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Do cooperatives participation and technology adoption improve farmers' welfare in China? A joint analysis accounting for selection bias

Dan Yang, Huiwei Zhang, Zimin Liu, Qiao Zeng

2021Journal of Integrative Agriculture55 citationsDOIOpen Access PDF

Abstract

This study examines the impact of farmers' cooperatives participation and technology adoption on their economic welfare in China. A double selectivity model (DSM) is applied to correct for sample selection bias stemming from both observed and unobserved factors, and a propensity score matching (PSM) method is applied to calculate the agricultural income difference with counter factual analysis using survey data from 396 farmers in 15 provinces in China. The findings indicate that farmers who join farmer cooperatives and adopt agricultural technology can increase agricultural income by 2.77 and 2.35%, respectively, compared with those non-participants and non-adopters. Interestingly, the effect on agricultural income is found to be more significant for the low-income farmers than the high-income ones, with income increasing 5.45 and 4.51% when participating in farmer cooperatives and adopting agricultural technology, respectively. Our findings highlight the positive role of farmer cooperatives and agricultural technology in promoting farmers’ economic welfare. Based on the findings, government policy implications are also discussed.

Topics & Concepts

Propensity score matchingSelection biasWelfareChinaAgricultureMatching (statistics)Government (linguistics)BusinessSelection (genetic algorithm)Sample (material)Agricultural economicsSurvey data collectionEconomicsPublic economicsGeographyStatisticsPhilosophyChemistryArchaeologyArtificial intelligencePathologyMarket economyComputer scienceMathematicsLinguisticsMedicineChromatographyAgricultural Innovations and PracticesCooperative Studies and EconomicsOrganic Food and Agriculture
Do cooperatives participation and technology adoption improve farmers' welfare in China? A joint analysis accounting for selection bias | Litcius