Does Digital Agricultural Technology Extension Service Enhance Sustainable Food Production? Evidence from Maize Farmers in China

Abstract

This research aims to investigate the average and heterogeneous impacts of digital agricultural technology extension service use on eco-efficiency among 1302 maize-producing farmers from a major maize-producing area in Northeast China in 2022. The slack-based measure model with undesirable outputs is applied to calculate the eco-efficiency of maize production. To obtain an unbiased estimation of the average effect, the self-selection problem generated by observable and unobservable factors is solved by the endogenous switching regression model. Quantile regression is utilized to analyze the heterogeneous effect. Notably, the mediated effects model is utilized to examine the potential mechanism between them. Our findings indicate that digital agricultural technology extension service use can increase maize production’s eco-efficiency. Digital agricultural technology extension service users would have reduced the eco-efficiency of the service by 0.148 (21.11%) if they had not used it. Digital agricultural technology extension service nonusers would have improved the eco-efficiency of the service by 0.214 (35.20%) if they had used it. The robustness check reconfirms the results. Moreover, digital agricultural technology extension service use is more helpful for maize farmers who have lower eco-efficiency than those who have higher eco-efficiency. Digital agricultural technology extension service use can improve the eco-efficiency of maize production through the application of organic fertilizers, green pesticides, and biodegradable agricultural films. There are policy implications of these findings: there is an argument for using the publicity of the digital agricultural technology extension service to encourage farmers to use sustainable inputs; additionally, it might be worthwhile to implement a categorized promotion strategy based on the different real-world situations.