Author
Listed:
- Haochen Jiang
(College of Rural Revitalization, Jiangsu Open University, Nanjing 210036, China)
- Yubin Wang
(College of Economics and Management, China Agricultural University, Beijing 100089, China)
- Feng Zhang
(College of Rural Revitalization, Jiangsu Open University, Nanjing 210036, China)
Abstract
With the increasing importance of green transformation in agricultural production, green pest control technologies (GPCTs), defined as a set of eco-friendly methods aimed at managing agricultural pests with reduced reliance on synthetic chemical pesticides, play a key role in improving agricultural production efficiency, ensuring product quality, and protecting the ecological environment. Based on field survey data from apple farmers in Yantai and Linyi cities, Shandong Province, collected in 2022, this paper employs endogenous treatment effects regression (ETR) and instrumental variable quantile regression (IVQR) models to analyze the impact of adopting green pest control technologies on household income and explores the heterogeneity of this effect across different income levels. The results show that the adoption of green pest control technologies significantly increases apple farmers’ net apple income and household income, confirming their income-boosting effect. Moreover, the income-boosting effect is more significant for lower-income farmers, suggesting that these farmers benefit more from the adoption of green pest control technologies by improving pest management and thus enhancing apple production efficiency. This study provides empirical evidence for the promotion of green pest control technologies and offers valuable references for policymakers, especially in supporting technology adoption among lower-income farmers.
Suggested Citation
Haochen Jiang & Yubin Wang & Feng Zhang, 2025.
"Economic Effects of Green Pest Control Technology Adoption on Apple Farmers’ Income: Evidence from China,"
Agriculture, MDPI, vol. 15(13), pages 1-23, June.
Handle:
RePEc:gam:jagris:v:15:y:2025:i:13:p:1335-:d:1684332
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