The Association Between Neighbor Labor Exchange and the Adoption of Green Production Technologies Among Plateau Farmers: Evidence from the Use of Low-Residue Pesticides and Organic Fertilizers

The adoption of green production technologies (GPTs) is an important component of the agricultural green transition. However, under the combined pressures of persistent rural labor outmigration and population aging, limited attention has been paid to the relationship between informal mutual-aid institutions within rural communities and GPT adoption. Using cross-sectional survey data from 675 plateau farmers in western Sichuan, a bivariate Probit model and mediation analysis are employed to examine the association between neighbor labor exchange and farmers’ willingness to adopt and adoption behavior of GPTs and to explore the potential explanatory pathways. The results show that participation in neighbor labor exchange is significantly and positively associated with both farmers’ willingness to adopt and adoption behavior of GPTs, and the findings remain robust after a series of robustness tests. Participation in neighbor labor exchange is significantly and positively associated with both outcomes, and similar patterns are obtained in several robustness checks. Green quality cognition is also associated with neighbor labor exchange and both adoption outcomes, providing exploratory evidence of a potential indirect pathway. Formal between-group tests indicate that the positive association with willingness to adopt GPTs is stronger among farmers with better self-rated health. They also provide tentative evidence that the positive association between neighbor labor exchange and adoption behavior of GPTs is stronger among agriculture-dependent households. In addition, the average marginal interaction results indicate that the positive association between neighbor labor exchange and willingness to adopt GPTs is weaker among market-oriented households, whereas no statistically significant interaction is found for adoption behavior of GPTs. They suggest that rural mutual-aid networks, GPT-related information and training, and differentiated extension strategies warrant consideration in the promotion of GPTs in plateau regions.