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Introduction Various dimensions of housing heterogeneity have gained relative popularity in recent years. The most essential aspect of housing heterogeneity is a set of differences including technical, governance, socio-economic, and ecological differences of each residential unit. The origin of these distinctions is an objective matter that is regarded as an essential aspect of the research framework, but is frequently overlooked in managerial decision-making. In the scientific community, the social, technical, and economic dimensions have received the most attention, whereas the role of the behavioral characteristics of investors in housing prices has received scant attention. Focusing on the aspects of behavioral economics theory, the present study analyzes the heterogeneity of the behavior of housing investors, as well as the internal and external factors influencing housing prices and their effects on inflation in Iran from 2011 to 2020. Methodology The primary objective of this article is to evaluate the effects of heterogeneous behavior of housing market investors on housing prices and the effects of heterogeneous behavior of housing market investors on inflation via housing prices. The following equation is used to determine the price of a house: POH=f1(A1. A2.A3) (1) In Equation 1, POH represents the expense of housing, A1 is a vector of exogenous factors influencing housing prices, A2 is a vector of exogenous factors influencing housing prices, and A3 is a vector of investor behavioral variables in the housing sector. Overoptimism and herding effect are considered to be two behavioral variables of housing sector investors: HBHt=1Tt=1T|et-em| (2) OCHt=QtSt (3) In equation 2, HBHt represents the herding effect of investors in housing sector, et represents the housing return at time t, and em represents the average return of housing market. In equation 3, OCHt represents overoptimism, Qt represents the number of building permits issued, and St represents the quantity of residential unit investment. Inflation is also viewed as a function of housing prices and other macroeconomic factors according to the equation below: INFR=f2(POH.B) (4) In equation 5, INFR represents inflation rate and B is a vector of independent variables influencing inflation. Findings During the period 2011-2020, land price, population growth rate, liquidity, and herding effect had a positive significant effect on housing prices in Iran, according to estimates. Conversely, the number of residential units constructed and the exchange rate has had a negative significant impact on housing prices in Iran; while, the variables of interest rate, per capita income growth rate, and overoptimism had nonsignificant effect on housing prices. Regarding the factors influencing inflation, the data also indicates that the housing price, exchange rate, and liquidity had a positive significant effect on Iran’s inflation rate between 2011 and 2020. In contrast, population growth and per capita income growth had a significant negative impact on inflation; while the interest rate had a negative but nonsignificant impact on Iran’s inflation rate over the period under review. Due to the nonsignificance of the effect of overoptimism on housing prices in the seemingly unrelated regression (SUR) model, it can be concluded that housing prices do not mediate the effect of overoptimism on inflation. Due to the significance of herding effect on housing prices, however, the mediating effect of housing prices and herding effect on inflation is confirmed. Discussion and Conclusion In this article, SUR was used to analyze the effects of behavioral and non-behavioral factors on housing prices and inflation in Iran from 2011 to 2020. The following results were obtained: • An increase of 1% in internal factors affecting housing prices, such as land prices, the number of completed construction units, population growth rate, and per capita income, have resulted in respective increases of 1.19, -1.36, 0.59, and -0.015 in the Iranian housing costs. • An increase of 1% in the behavioral factor of herding effect has resulted in a change of 0.77% in housing prices in Iran. • A 1% increase in housing prices, currency prices, and liquidity has resulted in an inflation rate increase of 0.18%, 0.92%, and 0.17% in Iran, respectively. A 1% increase in the population growth rate and the per capita income growth rate has caused a decrease of 1.53% and 0.141% in inflation rate, respectively. Through housing prices, the behavior of investors in the housing sector can indirectly influence the inflation rate. Considering the positive impacts of herding effect on housing prices and housing prices on inflation rate, it can be concluded that herding effect has a positive impact on inflation rate. In accordance with the stated findings, the following policy recommendations are provided to prevent the rise in housing prices and inflation: Considering the positive impact of herding effect on the housing price and, consequently, the inflation rate, it is necessary to take measures to control and reduce emotional and irrational behavior of investors in housing sector. Since the internal factors of land price and population growth rate have a positive effect on the housing price, while the number of completed construction units and per capita income have a negative effect on the housing price, it is recommended that government provide unused governmental lands and remove obstacles to complete half-finished buildings that have been halted for legal reasons, and assist in supplying more housing to reduce its price. In addition, government should help control housing demand and reduce demand pressure by adopting population control policies and establishing suitable working, health, and educational conditions for the villagers, to diminish immigration level.

This paper introduces a special issue of Housing, Theory and Society entitled "Behavioural biases in the housing market". First, we provide a brief overview of theoretical considerations and empirical research applying the behavioural economics approach to housing market studies. Second, we summarize the topics of the papers included in the special issue and, finally, point out directions for future analyses involving behavioural economics and the housing market. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to analyze the effect of the heterogeneous behavior of investors in the housing sector on housing prices and subsequently on Iran's economic growth during the period 2001:3 to 2020:3. For this purpose, first, the effect of herding behavior and overconfidence of investors on housing prices and then the effect of housing prices on economic growth was estimated by smooth transition regression (STR) method. Then, by calculating the Sobel statistic, the mediating role of the housing price in the transmission of the behavior of investors in the housing sector on economic growth was tested. The results showed that the housing price and economic growth functions have a threshold and two regimes. The imitative behavior of a previous period is the transition variable of the housing price function with a threshold equal to 0.0051 percent. The housing price is also a variable of economic growth function transfer with a threshold equal to 0.0266 percent The estimated coefficients of the first and second regimes indicate the asymmetric behavior of investors on housing prices. The estimation of the economic growth function showed that housing prices had a negative effect on economic growth in the first and second regimes, but this effect was strengthened in the second regime. The calculation of Sobel's statistic also showed that the housing price had a mediating role in transferring the effect of herding behavior on economic growth, but it did not act as a mediator in transferring the effect of overconfidence on economic growth.

The purpose of this article is to analyze the effect of the heterogeneous behavior of investors in the housing sector on housing prices and inflation in Iran during the period 2001:3 - 2020:3. The threshold effects of behavioral variables on housing prices and the effect of housing prices on inflation using smooth transition regression method (STR) is estimated. Then, using Sobel's statistic. The results of the estimation of house prices show that Herding behavior has a positive effect on housing prices in the first regime and the second regime. Overconfidence in the first regime was ineffective on housing prices, but in the second regime, it had a positive and significant effect. The results of estimating the inflation model also indicated that there are two limit regimes for the inflation function. Housing prices had a positive effect on the inflation rate in the first and second regimes. The calculation of the Sobel statistic also indicates the confirmation of the transmission of the effect of herding behavior on inflation from the housing price channel, while the Sobel test did not confirm the transmission of the effect of overconfidence from the housing price channel on inflation

When a household is disconnected from their electric utility service the consequences can be severe, including accumulation of debt, the inability to maintain comfortable temperatures, and in the most extreme cases, homelessness or mortality. While the survey-based literature on utility disconnections has yielded important findings about which households are most likely to experience a utility shutoff, only a few existing studies have used data from utility companies themselves. In this analysis, we utilize zip-code level data from four of California's largest utility providers to measure sociodemographic disparities in disconnections, in addition to the impact of adverse weather. We find that zip codes with a higher share of vulnerable households, especially Black and Hispanic households and households with young children, face a higher number and rate of utility disconnections, even after controlling for an extensive set of factors that are commonly thought to explain higher rates of energy insecurity, including income, housing characteristics, and energy costs. Our analysis also suggests that sociodemographic and weather disparities in disconnections differ between utility types. We conclude by discussing the implications of the findings for research and policy, including the impact of regulation, utility provider practices, and more extreme weather driven by climate change., (© 2024. The Author(s).)

In recent decades, economic activity has become increasingly concentrated in major global metropolises. Yet, the rise of working from home threatens this dominance of cities. Using multiple high-frequency datasets on spending, commuting, migration, and housing, we provide global evidence that remote work has dispersed economic activity away from city centers. We label this the "Donut Effect," which is much larger and more persistent in cities with high levels of remote work. Using detailed household microdata from the United States, we show that three-fifths of households that left city centers in big cities moved to the suburbs of the same city. This is likely explained by the rise of hybrid work, in which employees still commute to the office a few days a week. The enduring popularity of hybrid work into 2024 suggests that the Donut Effect will persist while also leaving broader metropolitan areas intact., Competing Interests: Competing interests statement:The authors declare no competing interest.

Importance: The US Department of Veterans Affairs (VA) partners with community organizations (grantees) across the US to provide temporary financial assistance (TFA) to vulnerable veterans through the Supportive Services for Veteran Families (SSVF) program. The goal of TFA for housing-related expenses is to prevent homelessness or to quickly house those who have become homeless., Objective: To assess the cost-effectiveness of the SSVF program with TFA vs without TFA as an intervention for veterans who are experiencing housing insecurity., Design, Setting, and Participants: This study used a Markov simulation model to compare cost and housing outcomes in a hypothetical cohort of veterans enrolled in the SSVF program. Enrollees who are homeless receive rapid rehousing services, while those who are at risk of becoming homeless receive homelessness prevention services., Exposure: The SSVF program with TFA for veterans who are experiencing housing insecurity., Main Outcomes and Measures: The effectiveness measure was the incremental cost-effectiveness ratio (ICER) with quality-adjusted life-years (QALYs). The model was parameterized using a combination of inputs taken from published literature and internal VA data. The model had a 2-year time horizon and a 1-day cycle length. In addition, probabilistic sensitivity analyses were conducted using 10 000 Monte Carlo simulations., Results: The base case analyses found that the SSVF program with TFA was more costly ($35 814 vs $32 562) and yielded more QALYs (1.541 vs 1.398) than the SSVF program without TFA. The resulting ICER was $22 676 per QALY, indicating that TFA is the preferred strategy at a willingness-to-pay threshold of $150 000 per QALY. This ICER was $19 114 per QALY for veterans in the rapid rehousing component of the SSVF program and $29 751 per QALY for those in the homelessness prevention component of the SSVF program. At a willingness-to-pay threshold of $150 000 per QALY, probabilistic sensitivity analyses showed that TFA was cost-effective in 8972 of the 10 000 Monte Carlo simulations (89.7%) for rapid rehousing and in 8796 of the 10 000 Monte Carlo simulations (88.0%) for homelessness prevention only., Conclusions and Relevance: This economic evaluation suggests that TFA is a cost-effective approach (ie, yields improved health benefits at a reasonable cost) for addressing housing insecurity for veterans enrolling in the SSVF program. Future research could examine the cost effectiveness of large, nationwide housing interventions such as this one among subpopulations of veterans such as those with certain comorbidities including severe mental illness or substance use disorders, those with chronic diseases, or those experiencing long-term housing instability vs acute loss of housing.

Background: Mothers experiencing homelessness and caring for young children struggle with high rates of substance use and mental health problems. A comprehensive supportive housing intervention was implemented to assist young mothers experiencing substance use disorder (SUD) and homelessness. The cost-effectiveness of this intensive intervention could inform future dissemination., Methods: A cost-effectiveness analysis was conducted alongside a randomized controlled trial that lasted from May 2015 to October 2018. Mothers experiencing homelessness between the ages of 18-24 years with a SUD were randomly assigned to housing+support services (HOU + SS) (n = 80), housing-only (HOU) (n = 80), or services as usual SAU (n = 80). Using incremental cost-effectiveness ratios (ICERs), the study compared the costs of HOU + SS and HOU to SAU for three outcomes: housing stability (percent days of stable housing), substance use (percent days of substance use), and depressive symptoms (Beck Depression Inventory score). Direct intervention costs of HOU + SS and HOU from both payor and societal perspectives were estimated. Cost data were collected from detailed study financial records. Outcomes were taken from 6-month assessments., Results: The average societal cost of HOU + SS per participant was $5114 [CI 95 %, $4949-5278], while the average societal cost of HOU was $3248 [CI 95 %, $ 3,140-$3341] (2019 U.S. dollars). The calculated ICERs show that HOU was more cost-effective than HOU + SS and SAU for housing outcome. For illicit drug use, HOU + SS was more cost-effective than HOU. Finally, for depressive symptoms, neither HOU + SS or HOU were more cost effective than SAU., Conclusion: While HOU is more cost-effective for increasing housing, HOU + SS is more cost-effective for reducing illicit drug use. However, housing without improvements in substance use may not be sustainable, and supportive services are likely essential for improved well-being overall beyond the housing outcome alone., Competing Interests: Declaration of competing interest The authors declare that they have no competing interests., (Copyright © 2024 Elsevier Inc. All rights reserved.)

What kind of impact does the government's housing support expenditure have on residents' consumption? This is a topic that deserves in-depth study and is of practical significance. This study constructs provincial equilibrium panel data based on China's guaranteed housing construction and financial expenditures on housing support data from 1999-2009 and 2000-2021. It applies the systematic GMM method to estimate the impact of government housing support expenditures on residents' consumption. The study found that whatever form of expenditure on housing support contributed to the total consumption of urban residents, while the impact on the consumption structure had different results. Based on the divisions of consumption structure, the results of the increase in government housing support expenditure on the consumption structure of urban residents are different. An examination of different forms of housing support reveals that the predominantly secure form of housing construction has a positive effect on all consumption structure divisions. Whereas the predominantly monetary subsidy form has a significant positive relationship with housing, necessity, and durability consumption expenditures, it has a weak or even negative relationship with non-housing, non-necessity, and non-durability consumption expenditures. The research in this paper makes up for the lack of current literature examining the economic effects of housing support from the perspective of consumption structure and provides a theoretical basis and policy reference for constructing a multi-level gradient housing support system., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Shang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

This paper examines the influence of housing wealth on fertility outcomes through a regression discontinuity design based on a 2006 Chinese housing-market policy. Our analysis reveals that the positive impact of this policy on housing wealth significantly enhances the likelihood of fertility by 7.3 %. Our result implies that a 1 % increase in housing wealth can raise the fertility rate by 0.18 %. Furthermore, we observe that children born subsequent to the positive housing wealth shock exhibit improved health, not only at birth but also over the long term. Lastly, we present suggestive evidence suggesting that both parental pre-birth time allocation and parental health may help explain the documented positive effects of housing wealth on fertility rates., (Copyright © 2024 Elsevier B.V. All rights reserved.)

In this brief article, we reflect on the contribution of Martin Lux and Petr Sunega to the role of sociology in the domain of housing economics. Applauding the attempt at injecting a more sociologically informed housing economics, we draw attention to the continuous need to guard against over-abstraction and to ensure that housing's role as a major source of material inequality in many societies must be fully recognized. [ABSTRACT FROM AUTHOR]

This commentary examines the concept of "pragmatic socio-economics" and argues that it is unlikely to offer a major breakthrough in the search for a holistic approach to the study of housing. Although the authors outline the serious barriers to the integration of sociological insights into neo-classical economics, they seek to avoid these through the adoption of concepts, such as that of social norms, that could be acceptable to economists. The result does not challenge some of the fundamental assumptions of neo-classical economics that need to be amended if meaningful integration with sociology is to be achieved. [ABSTRACT FROM AUTHOR]

Young people who transition to adulthood from out-of-home care (OOHC) are more likely to experience a range of poorer outcomes relative to their same-age peers in the community. This systematic review assessed the effectiveness of policies or interventions (hereafter "interventions") aimed at improving housing, health, education, economic, and psychosocial outcomes for youth leaving OOHC (hereafter "care leavers"). Eleven databases of published literature were reviewed along with gray literature. Eligible studies used randomized or quasi-experimental designs and assessed interventions that provided support to care leavers prior to, during, or after they left OOHC. Primary outcomes were housing and homelessness, health and well-being, education, economic and employment, criminal and delinquent behavior, and risky behavior, while secondary outcomes were supportive relationships and life skills. Where possible, results were pooled in a meta-analysis. Certainty of evidence was assessed using Grading of Recommendations Assessment, Development and Evaluation. Fourteen studies published in 27 reports were identified that examined independent living programs (ILPs) ( n  = 5), intensive support services ( n  = 2), coaching and peer support (C&PSP) ( n  = 2), transitional housing ( n  = 1), health information or coaching ( n  = 2), and extended care ( n  = 2). All but one study was conducted in the United States. Twenty small meta-analyses were undertaken encompassing ILPs and C&PSP, with two showing results that favored the intervention with certainty. The level of confidence in each meta-analysis was considered very low. A significant risk of bias was identified in each of the included studies. While some interventions showed promise, particularly extended care, the scope and strength of included evidence is insufficient to recommend any included approach., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: In their capacity as funders What Works for Children’s Social Care (WWCSC) reviewed and provided comment on a draft protocol and version of the review published as a technical report, for which they also facilitated an independent peer review process with anonymous reviewers. The views expressed in this report are the views of the authors and do not necessarily reflect those of WWCSC.David Taylor and Aron Shlonsky were authors of a study that was included in this review. Their conflict of interest was minimized by (a) ensuring that they were not part of decisions to include the study in the review, (b) they did not extract data for this study, and c) other team members undertook a ROB assessment. All other authors—Bianca Albers, Georgina Mann, Jane Lewis, Russell Taylor, Philip Mendes, and Geraldine Macdonald—declare that they have no conflicts of interest.

Background: Most individuals with severe mental illness (SMI) strongly prefer independent living over living in an institution. Independent Supported Housing (ISH) provides housing rehabilitation for persons with SMI in their accommodations. However, most individuals who need housing rehabilitation live in institutional housing settings (housing rehabilitation as usual: HAU). We investigated which housing rehabilitation setting is effective on which variable in the long term to support service users to form an informed preference for either housing rehabilitation setting., Methods: We conducted a two-year longitudinal observational non-inferiority study to test the effectiveness of ISH in improving participants' social inclusion, quality of life, emotional social support, capabilities, symptom severity, functioning, service utilisation and costs. Participants were assessed at baseline and after six, twelve, and 24 months. Mixed effects models were computed to test between-group and within-group effects., Results: The study included 83 participants in ISH (n = 31) and HAU (n = 52) housing rehabilitation settings with a mean age of 36.2 years. Most participants were male (64%) and had a primary psychotic or schizophrenic (35%) or an affective diagnosis (24%). During the study, ISH participants significantly improved their quality of life (β = 0.54; 95% CI: 0.26 to 0.82), symptoms (β = -0.32; 95% CI: -0.60 to -0.03), and capabilities (β = 4.46; 95% CI: 0.14 to 8.77) and decreased psychiatric hospitalisations (p = 0.04). HAU participants improved their quality of life (β = 0.40; 95% CI: 0.12 to 0.69). Housing and rehabilitation support costs were almost half with ISH than with HAU., Conclusion: ISH has been shown to be much less expensive than HAU and was associated with several improvements like reduced psychiatric hospitalisations and improved quality of life. Therefore, our findings strongly argue for a preference-driven provision of housing rehabilitation services and to end the institutionalisation of persons with SMI., Trial Registration: The study was registered on December 04, 2018, at ClinicalTrials.gov (NCT03815604)., (© 2024. The Author(s).)

Background: Exposure to cold temperatures is known to be associated with deterioration of physical and mental health as well as poorer well-being in many countries. The Winter Fuel Payment, an unconditional direct cash transfer of value between £250-£300, was designed to help older people in England cover heating costs during the winter months, to counteract the particular vulnerability of older people to the effects of cold weather., Aims: We evaluated the impact of the Winter Fuel Payment scheme on subsequent prevalence of care needs such as being unable to eat or shower independently, quality of life and the likelihood of having cold-related housing conditions. We also explored the potential effects of the Winter Fuel Payment across different sub-samples (poorer/richer individuals, those living in newer/older properties, and in the North/South of England) to explore whether its benefits (if any) are spread equally across the eligible population., Data and Methods: We used a regression discontinuity design approach with age as running variable to analyse seven waves of a nationally representative sample, the English Longitudinal Study of Ageing, covering the period 2002/2003 to 2016/2017, and consisting of 24,651 observations., Results: The Winter Fuel Payment had no overall effect on the outcomes of interest (care needs, quality of life, and cold-related housing problems). However, the Payment increased quality of life for poorer individuals, for those living in Northern regions of England, and for those living in newer dwellings. The likelihood of living in a property with at least one cold-related housing problem also decreased for those living in newer properties., Conclusions: Findings from this research provide important insights into the effectiveness of a winter cash transfer among the older population in England, and they are potentially relevant for other nations looking for strategies to deal with cold seasons and poorly insulated homes. In particular, this evaluation contributes to the 'universality versus targeting' policy debate and has implications for the development of energy-efficient policies., Competing Interests: Declaration of competing interest We have no conflicts of interest to disclose., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Access to safe and stable housing is important for child and adult well-being. Yet many low-income households face severe challenges in maintaining stable housing. In this article, we examine the impact of the 2021 temporary expansion to the Child Tax Credit (CTC) on housing affordability and the living arrangements of families with low incomes. We employ a parameterized difference-in-differences method and leverage national data from a sample of parents who are receiving or recently received Supplemental Nutrition Assistance Program benefits (N = ∼20,500), many of whom became newly eligible for the CTC. We find that the monthly CTC reduced parents' past-due rent/mortgages (both amounts and incidence) and their reports of potential moves due to difficulties affording rent/mortgages. The CTC increased the likelihood that parents reported a change in their living arrangements and reduced their household size, both effects driven by fewer mothers living with a partner (and not a reduction in doubling up). We find some differences in effects by race and ethnicity and earnings. Our findings illustrate that the monthly credit improved low-income parents' ability to afford housing, gain residential independence from partners, and reduce the number of people residing in their household., (Copyright © 2024 The Authors.)

Background: Housing is considered a social determinant of health. In Catalonia and Spain, ensuring affordable housing is challenging and cooperative housing under a grant-of-use emerges as an alternative, challenging traditional housing models. This study aims to quantify its impact on health before and after moving to the cooperative house., Methods: A longitudinal study of individuals in cooperative housing projects in Catalonia (July 2018-April 2023) was conducted. Data, including sociodemographic, housing information, and health-related details, were collected through baseline and follow-up surveys., Results: Seventy participants (42 women, 28 men) showed positive changes in housing conditions during follow-up. Improved perceptions of health, mental health, and social support were observed. Despite limitations in sample size and short follow-up, initial findings suggest improvements in health., Conclusions: Cooperative housing under a grant-of-use in Catalonia appears promising for improving health and living conditions. Further research is warranted to explore its full potential as an alternative amid housing challenges in the region., (© 2024. The Author(s).)

Millions of families with children in the U.S. struggle to afford adequate housing. Housing cost burden places families at risk for homelessness, and prevention efforts are hindered by limited understanding of insecure housing experiences at the margins. The present study investigated variation in housing insecurity experiences in a sample of mothers, as well as which risk profiles were most strongly associated with subsequent homelessness. Latent class analysis identified four distinct subgroups of housing insecurity: "Stable," "Unstable," "Rent-Focused," and "Strategic Bill-Paying." Classes differed on whether they made rent or utility payments on time, experienced utility shutoffs, or were evicted. Mothers who missed rent payments were significantly more likely to experience subsequent homelessness, whereas those who prioritized rent were more likely to have their utilities shut off but remain housed. Policy efforts should emphasize increased wages, rent control, changes to zoning laws and tax codes to prioritize affordable housing, and benefits that help mothers maintain their incomes such as comprehensive healthcare, paid maternity leave, and subsidized childcare., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Marçal, Barr. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The low-carbon transformation is a broad and profound systemic change that will inevitably impact many areas of the urban environment, economy, and social system. We evaluated the impact of China's ongoing "low-carbon pilot policy" on urban housing prices as a "quasi-natural experiment." Existing research findings and hedonic theory predictions suggest that the low-carbon city pilot (LCCP) policy is increasing urban housing prices through air quality improvements. However, this study contradicts these speculations based on the situation in China. This study employed the analytical framework of staggered difference-in-differences (DID), which revealed that the LCCP policy had generally reduced housing prices; the implementation of the policy had led to an average decrease of 6.2% in housing prices in pilot cities, compared to non-pilot cities. The LCCP policy affected housing prices by influencing both the "demand side" and "supply side" of housing. In terms of the demand side, the policy significantly reduced the level of urban air pollution but did not impact housing prices. Instead, it negatively affected housing prices by lowering labor wages. In terms of the supply side, housing prices were negatively affected, mainly by increasing the cost of emission reduction of real estate enterprises, which impacted the original longstanding housing production process. Additionally, there were significant differences in the impact of the LCCP policy on housing prices in cities across different geographical locations and different tiers of cities. This study suggests important policy insights for achieving stable market housing prices and promoting high-quality urban development in the process of low-carbon transformation., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Competing Interests: The authors declare no conflict of interest.

Background: Housing insecurity is an escalating problem in the UK but there is limited evidence about its health impacts. Using nationally representative panel data and causally focussed methods, we examined the effect of insecure housing on mental health, sleep and blood pressure, during a period of government austerity., Methods: We used longitudinal survey data (2009-2019, n = 11,164 individuals with annual data) from the UK Household Longitudinal Study. Outcomes were probable common mental disorder (GHQ-12), sleep disturbance due to worry, and new diagnoses of hypertension. The primary exposure was housing payment problems in the past year. Using doubly robust marginal structural models with inverse probability of treatment weights, we estimated absolute and relative health effects of housing payment problems, and population attributable fractions. In stratified analyses we assessed potentially heterogeneous impacts across the population, and potential modifying effects of government austerity measures. A negative control analysis was conducted to detect bias due to unmeasured confounding., Results: Housing payment problems were associated with a 2.5 percentage point increased risk of experiencing a common mental disorder (95% CI 1.1%, 3.8%) and 2.0% increased risk of sleep disturbance (95% CI 0.7%, 3.3%). Estimates were larger for renters, younger people, less educated, households with children, and people living in areas most affected by austerity-related cuts to housing support services. We did not find consistent evidence for an association with hypertension (risk difference = 0.4%; 95% CI -0.1%, 0.9%). The negative control analysis was not indicative of unmeasured confounding., Conclusions: Housing payment problems were associated with worse mental health and sleep disturbance in a large UK sample. Households at risk of falling into rent or mortgage arrears need more support, especially in areas where housing support services have been diminished. Substantial investment is urgently needed to improve supply of social and affordable housing., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The issue of property evaluation and appraisal has been of high interest for private and public agents involved in the housing industry for the purposes of trade, insurance and tax. This paper aims to investigate how different factors related to the location of a property affect its price over time. The predictive models applied in this research are driven by real estate transactions data of Tehran Metropolitan Area, captured from open data available to the public. The parameters of the functions that describe the behavior of the housing market are estimated through applying different types of statistical models, including ordinary least squares (OLS), geographically weighted regression (GWR) and geographically and temporally weighted regression (GTWR). This suite of models has been run in order to compare their efficiency and accuracy in predicting the variations in housing price. The GTWR model showed significantly better performance than OLS and GWR models, as the goodness of fit index (adjusted R2) improved by 22 percent. Therefore, spatio-temporal non-stationary modelling is significant in the explanation of the variations in housing value and the GTWR coefficients were found more reliable. Three internal factors (size of building; building age; building quality), and eight external factors (topography; land-use mix; population density; distance to city center; distance to subway station; distance to regional parks; distance to highway; distance to airport) influence the property price, either positively or negatively. Moreover, using significant variables that extracted from regression models, the optimum number of housing value clusters is generated using the spatial 'k'luster analysis by tree edge removal (SKATER) method. Five clusters of housing patterns were recognized. The policy implication of this paper is grouping of Metropolitan Tehran housing value data into five clusters with different characteristics. The varying factors influencing housing value in each cluster are different, making this data analysis technique useful for policy-makers in the housing sector. [ABSTRACT FROM AUTHOR]

Since 2001, social housing levels, traditionally a safety net for low-income households, have stagnated in Victoria. To increase social housing levels, the Victorian state government announced a programme to redevelop ageing public housing estates through public–private partnerships. This study compares private sector, community housing sector, and government-led redevelopment models, to determine which provides the best value for money method of redevelopment. Importantly, considering the Victorian government's plans to increase social housing levels post-COVID19, the study found that the government is best placed to deliver social housing, due, in part, to lower borrowing costs and no requirement for making profit. [ABSTRACT FROM AUTHOR]

Housing research is one of the hot topics in many countries. This paper provides a quick review of the housing economics research in the US, Sweden, Latvia, China, Corsica, and Italy published in this special issue. Bao and Shah studied the effects of home-sharing platforms in general and the effects of the US' Airbnb on neighbourhood rent. Wilhelmsson's results showed that interest rates directly affected house prices and indirectly affected bank loans in Sweden. Caudill and Mixon threw light on the relative negotiating power of the buyer and seller as a key element of real estate price models. Čirjevskis presented a real application of "step-by-step" valuation options for real estate development projects as a managerial risk management tool for similar real estate development projects in the EU to make investment decisions during COVID-19 and in the post-COVID-19 era. Pelizza and Schenk-Hoppé used an exponential Ornstein–Uhlenbeck process to model price dynamics provincially and regionally to estimate the liquidation value. [ABSTRACT FROM AUTHOR]

Background: Currently, China is steadily pursuing high-quality development and promoting common prosperity, for which residents' health is a precondition. However, high housing-price-to-income ratios and rent-to-income ratios have already triggered many social problems and have substantially affected people's work and life. It is of practical significance to examine the relationship between housing burden and residents' health., Methods: Combining city-level housing price-to-income ratio data and residents' health data from the China Family Panel Studies, this study employs a binary logit model to investigate the impact and mechanism of housing burden on residents' physical and psychological health., Results: Overall, a 1% increase in the housing-price-to-income ratio leads to a 1.2% decrease in physical health and a 1.9% decrease in psychological health. In terms of different psychological state indicators, a 1% increase in the housing price-to-income ratio leads to a 1.1% increase in depression, 1.1% increase in nervousness, 1.4% increase in relentlessness, 1.4% increase in hopelessness, 1.0% increase in a sense of incapability, and 1.4% increase in meaninglessness. According to mechanistic analyses, a 1% increase in the housing-price-to-income ratio leads to increases of 0.6 and 0.7% in the smoking rate and late sleep rate, respectively, while it leads to a 0.9% decrease in the noon nap rate., Conclusion: A growing housing burden significantly negatively impacts both the physical and psychological health of residents and increases the possibility of negative emotions. Further investigation revealed that the housing burden damages residents' health by increasing their likelihood of smoking and sleeping late and decreasing their likelihood of taking a nap at noon, while exercise alleviates the negative impacts of the housing burden on residents' physical and psychological health. Finally, we also find that housing burdens' impacts on physical and psychological health differ significantly in terms of gender, age, and educational attainment. From the perspective of improving livelihoods, governments should consider the relationship between housing burdens and residents' health when formulating livelihood policies. Location-specific and targeted policies should be followed. Additionally, efforts should be made to promote exercise among citizens., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Guo, Zhong, Li and Luo.)

This study addresses the satisfaction of housing-related needs in single-person households across European countries. The primary objective is to assess the housing satisfaction of single-person households in European countries, specifically within the Visegrad Group. The study seeks to identify trends in housing conditions, create a ranking of countries based on these conditions, and categorize countries with similar levels of unmet housing needs. The study employs statistical measures and methods to achieve its objectives. Time series are constructed for European countries, and linear trends are analyzed to identify statistically significant changes in selected housing aspects from 2005 to 2022. Various research tasks, including ranking countries and grouping them based on housing conditions, are accomplished using established methods like linear ranking and Ward's cluster analysis. Key findings include significant variations in financial burdens related to housing costs, thermal comfort, environmental pollution, and safety issues across European countries. The study reveals both improvements and challenges in housing conditions from 2005 to 2022 in one-person households. For instance, financial stress due to housing costs decreased in some countries, while thermal comfort issues improved in several nations. The results also highlight the heterogeneity within the Visegrad Group. The study concludes that there is a need for targeted actions to address housing-related issues in single-person households. The findings underscore the importance of investments in building energy efficiency, initiatives for affordable housing construction, and environmental policies. The research emphasizes the impact of housing conditions on health, well-being, and overall community life, urging policymakers to consider these factors for holistic improvement in the housing sector., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Marlena Piekut. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Unaffordable housing has been associated with poor health. We investigated the relationship between severe housing cost burden and premature cancer mortality (death before 65 years of age) overall and by Medicaid expansion status. County-level severe housing cost burden was measured by the percentage of households that spend 50% or more of their income on housing. States were classified on the basis of Medicaid expansion status (expanded, late-expanded, nonexpanded). Mortality-adjusted rate ratios were estimated by cancer type across severe housing cost burden quintiles. Compared with the lowest quintile of severe housing cost burden, counties in the highest quintile had a 5% greater cancer mortality rate (mortality-adjusted rate ratio = 1.05, 95% confidence interval = 1.01 to 1.08). Within each severe housing cost burden quintile, cancer mortality rates were greater in states that did not expand Medicaid, though this association was significant only in the fourth quintile (mortality-adjusted rate ratio = 1.08, 95% confidence interval = 1.03 to 1.13). Our findings demonstrate that counties with greater severe housing cost burden had higher premature cancer death rates, and rates are potentially greater in non-Medicaid-expanded states than Medicaid-expanded states., (Published by Oxford University Press 2024.)

With the rapid progress of urbanization in China, the real estate industry, characterized by a long industrial chain, has become a pillar industry for economic development. Therefore, we inspect the nexus between land finance, housing prices, and economic growth. For this purpose, we use the panel data of 277 cities at the prefecture level or above in China from 2011 to 2019, and empirically examine it by using the Panel Vector Auto Regression (PVAR) model. The results show that there is a causal relationship between housing prices and economic growth. Housing prices promote economic growth in the short term and inhibit it in the long term. Both economic growth and housing prices have a significant impact on land finance. The economic growth show a significantly positive impact, while housing prices promote land finance in the short term with a long-term trend from positive to negative. This is the first study that tries to probe the relationship between urban housing prices, land finance, and economic growth by considering 277 prefecture-level and above cities in China. To promote the stable development of the regional economy, local governments need to overcome their dependence on the housing market and land finance and promote the healthy development of the housing market., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Sun et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Rising housing prices are becoming a top public health priority and are an emerging concern for policy makers and community leaders. This report reviews and synthesizes evidence examining the association between changes in housing price and health outcomes., Methods: We conducted a systematic literature review by searching the SCOPUS and PubMed databases for keywords related to housing price and health. Articles were screened by two reviewers for eligibility, which restricted inclusion to original research articles measuring changes in housing prices and health outcomes, published prior to June 31st, 2022., Results: Among 23 eligible studies, we found that changes in housing prices were heterogeneously associated with physical and mental health outcomes, with multiple mechanisms contributing to both positive and negative health outcomes. Income-level and home-ownership status were identified as key moderators, with lower-income individuals and renters experience negative health consequences from rising housing prices. This may have resulted from increased stress and financial strain among these groups. Meanwhile, the economic benefits of rising housing prices were seen to support health for higher-income individuals and homeowners - potentially due to increased wealth or perception of wealth., Conclusions: Based on the associations identified in this review, it appears that potential gains to health associated with rising housing prices are inequitably distributed. Housing policies should consider the health inequities born by renters and low-income individuals. Further research should explore mechanisms and interventions to reduce uneven economic impacts on health., (© 2024. The Author(s).)

A widely used approach to valuing transport infrastructure is to look at its effects on housing prices, in treated vs control regions, before and after it is built. But anticipation effects mean that housing prices may start changing as soon as a project is announced. This creates complications for an analysis of the capitalization effects on prices. A long span of data is potentially required—because the time from a project's announcement to completion may be many years—and the assumption of common price trends between the treated and control regions must be maintained over this time span. An alternative approach is to use rents. This may be advantageous as rents are more directly related to the infrastructure's service-flow. Though account needs to be taken of the fact that those homes which are rented are often not representative of the housing stock as a whole. We investigate these issues for a new train line in Sydney and contrast the results from using both prices and rents. [ABSTRACT FROM AUTHOR]

This paper investigates the relationship between different forms of migration, perceptions of housing availability and production of new housing stock in Sweden. This is done using survey data on housing availability on the municipal level, dating from 2005 to 2015. Primary findings show that on the national scale, as well as in rural areas and smaller urban areas, internal migrants have stronger impacts on housing availability than foreign‐born migrants. However, when breaking down foreign‐born migrants into smaller groups, it is found that refugees have strong impacts on housing availability, too. Furthermore, evidence of overall and refugee migration having an indirect influence on the production of new housing stock is also found. [ABSTRACT FROM AUTHOR]

As housing prices in China continue to escalate and the limitations of the "personal unlimited liability system" for housing loans become more evident, the financial stress on families has significantly increased. This stress not only impacts the physical and mental health of family members but also results in rising health care costs. This paper presents empirical research examining how housing stress influences changes in household health care costs through a panel data analysis. The study is based on the China Family Panel Study (CFPS) database and employs a panel two-way fixed effect model alongside a mediating effect model to examine the impact of housing stress, family income, and health status on health care costs. The findings reveal a significant positive correlation between housing stress and health care costs; specifically, for every 1% point increase in housing stress, health care costs rise by 0.141. Robustness tests and propensity score matching (PSM) further validate these findings, even after addressing endogeneity issues. Mediation effect analysis indicates that for every 1% point increase in housing stress, household disposable income decreases by 1.749, and health status declines by 0.468, thereby increasing household health care costs. Heterogeneity analysis demonstrates that housing stress has a more pronounced impact on health care costs among western, eastern, urban, and rental households. The government should implement various measures, such as promoting a "personal limited liability system" mortgage policy, reducing housing prices, and ensuring equal rights to rent and purchase, to alleviate housing stress, enhance family income, and improve residents' health status. These actions would contribute to the promotion of both the housing market and medical care, supporting the sustainable development of the health care sector and ultimately improving long-term social welfare., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

The Department of Veterans Affairs provides a shallow subsidy (i.e., subsidizing 50% of an individual's rent for two years) to Veterans experiencing housing instability. We sought to describe the characteristics of Veterans who received these subsidies. Methods. We conducted a retrospective cohort study of Veterans between 10/2019-9/2021. We identified Veteran-level characteristics associated with receiving a shallow subsidy using a multivariable two-part regression model. We also conducted qualitative interviews to identify how shallow subsidies are allocated. Results Black race, higher income, more education, and older age were positively associated with receiving a shallow subsidy; previous homelessness, prior VA outpatient cost, and participating in permanent supportive housing were negatively associated with receiving a shallow subsidy. Interviews revealed that income was the most influential determinant of whether to give shallow subsidies. Discussion Our mixed methods findings were consistent, indicating that socioeconomic stability is an important driver of shallow subsidy allocation decisions.

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People's preferences regarding their neighborhood environment can vary depending on their socioeconomic status and the cities where they live. This study aims to discern the relationship between neighborhood environment factors and single-family detached house sales by sale price and by central and noncentral cities. We analyzed sale prices in the Tokyo Metropolitan Area from 2015 to 2020. The neighborhood environment was assessed using flood/sediment risk and neighborhood walkability measured by net residential density, intersection density, and facility density (walking opportunity). Flood and sediment risk is a major concern that restricts the available land and is included as a negative aspect of the neighborhood environment, taking the topographic features into consideration. A comparison of the results showed that the preference for neighborhood walkability varies by socioeconomic status as well as by target cities. For most facility types, the number of walking opportunities within walking distance from houses was found to be positively related to the sale price of single-family detached houses in all quantiles. The relationship of house price with population and intersection density was found to vary depending on the price level, with a negative relationship with the sale price of relatively more expensive houses being exhibited. People who considered buying houses with relatively higher sale prices were found to devalue houses located in flood/sediment-hazardous areas more. However, it was also found that the negative relationship was slightly mitigated in the highest quantile of sale prices for houses in areas with a moderate flood risk (maximum flooding depth: 3-5 m). Plains near rivers with amenities offer high walkability but pose a flood risk, resulting in a trade-off between flood risk and neighborhood walkability. The findings suggest the use of indices representing diverse preferences in accordance with the target socioeconomic status when policymakers assess the neighborhood environment., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Kim et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Existing research demonstrates that mean health care costs incurred by those experiencing homelessness are high. However, high mean health care costs mask the fact that a sizeable number of people experiencing homelessness incur low costs and that very high costs are driven by a minority of the homeless population. This paper examines health care costs estimated from two Australian surveys of those experiencing homelessness undertaken by the authors. It demonstrates three important findings. First, higher health care costs are most strongly associated with diagnosed mental health disorders, followed by long-term physical health conditions. Second, having a current drug or alcohol dependency, but no diagnosed mental health disorder or long-term physical health issue, is not associated with higher level health care costs. Finally, higher health care costs are incurred by those with long periods of rough sleeping. The findings of this research provide a significant economic argument for government intervention to break the cycle of homelessness as they reveal significant potential savings to effective interventions for homeless people with diagnosed mental health disorders and longterm rough sleeping. [ABSTRACT FROM AUTHOR]

Background: People using opioids alone in private settings are at elevated risk of dying in the event of an overdose. In San Francisco, single room occupancy (SRO) tenants are 19 times more likely to die of overdose than non-SRO residents. The "SRO Project" pilot aimed to reduce fatal overdoses in SROs by recruiting and training tenants to distribute naloxone and provide overdose education in their buildings. We explore the implementation and program impacts of the SRO Project pilot in two permanent supportive housing SROs., Methods: We conducted eight months of ethnographic fieldwork (May 2021 - Feb 2022), including 35 days observing SRO Project pilot activities, and semi-structured interviews with 11 housing staff and 8 tenant overdose prevention specialists ('specialists'). Data were analyzed using a grounded theory approach to characterize program impacts, implementation strengths, and implementation challenges from the perspective of specialists and housing staff., Findings: We found that the SRO project increased awareness, access to, and understanding of naloxone; facilitated other mutual-aid practices; supported privacy and autonomy of tenants regarding their drug use; and improved rapport, communication and trust between tenants and housing staff. Strengths of the implementation process included involvement of tenants with diverse social locations and skill sets and, at one site, a team-based approach that fostered program innovation, tenant solidarity and a sense of collective ownership over the project. Program implementation was challenged by frequent turnover and capacity constraints of housing staff, particularly during overnight shifts when overdose risks were greatest. Additional challenges arose due to the psychosocial burden of overdose response work, gendered violence, issues with compensation methods, and scope creep in specialists' roles., Conclusion: This evaluation contributes further evidence regarding the effectiveness of tenant-led naloxone distribution and overdose education in permanent supportive and SRO housing environments. Findings indicate program implementation and sustainability can be improved by expanding tenant specialist training, compensating specialists in cash, and building stronger psychosocial support for tenants responding to overdoses in their homes., Competing Interests: Declarations of Interest Emily Valadoa was the program manager for the SRO Project and is employed by the San Francisco Department of Public Health. Laura Guzman is the interim executive director of the National Harm Reduction Coalition and served as the Senior Director of Capacity Building & Mobilization with the DOPE Project., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Objectives: To examine the association between chronic obstructive pulmonary disease status and indicators of economic instability and stress to better understand the magnitude of these issues in persons with chronic obstructive pulmonary disease., Methods: Analyzed 2017 Behavioral Risk Factor Surveillance System data from 16 states that administered the 'Social Determinants of Health' module, which included economic instability and stress measures ( N  = 101,461). Associations between self-reported doctor-diagnosed chronic obstructive pulmonary disease status and each measure were examined using multinomial logistic models., Results: Adults with chronic obstructive pulmonary disease were more likely ( p  < 0.001) than adults without to report not having enough money at month end (21.0% vs. 7.9%) or just enough money (44.9% vs. 37.2%); being unable to pay mortgage, rent, or utility bills (19.2% vs. 8.8%); and that often or sometimes food did not last or could not afford to eat balanced meals (37.9% vs. 20.6%), as well as stress all or most of the time (27.3% vs. 11.6%). Associations were attenuated although remained significant after adjustments for sociodemographic and health characteristics., Discussion: Financial, housing, and food insecurity and frequent stress were more prevalent in adults with chronic obstructive pulmonary disease than without. Findings highlight the importance of including strategies to address challenges related to economic instability and stress in chronic obstructive pulmonary disease management programs.