Housing Market Research Articles

Private versus Public Flood Insurance: Differences in Premiums and Uptake Observed in Two Coastal Housing Markets Using Survey Data

Private versus Public Flood Insurance: Differences in Premiums and Uptake Observed in Two Coastal Housing Markets Using Survey Data

Unveiling housing preferences amidst flood risks: an empirical study in an emerging market

Purpose This study investigates the interplay between flood risk, financial constraints and buyer behavior in the housing market. It aims to discern how flood experience influences housing choices, particularly among financially constrained buyers. Design/methodology/approach Using hedonic pricing models and probit analysis, this research examines the implicit prices of house characteristics and evaluates the determinants of housing choices, considering factors such as flood risk, financial status and past flood experience. Findings The study underscores that lower house prices incentivize buyers to opt for homes in flood-prone areas, thereby increasing their vulnerability to flood risks. Consequently, financial constraints exacerbate this situation, compelling low-income buyers to accept higher flood risks. However, flood experience fosters risk awareness among buyers, encouraging them to steer clear of flood-prone areas, albeit with lesser efficacy among financially constrained individuals. Originality/value This research contributes to the understanding of how flood risk and financial limitations shape housing decisions. It highlights the role of flood experience in influencing buyer behavior and emphasizes the need for targeted policies to mitigate flood-related risks in the housing market, particularly among economically vulnerable populations.

Data‐sparse price indexes by spatio‐temporal regularization and PCA: An application to the Australian housing market

AbstractWe present two novel approaches to overcome the limitations of data‐sparse local house price indexes and combine them into a single model pipeline that is simple, computationally efficient, and interpretable. The first contribution is a new spatio‐temporal regularization of least squares dummy variable models, such as the repeat sales regression used here. This regularization encodes prior knowledge of the proximity of houses in space and their sales in time. It handles missing values in a natural way. The second is nonlocal regularization using truncated principal component analysis (PCA) applied to the resulting national collection of local price indexes. The PCA loadings show that there are important underlying socioeconomic factors that can be leveraged in the construction of Australian market indexes. This PCA reveals important socioeconomic factors, showing that many local markets can be described by a few broad aspects of the national market, consisting of a general trend that contrasts regions influenced by the mining industry with Sydney and Melbourne, and another trend that highlights lifestyle.

Characterizing the top trading cycles rule for housing markets with lexicographic preferences when externalities are limited

AbstractWe consider a housing market model with limited externalities where agents care both about their own consumption via demand preferences and about the agent who receives their endowment via supply preferences [we extend the associated lexicographic preference domains introduced in Klaus and Meo (Econ Theory 76:779– 811, 2023)]. If preferences are demand lexicographic, then our model extends the classical Shapley–Scarf housing market (Shapley and Scarf, J Math Econ 1:23–37, 1974) with strict preferences model. Our main result is a characterization of the corresponding top trading cycles (TTC) rule by individual rationality, pair efficiency, and strategy-proofness (Theorem 1), which extends that of Ekici (Theo Econ 19:551–564, 2024) from classical Shapley–Scarf housing markets with strict preferences to our model. Two further characterizations are immediately obtained by strengthening pair efficiency to either Pareto efficiency or pairwise stability (Corollaries 1 and 2). Finally, we show that as soon as we extend the preference domain to include demand lexicographic as well as supply lexicographic preferences (e.g., when preferences are separable), no rule satisfying individual rationality, pair efficiency, and strategy-proofness exists (Theorem 2).

Home construction financing and search frictions in the housing market

This paper studies the effects of financial frictions in construction on housing market dynamics. To this end, we build a search-theoretic model of the housing market in which there is endogenous entry of buyers and developers face credit constraints. We capture credit frictions by assuming that developers must search for financing before building a home à la Wasmer and Weil (2004). Our model explores a novel channel that links credit frictions faced by developers to the housing market. We calibrate the model to quantify the size of the credit channel during the 2012–2019 housing market recovery. Through a series of counterfactuals, our model predicts that the credit channel had a large impact on housing liquidity, construction, and the vacancy rate. Furthermore, it accounts for around half of the rise in prices during the 2012-2019 housing market recovery.

Differential flood insurance participation and housing market trajectories under future coastal flooding in the United States

Communities respond to flooding events based upon risk perceptions and available adaptive behaviors (e.g., emigrating, purchasing insurance, constructing levees). Across the United States, sea level rise, intensifying storm-surges, and extreme rainfall may alter human-flood dynamics. Here, we use calibrated Socio-Environmental models of contiguous US coastal census tracts and two shared socio-economic pathways (SSP245 and SSP585). We project that by 2100, total flood insurance claims will increase by +25% to +130% under low (SSP245) and high (SSP585) emissions scenarios, respectively. The increase in flood insurance claims will impact mainly socially vulnerable communities. Further, we project that active NFIP policies will increase from +30% under low emission scenario to +60% under high emission scenario. Our finding also suggests the growing debt of the National Flood Insurance Program under higher emissions. Raising the water elevation threshold for coastal flooding by +1 meter via levees may reduce future surge-related losses by 95% and 40% under low and high emission scenarios and stabilize housing markets. Our future projections of flood insurance claims, policy coverage, and the impact of water elevation serve as credible hypotheses for the evolution of human flood dynamics under climate change. They can inform national flood policy and future research.

Impact of Natural Disasters on House Prices: A Global Analysis and Policy Implications

This study addresses the limited research on how natural disasters affect house prices by analyzing data from 117 countries between 2000 and 2018, using a panel regression approach to assess these impacts. The results reveal that natural disasters tend to decrease house prices, a finding that holds strong across multiple robustness checks. Specifically, geological disasters are found to have the most significant negative impact on property values. The study also distinguishes between the effects of small and large disasters, with both showing a clear downward effect on house prices. These insights carry important implications for policymakers and investors, as lower house prices in disaster-prone areas may indicate reduced consumption and investment due to the wealth effect, potentially leading to wider economic downturns. To support these regions, economic policymakers might consider measures such as low-tax policies or quantitative easing. The findings also highlight the urgent need for governments to address climate change impacts on the housing market by adopting sustainable technologies and renewable energy sources. Keywords Natural Disasters, House Pricing, Climate Change, Statistical model

Demographic changes, technology growth, and retirement policy reform: Implications for U.S. housing dynamics

As the population aging process continues, concerns about how this situation impacts the housing market and social security rise. To address this question, this paper presents a developed and calibrated general equilibrium life-cycle model incorporating two production sectors to analyze the impacts of demographic structure changes and retirement policy reforms on housing price fluctuations and household choices. The model calibrated to the U.S. macroeconomic data between 1968 and 2018 suggests that in an economy with unlimited land supply, the housing supply curve exhibits perfect elasticity, rendering demographic changes insignificant in housing price fluctuations, while technological advancements lead to decreased prices. A 1% growth in productivity in both sectors results in a 2.6% decrease in house prices. Furthermore, a 1% decrease in population and a 5-year early retirement led to significant reductions of 25% and 30% in individual social security payments and 9% and 18% in interest rates, respectively. This suggests that during a recession caused by demographic structural changes, households become more conservative and prioritize precautionary saving strategies, increasing savings and investing more in housing assets. Consistent with empirical findings, during an economic boom, a decline in the capital-output ratio and the real housing price suggests a decrease in savings and housing asset investment. The rise in consumption drives the capital demand of the non-housing sector to increase, stimulating business expansion and labor inflow.

Inter-regional rail travel and housing markets connectedness between London and other regions

Taking London as a location with which to measure the ripple effect in the UK housing market, this study aims to explain and verify the high degree of correlation between inter-regional transportation and the regional correlation of the housing market. Based on the literature on the relationship between short-term mobility and long-term migration, this paper illustrates that the extent to which people use trains for travel across regions will be related to the ripple effect in the regional housing markets. Frequent railway transport behavior, whether for commuting or traveling, might increase people's desire to relocate between regions, and thus leading to information transmission effects across regional housing prices and transaction volume. First, we estimate a dynamic indicator for the ripple effect. Then, the empirical tests use panel data, including the ripple indicator and passenger number data across time (1996–2022) and regions (nine regions). It is found that if London house prices drive other regional house prices to rise, inter-regional transportation demand will increase, and in turn, the increase of house prices in other housing markets will again drive up London house prices. The number of passengers will affect the information transmitted by the housing market transaction volume in other regions to the London housing market. This implies that higher inter-regional transport needs may lead to migration between London and other property markets, causing their transaction volumes to change in the same direction. The results of this paper verify that travel behavior between regions is a crucial factor in the leading/lagging behavior of regional housing market performance, implying a relationship between short-term travel and long-term migration. The results also indicate that incorporating variables of housing market correlations may help in the prediction of passenger numbers or transportation demand.

Evaluating objective and perceived ecosystem service in urban context: An indirect method based on housing market

Ecosystem service (ES) evaluation is usually based on the stocks of natural resources and their functions. However, the value of ES in the urban area depends on human activities more than the existence of natural resources. This research implements an indirect market method by integrating hedonic housing price model to assess ES in urban context from both objective (remote sensing) and subjective perspectives (street view image). Machine learning tools are employed to investigate the impacts of objective and perceived ES on housing prices based on a case study in Wuxi, China. The analytical results suggest that the contribution of ES to house prices in Wuxi ranges from 0% to 10.85%. Further investigation found that visible trees are the most important ES factor of housing price, more important than the coverage of green space. We also find that the quality of blue-green spaces might modify the value of ES, while the poor landscape design and water pollution in the central urban area made the values of ES low in the housing market. This study proves that the indirect method based on the housing market is helpful in valuing ES in the urban context. The high importance of perceived blue-green spaces in ES encourages more efforts on landscape design rather than only increasing coverage.

China's newest design of apartment buildings with modernized façade: A comparative evaluation of its energy performance in five major climate zones

Many studies have indicated that the energy efficiency of residential buildings can greatly mitigate energy shortages and environmental problems. High window-to-wall ratio, flat geometric shape, and open space layout are the key characteristics of apartment buildings with modernized façade (ABMF), and the major design trend dominating China's housing market. This study aims to understand the isolated effects of these three design factors on the energy performance of ABMF in five major climate zones using a parametric performance design method. Three important findings were concluded: 1) the energy use intensity (EUI) of ABMF showed a positive relationship to the window-to-wall ratio in five climate zones. Qingdao in Cold Region (2.12 kWh/m2) and Kunming in Temperate Region (1.04 kWh/m2) exhibited lowest average increase in EUI; 2) the reduction of EUI was twice as much in Kunming than in the other four cities, when the aspect ratio of ABMF changed from 1.75 to 0.95; 3) the ‘exterior-side hall’ was the most energy-efficient layout in the five cities. This study is the first to investigate the energy performance of the newest apartment design and hopefully can attract more studies to explore the suitability of ABMF for the sustainable development of China's housing market.

Persistence and variation of schools as housing amenities

Research from the 1980’s to early 2000’s documents that home values reflect characteristics of neighborhood schools, but recent shifts in education and housing could be changing these patterns. In this paper, I first revisit an old question: how are neighborhood school characteristics capitalized into the value of housing? I then ask, how has this capitalization effect changed over time? In particular, I explore variation from 2008–2023, a period marked by rapid change in school choice, recovery from a housing bust, pandemic-related disruptions, and an increasingly competitive housing market. I use a boundary discontinuity design to compare property sales on either side of elementary school boundaries and explore variation in the capitalization of a variety of school characteristics across years and school and housing conditions. Overall, I document average patterns that are highly consistent with past literature, where test scores and student racial and socioeconomic demographics significantly affect housing sales prices but measures of school growth do not. I also find that the capitalization of test scores and student demographics varies over time, coinciding with the prevalence of school choice and the competitiveness of the housing market.

Cognitive limits of perceived flood risk on residential property values

Examining cognitive limits in flood risk perception for residential property values, we analyse the Richmond housing market in the state of New South Wales, Australia. Using micro-level home sales data, our study reveals that the market has integrated long-term flood risk into property values. A notable 10.8 % price discount is observed for properties within 1–100 Annual Exceedance Probability (AEP) flood zone, 4.4 % for those in an AEP 500 zone, with no discounts for AEP 1000 flood zone properties. Comparisons of 2019 and 2023 flood maps and property's Time-on-Market (TOM) affirm that people's cognitive limits constrain to the AEP 500 level.

Race, profit, and algorithms: Neighborhood-level analysis of iBuyers’ profit margin

ABSTRACT iBuyers are firms that use automated valuation models (AVMs), streamline home buying processes, and provide all-cash offers to purchase homes. Although the previous literature has explored the roles and limitations of iBuyers in the housing market, empirical research on the racial implications of these algorithmic home buying processes remains understudied. Using a spatial lag model, this study shows the spatial clustering of iBuyer profit margins, that iBuyers gain more profits when they resell to individuals than institutions, and that some iBuyers have a statistically significant correlation between their profit margins and the proportion of marginalized racial groups within a census tract, while controlling for individual housing characteristics, neighborhood housing quality and demand, and neighborhood amenities and socioeconomic factors. These findings suggest that the more adeptly iBuyers can forecast housing values, the greater the potential to maximize profits from homeowners in communities of color. Consequently, this research contributes to the understanding of how technological mechanisms operate within a purportedly race-neutral framework and advocates for the development and deployment of algorithmic systems guided by the principles of antisubordination, rather than relying solely on notions of “fairness” and anticlassification.

Election and Wallet: The Effect of Election Periods and Consumer Expectations on Consumer Confidence with ARDL and QARDL Model Approach

The growing significance of consumer confidence and the explanation of the factors influencing this confidence is an important issue worthy of study. This study aims to examine the effects of election periods and consumer expectations on the Consumer Confidence Index (CCI) in Turkey. To this end, the Autoregressive Distributed Lag (ARDL) and Quantile Autoregressive Distributed Lag (QARDL) models will be employed. Data on the variables in question were collected on a monthly basis from Turkish Statistical Institute (TUIK) over the period spanning 2012:1 to 2024:3. The ARDL model findings indicate that election periods exert a positive and significant influence on the TGE, both in the short run and in the long run. The intention to buy or have a house built and the intention to save have positive and significant effects on the TGE in both the short and long run. Conversely, the intention to buy a car and the cost of living index have a positive and significant effects on the TGE in the short run, but no significant effect was found in the long run. The QARDL model reveals that asymmetry is present, with all variables exhibiting disparate effects across different quartiles. The findings of this study indicate that in order to enhance consumer confidence and guarantee economic stability, it is essential to prioritise the housing market, savings patterns and reducing the cost of living. The development of policies that ensure the sustainability of the confidence and stability created during election periods is crucial. The research offers invaluable insights into ARDL and QARDL models that can inform Turkey's economic policies.

Domesticating Property: Moral Economies of Post‐Socialist Homeownership Through Rental and Neighbour Relations

This article analyses property relations in post‐socialism through the analytical lens of housing studies and moral economy, specifically in the context of rental and neighbour relations in urban apartment buildings. It draws on 50 in‐depth residential biographies of residents of St. Petersburg, Russia, collected between 2017 and 2021. The interviews represent a diversity of tenures, as well as direct and indirect voices of homeowners and non‐owners. The article begins by introducing the socio‐historical context of the privatisation and commodification of housing in post‐socialist Russia. Then, based on the stories of the origin of property and the intensity of attachment to it, I analyse owners’ homemaking through daily interactions with other owners and non‐owners who act as their tenants and neighbours. Focusing on privatised, mortgaged, and inherited residential property, I identify three trajectories of complex relationships between owners and non‐owners in urban buildings and modes of homemaking, at the intersection of monetary and non‐monetary relations and imaginaries of counterparts. I argue that despite everyday interactions in the housing market and in apartment blocks, both the owners of privatised Soviet property and new owner‐occupiers tend to avoid the total commercialisation of the home and to challenge the dominance of homeownership as the only socially sanctioned tenure.

Comparative Statistical Analysis of Changes in Average Asking Prices for Housing in the Administrative Districts of Moscow

The article presents the results of a comparative analysis of the residential real estate market in nine administrative districts of Moscow in 2016 and 2024. The paper focuses on the features of housing price formation and considers factors influencing pricing, including socio-economic conditions and transport infrastructure. The study outlines the role of housing construction and the investment attractiveness of various districts of the capital.The authors used official data from Russia's largest real estate technology service (CIAN) on asking prices for apartments for sale depending on their parameters. The article draws on such indicators as the local average price per square meter of the total area of dwellings and the number of offers of apartments for sale. It is shown that apartment prices in two administrative districts (AO) of Moscow have a stable growth trend in 2024, which was not observed in 2016. It is concluded that the real estate markets in the districts of Moscow in 2016 (exception for the Central AO) were strongly differentiated in price offers in 2024, and, therefore, it is incorrect to use the average price per square meter of Moscow residential real estate as a characteristic of housing quality in 2024.The article lists events that influenced changes in the Moscow residential real estate market without specifying the relative strength of their impact. According to the authors, each event had its causes, but their almost simultaneous appearance led to tension in the housing market for all participants.In conclusion, the significant impact of inflation and the restoration of residential premises (after renting) on the growth of residential property values and the potential for using housing as an investment object is emphasized

Crisis of housing cooperatives in Mexico City: A struggle for Palo Alto

This article features a conversation with Luis Márquez Cruz and Fabiola Carrera from the Palo Alto Cooperative, delving into the history and ongoing struggles of one of Mexico City's oldest housing cooperatives. Formed in the 1980s based on principles of solidarity, mutual aid, and self-management, the cooperative provided affordable housing to working-class families. However, changes to cooperative laws in 1994 halted new cooperative projects and shifted government support to private developers. Today, Palo Alto faces internal divisions as some members push for the cooperative's dissolution and sale of property amidst rising real estate prices, while others fight to preserve collective ownership. The article explores the cooperative’s international alliances, political training, and grassroots organizing efforts, highlighting the urgency of defending cooperative housing as an alternative to Mexico City's increasingly commodified and exclusionary housing market.

Yin-Yang Contracts in the Second-hand Housing Market: Problems, Causes and Governance Policies

Yin-Yang Contracts in the Second-hand Housing Market: Problems, Causes and Governance Policies

The state role in the housing sector in Hamburg and Havana challenges and successes of the state's claim to control in different political and planning systems

AbstractHousing supply is a controversial topic across the globe. In Europe, for example, housing provision is fundamentally characterised by capitalist market economy. However, the intensity of state intervention differs significantly in the respective European countries. Germany is certainly one of the countries in which the state traditionally intervenes considerably in the housing market and attempts to control it through various measures. In addition, the stakeholders in the housing market are very different, and the housing market is highly segmented. In Cuba, as a rather atypical example for Latin America, where the housing market is largely liberalised, the housing market is very strongly regulated by the socialist Cuban state. In this article, we address the topics of housing supply by analysing the institutional framework conditions and the different levels of intervention in the very different systems of Germany and Cuba. In doing so, we find that the objectives at the planning and political levels in these two case studies are quite similar despite the major political and social differences. It has become clear, that there is a gap between the aspiration of the political-administrative planning system and the planning expectations of the citizens in both systems. However, it is also emphasised that the state's claim to intervene in the housing market and the regulations, production and financing conditions are very different. Using Vaus’s ‘most-different-case approach’, we emphasise for the two cities of Hamburg and Havana that although considerable successes have been achieved in both systems in terms of adequate housing provision, but major challenges still exist in both cities. The analysis has also made clear how important it is to combine housing policy demands with the realities of housing industry, real estate markets and urban planning perspectives.