Agricultural productive services and rural income growth: An IV-based quantile regression analysis

Abstract

Little is known about the reverse causality between agricultural productive services and farmers' income. To address this research gap, in this study, we analyze the impact of agricultural productive services on rural incomes, using the data derived from the China Household Income Survey (CHIP) and an instrumental variable-based quantile regression model. The results show that the usage of agricultural productive services has a positive and significant impact on farmers' income, and there exerts a Matthew effect. In particular, the income effects of agricultural productive services are higher for farmers at higher income quantiles. Our findings suggest that promoting agricultural productive services and diversifying the service extension modes can help further increase rural incomes.