Informal Settlement Upgrading and the Rise of Rental Housing in São Paulo, Brazil

Rental housing was historically a minimal feature of urban informality. Now it is surging amid municipal attempts to “upgrade” informal settlements in São Paulo, Brazil. Drawing upon a mixed-methodological study of two favelas on São Paulo’s east side, we analyze how cycles of upgrading shape informal rental housing at the urban, community, block, and parcel levels, providing detailed comparative data for 2010–2020. Our findings suggest that rental housing redevelopment can increase precarity in urban living, but is an important source of low-income housing in already built-up and “consolidated” settlements where access is declining. Our study emphasizes the need for scholars, policy makers, and planners to further explore the praxis of informal renting and rental housing, which can be effective conduits for channeling public investments across consolidated informal settlements and into individual dwellings.

A Pricing Model for Urban Rental Housing Based on Convolutional Neural Networks and Spatial Density: A Case Study of Wuhan, China

With the development of urbanization and the expansion of floating populations, rental housing has become an increasingly common living choice for many people, and housing rental prices have attracted great attention from individuals, enterprises and the government. The housing rental prices are principally estimated based on structural, locational and neighborhood variables, among which the relationships are complicated and can hardly be captured entirely by simple one-dimensional models; in addition, the influence of the geographic objects on the price may vary with the increase in their quantities. However, existing pricing models usually take those structural, locational and neighborhood variables as one-dimensional inputs into neural networks, and often neglect the aggregated effects of geographical objects, which may lead to fluctuating rental price estimations. Therefore, this paper proposes a rental housing price model based on the convolutional neural network (CNN) and the synthetic spatial density of points of interest (POIs). The CNN can efficiently extract the complex characteristics among the relevant variables of housing, and the two-dimensional locational and neighborhood variables, based on the synthetic spatial density, effectively reflect the aggregated effects of the urban facilities on rental housing prices, thereby improving the accuracy of the model. Taking Wuhan, China, as the study area, the proposed method achieves satisfactory and accurate rental price estimations (coefficient of determination (R2) = 0.9097, root mean square error (RMSE) = 3.5126) in comparison with other commonly used pricing models.

The private rental housing market before and during the COVID-19 pandemic: A submarket analysis in Cracow, Poland

How the COVID-19 pandemic has altered the segmentation of residential rental markets is largely unknown. We therefore assessed rental housing submarkets before and during the pandemic in Cracow, Poland. We used geographically and temporally weighted regression to investigate the marginal prices of housing attributes over space–time. The marginal prices were further reduced to a few principal components per time period and spatially clustered to identify housing submarkets. Finally, we applied the adjusted Rand index to evaluate the spatiotemporal stability of the housing submarkets. The results revealed that the pandemic outbreak significantly lowered rents and modified the relevance of some housing characteristics for rental prices. Proximity to the university was no longer among the residential amenities during the pandemic. Similarly, the virus outbreak diminished the effect of a housing unit’s proximity to the city center. The market partitioning showed that the number of Cracow’s residential rental submarkets increased significantly as a result of the COVID-19 pandemic, as it enhanced the spatial variation in the marginal prices of covariates. Our findings suggest that the emergence of the coronavirus reshaped the residential rental market in three ways: Rents were decreased, the underlying rental price-determining factors changed, and the spatiotemporal submarket structure was altered.

Evaluation of impact of the Covid-19 pandemic on rental housing prices in the city of Brno between 2020 and 2021

The aim of the paper is an application of the basic principles in determining rental housing prices and factors that may affect them. In the experimental part, an analysis of rental housing in the city of Brno is performed for the 2020 – 2021 period affected by the covid-19 pandemic. The analysis is processed for individual city districts and divided according to apartment layout. Finally, all outputs are compared and the real estate market development is determined with a focus on the biggest changes and their occurrence.

Barriers to Institutional Investment in Rental Housing: A Systematic Review of Market Risks

Housing practitioners and policy experts are advocating for an expansion in rental housing supply in contemporary cities around the world. The objective is to convince institutional investors to include rental housing investment in their investment portfolio to contribute to boosting housing supply. Unfortunately, the rental sector is characterized by numerous uncertainties and challenges, making it unattractive to institutional investors. With the growing attention to institutional investors in various housing market contexts, an understanding of the market risks (also known as barriers), is useful to inform future research and policymaking. Using a systematic literature review methodology, this paper synthesizes the extant literature on the market risks inhibiting institutional investment in rental housing. Findings reveal the following barriers: low profitability, non-progressive rent control policies, unclear target group for rented projects, poor landlord-tenant relations, inadequate property management and unreliable property market information. Among all the barriers identified, low profitability and inadequate property management had great influence on their investment decision. Firstly, institutional investors perceive rental housing investment as less profitable and unattractive in terms of project performance. Secondly, the lack of supporting structures for the property management sector contributes to derailing rental yields. The review also finds that the target group for rental projects are often vague especially for projects under government assistance. The rental sectors in many countries are confronted with numerous problems, some of which greatly inhibit institutional investors from investing in the rental asset. This paper concludes that, although the idea of expanding rental housing supply seems laudable, ignoring these problems may be detrimental to housing markets in the long run. Rental markets in many countries are volatile, and thus not ready to receive institutional investors fully into the sector. An expanded rental sector could be advanced if policy makers take the appropriate steps to resolve the identified challenges. Adequate structural preparations must also be made for large scale rental housing supply.