Housing stratification and the politics of tenure: Socio-temporal inequalities in Leipzig

Abstract

Rental housing markets in Germany and other European countries are experiencing profound transformations, generating new forms of inequality. While existing research often emphasises binary divisions, such as between owners and tenants, or across generations, it rarely captures the layered stratifications within the rental sector itself. This paper uses original household survey data from Leipzig-Connewitz (n = 427), a neighbourhood marked by post-socialist restructuring and rapid investment influx, to explore how socio-temporal inequalities are shaped by residence duration and landlord type. The analysis develops an empirically grounded typology of rental housing experiences, ordered along a continuum from stability to vulnerability: (i) residents in public and non-profit housing enjoying security and rent affordability; (ii) affluent tenants in high-end private rentals, largely shielded from market pressures; (iii) tenants in corporate housing who face insecurity despite high incomes; and (iv) households in the financially fragile segment of the private rental market, with low rents but limited economic security. These types reflect how tenure structures intersect with socio-economic and temporal dimensions to produce differentiated patterns of housing security and vulnerability. By moving beyond conventional tenure binaries, the research provides a nuanced understanding of contemporary rental markets, particularly in housing systems with high tenant protection and significant non-profit segments. The typology developed here contributes to international housing debates by highlighting how post-reunification legacies, institutional diversity and temporal positioning shape uneven tenant experiences. It provides a conceptual lens for analysing stratification within rental-dominated contexts across East Germany and other regulated housing regimes facing significant investment dynamics.

Keywords

Germany housing inequalities landlord regimes Leipzig rental housing systems socio-temporal stratification

Introduction

The housing experience of tenants is fundamentally stratified by the time of entry and the type of tenancy. Conditions in today’s rental markets are radically different from those of two decades ago, particularly for mobile households. Across European cities, the convergence of housing affordability crises (Haffner and Hulse, 2021), intensified inner-city rental demand (Aalbers et al., 2021), luxury-oriented construction (Hirayama, 2017; Lauermann, 2022) and the transformation of housing into investment assets (Gabor and Kohl, 2022) exposes mobile households to rental markets dominated by landlord and owner elites (Hochstenbach, 2022). This results in access barriers, financial burdens, and, in the lower cost segments, precarious, unsafe and ultimately health-damaging conditions (James et al., 2024). Conversely, long-term tenants and residents in public and not-for-profit housing often enjoy relatively stable and affordable housing, despite increasing financial pressures also in these segments (Aalbers et al., 2017; Beswick and Penny, 2018; Zhang, 2023). This paper examines how such housing inequalities are produced through the interaction of tenure type and temporal positioning.

Recent scholarship has analysed these inequalities as manifestations of political-economic transformations under financialisation, assetisation and rentierisation, processes often described as transnational ‘acts of housing change’ (James et al., 2024: 1277). While much of this work focuses on constrained tenure choices among younger cohorts (Adkins et al., 2022; Ronald and Kadi, 2018; Waldron, 2024), more recent research also highlights intragenerational inequalities, segmentation within tenure types and the contextual heterogeneity of tenant experiences (Howard, 2025; Zhang, 2023).

However, spatial, social and temporal forms of stratification within rental sectors remain under-researched, particularly in regulated housing systems that retain significant non-profit segments despite increasing financialisation (Gustafsson, 2024; Stephens, 2020). Engaging with international debates, therefore, requires closer attention to specific housing regimes. In Germany, the national context offers distinctive features: (i) a rental market that functions as the dominant tenure form across social strata; (ii) comparatively strong rent regulation and (iii) especially in East Germany, rental rates approaching 90% (Rink, 2020; Rink et al., 2022). These particularities warrant a deeper analysis of how housing inequalities play out in the rental sector.

Our approach highlights how rental tenure types (public/non-profit, private, corporate¹) and temporal dimensions (tenure length, building age) jointly condition tenants’ experiences and shape housing inequalities (James et al., 2024). We argue that contemporary inequalities emerge along both axes: different types of landlords engage tenants in different ways, while long-established households remain relatively protected from current market pressures compared to new entrants. Our analysis thus captures how social and temporal differentiation affects tenant satisfaction, financial conditions and housing costs.

Empirically, we draw on an original district-level household survey (n = 427) in Leipzig – Germany’s fastest growing city since the early 2010s. The case allows for a focused examination of intra-rental inequalities: rapid urban change has triggered sharp rent increases, exposing pronounced contrasts between newcomers and long-term residents (Holm, 2025). Leipzig’s unusually high share of rental housing (around 90%) provides an ideal context for identifying patterns of stratification within the rental sector.

The remainder of the article unfolds in five steps: First, we develop a theoretical framework to situate spatial, social and temporal housing inequalities within broader political-economic transformations. We then contextualise the case of Leipzig by tracing its recent housing market developments and patterns of rental sector stratification. This is followed by a presentation of our data and the methodological approach. We then examine the relationship between tenure type and residence duration using our original survey data. Building on this, we construct an empirically grounded typology of rental housing experiences that captures socio-temporal patterns of inequality. In the final section, we discuss the wider implications of our findings for international housing debates and identify key directions for future research.

Rental housing change and the stratification of inequalities

Recent scholarship acknowledges that contemporary housing inequalities and socio-spatial reconfigurations (Haffner and Hulse, 2021; James et al., 2024) are rooted in deep structural transformations of housing markets. To make sense of these changes, urban and housing researchers have introduced a range of conceptual frameworks. Of relevance here is the notion of urban spatial valorisation (Madden, 2024), which captures how urban space is reconfigured through shifting investment logics. We also follow James et al.’s (2024) influential conceptualisation of housing processes, emphasising the multi-scalar and processual nature of contemporary housing transformations. Driven by political-economic transformations such as financialisation, assetisation and rentierisation, these dynamics have reshaped housing ownership and access as decisive characteristics of class position and key mechanisms of social, spatial and temporal inequality (Adkins et al., 2022; Madden, 2024). While each process highlights distinct mechanisms, they collectively reflect a broader direction of political-economic restructuring (Madden, 2024).

These transformations manifest through three interconnected dimensions of inequality among tenants. Social inequalities refer to the differential distribution of housing resources, quality, landlord relations, rent conditions and security across population groups. These differences cannot be explained simply through preferences, as access to adequate housing increasingly depends on income, savings, social networks and cultural capital of housing seekers (Feitosa et al., 2023). Spatial inequalities emerge through the uneven geographic distribution of affordable homes, housing quality, landlord types, market-led urban development and investment flows, producing spatial units with divergent material conditions and life chances (Kadi et al., 2022). These spatial patterns are not neutral sortings but reflect historical legacies and contemporary patterns of urban transformations, housing policies, capital flows and housing cost inflation that target and affect urban neighbourhoods differently. Temporal inequalities capture how the timing of market entry structures differential exposure to housing precarity, with recent entrants facing fundamentally different conditions than established residents (Arundel and Hochstenbach, 2020; Waldron, 2024). Together, these dimensions reveal housing as a stratified field where position depends not only on economic resources but also on when and where one enters the market, and through which institutional channels.

Scholars have examined these transformations and concomitant tenant inequalities through multiple analytical lenses. One strand investigates housing pathways and life course patterns (Adkins et al., 2022; Raya and Garcia, 2012), linking tenure choice to age, family formation, mobility and increasingly to income and assets (Andersen, 2011; Anderson et al., 2021). Associated research shows how households navigate housing under shifting conditions, often delaying key life stages due to housing-related constraints (Zhang, 2023).

A second body of work focuses on Generation rent, examining how rising costs and restricted mortgage access exclude younger cohorts from homeownership, creating involuntary dependence on rental housing (Arundel and Hochstenbach, 2020; Byrne, 2020; Lennartz et al., 2016). Rental tenure is associated with greater vulnerability: unstable contracts, inadequate maintenance, limited tenant rights and reduced well-being (Chisholm et al., 2020; Power and Gillon, 2021; Waldron, 2024). This contrasts with a Generation landlord – a growing property-owning class with multiple rental assets (Ronald and Kadi, 2018).

A third approach critiques overly binary owner tenant-based class divides or generational framings (Howard, 2025; Zhang, 2023). Scholars have argued that intra-tenure inequalities and contextual variation are central to understanding contemporary housing systems (Forrest and Hirayama, 2018; Howard et al., 2024; Rudolph et al., 2021; Woodman, 2022). Particularly in regulated housing systems like Germany and Sweden, ownership restructuring and rising costs have coincided with persistent middle-class renting and sizeable non-profit segments (Gustafsson, 2024; Stephens, 2020; Wimark et al., 2020). Stratification within rental sectors thus reflects local institutional histories and path-dependent housing arrangements (Aalbers, 2017). Within these dynamics, landlord type emerges as a key structuring factor. Our framework focuses on three dominant provider types: (i) public/non-profit, (ii) private and (iii) corporate landlords.

Public and non-profit housing providers once played a stabilising role across post-war Europe, offering affordable housing for broad populations. However, welfare state retrenchment has diminished their reach through privatisation, residualisation and reduced funding (Kadi and Lilius, 2024). Today, they often serve only low-income groups (Clarke et al., 2024; Schönig, 2020), while facing pressures to adopt profit-oriented management models (Aalbers et al., 2017; Beswick and Penny, 2018; Penny, 2022). Financialised logics have contributed to deteriorating housing quality and adverse health outcomes (Holding et al., 2020; Jara-Baeza et al., 2023; Morey et al., 2020). Nevertheless, this sector continues to provide vital protection against eviction and market volatility (Prentice and Scutella, 2020).

Private landlords have gained renewed prominence amid expanding rental markets (Aalbers et al., 2021; Ronald and Kadi, 2018). While small-scale ownership continues to dominate many European contexts, the sector increasingly includes multi-property owners who operate with explicitly profit-maximisation strategies (Hochstenbach, 2024; Kadi et al., 2020). These landlords often represent a new Rentier Class (Adkins et al., 2021), predominantly households with relatively high incomes and accumulated housing wealth (Adkins et al., 2021; Hulse et al., 2020). Their practices reflect property-based welfare strategies and the use of housing as an asset for intergenerational wealth accumulation. Described variously as housing-rich investors (Adkins et al., 2021), accumulating families (Forrest and Hirayama, 2018) or landlord elites (Hochstenbach, 2022), these actors are well positioned within housing-based class structures and have contributed to deepening inequalities within the rental market (Hochstenbach, 2022). Power asymmetries between tenants and landlords have intensified in this context, reinforced by knowledge gaps, fears of retaliation and weak enforcement of regulatory protections (Chisholm et al., 2020). As a result, many tenants are unable to exercise their rights, which undermines housing security and erodes their sense of belonging (Rolfe et al., 2023).

Corporate landlords are relatively recent, expanding rapidly since the Global Financial Crisis (GFC) via acquisitions of social housing stock and distressed assets (Alexandri and Hodkinson, 2025; Bernt et al., 2017; Janoschka et al., 2020; St-Hilaire et al., 2024;Wijburg and Aalbers, 2017). These actors pursue long-term, profit-maximising strategies that disrupt established housing governance (Lochlainn, 2023; Wijburg et al., 2024). Their practices – outsourced maintenance, poor communication, cost-cutting – have generated stress and uncertainty among tenants (Kadıoğlu and Kellecioğlu, 2024; Kockelkorn, 2022; Nethercote, 2023). In some contexts, they actively target state subsidies while applying technologies of surveillance and tenant discipline (Bernt et al., 2017; Janoschka et al., 2020; Seymour, 2023). Despite recent corporate social responsibility and performative engagement under political scrutiny (Alexandri and Janoschka, 2025; Wijburg et al., 2024), their management practices continue to produce persistent insecurity, emotional stress and material hardships in tenants’ everyday lives (Fields, 2017; Kadıoğlu and Kellecioğlu, 2024).

Although these three landlord types are well established in the literature, real-world housing provision is far more heterogeneous. Regional variation, regulatory diversity and multi-level governance all shape how these provider types operate in practice. Despite this complexity, distinguishing between public/non-profit, private and corporate providers allows us to analytically grasp the differentiated logics shaping rental housing outcomes, particularly in a context like Leipzig, where all three forms coexist.

Housing processes and urban restructuring in Leipzig

Leipzig’s housing trajectory has followed a distinct post-socialist path that diverges from West German housing institutions, yet increasingly reflects hybrid dynamics shaped by local legacies and global market pressures. Since 1989, the city has undergone profound political-economic restructuring. Restitution of pre-World War II housing stock, tax incentives and public housing debt assistance triggered a wave of privatisation, speculation and wealth redistribution (Holm and Bernt, 2021). Although policies promoted homeownership, structural constraints and unfamiliarity with market mechanisms led most residents to remain in the rental sector, which today accounts for 87% of the city’s housing (Rink, 2020).

This rental dominance preserved a relatively significant public and non-profit housing segment. Despite the policy-driven contraction of public housing after reunification, municipal and cooperative providers still manage over a quarter of Leipzig’s housing stock (10.5% and 15%, respectively), having each lost approximately 1 percentage point since the 2011 Population and Housing Census but still amounting to roughly 90,000 units according to the 2022 Census.² While these actors maintain affordability goals, they increasingly adopt entrepreneurial management models. Recent municipal policies aim to expand affordable housing by an additional 5000 units by the mid-2020s (Rink, 2020; Rink et al., 2022); however, this is less than the average annual population growth.

In parallel, the post-socialist transformation fostered the emergence of a dominant private rental sector, now comprising 53.9% of Leipzig’s housing (56.6% in 2011). Ownership is largely non-local, with many properties held by West German investors and managed by local intermediaries (Trautvetter and Knechtel, 2023). These intermediaries often prioritise owner interests over tenant needs, contributing to maintenance backlogs and substandard housing conditions. Facing growing refurbishment costs, many early investors are now selling off their portfolios and brownfield sites (Rink et al., 2022).

Over the past decade, corporate landlords have gained a growing foothold. Germany’s position as a post-crisis safe haven for global real estate capital (Gabor and Kohl, 2022) has also channelled investment into Leipzig. Following trends documented in the UK (Hofman and Aalbers, 2019), the city’s housing market has become increasingly professionalised through the involvement of international developers, financial intermediaries and stock-listed housing companies. Today, corporate landlords hold about 18.6% of the city’s housing stock (13% in 2011). Many emerged through the privatisation of public housing and pursue long-term investment strategies focused on rent extraction, service automatisation, fiscal optimisation and territorial expansion (Wijburg et al., 2018).

Taken together, these housing processes not only contributed to macro-level welfare gains – urban regeneration, employment and a growing housing economy – but also produced sharp social costs. Households increasingly face rising rents, land prices and housing-related costs, alongside decreasing vacancy rates following strong population growth, elevated lock-in effects and displacement pressures of long-term residents (Rink, 2020; Rink et al., 2022). These impacts unfold unevenly across landlord types and tenure forms, as the following empirical analysis shows.

Studying housing stratification in Leipzig-Connewitz

Despite growing interest in rental markets, direct engagement with tenants, landlords and intermediaries remains rare in empirical housing research (Nethercote, 2020). Rather than conducting original surveys, most studies rely on secondary analysis of large-scale, representative datasets (Kemp, 2020). Notable exceptions include Waldron and Redmond (2016, 2017) who examined neighbourhood-level consequences of Ireland’s post-GFC mortgage crisis.

Inspired by this approach, our study explores tenure-related housing inequalities and socio-temporal stratification at the neighbourhood level. The case site, Leipzig-Connewitz, is a southern district with nearly 12,000 housing units, characterised by a mix of public housing, pre-1918 housing stock, alternative markets following the legalisation of squats in the 1990s and recent high-end developments. Connewitz epitomises the city’s broader housing dynamics, particularly the intensification of investment since 2015, with new constructions accounting for more than 11% of the housing stock.³ These developments target premium market segments and reflect the logics of capital accumulation observed elsewhere (Leffers and Wekerle, 2020; Nethercote, 2020), making Connewitz an instructive context for tracing how global housing trends materialise locally.

Connewitz shares structural similarities with comparable transformation neighbourhoods across Germany – Hamburg’s St. Pauli, Berlin’s Friedrichshain-Kreuzberg, Frankfurt’s Gallusviertel or Cologne’s Ehrenfeld – all characterised by alternative cultural histories, working-class legacies and recent investment influxes. However, East German specificities distinguish it: near-complete rental dominance (vs. 60%–70% in western counterparts), post-socialist property restitution creating fragmented ownership, and the persistence of substantial public/non-profit housing that exceeds most western alternative neighbourhoods. These particularities make Connewitz an instructive case for understanding how broader processes of political-economic restructuring interact with local institutional legacies to produce the temporal stratification and tenure-based inequalities revealed by our analysis.

Despite the limited transparency of Germany’s housing data landscape, we managed to reconstruct a substantial proportion of local ownership structures at the address level (see Figure 1).⁴ Public and non-profit, and corporate actors are spatially clustered and thus relatively identifiable. Owner-occupied units can also be approximated through building typologies and qualitative research. However, the fragmented ownership of Wilhelminian-era housing stock, typically managed by local firms for dispersed, often non-local investors (Rink, 2020), remains largely undocumented. Yet even detailed ownership data would reveal little about landlords’ management strategies and their effects on tenant conditions. This geographic illegibility illustrates the limits of purely address-data-driven field access: capturing differentiated tenant experiences within the private sector requires alternative methods.

Figure 1.

Housing tenure types and project developments (ranging from 10 to 220 housing units in point size) in Leipzig-Connewitz.

To address this, we conducted a large-scale household survey using random sampling based on the official address database of residential buildings. We excluded owner-occupied single-family homes, vacant buildings and data errors. In total, 1525 surveys were distributed by hand or by mail, with returns available via pre-paid mail or online submission. The questionnaire collected demographic and socio-economic data alongside 74 items covering housing conditions, landlord-tenant relations, rent burdens and increases, maintenance and renovation experiences and relocation intentions. After cleaning, we retained 427 valid responses, a 28% response rate.

The resulting sample is highly representative of Connewitz. It covers 3.55% of all households (n = 12,020), and the randomised methodology minimises bias. Distributions of marital status, education, employment, housing costs, income and rent closely match available population benchmarks (see Table 1). Tenure types in the sample also approximate district-level patterns, though some limits in public data exist.

Table 1.

Survey returns relative to macro-level neighbourhood indicators.

	Survey	Macro-level
	% (n)	% (n)
Households	3.55 (427)	100 (12,020)
Tenure types^a
Private landlord	48 (199)	~50 (est. 6020)
Public/Non-profit	27 (114)	~30 (est. 3600)
Corporate landlords	18 (73)	~15 (est. 1800)
Owner occupiers	–	~5 (est. 600)
Gender
Female	59 (250)	51 (10,096)
Male	39 (163)	49 (9874)
Other	2 (9)	–
Marital status
Single	57 (241)	62 (12,218)
Married	30 (124)	23 (4519)
Divorced	10 (40)	6 (1222)
Widowed	4 (15)	4 (872)
Citizenship
German	98 (411)	91 (18,061)
Educational qualification
University entrance	61 (258)	62 (12,381)
Technical university entrance	15 (63)	19 (3794)
Secondary	19 (79)	18 (3595)
Primary or none	5 (20)	1 (200)
Professional qualification
University degree	60 (232)	65 (12,981)
Technical college degree	9 (38)	5 (999)
Skilled worker	26 (104)	18 (3595)
None	2 (7)	12 (2396)
Housing cost burden	28.18%	30%
Median household income	€2300	€2171
Median net rent	6.5 €/m²	6.8 €/m²
Average household size	2 ppl	1.6 ppl
Average age^b	45.5 years	40 years

Source: City Leipzig (figures from 2023), own recompilation (2020–2023).

Owner-occupiers were excluded from this tenant-focused survey. The estimation of the tenure types at the neighbourhood scale is extrapolated from our database. While precise data remain unavailable, the strong spatial clustering of public and non-profit, and corporate actors (see Figure 1) suggests the missing data predominantly falls within the private ownership category.

Note that children and adolescents younger than 18 years are not eligible to complete the questionnaire and are therefore excluded from the respondent sample, although they are recorded as household members; this mechanically raises the average age of respondents.

Connewitz shows some demographic deviations from the city average. The share of residents with university entrance qualification is comparatively high at 62%, though this aligns with Leipzig’s status as a university city. The foreign resident share of 9% falls below both the city average of 14.3% and other districts like Volkmarsdorf with 35.1%, reflecting the broader underrepresentation of foreign populations in East German cities. However, what makes Connewitz particularly instructive is not demographic exceptionalism but its housing market characteristics. With a rental rate approaching 93% (vs. 87% city-wide) and a diverse mix of tenure types,⁵ the neighbourhood provides an ideal setting for examining rental stratification.

Our analysis begins by examining how tenure type and residence duration relate to key aspects of tenant experience, including financial strain, housing satisfaction and views on maintenance and refurbishment. These relationships were assessed through chi-square tests to identify statistically significant patterns. Drawing on current debates about context-specific transformations of housing markets (Howard, 2025; Zhang, 2023), we hypothesise that housing inequalities are primarily stratified along (a) temporal dimensions (residence duration) and (b) tenure types (public and non-profit, private, corporate).

To deepen the analysis, we developed an empirically grounded typology of tenant experiences using cluster analysis. We chose cluster analysis as it groups observation units based on multiple variables simultaneously, enabling us to capture the stratification of housing experiences within the rental sector that extends beyond simple statistical ownership categories identified in the literature. Specifically, Two-Step Cluster Analysis was selected over supervised learning techniques (such as decision tree, random forest, SVM or k-nearest neighbours) as well as dimensional reduction methods (factor or correspondence analysis) for specific methodological reasons. Supervised techniques require predefined outcome categories or class labels, which would contradict our explicitly inductive approach – we sought to discover emergent patterns of housing inequality rather than classify observations into predetermined groups. Similarly, whilst factor or correspondence analysis prior to the cluster analysis could identify underlying dimensions, they would produce abstract continuous spaces that require subjective interpretation to derive meaningful tenant categories, and they would also necessitate recoding of our continuous variables, resulting in consequent information loss.

Two-Step Cluster Analysis offered particular advantages for handling our mixed data structure (categorical and continuous variables) without transformation, preserving the integrity of non-metric indicators such as income sufficiency, expected rent increases and concerns about rising service charges – subjective measures central to understanding housing inequality experiences. The method generates discrete, interpretable categories that translate directly into policy-relevant segments, whilst its automatic determination of optimal cluster numbers using the Bayesian information criterion provided statistical justification for our four-cluster solution. From an initial pool of 27 housing-related variables, we applied Spearman correlations and stepwise reduction to isolate 7 indicators with the highest discriminatory value. This process enabled transparent assessment of variable importance (shown in Table 4), revealing rental tenure type as the strongest predictor – empirically validating our theoretical framework about the centrality of landlord types. The resulting typology identifies latent similarity structures within the sample and, in combination with inferential testing, enables a nuanced examination of socio-temporal differentiation in Leipzig’s rental housing market.

Empirical findings: patterns of housing stratification in Leipzig-Connewitz

The analysis of our household survey in Leipzig-Connewitz reveals a distinct socio-temporal structuring of tenant experiences, in which patterns of inequality unfold along both institutional and temporal lines. While tenants report relatively exceptionally high levels of satisfaction with their social and neighbourhood environments, assessments of material housing conditions remain notably more critical. Foremost among the concerns are service charges and heating costs, issues that were likely intensified by the survey’s timing during spring 2023, in the wake of the European energy crisis. Notably, more than one-third of all households also express fear of future rent increases, underscoring how cost anxieties extend beyond current burdens to anticipated pressures.

More substantial inequalities emerge when examining the statistical associations between tenancy duration and housing cost burdens (Table 2). Tenants with long-standing residence are predominantly situated in the lowest rent categories, whereas newer entrants disproportionately occupy the highest brackets (p < 0.01). This temporal stratification reflects broader shifts in the political economy of housing, particularly the increasing exposure of mobile households to market pressures (Adkins et al., 2022; Madden, 2024). Yet, interestingly, expectations of future rent increases are evenly distributed across tenure groups and statistically insignificant (p = 0.556). This suggests a more generalised affective condition: rent-related anxieties appear to permeate across temporal strata, regardless of actual rent levels.

Table 2.

Relationship between residence duration and relevant housing market indicators.

Independent variables	Residence duration				Total responses	Notes
	2 Years or less	3–7 Years	8–1 5 Years	16 Years and longer	Total responses
	% (n)	% (n)	% (n)	% (n)	N
Net rent
Below 6 €/m²	24 (18)	26 (35)	52 (60)	68 (68)	181	χ² = 95.697, p ⩽ 0.01
6–6.99 €/m²	14 (10)	26 (36)	25 (29)	17 (17)	92
7–7.99 €/m²	23 (17)	23 (31)	16 (18)	13 (13)	79
8–8.99 €/m²	9 (7)	12 (16)	5 (6)	1 (1)	30
9 €/m² and above	30 (22)	14 (19)	3 (3)	1 (1)	45
Total	100 (74)	100 (137)	100 (116)	100 (100)	427
Warm rent
Below 8 €/m²	3 (2)	10 (13)	35 (39)	41 (39)	93	χ² = 106.612, p ⩽ 0.01
8–8.99 €/m²	8 (6)	15 (20)	22 (25)	28 (26)	77
9–9.99 €/m²	18 (13)	22 (29)	19 (21)	13 (12)	75
10–10.99 €/m²	26 (19)	27 (36)	12 (13)	14 (13)	81
11 €/m² and above	45 (33)	26 (35)	13 (14)	4 (4)	86
Total	100 (73)	100 (133)	100 (112)	100 (97)	412
Housing size in m²
Below 39 m²	10 (7)	3 (4)	0 (0)	2 (2)	13	χ² = 17,918, p = 0.118
40–59 m²	27 (20)	29 (40)	27 (31)	22 (22)	113
60–79 m²	35 (26)	27 (50)	34 (49)	41 (41)	156
80–99 m²	20 (15)	20 (28)	26 (30)	23 (23)	96
More than 100 m²	8 (6)	11 (15)	13 (15)	12 (12)	48
Total	100 (74)	100 (137)	100 (115)	100 (100)	426
Expected rental increase
Yes	32 (24)	30 (41)	25 (29)	34 (33)	127	χ² = 2.079, p = 0.556
No	68 (50)	70 (96)	75 (85)	66 (64)	295
Total	100 (74)	100 (137)	100 (114)	100 (97)	422
Worried about rising service charges
Yes	49 (36)	64 (87)	55 (64)	53 (53)	187	χ² = 5.149, p = 0.161
No	51 (38)	36 (50)	45 (52)	47 (47)	240
Total	100 (74)	100 (137)	100 (116)	100 (100)	427
Satisfaction^a with rent
Yes	50 (37)	64 (89)	84 (98)	82 (82)	306	χ² = 34.461, p ⩽ 0.001
No	50 (37)	36 (47)	16 (18)	18 (18)	120
Total	100 (74)	100 (136)	100 (116)	100 (100)	426
Overall housing satisfaction^b
Yes	82 (61)	78 (107)	84 (97)	85 (83)	348	χ² = 2.337, p = 0.505
No	18 (13)	22 (30)	16 (18)	15 (15)	76
Total	100 (74)	100 (137)	100 (115)	100 (98)	424
Income
Below €1.300	33 (24)	17 (22)	8 (9)	14 (13)	68	χ² = 25.537, p = 0.005
€1.300–1.999	11 (8)	20 (26)	23 (26)	21 (20)	80	χ² = 25.537, p = 0.005
€2.000–3.200	32 (23)	38 (50)	37 (42)	38 (36)	151
More than €3.200	24 (17)	25 (33)	32 (37)	27 (25)	112
Total	100 (72)	100 (131)	100 (114)	100 (94)	411
Sufficiency of income
Insufficient	8 (6)	13 (13)	8 (9)	2 (2)	30	χ² = 12.345, p = 0.195
Barely sufficient	24 (17)	15 (15)	17 (20)	15 (15)	67
Sufficient	35 (25)	51 (53)	41 (48)	39 (38)	164
More than sufficient	33 (24)	21 (22)	34 (39)	44 (13)	68
Total	100 (72)	100 (131)	100 (116)	100 (99)	418
Age
25 Years or younger	27 (20)	7 (9)	1 (1)	0 (0)	30	χ² = 233.340, p ⩽ 0.001
26–44 Years	62 (46)	71 (96)	49 (56)	6 (6)	204
45–64 Years	10 (7)	18 (24)	41 (47)	49 (48)	126
65–79 Years	1 (1)	4 (6)	9 (8)	29 (29)	45
80 Years or older	0 (0)	0 (0)	1 (1)	16 (16)	17
Total	100 (74)	100 (135)	100 (114)	100 (99)	422
Construction period^c
Before 1919	27 (13)	29 (29)	40 (36)	32 (30)	108	χ² = 59.804, p ⩽ 0.001
1919–1945	36 (18)	32 (32)	35 (31)	41 (39)	120
1946–1990	12 (6)	18 (18)	13 (12)	12 (11)	47
1991–2010	4 (2)	9 (9)	9 (8)	16 (15)	34
Since 2011	20 (10)	12 (12)	2 (2)	0 (0)	24
Total	100 (49)	100 (100)	100 (89)	100 (95)	333
Need for renovation
Very low	43 (31)	23 (31)	27 (31)	19 (19)	112	χ² = 20,41, p = 0.016
Rather low	34 (25)	50 (67)	38 (43)	58 (57)	192
Rather high	18 (13)	20 (27)	27 (30)	17 (17)	87
Very high	6 (4)	7 (10)	8 (9)	5 (5)	28
Total	100 (73)	100 (135)	100 (113)	100 (98)	416
Rental tenure type
Private	53 (37)	51 (63)	56 (60)	45 (39)	199	χ² = 19.660, p = 0.003
Public/Non-profit	17 (12)	26 (32)	32 (34)	42 (36)	114
Corporate	30 (21)	23 (28)	12 (13)	13 (11)	73
Total	100 (70)	100 (123)	100 (107)	100 (86)	386

Satisfaction levels were initially measured using a 10-point Likert scale (1 = completely dissatisfied, 10 = completely satisfied). Given the pronounced positive skew observed across response distributions, we dichotomised this variable for analytical purposes (7–10 = satisfied; 1–6 = dissatisfied). This transformation partially mitigates the positivity bias frequently encountered in social science research, even within anonymised survey instruments (Hoorens, 2021).

This refers specifically to housing satisfaction rather than general life satisfaction, though housing conditions constitute a substantial component of overall quality of life.

The questionnaire included the option to respond ‘Not sure’; however, this was excluded from analysis due to its limited explanatory power. Therefore, the total responses listed here do not exceed n = 333.

A similar divergence between objective conditions and subjective perception appears in relation to income. While recent market entrants are overrepresented in the lower income brackets (p = 0.005), they do not report significantly lower levels of perceived income sufficiency (p = 0.195). This incongruence may reflect either psychological adaptation to financial constraints or the effects of narrowed reference groups, in which tenants benchmark their own conditions against peers similarly exposed to current market realities (Parkinson et al., 2024). It may also result from the demographic composition of more recent entrants, including younger adults and students (p ⩽ 0.001), for whom lower income levels may not be perceived as problematic or unusual.

Housing satisfaction reflects these patterns: tenants with shorter residence durations (2 years or fewer) report markedly lower satisfaction levels regarding rent (p < 0.001). However, broader indicators of overall satisfaction, encompassing the neighbourhood context, do not follow this trend (p = 0.505). This suggests that dissatisfaction is most sharply felt where costs intersect with recent market entry, rather than with dwelling quality more generally. Under different market conditions, such dissatisfaction might reasonably be expected to prompt relocation; yet, as Power and Gillon (2022) have noted, constrained supply and rising prices often leave tenants effectively locked in, even under suboptimal conditions.

A similar pattern emerges when examining housing quality indicators. Whilst dwelling size demonstrates no statistically significant variation across different tenancy durations (p = 0.118), recent market entrants notably exhibit a lower requirement for renovation (p = 0.016). This suggests that the current housing supply is predominantly composed of refurbished and recently constructed dwellings. Building age (p < 0.001) further nuances this pattern: established tenants are primarily located in older buildings (pre-1945), while newer arrivals are concentrated in recently constructed dwellings that tend to target higher-income groups. Yet this newer segment is internally polarised. On the one hand, affluent in-movers increasingly populate high-end developments. On the other hand, recent arrivals are also overrepresented in lower income brackets (p = 0.005), indicating that low-income groups, such as students or young adults, continue to enter the neighbourhood, though likely into more modest housing segments. This dual influx reinforces spatial and social stratification, as long-standing tenants with favourable contracts remain insulated from market dynamics, while the mobile population bifurcates into upward and downward trajectories.

Further differentiation emerges when comparing housing conditions across provider types (Table 3). Rents are lowest in the public/non-profit segment (p < 0.001), and satisfaction levels are highest (82%). In contrast, tenants in corporate housing face elevated costs, the highest reported dissatisfaction (47%) and comparatively limited access to designated contact persons (p < 0.01), reflecting the more standardised, transactional management practices often associated with institutional landlords (Nethercote, 2023). However, private actors exhibit considerable internal diversity: while some tenants benefit from long-standing relationships and stable conditions, others experience uncertainty, limited transparency and elevated cost burdens. This heterogeneity reflects the fragmented nature of ownership and management structures in this segment (Chisholm et al., 2020).

Table 3.

Relationship between rental tenure types and housing indicators covering satisfaction levels and rental conditions.

Independent variables	Rental tenure type^a			Total responses	Notes
	Private	Public/Non-profit	Corporate	Total responses
	% (n)	% (n)	% (n)	N
Net rent
Below 6 €/m²	36 (71)	60 (68)	36 (26)	165	χ² = 42.001, p ⩽ 0.01
6–6.99 €/m²	21 (41)	25 (29)	16 (12)	82
7–7.99 €/m²	23 (46)	8 (9)	21 (15)	70
8–8.99 €/m²	9 (18)	3 (3)	7 (5)	26
9 €/m² and above	12 (23)	4 (5)	21 (15)	43
Total	100 (199)	100 (114)	100 (73)	386
Warm rent
Below 8 €/m²	20 (38)	34 (38)	13 (9)	85	χ² = 42.511, p ⩽ 0.001
8–8.99 €/m²	18 (34)	23 (25)	14 (10)	69
9–9.99 €/m²	15 (28)	25 (28)	14 (10)	66
10–10.99 €/m²	23 (45)	11 (12)	23 (16)	73
11 €/m² and above	24 (47)	7 (8)	36 (25)	80
Total	100 (192)	100 (111)	100 (70)	373
Housing size in m²
Below 39 m²	3 (5)	2 (2)	8 (6)	13	χ² = 21.001, p = 0.007
40–59 m²	27 (53)	22 (25)	30 (22)	100
60–79 m²	35 (70)	50 (57)	25 (18)	144
80–99 m²	25 (50)	19 (22)	20 (15)	87
More than 100 m²	11 (21)	7 (8)	16 (12)	41
Total	100 (198)	100 (114)	100 (73)	385
Expected rental increase
Yes	31 (61)	18 (21)	52 (37)	119	χ² = 23.125, p ⩽ 0.001
No	69 (135)	82 (93)	48 (34)	262
Total	100 (196)	100 (114)	100 (71)	381
Worried about rising service charges
Yes	52 (103)	50 (57)	68 (50)	210	χ² = 7.294, p = 0.026
No	48 (96)	50 (57)	32 (23)	176
Total	100 (199)	100 (114)	100 (73)	386
Satisfaction with rent
Yes	71 (142)	82 (93)	53 (39)	111	χ² = 18.030, p ⩽ 0.001
No	29 (57)	18 (20)	47 (34)	274
Total	100 (199)	100 (113)	100 (73)	385
Overall housing satisfaction
Yes	85 (167)	83 (94)	73 (53)	314	χ² = 5.497, p = 0.064
No	15 (30)	17 (19)	27 (20)	69
Total	100 (197)	100 (113)	100 (73)	383
Income
Below €1.300	19 (36)	12 (13)	19 (13)	62	χ² = 6.281, p = 0.392
€1.300–1.999	16 (31)	25 (28)	17 (12)	71
€2.000–3.200€	37 (70)	33 (36)	39 (27)	133
More than €3.200	28 (54)	30 (33)	26 (18)	105
Total	100 (191)	100 (110)	100 (70)	371
Sufficiency of income
Insufficient	6 (12)	6 (7)	8 (6)	25	χ² = 7.735, p = 0.258
Barely sufficient	13 (26)	15 (17)	25 (18)	61
Sufficient	38 (74)	43 (49)	34 (24)	147
More than sufficient	42 (81)	35 (40)	32 (23)	144
Total	100 (193)	100 (113)	100 (71)	377
Construction period
Before 1919	49 (72)	9 (9)	36 (20)	101	χ² = 114.142, p ⩽ 0.001
1919–1945	30 (44)	46 (47)	25 (14)	105
1946–1960	4 (6)	9 (9)	4 (2)	46
1961–1990	1 (1)	25 (25)	5 (3)	29
1991–2010	13 (19)	7 (7)	7 (4)	30
Since 2011	3 (5)	5 (5)	23 (13)	23
Total	100 (147)	100 (102)	100 (56)	305
Need for renovation
Very low	24 (48)	32 (36)	28 (20)	104	χ² = 6.514, p = 0.368
Rather low	45 (89)	49 (55)	41 (29)	173
Rather high	23 (46)	14 (16)	23 (16)	78
Very high	7 (14)	5 (5)	9 (6)	25
Total	100 (197)	100 (112)	100 (71)	380
Designated contact person?
Yes	78 (155)	78 (87)	55 (40)	282	χ² = 19.357, p ⩽ 0.01
No	22 (43)	22 (25)	45 (33)	101
Total	100 (198)	100 (112)	100 (73)	383

The questionnaire included additional ownership categories (‘other company’ and ‘someone else’); however, these classifications are excluded from analysis due to insufficient response frequencies. Therefore, the total responses listed here do not exceed n = 386.

Table 4.

Typology of tenant types.

Variables	Stable public/non-profit		Affluent private		Secure but dissatisfied corporate		Fragile private
Variables	N	%	n	%	n	%	n	%
Size	50	15.4	73	22.5	54	16.7	147	45.4
Variables	Dominant value (%)		Dominant value (%)		Dominant value (%)		Dominant value (%)		Predictor importance
Rental tenure type	Public/Non-profit (96)		Private (89)		Corporate (57.4)		Private (55.8)		1
Sufficiency of income	More than sufficient (58)		More than sufficient (94.5)		More than sufficient (57.4)		Sufficient (67.3)		0.92
Construction period	1919–1945 (52)		Before 1919 (39.7)		Since 2011 (33.3)		Before 1919 (32.7)		0.67
Average net rent	€396		€503		€730		€437		0.43
Average warm rent	€591		€707		€973		€628		0.37
Average income	€2884		€3255		€3601		€1963		0.35
Expected rental increase	No (90)		No (86.3)		Yes (61.1)		No (69.4)		0.19
Worried about rising service charges	No (58)		No (54.8)		Yes (38.9)		Yes (53.1)		0.17

Lastly, construction period and landlord type correlate strongly (p < 0.001). Private actors dominate the pre-1918 and interwar housing stock, public providers are concentrated in mid-century developments, while the corporate segment maintains a significant presence in both recent constructions and formerly public housing acquired en bloc. This pattern is further substantiated by housing size (p = 0.007), where corporate actors notably offer both the largest and smallest apartments, suggesting a bifurcated provision and management strategy targeting distinct market segments.

In sum, the findings highlight a multi-layered structure of inequality. Housing conditions in Leipzig-Connewitz are not primarily shaped by income levels or demographic characteristics, but rather by the interplay of institutional regimes and timing of market entry. It is this socio-temporal positioning, anchored in proprietary type, residence duration and building age, that structures tenants’ exposure to both material hardship and affective insecurity, echoing Fields’ (2017) observation that tenants become unwilling subjects of broader housing transformations.

A typology of rental housing inequality

While the previous analysis revealed clear socio-temporal stratifications within Leipzig’s rental sector, it also pointed to a more complex terrain of overlapping pressures and institutional diversity, particularly within the private rental market. To explore these patterns further, we conducted a cluster analysis, grouping households by shared housing conditions, perceived burdens and tenure arrangements. What emerges is a typology of four tenant formations, situated along a continuum from housing stability to vulnerability. Rather than reproducing binary distinctions, these clusters offer a more nuanced understanding of housing inequality, highlighting how landlord type, income sufficiency, rent burden and anticipatory cost anxiety interact to shape different tenant experiences.

Type 1: stable public and non-profit housing tenants

This type includes households living predominantly in public and non-profit housing, typically located in interwar and mid-20th-century state-socialist era buildings. Their housing arrangements are characterised by low rents, long tenure and a strong sense of stability and affordability within a regulated institutional framework. Households benefit from rent levels well below the sample average. Despite moderate income levels (€2,884 on average), more than half report their income situation as ‘very good’. Expectations of future rent increases are minimal, and concerns about service charges are rare. These tenants also report the highest levels of satisfaction with their current housing situation across all tenure types. The combination of institutional ownership structures and longer tenancies helps to create a sense of shielding from market-driven volatility. While the share of public and non-profit housing in Leipzig remains limited, this type of housing illustrates its continued role as a protective segment, offering stability and affordability even amid broader housing system transformations.

Type 2: affluent private rental households

This type covers tenants in the private rental market who, despite elevated housing costs, experience a high degree of financial security and stability because of their substantial economic resources. Their position illustrates how prosperity enables households to navigate and absorb market pressures with relative ease. These tenants are mainly located in pre-1919 Wilhelminian buildings but are also represented in interwar and new housing developments. They report the second-highest average rent levels in the sample, yet housing costs do not appear to threaten their overall security. With an average household income of €3255, almost 95% of respondents describe their income situation as ‘very good’. The vast majority do not expect rents to increase, and over half are not concerned about service charges. These tenants show a high level of satisfaction with their housing situation, suggesting that economic capital is replacing regulatory protection in securing stable housing outcomes. This type represents a financially privileged segment of Leipzig’s rental market, embedded in older but modernised housing stock, but largely shielded from the material insecurities that affect other tenant groups.

Type 3: corporate tenancies with financially secure but less satisfied households

This type captures tenants in corporate-managed housing who combine material affluence with pronounced anxieties about future affordability and housing stability. Despite their economic resources, these households experience a distinct form of insecurity shaped by the specific governance logics of corporate rental provision. A substantial proportion of these tenants live in recently constructed buildings, particularly those completed after 2011, although a smaller part also lives in older properties acquired en bloc by corporate landlords. Average incomes are the highest in the sample (€3602), and income adequacy is consistently reported as very high. However, this economic security does not translate into confidence about future housing costs, with over 60% expecting rent increases and significantly higher levels of concern about service charges. At an average of almost €1000, this group is the most exposed to absolute cost burdens. Despite living in modern dwellings, satisfaction levels are lower than would be expected given the material standard of the housing stock (see Table 3). The combination of high rents, limited tenant contact structures and expectations of price escalation creates a form of affective housing insecurity that distinguishes this group from other affluent tenant types. This type illustrates how the practices of corporate landlords, often optimised for financial return, can undermine housing stability even among tenants with otherwise robust economic positions.

Type 4: financially fragile households in the private rental market

This type comprises the largest proportion in the sample (45.4%), with tenants in the private rental market who face a convergence of limited economic resources, modest housing conditions and increased risk of future financial strain. It represents the most precarious segment within Leipzig’s stratified rental landscape and the only one that spends on average more than 30% of their household income for rent. Households are predominantly located in pre-1919 and interwar buildings, many of which show signs of material obsolescence and inconsistent maintenance. While current rent levels are comparatively low, income levels are equally modest (€1,963 on average), and no respondent in this group reported their income as ‘very well’. Approximately one-third of the households rate their financial situation as inadequate, indicating narrow margins of resilience. Although few expect rents to rise in the immediate future, more than half express concern about additional charges, highlighting the fragility of perceived affordability. The combination of low rents and constrained incomes may lead to a normalisation of substandard conditions, as households lack the means to relocate or negotiate better terms. This type illustrates a structural precariousness that is rooted not only in housing cost burdens but also in the limited agency of low-income tenants navigating an increasingly competitive and opaque private rental sector.

Socio-temporal inequalities and the politics of tenure

Over the past decade, international housing scholarship has extensively examined the growing constraints on tenure choice for mobile households in the context of a deepening global housing crisis. Much of this literature continues to foreground binary class divides, between owners and tenants, or across generations, as explanatory frameworks for housing precarity. However, such binaries often obscure the subtle socio-temporal stratifications that shape rental-dominated housing systems. In contexts like (East) Germany, historical legacies and institutional arrangements have given rise to distinctive forms of tenure differentiation. Recent research has begun to pay more attention to within-tenure variation, intragenerational inequality and the contextual heterogeneity of rental experiences (Howard, 2025; Zhang, 2023). However, important empirical gaps remain, particularly regarding how socio-temporal differentiation unfolds within regulated housing systems characterised by significant non-profit segments and increasing financial constraints. This necessity is further reinforced by existing data access difficulties, as pure owner-address data – even when geographical distribution of rental tenure types within a district can be partially reconstructed – remains inadequate for revealing the significant experiential differences within these tenure types.

Our analysis responds to this gap by examining how tenure, property owner type and perceived affordability intersect to structure unequal housing experiences. The results reflect the spatial and institutional dynamics of Leipzig’s post-reunification housing market, which has been shaped by large-scale privatisation, new investment flows and the emergence of corporate landlordism (Rink, 2020; Rink et al., 2022). New entrants face pronounced cost burdens, lower incomes and limited satisfaction, often in high-priced new developments controlled by corporate actors. In contrast, public and non-profit providers offer the most secure conditions: lower rents, longer tenancies, higher satisfaction and greater stability. Private property owners occupy an intermediate and internally fragmented space, spanning both long-standing tenancy relationships and more volatile ownership arrangements. These findings corroborate the patterns of ownership identified in our fieldwork (see Figure 1), where corporate and public/non-profit landlords have clearer structures of accountability, while private ownership remains diffuse and opaque (Chisholm et al., 2020).

Crucially, our findings show that housing cost anxiety and dissatisfaction are not confined to new arrivals. Despite lower rents and longer tenancies, many long-standing tenants also report concerns about future affordability. These findings challenge conventional assumptions about housing security trajectory, the linear accumulation of hardship and cohort-based stratification. Instead, they highlight a paradoxical spread of anticipatory insecurity across all temporal strata, suggesting that the type of landlord is a more salient determinant of perceived insecurity than tenure alone. This is particularly evident in the cluster analysis, which identifies four types of tenure formations that lie along a continuum from stability to vulnerability. The typology demonstrates that landlord structure, and the political economy in which it is embedded, is central to understanding contemporary housing inequality.

These four types illustrate the layered nature of tenure stratification, each expressing a specific configuration of tenure, economic capacity and exposure to market pressures. Type 1 (stable public and non-profit housing) illustrates the continuing relevance of public/non-profit provision in mitigating housing inequalities, with tenants enjoying secure, affordable housing in older buildings. Type 2 (affluent private renters) represents a financially shielded group, largely unaffected by wider market pressures. Most unexpectedly, Type 3 (financially secure but less satisfied corporate tenants) includes tenants in newer corporate-owned developments whose high incomes do not protect them from widespread concerns about affordability and stability. This differs from assumptions that the existence of high economic capital automatically entails housing security. Type 4 (financially vulnerable private tenancies) is characterised by low incomes, limited perceived sufficiency and heightened sensitivity to even small cost increases – despite nominally low rents. The bifurcation within the private rented sector is particularly significant: Types 2 and 4 share similar institutional arrangements, but diverge sharply in terms of economic position and housing outcomes – a finding that suggests conceptualisations of private rental markets as more than uniformly precarious or stable (Waldron, 2024).

In this sense, this typology improves our conceptual understanding of tenure stratification. It challenges simplistic dichotomies by showing how tenure type, economic capacity and time in place intersect to shape vulnerability. While corporate landlordism introduces new forms of affective insecurity – even among high-income tenants – non-profit provision continues to buffer households from exposure to market volatility. These findings not only align with recent international research on the governance effects of financialised rental platforms (Alexandri and Janoschka, 2025; Kadıoğlu and Kellecioğlu, 2024) but also highlight the importance of context-specific housing legacies.

Methodologically, this study contributes to calls for greater empirical engagement with tenants’ lived realities (Keller, 2025; Nethercote, 2020). Going beyond secondary data, our neighbourhood-level survey allowed for a fine-grained analysis of how tenure relationships and temporal positioning shape subjective and material housing outcomes. While limited to a single neighbourhood, the findings are indicative of broader processes across East Germany and similarly structured housing systems. Future research could extend this approach through comparative studies across cities and housing regimes. Combining quantitative analysis with qualitative methods would also provide a deeper insight into tenants’ embodied experiences of housing insecurity and time strain. In particular, the concept of unwillingness (Fields, 2017), while analytically productive, would benefit from more direct interpretative engagement through in-depth interviews or ethnographic studies. Our findings suggest that experiences of unwillingness are not evenly distributed, but instead mediated by tenure type, landlord practices and households’ temporal positioning within the housing system.

Finally, our findings open up space for further theorisation of the temporal politics of housing. By treating tenure, tenure security and anticipatory anxiety as interrelated dimensions of inequality, we move beyond static housing typologies towards a more dynamic understanding of socio-temporal differentiation. Time – lived, institutional and financial – emerges as a key medium through which political-economic transformation shapes tenants’ material and affective conditions. Attending more closely to the multiple temporalities of housing can thus help to capture how accelerating investment logics restructure everyday life within contemporary rental systems (Kubala, 2021; Sugarman and Thrift, 2020). Understanding the politics of tenure thus requires attention not only to who owns and manages rental housing but also to how temporal positioning and institutional arrangements structure differentiated modes of dwelling, security and constraint. Our findings reveal that these configurations produce unexpected inversions: material prosperity without security, institutional modernisation without satisfaction and temporal stability without confidence – patterns that fundamentally challenge generational or cohort-based housing narratives.

Supplemental Material

sj-docx-1-eur-10.1177_09697764261424196 – Supplemental material for Housing stratification and the politics of tenure: Socio-temporal inequalities in Leipzig

Supplemental material, sj-docx-1-eur-10.1177_09697764261424196 for Housing stratification and the politics of tenure: Socio-temporal inequalities in Leipzig by Dennis Hof, Michael Janoschka and Marius Strohdiek in European Urban and Regional Studies

Footnotes

Acknowledgements

We would like to thank the two anonymous reviewers for their constructive and insightful comments, which substantially improved the quality of the manuscript. We would like to thank Alejandro Armas-Díaz, Lea Schirbel and Julie Kauke for their valuable contributions and support in the research project ‘Who owns Connewitz?’ We would also like to thank Dieter Rink for introducing us with the particularities of Leipzig’s housing market, Christoph Trautvetter for helping to disentangle the maze of opaque ownership regimes and Matthias Bernt for his thoughtful insights into housing processes in Eastern Germany. Lastly, we extend our gratitude to Marion Hitzeroth for her guidance in adapting our research design to robust statistical methodologies.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The research leading to this publication has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement number 873082 with the Acronym ‘CONTESTED_TERRITORY’.

Ethics approval and informed consent

This study collected fully anonymised survey data with no personally identifiable information gathered or stored. Participants were informed about the study’s purpose and data usage before participation, and completion of the survey constituted implied consent. According to the guidelines of the Karlsruhe Institute of Technology (KIT), which adhere to the European General Data Protection Regulation (GDPR), formal ethical committee approval is not required for anonymised surveys posing minimal risk to participants.

Disclaimer

Claims expressed in this article do not necessarily have to coincide with the positions of the BBR/BBSR.

Data availability statement

The data underlying this study are not currently publicly available. However, a public release of the dataset with a citable DOI is planned. The data will be made available in a suitable public repository upon completion of the publication process.

ORCID iDs

Dennis Hof

Marius Strohdiek

Supplemental material

Supplemental material for this article is available online.

Notes

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