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We study the valuation of collateral by comparing spreads on loans by the same bank, to the same borrower, at the same origination date, but backed by different types of collateral. Pledging collateral reduces borrowing costs by 23 BPS on average. The effect varies across different types of collateral, with marketable securities being most valuable, and real estate and accounts receivables and inventory being more valuable than fixed assets and a blanket lien. Further, the rate reduction from pledging collateral is sensitive to the value of the underlying collateral, and collateral tends to be more valuable for smaller and private firms and for loans with longer maturity. [ABSTRACT FROM AUTHOR]

I identify the effect of financial constraints on product prices using granular data on home-builder housing developments from the 2006–2009 housing crisis. Builders who experience losses in one area subsequently sell homes in unaffected areas at a discount to raise cash quickly. When builders cut prices, they sell homes faster and builders cut prices more in areas in which price cuts produce larger declines in time-to-sale. Financially constrained firms are more likely to cut prices of homes in healthy areas following losses elsewhere. Firms cut prices following losses in other projects only during the crisis, not during the boom. [ABSTRACT FROM AUTHOR]

Homeowners who originally bought when marketwide price levels were high (low) fetch high (low) sales prices and rents, even decades later. We study the propagation of reference-dependence to neighboring listings. The "spillover" reference point effect is about one-half as large as the "own" reference point effect. Neither house quality nor location appears capable of explaining the result. Using a simple model to provide empirical predictions, we find support for a competition-based mechanism. We quantify the aggregate effect of own and spillover reference point effects on aggregate prices and/or rents at the ZIP code level. Authors have furnished an Internet Appendix , which is available on the Oxford University Press Web site next to the link to the final published paper online. [ABSTRACT FROM AUTHOR]

This study provides novel evidence regarding the effects of loan-to-value (LTV) limits on housing choices. Using a detailed loan-level dataset, I exploit the introduction of LTV limits in Israel. I find that the LTV limits led borrowers to choose housing units that were more affordable, farther from the central business district, and in lower socioeconomic neighborhoods. Additionally, these LTV limits increase interest rates and decrease loan amounts. The findings of this study indicate that macroprudential policies, which focus on the stability of the financial system, have micro implications on location choices, commuting costs, and movement to less-advantaged areas. [ABSTRACT FROM AUTHOR]

This article seeks to explore the efficacy of the Housing-Resale Restriction (HRR) policy in curtailing housing speculation, complementing existing literature that primarily examines the impact of taxation. The HRR policy directly reduces speculative opportunities through heightened liquidity constraints. Employing the methodology of regression discontinuity in time (RDiT), this study analyzes the impact of liquidity constraints on housing price growth rates based on the monthly community-level data from Qingdao, China, where the HRR policy was the most stringent in terms of scope and holding time requirement. The results show that the HRR policy reduced housing price growth rates by 1.3881 to 2.1001% points on average. Moreover, the disincentive impact was less pronounced in affluent, recently developed communities and those near subway stations. These findings provide valuable insights for policymakers to regulate the real estate market, mitigate excessive speculation, and prevent market bubbles. [ABSTRACT FROM AUTHOR]

This study uses panel data for the 50 states of the U.S. plus the District of Columbia from 1998 to 2018 to examine pricing effects of climate change on housing and insurance markets. We apply the mean group estimator and separate short-run from long-run impacts. The results indicate long-run relationships between the housing/insurance market and climate change, although no significant impacts of climate change on these markets appear in the long-run. In the short-run, we find significant negative impacts of fire occurrences on housing prices and mortgage rates, and significant positive impacts of flooding on insurance markets. Further analysis of states exposed to severe climate risks indicates no short- or long-run impacts of climate change. Thus, while realtors and insurance providers may price some climate-risks into mortgage and insurance in the short-run, they do not in the long-run. [ABSTRACT FROM AUTHOR]

Mortgage credit has been central in fuelling housing market dynamics in many countries. While mortgage debt and house price increases used to go hand in hand, we see an uncoupling post-global financial crisis, with relative mortgage debts decreasing while house prices are increasing at unprecedented rates. This article scrutinises this uncoupling, contributing in three ways. First, we argue it is representative of how debt-driven housing dynamics have been supplemented by wealth-driven ones: while mortgage debt remains crucial, it has stagnated, and increased wealth investments have fuelled a new round of price increases. Second, we explore key examples of wealth-driven housing dynamics: the increase in private landlordism (buy-to-let), older homeowners reinvesting accumulated housing wealth and intergenerational house purchases. Third, we demonstrate that these dynamics are associated with increasing fractures along the lines of class, age and place, particularly benefiting affluent and older insiders while advancing uneven development. We base our arguments on an empirical analysis of the Netherlands, a country with a highly financialised owner-occupied market boasting one of the highest mortgage-debt-to-GDP ratios in the world, but our arguments have wider relevance. We conclude that current dynamics point to a new era of house price rentierism. [ABSTRACT FROM AUTHOR]

Geographically weighted regression (GWR) and its extensions are important local modelling techniques for exploring spatial heterogeneity in regression relationships. However, when dealing with spatial data of overlapping samples – for example, when precise locational information is aggregated to a shared neighbourhood to avoid revealing the addresses of individual survey respondents – GWR-based models can encounter several problems, including obtaining reliable bandwidths. Because data with this characteristic exhibit spatial hierarchical structures, we propose combining hierarchical linear modelling (HLM) with GWR to give a hierarchical and geographically weighted regression (HGWR) model that divides coefficients into sample-level fixed effects, group-level fixed effects, sample-level random effects, and group-level spatially weighted effects. This paper presents a back-fitting likelihood estimator to fit the model, a simulation experiment that suggests that HGWR is better able to capture these effects and the spatial heterogeneity within them than are traditional HLM or GWR models, and a case study looking at predictors of housing price in Beijing, China. The ability of HGWR to tackle both spatial and group-level heterogeneity simultaneously suggests its potential as a promising data modelling tool for handling spatio-temporal big data with spatially hierarchical structures. [ABSTRACT FROM AUTHOR]

In the past, for urban governance issues, local governments tended to only focus on the economic development of cities, but in recent years, in the context of the global pursuit of sustainable goals, how to propose public investment policies that can attract more people willing to relocate to cities has become more important. This paper explores the impact of public investment with different goals (types) on urban development to illustrate that public investment only in pursuit of economic development (income growth) may result in cities deviating from achieving their sustainable goals. Excessive housing prices and pollution may reduce people's willingness to move there. Only investing in both economic development and infrastructure that can improve the living environment may enable cities' housing prices and populations to grow moderately. By constructing a theoretical model and numerical simulation analysis, this paper not only explains the positive and negative externalities of public investment but also proposes what factors affect cities' housing prices, population, and the benefits of public investment. The results of this paper can help local governments formulate urban governance policies and supplement the literature on sustainable cities. [ABSTRACT FROM AUTHOR]

In this paper, house prices in Christchurch are analysed over three distinct periods of time: post-2011 earthquake, pre-COVID-19 lockdown, and post-COVID-19 lockdown. The first method used is the well-established hedonic price model, additionally a second method incorporates random effects into the model to capture unobserved heterogeneity in buyers' preferences for certain features of a house. Results show that buyers, in periods that are temporally distant from the 2011 Christchurch earthquake, underappreciate the risk of potential earthquake damage to a property. We find that there are observable shifts in buyer preference across the different time periods, specifically in terms of section size. We also examine heterogeneity and correlations in buyers' preferences for floor area, land area, and age of a property. [ABSTRACT FROM AUTHOR]

Housing price growth resulting from rapid urbanization in China has become a major concern in sustainable research. Taking southern Jiangsu province as an example, we tried to identify urban areas in 1995, 2010, and 2020 at the block scale. Mean centers of housing prices and urban areas in different periods were used as proxies for evaluating the coordination degree. Moreover, a geographically weighted regression model (GWR) was used to discuss the impacts of location, neighborhood, urban vitality, and landscape on housing prices. Results show that: (1) housing prices in a city generally decrease from urban centers to rural areas, indicating that urbanization affects housing prices; (2) mean centers of housing prices and urban areas show a similar trajectory in the entire region, demonstrating a high quality of urban development; (3) location, landscape, and urban vitality typically positively impact home price growth, while neighborhoods negatively impact it; these relationships vary across different cities. The results provide basic knowledge for urban management. [ABSTRACT FROM AUTHOR]

The features of the micro-location and in particular the micro-neighborhood that residents perceive on a daily basis have a considerable influence on the quality of living and also on housing prices. For automated valuation models (AVMs), the use of micro-neighborhood information would be beneficial, as incorporating additional spatial effects into the price estimate could potentially reduce the empirical error. However, measuring related features is difficult, as they must first be defined and then collected, which is extremely challenging at such a small spatial level. In this study, we investigate the extent to which the quality of micro-neighborhoods can be assessed holistically using multiple data modalities. We design a scalable approach using alternative data (images and text), with the potential to expand coverage to other urban regions. To achieve this, we propose a multimodal deep learning architecture that integrates both textual and visual inputs and fuses this information. In addition, we introduce a training strategy that enables a targeted fusion of orthogonal visual representations of the residential area within the model architecture. In our experiments, we test and compare different unimodal models with our multimodal architectures. The results demonstrate that the multimodal model with targeted fusion of the orthogonal visual inputs achieves the best performance and also improves the prediction accuracy for underrepresented location quality classes. [ABSTRACT FROM AUTHOR]

This study investigates the impact of telecommunication infrastructure on residential property prices in Poland. This study contributes to the discussion of economic externalities related to new public infrastructure within the urban landscape. We use hedonic regression, matching techniques, and a difference-in-differences estimator to assess the impact of base transceiver stations on apartment prices in Warsaw, the capital of Poland, which covered market data on the sales of residential premises located in Miasteczko Wilanów estate in Warsaw from 2016 to 2021. In the analysed period, 1,825 residential sales were recorded and used for econometric modelling. The results do not confirm the influence of the vicinity of the wireless communication technology infrastructure on residential real estate prices in the studied local market. In particular, we did not observe a detrimental effect of cell phone towers on housing prices. Additionally, we investigate whether residential sale prices in proximity to BTS changed significantly after the introduction of the 5G standard. This particular issue has not been addressed in the economic literature. We found that the sale prices of apartments located in Warsaw were not statistically affected by the introduction of a fifth-generation technology standard for broadband cellular networks. Our research contributes to a better understanding of stigmatisation effects related to telecommunication infrastructure, and in particular, the links between the presence of cell phone towers and residential property values in the neighbourhood. The results may be of interest to all potential agents involved in neighbourhood conflicts arising from investments in cell phone towers and the development of new communication infrastructure in urban landscapes. Highlights: The proximity of the base transceiver stations does not significantly affect the transaction prices. The introduction of 5G technology did not have a significant effect on residential property prices near cell phone towers. These findings contribute to a better understanding of the complex interplay between urban development, community conflicts, and housing prices. [ABSTRACT FROM AUTHOR]

This study examines the relationship between changing house prices and assessed value in the Detroit Michigan region. Using parcel-level data from 2008 through 2016, we construct a Hedonic Housing Price Index and an Assessed Value Index for 120 Michigan assessing jurisdictions in the five-county region surrounding Detroit (Macomb, Monroe, Oakland, Washtenaw, and Wayne). Our findings are consistent with the literature, indicating at least a three-year lag between changes in house prices and changes in property assessments. Communities considered to be distressed tended to over-assess properties before the crisis, but these communities recalibrated assessments to better align with market conditions after the financial crisis. Our evaluation also shows that while assessed values decreased more slowly than housing prices fell during the crisis, assessed values tended to fall to even deeper levels than housing prices over a longer time horizon. JEL Codes: H71, H83, G01 [ABSTRACT FROM AUTHOR]

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While quality‐adjusted indices tracing the evolutions of regional house prices are increasingly available, this is less the case for data on regional house price levels. Yet, such information is fundamental to assess housing affordability and barriers to labour mobility. This article puts forward a method to compile regional house price levels that are consistent with the evolutions given by house price indices, representative of the underlying stock of dwellings, and based on the information on house price levels that is available at all dates rather than in a single reference period. Results for Spain show that the decline in house prices following the 2008–2009 crisis initially reduced the dispersion in house prices across Spanish regions, but this dispersion has increased again afterwards. Moreover, the relative housing affordability of Madrid deteriorated compared to all other Spanish regions in the last decade. Monitoring whether COVID‐19 will reverse this trend will be key. [ABSTRACT FROM AUTHOR]

This study highlights the importance of the relationship between housing prices and tourism labour mobility. This study uses dynamic panel threshold approach to examine the nonlinear effect of housing prices on tourism labour mobility in Chinese mainland during the years 2000-2021. The empirical results show that rising housing prices are positively associated with tourism and its subsectors' employment across different levels of housing prices. At the regional level, there exists regional heterogeneity of housing price affecting labour mobility within tourism industry and its subsectors in Eastern, Central and Western regions. Lastly, further discussion and policy suggestion are provided. [ABSTRACT FROM AUTHOR]

Climate change‐driven extreme heat events pose a major threat to urban expansion globally. This study evaluates the relationship between extreme heat and housing prices utilizing panel data from Chinese cities between 2009 and 2019. Our findings indicate a significant negative correlation between housing prices and extreme temperatures. Specifically, we observe a 0.1% reduction in housing prices for each additional day per year with temperatures surpassing 35°C. This research evaluates two primary mechanisms underpinning this finding. Firstly, our analysis demonstrates a decline in labor inflows to cities experiencing extreme heat, with a particularly significant effect on the influx of high‐skilled workers. In addition, existing residents in these hotter urban environments exhibit reduced home‐buying intentions and reduced proclivity for long‐term residency, coupled with higher living costs. Secondly, our findings indicate that extreme heat acts as a deterrent to firm entry, thereby further suppressing housing demand. This study contributes valuable empirical insights into the capitalization of climate risk in housing markets, with a specific emphasis on the effect of extreme heat. Moreover, it highlights the urgent necessity for the development and implementation of sustainable adaptation strategies to reduce the negative effects of evolving climatic conditions. [ABSTRACT FROM AUTHOR]

This study probably marks the first attempt to differentiate between investment and owner-occupancy when measuring real estate price bubbles. The housing tenure and leverage status of each residential sale in the Auckland housing market are identified, and four groups of transactions are created: leveraged investment (LI), leveraged owner-occupancy (LO), unleveraged investment (UI) and unleveraged owner-occupancy (UO). This research applies a present value model to estimate housing price bubbles for the four groups. We discover that, in terms of the duration and size of bubbles, there are minor differences among the four groups. In addition, the overvaluation for all groups is mainly related to momentum behaviour. [ABSTRACT FROM AUTHOR]

In this study, we utilized the ArcGIS Geographic Information System (ArcGIS) to study the relevant datasets of park green and residential subsidiary green spaces in Wuhan City, and at the same time, scraped residential area prices data in Wuhan using big data technology. The inverse distance weight spatial interpolation method is employed to analyze the spatial patterns of residential area prices. Distances from each residential area to park green spaces at different scales are calculated to investigate their impact on residential area prices. Three strategies are proposed: the tailored allocation of different types of park based on regional characteristics, the implementation of "quantity guarantee and quality improvement" measures to enhance the quality of residential green spaces, and the promotion of interaction between park green and residential green spaces. These strategies aim to particularly uplift housing prices in economically disadvantaged areas, ultimately achieving shared prosperity. [ABSTRACT FROM AUTHOR]

Periodically collapsing bubbles, if they exist, induce asymmetric dynamics in asset prices. In this article, I show that unit root quantile autoregressive models can approximate such dynamics by allowing the largest autoregressive root to take values below unity at low quantiles, which correspond to price crashes, and above unity at upper quantiles, that correspond to bubble expansions. On this basis, I employ two unit root tests based on quantile autoregressions to detect bubbles. Monte Carlo simulations suggest that the two tests have good size and power properties, and can outperform recursive least‐squares‐based tests. The merits of the two tests are further illustrated in three empirical applications that examine Bitcoin, US equity and US housing markets. In the empirical applications, special attention is given to the issue of controlling for economic fundamentals. The estimation results indicate the presence of asymmetric dynamics that closely match those of the simulated bubble processes. [ABSTRACT FROM AUTHOR]

The distributional single index model is a semiparametric regression model in which the conditional distribution functions P(Y≤y|X=x)=F0(θ0(x),y)$$ P\left(Y\le y|X=x\right)={F}_0\left({\theta}_0(x),y\right) $$ of a real‐valued outcome variable Y$$ Y $$ depend on d$$ d $$‐dimensional covariates X$$ X $$ through a univariate, parametric index function θ0(x)$$ {\theta}_0(x) $$, and increase stochastically as θ0(x)$$ {\theta}_0(x) $$ increases. We propose least squares approaches for the joint estimation of θ0$$ {\theta}_0 $$ and F0$$ {F}_0 $$ in the important case where θ0(x)=α0⊤x$$ {\theta}_0(x)={\alpha}_0^{\top }x $$ and obtain convergence rates of n−1/3$$ {n}^{-1/3} $$, thereby improving an existing result that gives a rate of n−1/6$$ {n}^{-1/6} $$. A simulation study indicates that the convergence rate for the estimation of α0$$ {\alpha}_0 $$ might be faster. Furthermore, we illustrate our methods in an application on house price data that demonstrates the advantages of shape restrictions in single index models. [ABSTRACT FROM AUTHOR]

How urban entrepreneurialism is enacted at the neighbourhood level while connecting with broader urban processes remains insufficiently explored. This study introduces a novel conceptual framework of multiscalar and multidirectional urban entrepreneurialism to examine the governance of gated communities that involves dynamic interactions between the entrepreneurial local state, developers, gated communities and individual homeowners/investor-citizens. In Chinese cities, the pursuit of quality living and good schools has given rise to 'education-featured gated communities' that package privileged access to K–12 schools with tailor-made residential services. By turning education from a public good into a club good that can be capitalised in the housing price and leveraged in urban (re)development, education-featured gated communities are highly sought after by homebuyers, developers, and local states, becoming an important and integral component of urban entrepreneurialism. When the rising demands of gated community homeowners for school places are not met, activism for quality education within gated communities becomes ubiquitous. Drawing on multiple case studies and multi-source empirical data including national and local policies/documents, in-depth interviews, non-participant observation and site visits, this research examines how homeowners negotiate their exclusive right to public schools through intensive interactions with local authorities. We argue that the semi-private governance of gated communities forms the institutional basis for the 'shareholding enterprise' centring on property values. By unpacking the multidirectional processes of entrepreneurial governance that built upon an effective feedback loop involving multiscalar entrepreneurial endeavours based on shareholder value, this study offers a nuanced and enriched understanding of contemporary urban entrepreneurialism. [ABSTRACT FROM AUTHOR]

Foreign capital and buyers are often blamed for pushing up housing prices and reducing the supply of affordable housing in Australia. We examine this issue by assessing the impact of Chinese macroprudential policies, such as the limitation on currency transactions (LCT), on Sydney housing prices. Using propensity score matching and difference-in-differences techniques, we find that the LCT policy issued by the People's Bank of China in 2017 had a strongly negative impact (about −3%) on housing prices in suburbs with larger concentrations of Chinese residents, which are measured by multiple cutoff points—hereafter, Chinese suburbs—in Sydney, Australia. The results are consistent with home bias abroad, which implies that Chinese capital for residential real estate overseas most likely flows to predominately Chinese neighbourhoods in the destination city. We also find evidence that the relationship between this Chinese macroprudential policy and overseas housing prices is more direct to Chinese suburbs, with little impact on housing prices outside Chinese neighbourhoods within the studied period. [ABSTRACT FROM AUTHOR]

This paper introduces insights into the Turkish real estate market, which can be generalized globally. It primarily aims to find the best forecasting algorithms for the housing price index and compare their prediction performance over three, six, nine, and twelve months ahead by using recurrent neural networks (RNN) with a comparison of out-of-sample predicting power of econometrical models. For these purposes, we employ three RNN architectures in twenty-four settings, revealing that certain RNN architectures are the best predictors in forecasting the Turkish real housing price index. The RNN architectures outperform traditional econometric models; however, the more months forecasted, the lower the prediction power. The lagged values of the price-to-rent ratio, real rents, and the lagged USDTRY values contribute more than the other predictors in forecasting the real housing price index. The outcomes suggest that stocks, real estate investment trusts, and gold are neither complementary nor competing financial instruments since housing is an illiquid asset. [ABSTRACT FROM AUTHOR]

The issue of land financialisation has received considerable critical attention, with the literature focusing on the definition and process of land financialisation and its contribution to urban development. This paper draws upon the capitalist spatial production theory to explore how the ongoing financialisation process in the land market is related to the housing market. After controlling for observed city characteristics and unobserved city and year fixed effects, we find a positive correlation between land financialisation and housing prices. Furthermore, our results suggest that this positive effect is strengthened in tier‐1 cities and when land transfer is fully marketised, but weakened when more affordable housing is available. Overall, this study contributes to the literature on land financialisation and housing prices by critically discussing the consequences of land financialisation on housing prices, providing new insights into the reasons for soaring housing prices, and enriching the knowledge of urban governance. [ABSTRACT FROM AUTHOR]

Maintaining a stable residence is a primary requirement of probation compliance. Prior research has spoken to the increase in requirements for people on probation and how they are often tied to financial capability. Using data from in-depth interviews with people on probation and probation staff, our analysis extends extant research by highlighting the unique challenges of finding housing during a historic rise in housing and rental prices in the context of COVID-19. This work furthers research on the role that economic means play in the probation revocation process. Results from the research suggest that housing is a barrier to success on probation, which is further hampered by the lack of employment opportunities available to individuals with felony criminal records. Participants relayed that the lack of affordable housing led to heavy reliance on family members for assistance. Information from staff triangulated their concerns about how compliance was tied to poverty. [ABSTRACT FROM AUTHOR]

We study how house prices responded to a deadly 2010 pipeline explosion in San Bruno, California, which shocked attention and information. We find that home prices near pipelines in the Bay Area declined by 2% initially, but this gap quickly dissipated. We see no response among properties similarly exposed in other markets or in response to an informational letter sent to households the following year. These results suggest that home buyers are willing to pay to avoid pipeline risk when the issue has their attention, but this attention is hard to capture and is fleeting. [ABSTRACT FROM AUTHOR]

With unique datasets, this paper studies the effects of dockless bike sharing on house prices. We find that in neighborhoods relatively far from subway stations, house prices increase with the usage intensity of shared bikes. This indicates a positive value of bike sharing as a complement to the subway network. Meanwhile, shared bike usage intensity also has a negative impact on house prices. The negative effect is mitigated for luxury neighborhoods and neighborhoods near City Management Teams, suggesting that the negative effect is related to bike misplacement. Since the breakout of COVID-19, both the positive and negative price impacts have become more evident. This is consistent with the fact that the user base of shared bikes, which allow for social distancing in an open space, has increased during the pandemic. This may enhance people's confidence in the long survival of the bike sharing industry. [ABSTRACT FROM AUTHOR]

This paper studies if information on radiation from uranium and radon is capitalized into housing prices and tests if homeowners sort vertically to avoid increased ground-level radiation. Using detailed measurements on the level of radiation, I estimate housing price elasticities with respect to radiation among both single-family detached homes and apartments in multi-story buildings. The results for the single-family homes show that both uranium in the bedrock and indoor radon levels are negatively correlated with the housing price. While the estimates for the single-family homes might be biased due to omitted geographical variables that are correlated with the level of radiation, the capitalization of radiation among apartments in multi-story buildings can be estimated using only within-building variation in the level of radiation. I use building-fixed effects to test for the existence of a vertical pollution price component to the vertical rent curve. Radon gas is heavier than average indoor air and higher concentrations are mostly found on lower floors in areas with high uranium concentrations in the bedrock. Theory predicts that apartments on higher floors will be priced higher relative to the first floor in more polluted areas. The results show that vertical price difference between the first floor and the fifth floor or above is on average 0.7 percent higher due to the uranium in the bedrock while the price effect for the indoor radon measurements is close to zero. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the effects of air quality on housing prices from the short-run and long-run perspectives. We utilize monthly housing price data and the particulate matter 2.5 (PM2.5) index for prefecture-level cities in China. Relying on instrumental variable (IV) estimation and dynamic common correlated effects-pooled mean group (DCCE-PMG) techniques, our results reveal a short-run negative causal and a long-run inverted-U relationship between air pollution and housing prices. This finding suggests that the effect of anti-pollution efforts on housing prices is nonmonotone; initially having a favorable effect and then after reaching a certain turning point, the pollution reduction effort is associated with depression in housing prices. We further find that the heterogeneity in the points of different cities can be explained by socio-demographic factors. Specifically, our results reveal that while pollution-reduction campaign initially had effects related to willingness-to-pay (WTP) theory, further control measures had an adverse effect on housing prices. Thus, our study presents important implications for the effectiveness of environmental regulations. [ABSTRACT FROM AUTHOR]

We examine the house price convergence across 12 OECD countries over the period 1905–2016. Using novel quantile unit root tests which allow for smooth breaks via a Fourier expansion series, we find that nine countries show the presence of relative house price convergence at all the quantiles. Focusing on several specific quantiles, 11 countries have significant convergence tendencies. Moreover, there are four definite patterns related to shocks in the relative house prices across quantiles. [ABSTRACT FROM AUTHOR]

The widely acknowledged rating system of the Federal Homeowners' Loan Corporation (HOLC) was a relative measure of pre-1940 racist practices in residential real estate activities in large United States central cities. It was not an assessment that guided HOLC or later Federal Housing Administration (FHA) mortgage lending practices. The research question examined here is whether a similar home in different HOLC-rated neighborhoods in the City of Sacramento (California) sold for a different price eight decades after receiving its HOLC grade. A hedonic regression result shows that homes in the two forms of lower-rated neighborhoods sold for about 13% less than those in the two forms of higher-rated neighborhoods. A Blinder-Oaxaca decomposition breaks down the average selling price difference of $195,000 between a home sold in HOLC green/blue compared to yellow/red rated neighborhoods. A third of this difference in home prices, which is not due to home characteristics, represents a starting measure of the legacy of discriminatory housing practices. The remaining two-thirds of the difference could be due to variations in current home characteristics also influenced by Pre-1940s discriminatory housing practices. These findings are relevant to understanding the contribution of past structural racism in the housing market to present inequalities. [ABSTRACT FROM AUTHOR]

We present a tractable model that accommodates asset‐market sentiment in a standard Dynamic Stochastic General Equilibrium (DSGE) setting, allowing us to quantitatively evaluate sentiment‐driven macroeconomic fluctuations. In our model, changes in households' perceived uncertainty about housing prices lead to self‐fulfilling fluctuations in housing prices, which then impact investment and output through entrepreneurs' collateral constraints. Household sentiment shocks hence are transmitted and propagated to the macroeconomy, generating boom–bust cycles. Uncertainty, housing prices, and the real economy are linked. Quantitatively, the sentiment shock in the form of risk–panic is a crucial driver of business cycle fluctuations despite the presence of various competing shocks. [ABSTRACT FROM AUTHOR]

Studying the mechanism by which urban subway construction in China increases housing prices can help deepen the understanding of the factors that rises in housing prices and may assist the government to conduct reasonable macro-control of the real estate market. This article takes unbalanced panel data from 31 major cities in China as research samples and studies the mechanism by which urban subway construction increases housing prices by influencing urban economic growth. Our findings are as follows: (1) Subway construction promotes urban economic growth, and urban economic growth, from both the demand and supply sides, increases housing prices by increasing the disposable income of urban residents and the purchase price of residential land. (2) Urban subway construction increases city land purchase prices by affecting investors' expectations of urban land development through the regulating effects of urban economic growth, which in turn increases housing prices. (3) Effective policy measures aimed at managing the speculative impact of metro construction on housing prices need to be viewed for the expectation management of housing and land speculative demand from both the demand side and the supply side. [ABSTRACT FROM AUTHOR]

AbstractWhen skyrocketing house prices worsen housing affordability, parental financial support is suggested to be more important and prevalent in young people’s housing transition. However, little is known about young people’s perceptions and responses to it, particularly when they struggle among different sets of conflicting norms – the values of self-reliance, deep-seated home ownership preference, and marriage and gender expectations. Based on in-depth interviews with 50 highly educated young people aged 25–34 in Hong Kong, this study found that many young people were torn between the housing ideal – achieving home ownership by themselves – and economic realities. They did not necessarily welcome their parents’ home financing while many struggled to establish their financial responsibility even when they agreed to accept parents’ money. Some explicitly rejected parents’ assistance due to different concerns, such as preserving decision-making power. Gender and marriage norms also shape parents-of-daughters’ financing and young men’s acceptance. Young people’s attempts to carefully delineate financing responsibility in own housing projects (e.g. an outright rejection of parents’ money) may impede parents’ accumulating reciprocal support resources and shape intergenerational relationships in the long term. [ABSTRACT FROM AUTHOR]

In 2021 and 2022, inflation expectations of households in the euro area rose dramatically. Based on a time-series investigation from 1995 to 2022, I find that inflation expectations are driven by current price developments of three consumption product categories and house prices (which are not included in the consumer price index). About half of the recent rise was fuelled by energy prices, 20% by food prices, over 10% by transportation costs and almost 20% by house prices. On a macro-level, controlling for a standard set of spending determinants, a regression analysis suggests that accelerating inflation expectations in general will slow down growth of area wide real private consumption, but under circumstances of low nominal interest rates helped to cushion the negative shock of the covid pandemic and the energy crisis. [ABSTRACT FROM AUTHOR]

Evaluating the balance between a city’s physical and socioeconomic environmental development is crucial for creating sustainable and livable urban spaces. Although they might appear contradictory, they jointly support the comprehensive sustainable urban development strategy. Traditional methods usually focus on assessing this balance from a specific perspective, such as how neighborhood greenery shapes real estate value. Yet, they fail to deliver a holistic balance assessment in developing the physical and socioeconomic dimensions. To fill this gap, this study introduces a research framework that measures this balance through house prices based on transferred bias. Using house price as an indicator shaped by both physical and socioeconomic environments, the framework first constructs a series of deep learning models to estimate house prices through street view images for each city. These models capture the relationship between neighborhood appearance and house price. Second, by leveraging transfer inference, we introduce neighborhood appearance from one city into the model trained from another city. This process identifies the transferred bias, which is the disparity between inaccurate inference resulting from a mismatched neighborhood appearance and the trained model. Through transferred bias, we can quantify the differences in physical and socioeconomic environments across cities and evaluate the urban balances of these two environments. The results show that the transferred bias effectively quantifies the disparities among cities in physical and socioeconomic environments, thereby facilitating further investigation into the urban balance between these two environments. [ABSTRACT FROM AUTHOR]

Prior work suggests when instrumental goals are salient, linguistic complexity associates with positive behavioral outcomes compared to linguistic simplicity. The current work tested this idea using descriptions from over 1,000 online realty advertisements to associate with housing prices. The evidence suggested linguistic complexity (e.g., fewer common words, more analytic writing, and less readable writing) indeed associated with higher housing prices. These data explicated the contingent-on-effort hypothesis : linguistic complexity is favored when people value effort in a particular setting. [ABSTRACT FROM AUTHOR]

The UK's city centre apartment markets have been affected by the coronavirus pandemic and a building safety crisis in ways not experienced by its suburban and rural housing markets. Sellers and estate agents have encountered falling demand and prices, elevated safety concerns, reluctant lenders and changes in buyers' preferences. Against this backdrop, we investigated the narratives and images used to sell what have sometimes appeared to be 'less sellable' homes. Analysing the textual and visual content of 100 adverts for city centre flats, we explored the possible effects of the pandemic on property advertising, the positioning within adverts of building safety and, noting growing interest in sustainability, the presence of sustainability messages. Findings suggest that the core narratives used to sell city centre flats remain largely unchanged from those deployed to first market the concept of 'city living' to UK buyers in the late 1990s. Messages about building safety and sustainability appear uncommon. The implications of the findings are considered. [ABSTRACT FROM AUTHOR]

Constructing new roads and upgrading existing roads are two common approaches to address congestion caused by increasing traffic volumes. But they can also impact local communities if roads are built through neighborhoods or existing roads and intersections are widened and placed closer to nearby homes. In this paper, we estimate how local communities are impacted by these changes using data on housing prices near roads and roadway construction projects. We find that homes near major roads sell for less than homes further away, but that congestion-reducing road improvements only lead to small average increases in nearby home prices. Our results suggest that major roads in close proximity negatively impact housing prices by affecting neighborhood aesthetics, and this relationship is not contingent upon the level of traffic on the roads. Our results can help policymakers consider the external costs borne by local communities when conducting cost–benefit analyses of roadway expansions or improvements. • Homes near roadways face price penalty, regardless of traffic on the roadway. • Roadway construction increases home prices only slightly. • Co-located amenities likely mute effect of traffic on home prices. [ABSTRACT FROM AUTHOR]

This article identifies the shortage of affordable, secure housing as a key driver of political alienation, particularly among young people. The social consequences of this trend for this group include, but are not limited to, delayed independent living and family formation, declining mental health and diminishing belief in their ability to match the living standards of their parents. Increasingly vulnerable and insecure, many young people now link the issue of housing with inward migration. Left unresolved, this issue will further polarise (and radicalise) the political choices of younger generations in the years ahead. In response, this article proposes three immediate actions. First, a dramatic expansion of construction for all types of housing where excess demand exists. Second, the use of public money to ensure that housing options exist for people of all ages, social classes and income levels. Public money should not be utilised for schemes which ultimately inflate house prices further. Third, to tackle widening intergenerational inequalities, existing housing wealth must be taxed fairly. [ABSTRACT FROM AUTHOR]

A machine learning technique merging Bayesian method called Bayesian Additive Regression Trees (BART) provides a nonparametric Bayesian approach that further needs improved forecasting accuracy in the presence of outliers, especially when dealing with potential nonlinear relationships and complex interactions among the response and explanatory variables, which poses a major challenge in forecasting. This study proposes an adaptive trimmed regression method using BART, dubbed BART(Atr) to improve forecasting accuracy by identifying suspected outliers effectively and removing these outliers in the analysis. Through extensive simulations across various scenarios, the effectiveness of BART(Atr) is evaluated against three alternative methods: default BART, robust linear modeling with Huber's loss function, and data-driven robust regression with Huber's loss function. The simulation results consistently show BART(Atr) outperforming the other three methods. To demonstrate its practical application, BART(Atr) is applied to the well-known Boston Housing Price dataset, a standard regression analysis example. Furthermore, random attack templates are introduced on the dataset to assess BART(Atr)'s performance under such conditions. [ABSTRACT FROM AUTHOR]

Urban parks, a core component of urban landscapes, play a crucial role in mitigating the negative effects of rapid urbanization and achieving sustainable urban development. In densely populated urban environments, providing urban parks fairly and efficiently, taking social preferences into account, is an important challenge. In this regard, we take Hangzhou, China, as an example and use a hedonic pricing model with a difference-in-differences estimator to test the effect of different types of urban parks on housing prices, quantify their respective economic values, and reflect homebuyers' preferences. The findings indicate that the construction of new urban parks leads to an overall increase in the value of the surrounding real estate to some extent. Specifically, the construction of comprehensive parks and large parks significantly enhances the value of nearby housing, while proximity to new medium-sized parks also results in a housing price premium, albeit to a lesser extent. In contrast, community parks and specialized parks have a less significant impact on housing prices. These findings provide valuable insights for equitable urban development and planning, optimizing the allocation of urban parks and determining investment priorities for different types of parks to enhance the sustainability of the urban environment and human well-being. [ABSTRACT FROM AUTHOR]

While newly built urban green spaces aim to address environmental concerns, the resulting green gentrification and social inequality caused by escalating property values have become critical topics of urban socio-spatial research. To prevent green initiatives from becoming unaffordable for their intended beneficiaries in rapidly urbanizing cities, it is essential to examine the spatial and temporal relationships between the construction of new green spaces and rising housing prices. This study employs a difference-in-differences methodology to analyze regional disparities, impact periodicity, and the influence of park size on housing prices, using Nanjing, China as a case study. This result reveals that the introduction of new-built parks in Nanjing significantly impacts housing prices within an 800 m radius. The premium effect of these parks is substantially higher in urban core areas compared to suburban locales, demonstrating spatial differentials. Suburban parks temporally exhibit a prolonged lag and a shorter premium impact duration. Moreover, among various park areas, medium-sized parks demonstrate the most pronounced leverage effect, approximately double that of large parks, while small parks do not significantly affect housing prices. To mitigate the exacerbation of premium effects and enhance social justice in green strategies, we advocate prioritizing the development of small parks, particularly in urban core areas, and leveraging the temporal delay in new-built park impacts for urban policy interventions. [ABSTRACT FROM AUTHOR]

The relationship between residential patterns and socioeconomic statuses highlights the complex interactions between the economic regime, welfare system, and neighborhood effects, which are crucial in urban inequality studies. With the diversification of the housing demand and supply system, the traditional analysis conducted separately from the ethnic or spatial segregation perspective fails to capture the rising inequalities and changing socio-spatial context. Taking Nanjing as an example, based on a multi-source database including the housing price, residential environmental quality, surrounding support facilities, and mobile phone user portrait data, this paper proposed a modified method for discovering the coupling relationship between residential patterns and socioeconomic statuses. It is found that socioeconomic status contributes to residential spatial aggregation and that the relationship between social and spatial dimensions of residential differentiation is tightly coupled and related. The lower socioeconomic strata were displaced to the periphery and the older urban core, while affluent inhabitants were more likely to settle voluntarily in segregated enclaves to isolate themselves from the general population through more flexible housing options. The heterogeneity of the urban socioeconomic dimension is primarily affected by consumption and occupational status, while housing prices mainly determine the divergence of spatial distribution. [ABSTRACT FROM AUTHOR]

The article "UK forecast in detail" from the Economic Outlook journal discusses the current fiscal policy, monetary policy, prices, wages, activity, consumer demand, housing market, company sector, labor market, trade, and sectoral balances in the UK. It highlights the challenges faced by the government in managing borrowing, spending, and investment, as well as the impact of factors like inflation, interest rates, and consumer behavior on the economy. The article provides forecasts and analysis based on data from Oxford Economics, offering insights into the economic outlook for the UK in the coming years. [Extracted from the article]

The impact of house prices rising on urban labor costs has typical heterogeneity and lag effects, but there is little literature on it. Based on the panel data of 283 prefecture level cities from 2001 to 2017, we constructed panel model considering lag effect and threshold effect. The results show that lag one period of housing price has significant positive impact on urban labor costs, with the increase of housing prices, the effect of pushing up the current labor costs is gradually increasing. So, this impact has obvious lag effect and threshold effect. Through grouped regression to test heterogeneity effect, at the regional level, the heterogeneity of the impact is more significant. The more developed the economy is, the greater the pushing effect of house prices on labor costs. [ABSTRACT FROM AUTHOR]

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