The sweet burden: Does homeownership improve the economic status of households?

The paper examines whether homeownership improves household economic status in China amid substantial socio-structural changes, widening income gaps, and increasing wealth concentration. Housing is the largest asset for most households and may influence social mobility via a positive wealth effect (wealth accumulation, social and political capital) but may also impose constraints through mortgage burdens and reduced labor mobility (the "housing mortgage label/slave effect"). The study directly evaluates how homeownership relates to changes in household income classes, explores mechanisms (particularly decreased job mobility and risk aversion due to mortgage pressure), and investigates heterogeneity by intergenerational financial support. The goal is to clarify the net effect of homeownership on economic status changes and inform policy on housing and social mobility in China.

The review highlights extensive evidence of socio-economic benefits of homeownership: higher social capital and civic engagement (DiPasquale and Glaeser, 1999), wealth accumulation (Turner and Luce, 2009; Wainer and Zabel, 2020), portfolio effects (Chetty et al., 2017), labor market participation (Chen et al., 2023; Fu et al., 2016), home maintenance, political engagement (Holland, 2011; Yoder, 2020), well-being (Yu et al., 2012), and positive impacts on children (Boehm and Schlottmann, 1999; Green and White, 1997; Haurin et al., 2002). Coulson and Liu (2013) quantify benefits of transitioning from renting to owning (~USD 1,300 equivalent). China-specific studies find increases in political participation, financial market participation, happiness, entrepreneurship, and consumption post-homeownership. However, in China, housing also functions as an investment vehicle and a prerequisite for marriage, and rising prices may crowd out entrepreneurial and other economic activities (Li and Wu, 2014). These conflicting forces make the net impact of homeownership on economic status ambiguous and context-dependent.

Data: The study uses the China Family Panel Studies (CFPS) longitudinal microdata for 2010, 2012, 2014, and 2016, with supplemental use of 2020 for mechanism robustness. Sampling covers most mainland provinces using multistage probability sampling. Sample construction: Urban-only sample due to rural property ownership constraints; winsorization at 1% tails for variables such as income; balanced panel across five years (four consecutive changes) retaining individuals with complete participation; exclusion of missing key variables. Final sample: 13,384 observations from 3,346 individuals across 26 provinces. Measures:

• Dependent variable: Change in household income level between consecutive waves. Households are ranked into 10 ascending income levels each wave; change equals current level minus prior level, ranging from -9 to +9. Positive indicates upward mobility. Robustness uses alternative level partitions (7–9 and 11–13 bins).
• Key independent variable: Homeownership dummy equals 1 if dwelling is full ownership or shared ownership with employer (including certain rent-free/government-provided cases as defined by CFPS ownership categories), 0 otherwise (renters).
• Controls: Marital status, age, sex, hukou (urban), CCP membership, and education. Region/community and year fixed effects are included in panel specifications. Models:
• Baseline OLS of income-class mobility on homeownership and controls with region and year effects.
• Panel fixed-effects and random-effects models to control for unobserved time-invariant heterogeneity at individual/household and community levels.
• Endogeneity addressed via instrumental variables: provincial land supply area (years 2010, 2012, 2014, 2016, 2018), argued to be exogenous due to administrative control over land supply.
• Propensity score matching (nearest-neighbour, radius, kernel) to mitigate selection bias.
• Robustness checks: alternative income binning; adding perceived housing price appreciation (annual and multi-year average regional housing price growth rates) to control for expected wealth effects; re-estimation with latest CFPS 2020 data. Mechanism test: Uses CFPS 2010 and 2020 job mobility item "Is your current job your first job?" (1=yes) to proxy lower job mobility; estimates OLS/Logit/Probit models to test if homeowners are more likely to remain in first job. Heterogeneity: Splits sample by presence/absence of intergenerational financial support to assess whether parental/grandparental financial help mitigates mortgage burden effects.

• Baseline and panel estimates: Homeownership is significantly negatively associated with changes in household income level (lower upward mobility). Coefficients around -0.256 to -0.425 across OLS, fixed- and random-effects (e.g., Table 2: OLS -0.277*** (0.096), FE -0.256*** (0.095), RE -0.295** (0.104)).
• Instrumental variable approach: Using provincial land supply area as IV, the negative relationship persists and remains significant at the 1% level, corroborating baseline results (Table 3).
• Propensity score matching: Across nearest-neighbour, radius, and kernel matching, homeownership retains a significantly negative effect on income mobility (e.g., -0.239*** to -0.267***; Table 4).
• Alternative income binning: Using 7–9 and 11–13 income levels, the homeownership coefficient remains negative and significant (e.g., -0.221** to -0.375**; Table 5), indicating robustness to categorization.
• Controlling perceived housing price growth: Adding recent regional housing price growth rates leaves the homeownership coefficient negative and significant (about -0.293***; Table 6).
• Latest CFPS 2020: Fixed-effects estimates continue to show a negative association (about -0.419** to -0.422**; Table 7).
• Mechanism – job mobility: Homeowners are more likely to remain in their first job, indicating lower job mobility (OLS: 0.052** (0.017); Logit: 0.214*** (0.071); Probit: 0.133*** (0.044); Table 8).
• Heterogeneity by intergenerational support: For households without intergenerational financial support, homeownership has a significant negative relationship with income status changes (e.g., -0.471** (0.209)); for those with intergenerational support, the effect is not significant (Table 9). Overall, results imply mortgage burdens and reduced mobility drive the adverse association, and family financial transfers can mitigate it.

The findings indicate that, in China’s context, the net impact of homeownership on short- to medium-term changes in household economic status is negative, contrary to the often-cited wealth and social-capital benefits of owning. The results support a mechanism where housing’s spatial immobility and mortgage obligations lock homeowners into existing jobs, reduce job changes toward higher-paying opportunities, and discourage risk-taking in entrepreneurship and high-return investments. Robustness across multiple econometric strategies (FE/RE, IV, PSM), alternative income classifications, and controls for expected housing wealth gains suggest the negative association is not an artifact of model specification or selection. The heterogeneity analysis shows that intergenerational transfers alleviate the mortgage burden, neutralizing the negative effect, consistent with a financing-constraint channel. Within China’s institutional environment—where public services and social resources are highly tied to ownership and housing absorbs a large share of household portfolios—the mortgage burden can outweigh potential wealth effects for mobility in income class, especially absent family support.

The study contributes by directly linking homeownership to measured changes in household income class using rich CFPS panel data and by illuminating the mechanism of reduced job mobility (“housing mortgage slave effect”). It establishes that homeownership, on average, does not improve and is associated with a decline in household income mobility in urban China; effects are robust to endogeneity and alternative specifications. Mechanism analysis shows homeowners have lower job mobility, and heterogeneity analysis reveals that intergenerational financial support mitigates the negative association. Policy implications include: avoiding over-promotion of ownership as a mobility tool; reducing mortgage burdens (e.g., lower interest rates, longer maturities); developing deeper financial markets to diversify household assets beyond housing; equalizing access to public services for renters and owners; and continuing policies aimed at curbing housing speculation. Future research should test generalizability across different economic cycles, housing market regimes, and cultural contexts.

• Temporal context: Results are estimated during a period of rapid economic growth and structural transformation in China; effects may differ across economic cycles.
• Housing boom period: Extraordinary appreciation may obscure or offset income mobility effects.
• Cultural and institutional specificity: China’s strong cultural preference for ownership and institutional ties between public services and homeownership may limit generalizability.
• Data constraints: Mechanism tests rely on available job mobility proxy (remaining in first job) and on CFPS waves with that item (2010, 2020).