No abstract

This letter investigates the factors that drive farmers’ willingness to adopt (WTA) e‐commerce, with a focus on the role of Internet use. The recursive bivariate probit model is applied to analyze data collected from rural China. The empirical results reveal that Internet use increases the likelihood of farmers’ WTA e‐commerce by 20%. Further, we show that the WTA effects of Internet use are heterogeneous between male and female household heads and among different regions.

Crop production in developing and emerging countries is increasingly dependent on the usage of farm machinery. However, it remains unclear whether low-productive and high-productive farmers benefit equally from farm machinery use. To address the research gap, this study examines the potential heterogeneous effects of farm machinery use on maize yields, using an unconditional quantile regression model and survey data from China. We employ a control function approach to address the selection bias issue associated with farm machinery use. The empirical results show that the use of farm machinery significant increases maize yields for all the selected quantiles (except for the 80th quantile); the low-productive farmers tend to benefit more from farm machinery use relative to their high-productive counterparts; and farm machinery use reduces the inequality and variability of maize yields.

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Although chemical pesticide use has increased agricultural productivity, it has caused adverse effects on human health and the environment. For example, pesticide exposure may result in the incidence of a human health condition (e.g., heart disease, immune disorders, cancer, and damaged skin) and it can pollute air, water, and soil conditions and damage biodiversity. Mitigating the negative externalities associated with pesticide use is essential to improve human health and environmental performance. In this study, we are trying to explore whether farm machine use reduces pesticide expenditure by analyzing farm household survey data collected from 493 maize farmers in China. An endogenous switching regression model is employed to address the sample selection bias issue associated with voluntary farm machine use. The empirical results reveal that farm machine use exerts a negative and statistically significant impact on pesticide expenditure. The findings highlight the important role of farm machines in helping reduce pesticide expenditure, which is, in turn, beneficial for improving human health conditions and environmental performance.