Peer Effects in Digital Finance Usage and Rural Household Consumption: A Double Machine Learning Approach

Using data from the China Household Finance Survey (CHFS), this study develops a simplified intertemporal household consumption‐saving model and uses double machine learning to examine peer effects in digital finance usage and their influence on rural household consumption. The results show significant peer effects in rural households' digital finance usage. The estimates further show that peer households' digital finance usage is positively related to consumption among focal households. The positive relationship is more pronounced among households with greater wealth, higher education levels and lower degrees of ageing. Mechanism analyses suggest that peer households' digital finance usage is linked to weaker liquidity constraints and lower precautionary saving motives among focal households. Further analysis indicates that peer households' digital finance usage relates to both survival‐oriented consumption and development‐oriented consumption, as well as greater breadth of consumption‐category participation. Accordingly, this study argues that strengthening the social learning effect of digital finance usage is crucial for enhancing rural households' consumption capacity and fostering sustainable rural economic development.