Stagnation or upward mobility? The influence of achieved and ascribed factors on the housing careers of residents in Shanghai

Rapid housing price increases have intensified barriers to homeownership and widened housing inequality globally and in China. While many studies examine cross-sectional housing states or discrete events (e.g., homeownership entry), individuals’ housing states change across the life course, producing divergent trajectories even among similar individuals. The study foregrounds “housing careers” as sequences of tenure and location/price states over time. In China, market-oriented housing reforms—privatization of public housing and market mechanisms—have transformed constraints and opportunities, likely altering the roles of achieved factors (education, occupation) and ascribed factors (family and place of origin). Prior Chinese research largely examined discrete events and emphasized achieved factors, overlooking life-course dynamics and inherited advantages. This paper asks: (1) How do individual housing states change over time? (2) How do ascribed and achieved factors affect housing careers? (3) Do these effects vary across cohorts under China’s housing reforms? Using a retrospective Shanghai survey (2018–2019), the study integrates discrete events into continuous sequences and incorporates family of origin and place of origin to illuminate cohort differences and temporal dynamics in housing inequality.

Housing careers describe sequences of tenure and location/price states through residential moves, with transitions to homeownership often viewed as a key goal. Prior work highlights achieved factors, especially education and occupation, but their effects vary by context: strong effects where homeownership is culturally promoted, weaker in tenure-neutral systems (e.g., Germany). Cultural regimes shape trajectories: in rental-oriented societies, long renting with limited parental support is common; in ownership-oriented societies, intergenerational transfers are prevalent. Ascribed factors—family of origin (parental homeownership, economic status, employer type, sibship) and place of origin—have gained importance amid price inflation and precarious labor markets. Evidence shows parental resources increasingly facilitate earlier homeownership, particularly where renting is less feasible. Place of origin matters through housing cultures and institutions; in China, hukou stratifies access, with migrants disadvantaged versus locals in tenure and location. Despite extensive findings on discrete transitions, fewer studies examine how ascribed and achieved factors shape full housing careers, especially under China’s evolving housing system. Market transition and rising prices suggest changing influences across cohorts: achieved factors may grow in salience with marketization, while soaring prices may heighten the role of ascribed advantages for younger cohorts.

Conceptual framework and hypotheses: The study posits both achieved factors (education level, employer type, CCP membership, current hukou) and ascribed factors (parental economic level, parental homeownership, parental employer type, sibship configuration, initial hukou) shape housing careers, with potentially changing effects across cohorts under housing reforms. Hypotheses: H1—higher education, public-sector employment, and CCP membership associate with upward housing careers; H2—higher parental economic status, parental homeownership, and public-sector parental employment associate with earlier homeownership and upward careers; H3—housing ladder advantage by hukou group: locals > permanent migrants > temporary migrants; H4—effects of achieved/ascribed factors vary by cohort, with achieved factors (e.g., education) gaining influence over time and ascribed factors weighing more for younger cohorts due to affordability pressures. Data and sampling: A multi-stage, stratified PPS survey in Shanghai (2018–2019) sampled sub-districts in 13 districts, then one neighborhood per selected sub-district, then 25–40 households per neighborhood. Respondents were household heads/spouses aged 18–60 residing >6 months. 1127 households surveyed; 1050 valid for analysis (some tables report n=1009–1052 depending on model/sequence completeness). The retrospective life-history survey collected annual housing states from age 18–60 in Shanghai, socio-demographics, achieved factors, and family-of-origin attributes (parental economic status, employer type, homeownership at respondent age 14). Measures: Annual housing state (age 18–60) defined by tenure and location/price: renters within middle ring (RC) vs outside middle ring (RS); owner-occupiers by neighborhood 2018 unit price: O1 <40k RMB/m2; O2 40–60k; O3 60–80k; O4 >80k. Generalized housing career categories: R (rental throughout), O (ownership throughout), UP (rent→own and/or move from lower- to higher-priced ownership), DW (own→rent and/or higher→lower-priced ownership). Key predictors: cohort (Post60&70 vs Post80&90), hukou status (locals; permanent migrants—transferred to local hukou; temporary urban migrants; temporary rural migrants), achieved factors (education: below HS, HS, junior college, bachelor+; employer type public; CCP membership), ascribed factors (parental economic level, parental homeownership, parental employer type, sibship configuration: sex by one-child vs multi-child). Controls: marital status; length of housing career in Shanghai since age 18 (years). Analytic strategy: Sequence analysis (TraMineR in R) produced sequence index and state distribution plots to visualize trajectories by age and by subgroups (education, parental homeownership, hukou). Multinomial logistic regression (Stata 15) modeled housing career category (ref: R), with Model 1 including achieved and ascribed factors plus controls; Models 2–4 added interactions: cohort×hukou, cohort×education, cohort×parental homeownership. VIFs <3 indicated no multicollinearity.

Descriptive sequence patterns: - Many respondents began as homeowners; among renters, upward mobility (rent→own; O1/O2→O3/O4) increased with age. Renters in central areas (within middle ring, RC) were more likely to transition to ownership than suburban renters (RS). - Before age 30, >70% had only one housing experience; homeownership rates rose with age and peaked around age 50, especially in O3/O4. By education: - Higher education associated with earlier and higher rates of homeownership and greater prevalence of higher-priced ownership (O3/O4). Those below high school were more likely to remain renters. Individuals with bachelor+ started with lower rental shares and saw rapid increases in O3/O4 with age. By parental homeownership: - Parental homeownership conferred early advantages: higher initial homeownership, especially in O3/O4. Differences in homeownership rates narrowed with age as non-advantaged groups caught up, but initial gaps were substantial. By hukou: - Locals had pronounced advantages—earlier transition to homeownership and longer dwelling stability. Permanent migrants improved rapidly, with most becoming owners by ~age 30 and many reaching O3; temporary migrants—especially temporary rural—were often trapped in suburban renting (RS) with persistently low homeownership. Generalized housing career categories (Table 2): - R (rental throughout): 18.73%. - O (ownership throughout): 45.25%. - UP (upward moves): 26.99%. - DW (downward moves): 9.03%. Multinomial regression (ref: R), main effects (Model 1): - Cohort: Younger cohorts (Post80&90) were less likely to achieve UP and more likely to remain renters than older cohorts, consistent with price escalation reducing mobility. - Hukou: Locals most advantaged; permanent migrants lagged locals but fared better than temporary migrants; temporary rural migrants faced the greatest disadvantages in O and UP. - Achieved factors: Education had strong, positive effects; bachelor+ and junior college markedly increased odds of O and UP relative to below high school. Public-sector employment and CCP membership did not confer advantages in upward mobility, indicating weakening institutional effects under affordability stress. - Ascribed factors: Higher parental economic status and parental homeownership significantly increased odds of UP and earlier O. Parental employer type was not significant. Sibship configuration mattered: being an only child (male or female) conferred advantages; males/females in multi-child families were less likely to attain O or UP, supporting the quantity–quality trade-off. - Controls: Marriage and longer housing career length in Shanghai increased odds of UP and O. Interactions across cohorts: - Cohort×hukou (Model 2): Disadvantages for migrants vs locals intensified among younger cohorts. Permanent migrants showed no significant disadvantage among older cohorts but did among younger cohorts; gaps for temporary urban and especially temporary rural migrants widened for younger cohorts. - Cohort×education (Model 3): Education effects strengthened among younger cohorts; higher education was more strongly associated with O/UP for Post80&90 than for older cohorts. - Cohort×parental homeownership (Model 4): No significant cohort differences; the effect of parental homeownership did not vary across cohorts. Overall: Ascribed advantages shape the starting point (early entry, higher-priced ownership), while achieved advantages—especially education—exert cumulative effects and have grown in importance for younger cohorts. Permanent migrants can overcome initial disadvantages and achieve upward trajectories, whereas temporary migrants are more likely to remain renters.

The study demonstrates that housing inequality in Shanghai is best understood as a dynamic process: trajectories diverge over time even from similar starting points. Findings address the research questions by showing (1) housing states generally progress toward ownership and higher-priced ownership with age, yet a sizeable share remains renters throughout; (2) ascribed factors (parental resources, place of origin via hukou) strongly influence initial positions, while achieved factors (education) shape subsequent mobility and cumulative advantages; and (3) cohort differences reflect China’s housing reforms and price dynamics—education’s positive impact intensifies for younger cohorts, while disadvantages linked to non-local hukou have become more pronounced. Policy implications include targeted support: reduce early-stage disadvantages for permanent migrants and provide sustained assistance for temporary migrants, particularly temporary rural migrants who face persistent barriers. The growing salience of education for younger cohorts indicates that human capital remains a key pathway to upward housing mobility, but rising prices magnify inherited inequalities at the starting line.

The paper contributes a temporal perspective to housing inequality in China by analyzing full housing careers rather than discrete events. It integrates ascribed (family and origin) and achieved (education, employment, CCP, current hukou) factors, revealing that parental resources and local origin facilitate early ownership and higher-quality housing, while education drives upward mobility over time. Cohort analyses show that education’s influence has strengthened among younger cohorts, whereas disadvantages tied to non-local hukou have deepened. Permanent migrants can catch up and achieve upward trajectories, but temporary migrants are often locked into renting. Future research should expand measurement of housing careers to include multiple-home ownership and more granular origin characteristics, and examine policy interventions that mitigate early disadvantages while supporting mobility throughout the life course.

- The analysis captures sequences of housing states (tenure and location/price) but not the number of housing units owned; multiple-home ownership—prevalent among urban residents—was not incorporated. - Place of origin for temporary migrants was proxied by rural/urban hukou, without finer differentiation by sending city, limiting granularity on origin effects. - The residence-based sample covered formal neighborhoods only; migrants in informal housing (e.g., factory dormitories, urban villages) were not included, potentially biasing estimates of migrants’ housing careers.