Empowering migrant worker households: digital finance for inclusive growth
DOI: https://doi.org/10.3846/tede.2026.25796Abstract
This study establishes a Digital Buffer Enhancement framework based on the buffer-stock model to investigate how digital finance affects consumption levels of migrant worker households, with implications for inclusive growth and sustainable development. Utilizing microdata from the 2019 China Household Finance Survey (CHFS) and applying Endogenous Switching Regression (ESR), Instrumental Variable (IV) approach, and quantile regression analysis, the research reveals three key findings. First, digital finance adopters exhibit 13.74% higher consumption levels, while non-adopters could increase consumption by 5.62% via adoption. Intriguingly, the Digital Buffer Enhancement framework identifies three complementary mechanisms: transaction convenience leapfrogging, liquidity constraint mitigation, and income uncertainty reduction, which together reduce precautionary savings thresholds. Second, enhanced marginal effects emerge among elderly households, eastern regions, and low-consumption quantile groups. Third, analysis of consumption structure heterogeneity indicates that developmental consumption elasticity substantially exceeds hedonic and subsistence consumption, with credit functions demonstrating the strongest impact among digital finance types, followed by payment and wealth management services. These findings advance theoretical understanding of technology-driven consumption transformation and provide practical guidance for developing inclusive digital finance policies in emerging economies.
First published online 5 June 2026
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digital finance, migrant worker household consumption, buffer-stock model, ESR modelHow to Cite
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Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University.
This work is licensed under a Creative Commons Attribution 4.0 International License.
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