Do pesticide retailers’ recommendations aggravate pesticide overuse? Evidence from rural China

Artikel

In rural China, pesticide retailers are often accused of recommending farmers apply more pesticides than the scientifically recommended rate, while playing an important role in providing technical information regarding pesticide use to farmers. However, there is little empirical evidence on the relationship between pesticide retailers’ recommendations and farmers’ pesticide overuse. Using survey data from 1084 rice farmers in four provinces, this study utilized an endogenous switching probit model to examine the impact of pesticide retailers’ recommendations on the overuse of pesticides at the level of pest-control observation, accounting for potential self-selectivity bias. Results show that the proportion of pesticide overuse at the level of pest-control observation for controlling major pests, secondary pests, and weeds is 58.5, 55, and 40.6%, respectively. Pesticide retailers’ recommendations are found to increase the probability of pesticide overuse at the level of pest-control observation for controlling major pests, secondary pests, and weeds by 62.1, 59.3, and 58.3%, respectively. The robustness check using a conditional mixed process model provided consistent findings. Accordingly, this study proposes that more efforts should be made to provide additional technology training activities for pesticide retailers, strengthen regulations on pesticide retailers’ information recommendations, and further improve socialized agricultural technology services.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Journal: Agriculture ; ISSN: 2077-0472 ; Volume: 13 ; Year: 2023 ; Issue: 7 ; Pages: -- ; Basel: MDPI

Klassifikation und Themen

• Klassifikation: Landwirtschaft, Veterinärmedizin
• Thema: pesticide use ; information source ; endogenous switching probit model ; self-selectivity bias

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Sun, Shengyang ; Zhang, Chao ; Hu, Ruifa ; Liu, Jian
• Ereignis: Veröffentlichung
• (wer): MDPI
• (wo): Basel
• (wann): 2023

Weitere Informationen

• DOI: doi:10.3390/agriculture13071301
• Handle: http://hdl.handle.net/10419/273152
• Letzte Aktualisierung: 10.03.2025, 11:43 MEZ