Identifying the determinants of crop yields in China since 1952 and its policy implications

Abstract

Food security is one of the main challenges facing humanity, and increasing crop yields is critical to meet the growing global food demand. Grain production in China has remarkably improved since its founding in 1949, but the growth remains uneven across regions. The goal of this research was to assess the determinants of the yields of three major food crops (maize, rice, and wheat) in China and the mechanism of their responses to increased crop yields. Boosted regression tree models were created to capture the linked complex predictor-response relationships between crop yields and individual explanatory variables using prefecture-level agricultural statistics in China coupled with geographic data during the period from 1952 to 2017. The results showed that technological inputs (e.g., fertilizers, electricity consumption, and power of agricultural machinery) played a key role in the increase of crop yields, which explained 47%, 39%, and 62% of the variances in the yields of maize, rice, and wheat during the period 1952–2017, respectively. However, the contribution of technology became weaker over time, while the contribution of agro-environmental conditions and structural characteristics of administrative regions became stronger. Partial dependence plots indicated that encouraging higher technological inputs, accelerating large-scale grain production, shortening the urban-rural income gap, and improving the education of farmers were conductive to increasing crop yields. Overall, our results suggest that grain production policies aimed at increasing crop yields should better reflect the spatial heterogeneity of yield gaps; low-yield-gap regions should improve the utilization efficiency of water and fertilizer and formulate measures to inhibit non-grain production on cultivated land, while high-yield-gap regions should focus on improving technological inputs and promoting agricultural restructuring. This study provides deep insights into the processes of how individual explanatory variables affect crop yields, which is essential to develop differentiated grain production policies and provide valuable references for shortening yield gaps in high-yield-gap regions.