Farm machinery use, off-farm employment and farm performance in China

Abstract

We analyse the joint impacts of farm machinery use and off-farm employment on maize yields and agrochemical expenses from a household survey of 493 farmers in China. Our findings are obtained from an innovative two-stage econometric procedure that combines a bivariate ordered probit model with an endogeneity-corrected ordinary least square regression model. The results show that farmers are jointly making decisions to use farm machines and to work off the farm and that these two household activities affect maize yields and agrochemical expenses in different ways. We show that farm machinery use significantly increases both maize yields and agrochemical expenses, while off-farm employment significantly decreases agrochemical expenses. Our findings highlight the importance of additional machinery use in increasing farm production; the need to account for possible endogeneity in estimation; and the statistical significance of key household characteristics (gender, education, and household size) on overall farm production.