For younger (18-40) potential first-time buyers in the United Kingdom (UK) there are a number of barriers that are stopping them from owning their very own home. For ** percent of respondents surveyed raising a deposit was the main barrier. Other reasons stopping potential first-time buyers were the fact that they could not get a mortgage on their current income and that their credit ratings were not good enough.

The high residential property prices were the leading reason behind the low homebuyer sentiment in the United States as of the third quarter of 2022. About ** percent of homeowners and ** percent of renters who believed the time is not right to purchase a home were discouraged by the prices. Additionally, over ** percent pointed out that the current economic conditions were not favorable.

The number of U.S. home sales in the United States declined in 2024, after soaring in 2021. A total of four million transactions of existing homes, including single-family, condo, and co-ops, were completed in 2024, down from 6.12 million in 2021. According to the forecast, the housing market is forecast to head for recovery in 2025, despite transaction volumes expected to remain below the long-term average. Why have home sales declined? The housing boom during the coronavirus pandemic has demonstrated that being a homeowner is still an integral part of the American dream. Nevertheless, sentiment declined in the second half of 2022 and Americans across all generations agreed that the time was not right to buy a home. A combination of factors has led to house prices rocketing and making homeownership unaffordable for the average buyer. A survey among owners and renters found that the high home prices and unfavorable economic conditions were the two main barriers to making a home purchase. People who would like to purchase their own home need to save up a deposit, have a good credit score, and a steady and sufficient income to be approved for a mortgage. In 2022, mortgage rates experienced the most aggressive increase in history, making the total cost of homeownership substantially higher. Are U.S. home prices expected to fall? The median sales price of existing homes stood at 413,000 U.S. dollars in 2024 and was forecast to increase slightly until 2026. The development of the S&P/Case Shiller U.S. National Home Price Index shows that home prices experienced seven consecutive months of decline between June 2022 and January 2023, but this trend reversed in the following months. Despite mild fluctuations throughout the year, home prices in many metros are forecast to continue to grow, albeit at a much slower rate.

This dataset denotes the Pathways to Removing Obstacles to Housing (PRO Housing) Priority Geography Map. Under the Need rating factor, applicants will be awarded ten (10) points if their application primarily serves a ‘priority geography’. Priority geography means a geography that has an affordable housing need greater than a threshold calculation for one of three measures. The threshold calculation is determined by the need of the 90th-percentile jurisdiction (top 10%) for each factor as computed comparing only jurisdictions with greater than 50,000 population. Threshold calculations are done at the county and place level and applied respectively to county and place applicants. An application can also quality as a priority geography if it serves a geography that scores in the top 5% of its State for the same three measures.

About 36 percent of homeowners in England were aged 65 and above, which contrasts sharply with younger age groups, particularly those under 35. Young adults between 25 and 35, made up 15 percent of homeowners and had a dramatically lower homeownership rate. The disparity highlights the growing challenges faced by younger generations in entering the property market, a trend that has significant implications for wealth distribution and social mobility. Barriers to homeownership for young adults The path to homeownership has become increasingly difficult for young adults in the UK. A 2023 survey revealed that mortgage affordability was the greatest obstacle to property purchase. This represents a 39 percent increase from 2021, reflecting the impact of rising house prices and mortgage rates. Despite these challenges, one in three young adults still aspire to get on the property ladder as soon as possible, though many have put their plans on hold. The need for additional financial support from family, friends, and lenders has become more prevalent, with one in five young adults acknowledging this necessity. Regional disparities and housing supply The housing market in England faces regional challenges, with North West England and the West Midlands experiencing the largest mismatch between housing supply and demand in 2023. This imbalance is evident in the discrepancy between new homes added to the housing stock and the number of new households formed. London, despite showing signs of housing shortage, has seen the largest difference between homes built and households formed. The construction of new homes has been volatile, with a significant drop in 2020, a rebound in 2021 and a gradual decline until 2024.

Percentage of provincially, territorially, regionally and municipally owned social and affordable housing assets with barrier free design structures for all provinces and territories.

Background: China is continuing to witness rising numbers of migrants (e.g., individuals migrating from rural tourban areas), and alongside this are the social restrictions and institutional barriers migrants face. Such restrictions and barriers are a consequence of the long-standing urban-rural dualist system and can create a sense ofrelative deprivation among migrants—that is, dissatisfaction when migrants perceive they are at a disadvantagecompared with local residents of an area.Objective and method: Based on Pierre Bourdieu’s field theory, the current study used data from the 2017 ChineseGeneral Social Survey (N = 1849) to explore the mechanism through which migrants’ home ownership or nonownership in the migration process affects their sense of relative deprivation. To do so, a ranked regression andparallel multiple mediation model were developed. Additionally, a heterogeneity analysis was conducted toaccount for the region in which migrants lived and their age.Results: The results revealed that home ownership significantly reduced migrants’ relative deprivation. Moreover,the perception of economic and symbolic capital was found to play a role in the effects of wealth and class,respectively. From the heterogeneity analysis, the direct and mediated effects of housing attributes on migrants’relative deprivation were more significant for migrants in the eastern versus central and western regions ofChina, as well as among new-versus older-generation migrants.Conclusion: To improve the feasibility of home ownership among migrants and, thus, alleviate their relativedeprivation in the inflow area, relevant policies (e.g., improving the housing system pathway) should bedeveloped and implemented.

For the past decade, buying a home in the UK has been more affordable than renting one, when only considering the monthly costs. The renting versus buying gap fluctuated during the period and in 2016, it reached its highest value of 131 British pounds. In 2023, the monthly costs for a first-time buyer were 1,231 British pounds, compared to 1,258 British pounds for renters. Rental growth vs house price growth Housing costs in the UK have been on an uprise, with both renting and buying a home increasingly unreachable. Though the monthly costs of buying have consistently been lower in the past decade, house price growth has been much stronger than rental growth since the beginning of the pandemic. Additionally, buyers have been affected by the aggressive mortgage rate hikes, making acquiring their first home even less affordable. Barriers to homeownership Buying a home is not straightforward. For younger (18-40) potential first-time buyers, there are a number of barriers. Approximately one in three first-time buyers point out that raising a deposit was the main obstacle. Other reasons stopping buyers were not being able to take out a mortgage on their current income and poor credit ratings. Unsurprisingly, the highest share of people who buy a home with a mortgage was in the age group of 45 to 55-year-olds.

Pathways to Removing Obstacles to Housing (PRO Housing) Pathways to Removing Obstacles to Housing, or PRO Housing, is a competitive grant program being administered by HUD. PRO Housing seeks to identify and remove barriers to affordable housing production and preservation.

Under the Need rating factor, applicants will be awarded ten (10) points if their application primarily serves a ‘priority geography’. Priority geography means a geography that has an affordable housing need greater than a threshold calculation for one of three measures. The threshold calculation is determined by the need of the 90th-percentile jurisdiction (top 10%) for each factor as computed comparing only jurisdictions with greater than 50,000 population. Threshold calculations are done at the county and place level and applied respectively to county and place applicants. An application can also quality as a priority geography if it serves a geography that scores in the top 5% of its State for the same three measures. The measures are as follows:

Affordable housing not keeping pace, measured as (change in population 2019-2009 divided by 2009 population) – (change in number of units affordable and available to households at 80% HUD Area Median Family Income (HAMFI) 2019-2009 divided by units affordable and available at 80% HAMFI 2009). Insufficient affordable housing, measured as number of households at 80% HAMFI divided by number of affordable and available units for households at 80% HAMFI. Widespread housing cost burden or substandard housing, measured as number of households with housing problems at 100% HAMFI divided by number of households at 100% HAMFI. Housing problems is defined as: cost burden of at least 50%, overcrowding, or substandard housing.

For more information on Pro Housing, please visit: https://www.hud.gov/program_offices/comm_planning/pro_housing

ID 2007: Barriers to Housing and Services domain (measures barriers to housing and key local services) Source: Communities and Local Government (CLG): ID 2007 Publisher: Neighbourhood Statistics Geographies: Lower Layer Super Output Area (LSOA) Geographic coverage: England Time coverage: 2007 (using data from 2001 and 2005) Type of data: Administrative data/Modelled data

This document presents the qualitative interview protocols for the research on Collaborative Housing (CH) in Chile. The interviews are aimed at key actors with knowledge of housing and focus mainly on determining the barriers and enablers to collaborative housing in Chile. In addition, the interviews focus on investigating the historical precedents and current Chilean housing initiatives. The interviews were conducted in two cross-sectional fieldworks. The first was carried out between December 2019 and January 2020, and the second between June and August 2022. The dataset also contains the interview protocols in Spanish, the original language of the interviews conducted by this research lead author.

ID 2004 Wider Barriers Subdomain (issues relating to access to housing such as affordability) Source: Office of the Deputy Prime Minister (ODPM): ID 2004 Publisher: Communities and Local Government (CLG) Geographies: Lower Layer Super Output Area (LSOA) Geographic coverage: England Time coverage: 2004 (using data from 2001 and 2002) Type of data: Modelled data

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This dataset contains replication files for "Creating Moves to Opportunity: Experimental Evidence on Barriers to Neighborhood Choice" by Peter Bergman, Raj Chetty, Stefanie DeLuca, Nathaniel Hendren, Lawrence Katz, and Christopher Palmer. For more information, see https://opportunityinsights.org/paper/cmto/. A summary of the related publication follows. Low-income families in the United States tend to live in neighborhoods that offer limited opportunities for upward income mobility. One potential explanation for this pattern is that low-income families prefer such neighborhoods for other reasons, such as affordability or proximity to family and jobs. An alternative explanation is that families do not move to high-opportunity areas because of barriers that prevent them from making such moves. We test between these two explanations using a randomized controlled trial with housing voucher recipients in Seattle and King County. We provided services to reduce barriers to moving to high-upward-mobility neighborhoods: customized search assistance, landlord engagement, and short-term financial assistance. The intervention increased the fraction of families who moved to high-upward-mobility areas from 14% in the control group to 54% in the treatment group. Families induced to move to higher opportunity areas by the treatment do not make sacrifices on other dimensions of neighborhood quality and report much higher levels of neighborhood satisfaction. These findings imply that most low-income families do not have a strong preference to stay in low-opportunity areas; instead, barriers in the housing search process are a central driver of residential segregation by income. Interviews with families reveal that the capacity to address each family’s needs in a specific manner from emotional support to brokering with landlords to financial assistance was critical to the program’s success. Using quasi-experimental analyses and comparisons to other studies, we show that more standardized policies increasing voucher payment standards in high-opportunity areas or informational interventions have much smaller impacts. We conclude that redesigning affordable housing policies to provide customized assistance in housing search could reduce residential segregation and increase upward mobility substantially.

Revenue for apartment lessors has expanded through the end of 2025. Apartment lessors collect rental income from rental properties, where market forces largely determine their rates. The supply of apartment rentals has grown slower than demand, which has elevated rental rates for lessors' benefit. As the Federal Reserve hiked interest rates 11 times between March 2022 and January 2024, homeownership was pushed beyond the reach of many, resulting in a tighter supply and increased demand for rental properties. Despite three interest rate cuts in 2024, mortgage rates have remained high, further encouraging consumers to rent. Revenue has climbed at a CAGR of 2.9% over the past five years and is expected to reach $299.7 billion by the end of 2025. This includes an anticipated 3.0% gain in 2025 alone. The increasing unaffordability of housing is caused by the steady climb of mortgage rates and high prices maintained by a low supply. Supply has been held down as buyers who locked in low rates stay put, and investment groups hold a strategic number of their properties empty as investments. Industry profit has remained elevated because of solid demand for apartment rentals. Through the end of 2030, the apartment rental industry's future performance is likely to be shaped by varying factors. The apartment supply in the US, which hit a record in 2024, is expected to taper off, which will, in turn, push rental prices and occupancy rates up to the lessors' benefit. Other factors, such as further interest rate cuts, decreasing financial barriers to homeownership, and a high rate of urbanization, will also significantly impact the industry. Wth approximately 80.7% of the US population living in urban areas, demand for apartment rentals will strengthen, although rising rental prices could force potential renters to cheaper suburbs. Demand will continue to outpace supply growth, prompting a climb in revenue. Revenue is expected to swell at a CAGR of 2.8% over the next five years, reaching an estimated $344.3 billion in 2030.

This indicator presents a summary of the main housing policy objectives in national housing strategies, as well as obstacles faced in ensuring access to affordable housing, as identified by countries that responded to the 2021, 2019 and 2016 OECD Questionnaire on Affordable and Social Housing (QuASH 2021, QuASH 2019, QuASH 2016). This indicator summarises the reported obstacles by country, whilst classifying the policy objectives into 11 broad categories (Figure PH 1.2). The full list of policy objectives is available in Table PH 1.2.2 in Annex I.

VITAL SIGNS INDICATOR Housing Production (LU4)

FULL MEASURE NAME Produced housing units by unit type

LAST UPDATED October 2019

DESCRIPTION Housing production is measured in terms of the number of units that local jurisdictions produces throughout a given year. The annual production count captures housing units added by new construction and annexations, subtracts demolitions and destruction from natural disasters, and adjusts for units lost or gained by conversions.

DATA SOURCE California Department of Finance Form E-8 1990-2010 http://www.dof.ca.gov/Forecasting/Demographics/Estimates/E-8/

California Department of Finance Form E-5 2011-2018 http://www.dof.ca.gov/Forecasting/Demographics/Estimates/E-5/

U.S. Census Bureau Population Estimates 2000-2018 https://www.census.gov/programs-surveys/popest.html

CONTACT INFORMATION vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator) Single-family housing units include single detached units and single attached units. Multi-family housing includes two to four units and five plus or apartment units.

Housing production data for metropolitan areas for each year is the difference of annual housing unit estimates from the Census Bureau’s Population Estimates Program. Housing production data for the region, counties, and cities for each year is the difference of annual housing unit estimates from the California Department of Finance. Department of Finance data uses an annual cycle between January 1 and December 31, whereas U.S. Census Bureau data uses an annual cycle from April 1 to March 31 of the following year.

Housing production data shows how many housing units have been produced over time. Like housing permit statistics, housing production numbers are an indicator of where the region is growing. However, since permitted units are sometimes not constructed or there can be a long lag time between permit approval and the start of construction, production data also reflects the effects of barriers to housing production. These range from a lack of builder confidence to high construction costs and limited financing. Data also differentiates the trends in multi-family, single-family and mobile home production.

This dataset provides detailed information on the 2019 Index of Multiple Deprivation (IMD) for Birmingham, UK. The data is available at the postcode level and includes the Lower Layer Super Output Area (LSOA) information.Data is provided at the LSOA 2011 Census geography.The decile score ranges from 1-10 with decile 1 representing the most deprived 10% of areas while decile 10 representing the least deprived 10% of areas.The IMD rank and decile score is allocated to the LSOA and all postcodes within it at the time of creation (2019).Note that some postcodes cross over LSOA boundaries. The Office for National Statistics sets boundaries for LSOAs and allocates every postcode to one LSOA only: this is the one which contains the majority of residents in that postcode area (as at 2011 Census).

The English Indices of Deprivation 2019 provide detailed measures of relative deprivation across small areas in England. The Barriers to Housing and Services dataset is a key component of this index, measuring the physical and financial accessibility of housing and local services. This dataset includes indicators such as household overcrowding, homelessness, housing affordability, and the distance to key services like primary schools, general stores, and GP surgeries. It helps identify areas where residents face significant barriers to accessing adequate housing and essential services, guiding policy interventions and resource allocation to improve living conditions and accessibility.

This dataset contains a summary measure of the Indices of Deprivation 2010 Barriers to housing and services domain at local authority district level. It puts the 326 Local Authority Districts into a rank order based the population weighted average rank of all LSOAs in the LAD. A rank of 1 is the most deprived.

The English Indices of Deprivation provide a relative measure of deprivation at small area level across England. Areas are ranked from least deprived to most deprived on seven different dimensions of deprivation and an overall composite measure of multiple deprivation. Most of the data underlying the 2010 indices are for the year 2008.

The Indices are designed for small areas, but one way of summarising relative deprivation at local authority level is by calculating the average rank of the LSOAs within it.

For the IMD and each domain, the summary measure is calculated by averaging all of the LSOA ranks in each local authority district. For the purpose of calculation, LSOAs are ranked such that the most deprived LSOA is given the rank of 32,482. The LSOA ranks are population weighted within a local authority district to take account of the fact that LSOA size can vary. (For simplicity in summarising the domains, the same total population size is used for all domains.) Finally the LADs are ranked according to the average rank of the LSOAs, from 1 to 326 where 1 is the most deprived.

The ‘Rank of average rank’ summary measure of for local authorities is also published for the IMD at: http://www.communities.gov.uk/documents/statistics/xls/1871689.xls.

Adjusted odds ratios (and 95% confidence intervals) from binary logistic regression of ever experiencing housing loss due to "housing/financial loss", "health issues", and "interpersonal/family issues" by selected characteristics among homeless individuals (N = 207), Nipissing District, Ontario 2021.