Towards a Landscape of Rental Housing Ownership: Legal and Spatial Characteristics of Residential Landlords in the United States
Notice bibliographique
Résumé
This dissertation documents ongoing changes to the legal and spatial structures of rental housing ownership in the United States and considers potential consequences of these changes for tenants, neighborhoods, and cities. In particular, it draws attention to a frequently overlooked sector of urban rental housing markets – the small rental properties in which a majority of U.S. renters reside – and a historically understudied group of urban actors – the small and modestly-scaled landlords who own and operate a majority of these properties. Chapter One describes the legal characteristics of rental housing ownership across and within the 50 largest metropolitan areas in the United States. Findings document that the use of non-traditional ownership configurations – particularly those involving the use of limited liability companies (LLCs) – is increasingly commonplace in urban rental markets, particularly within predominantly Black neighborhoods. In real estate markets, entity-based ownership structures are typically associated with the activity of financialized, large-scale landlords. However, results from Chapter One make clear that these tools are also widely used by small and modestly-scaled landlords, a significant shift in the legal structure of housing ownership. Chapter Two investigates whether the additional protections afforded to landlords by LLC ownership might facilitate or accelerate housing disinvestment. Findings from Milwaukee, WI, indicate that signs of housing disinvestment increase when properties transition from individual to LLC ownership. This increase is not explained by selection on property characteristics or by divergent pre-transfer trends, suggesting that legal structures for ownership which circumscribe risks for real estate investors may generate unintended costs for tenants and cities. Chapter Three describes heterogeneity and change in the spatial structure of rental housing ownership and considers potential implications for housing conditions. Real estate investing has been – and remains – a highly local activity. Accordingly, the spatial relationship between landlord and property has rarely been the focus of empirical study, despite the emergence of new legal and technological tools that have made it easier to own and operate rental housing from afar. Findings from Boston, MA, indicate rising levels of absentee ownership and modest decreases in landlord proximity among absentee owned properties. Yet findings also indicate that for small property owners, even modest decreases in owner proximity may be associated with diminished property upkeep. Results suggest that sophisticated investors and landlords who possess stronger neighborhood ties may be better equipped or more motivated to overcome obstacles to property upkeep imposed by greater distance. Observed nonlinearities in the relationship between owner proximity and property upkeep raise new questions about the character of small property ownership and affirm that more granular measures of landlord characteristics may reveal potentially important aspects of the urban landscape. Together, these analyses clarify legal and spatial structures that undergird rental housing ownership. Findings from this dissertation indicate that even among small and modestly-scaled investors, the legal and spatial relationships that connect owner and property are changing. Such changes are likely to have continued consequences for landlords, tenants, and cities.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».