Unveiling the impact and mechanism of agricultural input allocation on the income mobility of rural households: Evidence from China

IF 5.2 1区 经济学 Q1 ECONOMICS 中国经济评论 Pub Date : 2025-01-23 DOI:10.1016/j.chieco.2025.102356
Yun Shen , Di Zeng , Alec Zuo
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Abstract

Income mobility is crucial in dismantling social stratification and fostering social integration. Facilitated by a balanced panel dataset comprising 792 rural households from 1986 to 2020 in Sichuan province, China, this study seeks to assess the impact of agricultural input allocation on rural households' income mobility. A multi-level differentiated polarization index is constructed to capture the dynamic characteristics of farmers' income polarization. Shapley value decomposition is used to breakdown farmers' income polarization index according to the source of income. Based on these, panel data econometric modelling is further utilized to answer the research question. It is found that optimal allocation of agricultural inputs fosters income mobility and mitigates income polarization. Misallocation in agricultural inputs, especially labour and intermediate products, substantially elevate the income polarization level for about one third of rural households. However, mediation analysis reveals that the surge in off-farm employment alters the income mobility structure by shifting the source of income polarization from agricultural income to off-farm income. Elevating the proportion of off-farm employment among rural households and accelerating agricultural socialization services can therefore help optimize agricultural input allocation and facilitate income class upgrades among rural households.
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来源期刊
中国经济评论
中国经济评论 ECONOMICS-
CiteScore
10.60
自引率
4.40%
发文量
380
期刊介绍: The China Economic Review publishes original works of scholarship which add to the knowledge of the economy of China and to economies as a discipline. We seek, in particular, papers dealing with policy, performance and institutional change. Empirical papers normally use a formal model, a data set, and standard statistical techniques. Submissions are subjected to double-blind peer review.
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