PurposeThe purpose of this study is to investigate the interactive relationship between non-farm employment and mechanization service expenditure.Design/methodology/approachThe study employs an innovative two-stage probit least squares (2SPLS) model to analyze the survey data collected from 1,148 rural households in China. This model not only simultaneously estimates the impact of non-farm employment on mechanization service expenditure and the impact of mechanization service expenditure on non-farm employment, but also addresses endogeneity issues associated with these two activities.FindingsThe empirical results show that non-farm employment and mechanization service expenditure are jointly determined. In particular, the study finds that non-farm employment significantly increases mechanization service expenditure, and vice versa. The results are confirmed by an estimation that captures a dichotomous decision of mechanization service usage. The interactive effects of non-farm employment on mechanization service expenditure are heterogeneous between male and female household heads and among households with different member sizes. Further analyses reveal that (1) mechanization service expenditure increases with increasing non-farm working time; (2) local non-farm employment, rather than provincial non-farm employment, has a larger impact on mechanization service expenditure; and (3) the number of household members employed in non-farm works does not affect mechanization service expenditure significantly.Originality/valueAlthough mechanization service markets are rapidly growing in many developing and transition countries, little is known about how service purchasing interacts with farmers' decisions to work in the non-farm sector. This study makes the first attempt by investigating the interactive effects of non-farm employment on mechanization service expenditure in rural China. The findings provide significant evidence for policymakers in China and other countries in their efforts to generate non-farm work opportunities and promote agricultural mechanization, with the aim of boosting rural development and improving farm economic performance.
Increasingly, rural households in developing countries are shopping for food online, and the COVID-19 pandemic has accelerated this trend. In parallel, dietary guidelines worldwide recommend eating a balanced and healthy diet. With this in mind, this study explores whether online food shopping boosts dietary diversity—defined as the number of distinct food groups consumed—among rural households in China. Because people choose to shop for food online, it is important to account for the self-selection bias inherent in online food shopping. Accordingly, we estimate the treatment effects of online food shopping on dietary diversity using the endogenous switching model with a count outcome variable. The results indicate that online food shopping increases dietary diversity by 7.34%. We also find that education, asset ownership, and knowing the government’s dietary guidelines are the main factors driving rural households’ decisions to shop for food online.
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