Renting-in cropland, machinery use intensity, and land productivity in rural China

Abstract

This study examines the impacts of renting-in cropland on machinery use intensity, utilizing an innovative endogenous-treatment Poisson regression (ETPR) model and survey data from wheat farmers in China. We also analyse how machinery use intensity affects land productivity, reflected by wheat yields and net returns, using a two-stage residual inclusion (2SRI) model. Unlike previous studies that consider general machinery use, this study considers self-owned machinery use intensity and purchased machinery service use intensity. The ETPR model results reveal that renting-in cropland significantly increases self-owned machinery use intensity. However, it has a negative and insignificant impact on purchased machinery service use intensity. The 2SRI model estimates show that increasing self-owned machinery use intensity and purchased machinery service use intensity significantly increases wheat yields and net returns. Our findings suggest that it is essential to take stakeholders’ land transfer status into account when designing policies to promote agricultural mechanization and enhance land productivity.