Impact of Digital Agro-Technology Services on Technical Efficiency and Income of Small-Scale Farmers: Empirical Study from Mango Production in China
文献类型: 外文期刊
作者: Chongxin Xie;Yun Gao;Yu Zhong;Zhijun Zhao
作者机构:
关键词: digital agro-technology services;income level;technology efficiency
期刊名称: Agriculture (Switzerland)
ISSN: 2077-0472
年卷期: 2024 年 14 卷 12 期
页码:
收录情况: SCIE(2024版)
摘要: With the market-driven approach to agricultural technical services and the application of digital technology, digital agro-technical services have gradually emerged as a novel service model. However, there is a lack of empirical research on the effectiveness of this service in the academic literature. To address this research gap, this study measured the impact of this service on the technical efficiency and income levels of mango farmers, using data collected from 131 mango farmers in Hainan Province, China, from 2022 to 2024. This study employed the endogenous switching regression model (ESRM) and the inverse probability-weighted regression adjustment model (IPWRA) to analyze the data, addressing endogeneity through the instrumental variable method by replacing core explanatory variables and conducting sub-regional regression for robustness testing. The main research conclusions are as follows: Under the counterfactual assumption of ESRM, farmers who adopt this service would have experienced a decrease in technical efficiency by 0.025 (a decline of 3.6%) if they had not adopted the service. Conversely, farmers who did not adopt it would have seen an increase in technical efficiency by 0.047 (an increase of 7.3%) if they had chosen to do so. Additionally, under the post-treatment income effect estimation using IPWRA, compared to farmers who did not receive the service, those who did so saw an income increase of 15.6%. The analysis results from methods such as K-nearest neighbors matching also confirm this conclusion. Therefore, it is evident that digital agro-technology services play a significant role in improving the technical efficiency and income levels of small-scale farmers.
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