Reducing fertilizer overuse via mechanized fertilization in China: Is outsourcing more effective?

Abstract

This study examines the impact of different mechanized fertilization models- specifically, outsourcing fertilization services versus purchasing fertilization machinery- on fertilizer use intensity, using survey data from rice scale farms in East China. To address potential selection bias, we employ a treatment effect model to examine the average (homogeneous) impact of outsourcing and use an unconditional quantile regression model combined with a two-stage predictor substitution approach to explore the impact at different levels of fertilizer use intensity. Additionally, we construct a stochastic meta-frontier input distance function to evaluate fertilizer use efficiency and the fertilization technology gap ratio among farmers using different mechanized fertilization models. To further elucidate the mechanisms through which outsourcing influences fertilizer use intensity, we apply a fractional regression model. Empirical results reveal that outsourcing fertilization services significantly reduces fertilizer use intensity compared to the use of self-owned fertilization machinery, with an average decrease of 7.93 % per mu and 7.88 % per 100 kg of rice yield. Notably, the reduction is more pronounced among farmers with initially higher levels of fertilizer use intensity. While farmers using outsourcing achieve similar fertilizer use efficiency relative to their frontiers as those using self-owned fertilization machinery, they differ significantly in the fertilization technology gap ratio. Outsourcing significantly improves the technology gap ratio, suggesting that its advantage in reducing fertilizer use intensity primarily due to improved fertilization techniques.