Abstract

BackgroundThere is limited evidence on the association between housing debt and depressive symptoms in China. This study aimed to examine the impact of housing debt on depressive symptoms and explore the heterogeneous impacts arising from two sources of housing debt and two types of housing demands.MethodsUsing data from the 2016 and 2018 China Family Panel Studies (CFPS), this study included 25,232 Chinese individuals. Depressive symptoms were assessed using the eight-item Center for Epidemiological Studies Depression Scale (CES-D8). Housing debt was measured by dummy variables, indicating whether an individual had housing debt, and continuous variables, which were the logarithm of the total amount of housing debt. The two-way fixed effects model was used to examine the relationship.ResultsHousing debt had a significant positive impact on depressive symptoms in China. Individuals with housing debt had a 0.176-point higher depressive symptom score than those without housing debt. A 10% increase in the total amount of housing debt led to a 0.16-point increase in depressive symptoms. Non-bank housing loans significantly increased the level of depressive symptoms with a larger coefficient (coef = 0.289), while the impact of bank housing loans was small and not statistically significant. In terms of the types of housing demands, a positive impact was observed only among individuals who had only one property meeting their housing consumption demands.ConclusionsThis study found a significant positive impact of housing debt on depressive symptoms, primarily driven by non-bank housing loans. Furthermore, housing debt increased the depressive symptoms among individuals with consumption demands, while those with investment demands did not show a significant impact. Government interventions should prioritize easing formal financial constraints and providing support for individuals with housing consumption demands.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call