD, Dschang, Cameroon
关键词
Productivity; Agriculture; Artificial intelligence; SHIP; TFP and DID; N57; N77; Q16; PRECISION AGRICULTURE; PROPENSITY SCORE; US;
D O I
10.1007/s10668-024-05528-y
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This study analyzes the impact of artificial intelligence (AI) on agricultural total factor productivity (TFP) in 53 African countries from 2012 to 2020. The results of the propensity score matching analysis show that Artificial Intelligence improves Total Factor Productivity. The average treatment effect (ATT) is 12.40 with a T-test of 4.74, indicating a positive and significant effect at 1%. The graphs show strong data overlap, with no unsupported units. Robustness tests, including the difference-in-difference (DID) method, confirm these results. Other econometric techniques, such as ordinary and generalized least squares, fixed and random effects, also corroborate these findings. To take full advantage of Artificial Intelligence in African agriculture, it is crucial to strengthen policies in the areas of digital infrastructure, training, financing, innovation, data regulation and awareness-raising.
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页数:29
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