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.

Micro-Analysis of Price Spillover Effect among Regional Housing Submarkets in Korea: Evidence from the Seoul Metropolitan Area

This study examined the price spillover effect of housing submarkets in cities in the Seoul metropolitan area in South Korea by using the Granger causality test and vector autoregressive model (VAR). We found that housing prices showed a higher spillover effect within regions with similar housing market characteristics. Additionally, the spatial spillover of housing prices revealed a difference between sales price and jeonse price. The spillover of jeonse price was characterized by mutual influence among neighboring cities, while that of sales price was characterized by the influence being transferred in one direction hierarchically. Furthermore, the effects of housing price indicated a slight difference between sales price and jeonse price. Although jeonse price was mainly affected by a neighboring area (geographic boundary), sales price was more influenced by the city with the highest housing prices. Lastly, the housing price spillover tended to be expansive around the city with the highest price. These results suggest that housing price policies targeting specific regions or areas in Korea must be differentiated according to the type of occupancy (jeonse or sales), and it is essential to consider the externalities when promoting policies in the housing market wherein externalities may be significant.

Subdividing the sprawl: Endogenous segmentation of housing submarkets in expansion areas of Santiago, Chile

Urban sprawl is a phenomenon observed in most cities around the globe and especially in Latin America, where it is associated to socioeconomic segregation. In the case of Chile, sprawl has been generally based on large real estate projects. Developers target their projects to different types of consumers, which translates into submarkets with a broad range of housing-unit’s characteristics, but also different location strategies. This heterogeneity has been analyzed and measured in the literature, but quantitative studies have used exogenous or sequential methods to identify submarkets, leading to potential bias in the segmentation. In this paper, we propose an econometric model to measure location drivers for different types of real estate projects that fills this gap. The modeling framework is based on discrete-choice and latent-class models, allowing us to simultaneously identify market segmentations, and their particular location choice preferences, without the need of arbitrary or ex-ante definitions of submarkets. The model is applied to the city of Santiago, Chile. The results reveal two clearly different approaches taken by developers to produce housing, with one submarket of “exclusive” and more sprawling projects, and another submarket of “massive” and more density driven projects. Location strategies are very different between submarkets, reproducing the socio-spatial segregation already observed in the consolidated city.

Measuring the Effect of Location on House Prices in Italy

The Italian housing market is characterised by both a strong heterogeneity of real estate assets and a reduced number of property sales. These features, indeed, hamper the use of the hedonic price method, namely, the method that is mostly used for assessing the house prices and for estimating the monetary value of housing characteristics. In this paper, therefore, a hedonic model with dummy variables that identify housing submarkets is used to achieve two important results: enabling greater use of multiple regression analysis in the study of the Italian real estate market, and catching, in the simplest possible manner, the effect of location on house price. Indeed, the house's location is, together with the area in square metres, the housing characteristic that most influences the house price.

Detecting Intra-Urban Housing Market Spillover through a Spatial Markov Chain Model

This study analyzed the spillovers among intra-urban housing submarkets in Beijing, China. Intra-urban spillover imposes a methodological challenge for housing studies from the spatial and temporal perspectives. Unlike the inter-urban spillover, the range of every submarket is not naturally defined; therefore, it is impossible to evaluate the intra-urban spillover by standard time-series models. Instead, we formulated the spillover effect as a Markov chain procedure. The constrained clustering technique was applied to identify the submarkets as the hidden states of Markov chain and estimate the transition matrix. Using a day-by-day transaction dataset of second-hand apartments in Beijing during 2011–2017, we detected 16 submarkets/regions and the spillover effect among these regions. The highest transition probability appeared in the overlapped region of urban core and Tongzhou district. This observation reflects the impact of urban planning proposal initiated since early 2012. In addition to the policy consequences, we analyzed a variety of spillover “types” through regression analysis. The latter showed that the “ripple” form of spillover is not dominant at the intra-urban level. Other types, such as the spillover due to the existence of price depressed regions, play major roles. This observation reveals the complexity of intra-urban spillover dynamics and its distinct driving-force compared to the inter-urban spillover.

Housing Submarkets and Future Demographic Developments

Europe is undergoing a profound demographic change. This change will affect significantly all aspects of modern economies including the demand and the prices of the housing stock. The relationship between prices of the housing market and associated demographic variables has been long established. However, in the current literature, the housing market is considered to be unitary and coherent, that is one price reflects the housing stock without taking into account the housing characteristics which in real economy are considered essential for price calculation. To this respect it must be noted that housing submarkets existence has been long established based on the current literature. However and in relation to housing submarkets, the actual goal of the studies currently exist was the definition process, the models and the techniques that should be employed in order to acquire best results. Housing submarkets are considered important in the understanding of different social phenomena. In this chapter an attempt is made to review the relationship of housing prices to demographic variables and then a review on the definition process of housing submarkets.

Property valuation: the hedonic pricing model – location and housing submarkets

Purpose The purpose of this paper is to comment upon the use of hedonic pricing models for the valuation of property. This model can be particularly useful for some housing markets. Design/methodology/approach This Education Briefing is an explanation of the how hedonic pricing can be useful in looking at the effect of “location” on the house prices within different submarkets using the Italian real estate market as an example. Findings Although, this case study is relatively straightforward, it shows how the application of the market approach can provide insights in cases where the comparable properties belong to different submarkets with relatively few transactions. Practical implications In cases of mass appraisals, hedonic pricing models can provide a broad indication of value across submarkets. Originality/value This paper develops a general framework that connects multiple regression analysis, direct comparison model and submarket binary variables.