The Rent Affordability data table includes units disaggregated by rent affordability for each building in a Local Law 44 Housing Development Project. This information is reported pursuant to Local Law 44 of 2012, and is part of the <a Housing Projects Receiving City Financial Assistance (Local Law 44) collection of data tables.

Rental Affordability Analysis Based on Median Income

Trends in Tier-Based Affordability Across the U.S

By Zillow Data [source]

About this dataset

This dataset contains rental affordability data for different regions in the US, giving valuable insights into regional rental markets. Renters can use this information to identify where their budget will go the farthest. The cities are organized by rent tier in order to analyze affordability trends within and between different housing stock types. Within each region, the data includes median household income, Zillow Rent Index (ZRI), and percent of income spent on rent.

The Zillow Home Value Forecast (ZHVF) is used to calculate future combined mortgage pay/rent payments in each region using current median home prices, actual outstanding debt amounts and 30-year fixed mortgage interest rates reported through partnership with TransUnion credit bureau. Zillow also provides a breakdown of cash vs financing purchases for buyers looking for an investment or cash option solution.

This dataset provides an effective tool for consumers who want to better understand how their budget fits into diverse rental markets across the US; from condominiums and co-ops, multifamily residences with five or more units, duplexes and triplexes - every renter can determine how their housing budget should be adjusted as they consider multiple living possibilities throughout the country based on real-time price data!

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How to use the dataset

Introduction

Getting Started

• First, you'll need to download the TieredAffordability_Rental.csv dataset from this Kaggle page onto your computer or device.

• After downloading the data set onto your device, open it with any CSV viewing software of your choice (ex: Excel). It will include columns for RegionName**RegionName** , homes type/housing stock (All Homes or Condo/Co-op) SizeRank , Rent tier tier , Date date , median household income income , Zillow Rent Index zri and PercentIncomeSpentOnRent percentage (what portion of monthly median house-hold goes toward monthly mortgage payment) .

• To begin analyzing rental prices across different regions using this dataset, look first at column four: SizeRank; which ranks each region based on size - smallest regions listed first and largest at last - so that you can compare a similar range of Regions when looking at affordability by home sizes larger than one unit multiplex dwellings.*Duples/Triplex*. Once there is an understanding of how all homes compare overall now it is time to consider home types Multifamily 5+ units according to rent tiers tier .

• Next, choose one or more region(s) for comparison based on their rank in SizeRank column –so that all information gathered about them reflects what portionof households fall into certain categories ; eg; All Homes / Small Home /Large Home / MultiPlex Dwelling and what tier does each size rank falls into eg.: Affordable/Slightly Expensive/ Moderately Expensive etc.. This will enable further abstraction from other elements like date vs inflation rate per month or periodical intervals set herein by Rate segmentation i e dates givenin ‘Date’Columns – making the task easier and more direct while analyzing renatalAffordibility Analysis Based On Median Income zri 00 zwi & PCISOR 00 PCIRO

Research Ideas

• Use the PercentIncomeSpentOnRent column to compare rental affordability between regions within a particular tier and determine optimal rent tiers for relocating families.
• Analyze how market conditions are affecting rental affordability over time by using the income, zri, and PercentageIncomeSpentOnRent columns.
• Identify trends in housing prices for different tiers over the years by comparing SizeRank data with Zillow Home Value Forecast (ZHVF) numbers across different regions in order to identify locations that may be headed up or down in terms of home values (and therefore rent levels)

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

See the dataset description for more information.

Columns

File: TieredAffordability_Rental.csv | Column name | Description | |:-----------------------------|:-------------------------------------------------------------| | RegionName | The name of the region. (String) ...

Build-to-Rent Housing Market Outlook

As per our latest research, the global Build-to-Rent (BTR) housing market size reached USD 74.3 billion in 2024, reflecting a robust expansion driven by rising demand for professionally managed rental communities. The market is projected to grow at a CAGR of 10.1% from 2025 to 2033, reaching an estimated USD 192.2 billion by 2033. This impressive growth trajectory is primarily fueled by evolving lifestyle preferences, increasing urbanization, and a shift in housing affordability, which are collectively redefining the residential real estate landscape worldwide.

One of the most significant growth factors for the Build-to-Rent housing market is the changing demographic profile of urban populations. Young professionals and millennials increasingly prioritize flexibility and convenience over homeownership, leading to a surge in demand for rental properties that offer modern amenities and community-centric living. The BTR model, with its professionally managed services, maintenance support, and enhanced communal facilities, appeals strongly to this demographic. Additionally, the growing number of digital nomads and remote workers is further amplifying the need for adaptable, high-quality rental housing, particularly in metropolitan areas and emerging urban centers.

Another major driver for the Build-to-Rent housing market is the ongoing affordability crisis in many global cities. Escalating property prices and stringent mortgage requirements have made homeownership unattainable for a significant portion of the population, especially in North America and Europe. As a result, institutional investors and real estate developers are capitalizing on this opportunity by expanding their BTR portfolios. The stable, long-term rental income streams offered by BTR assets are particularly attractive to pension funds, insurance companies, and private equity firms seeking diversification and resilience in their investment portfolios.

Technological advancements and innovation in construction methods are also catalyzing the growth of the Build-to-Rent housing market. The adoption of modular and prefabricated construction techniques is enabling developers to accelerate project timelines, reduce costs, and improve sustainability outcomes. These methods are particularly suited to the BTR model, where speed to market and operational efficiency are critical. Furthermore, the integration of smart home technologies and digital management platforms is enhancing tenant experiences and operational transparency, thereby increasing the appeal of BTR properties to both residents and investors.

Regionally, North America and Europe continue to dominate the Build-to-Rent housing market, accounting for a combined market share of over 65% in 2024. However, Asia Pacific is emerging as a high-growth region, driven by rapid urbanization, rising middle-class populations, and supportive government policies. Latin America and the Middle East & Africa are also witnessing growing interest in the BTR model, particularly in gateway cities with expanding expatriate communities and young workforces. The regional outlook for the BTR market remains highly positive, underpinned by favorable demographic trends and increasing investor appetite for income-generating real estate assets.

Property Type Analysis

The Build-to-Rent housing market is segmented by property type into single-family homes, multi-family apartments, townhouses, and others. Among these, multi-family apartments currently hold the largest market share, accounting for over 55% of the global BTR inventory in 2024. The preference for multi-family developments is rooted in their efficient land use, scalability, and ability to offer a wide array of amenities such as gyms, co-working spaces, and communal lounges. These features are highly attractive to young professionals and urban dwellers seeking community engagement and convenience. Furthermore, mul

Monthly data showing the proportion of gross income spent on rent for new tenancies across the UK, from Dataloft Rental Market Analytics (DRMA). These are official statistics in development. Source: Dataloft. Dataloft is a PriceHubble company.

Portugal, Hungary, and Mexico were the countries with the highest house price-to-rent-ratio in the ranking in the second quarter of 2025. In all three countries, the ratio exceeded 160 index points, meaning that house price growth had outpaced rents by over 60 percent between 2015 and 2025. What does the house-price-to-rent ratio show? The house-price-to-rent-ratio measures the evolution of house prices compared to rents. It is generally calculated by dividing the median house price by the median annual rent. In this statistic, the values have been normalized with 100 equaling the 2015 ratio. Consequentially, a value under 100 means that rental rates have risen more than house prices. When all OECD countries are considered as a whole, the gap between house prices and rents was wider than in the Euro area. Measures of housing affordability The national house-price-to-rent ratio may not fully reflect the cost of housing in a particular country, as it does not capture the price variations that can exist between different regions. It also does not take into consideration the relationship between incomes and housing costs, which is measured by the house-price-to-income and household-rent-to-income ratios. Taking both these factors into account uncovers vast differences in housing affordability between different regions and different professions.

The Rental Report time series dataset provides detailed time-series statistics for some key Rental Report data from the March quarter of 2000 to the December quarter of 2017. This specific dataset presents statistics on affordable 1 bedroom rental properties by the 2016 Local Government Areas geographic level. Affordable rental properties are those within 30 per cent of gross income for low-income households. The rental thresholds are taken from the household incomes for whom that number of bedrooms is a minimum: For one-bedroom properties, we have taken the income of singles on Newstart allowance; For two-bedroom properties, we have taken a single parent pensioner with one child aged under 5;

This section of the Rental Report provides a summary of the affordability of rental housing for lower income households in Victoria. The method used in this section measures the supply of affordable new lettings based on the Residential Tenancies Bond Authority data used in this Report. The affordability benchmark used is that no more than 30 per cent of gross income is spent on rent. Lower income households are defined as those receiving Centrelink incomes.

The Rental Report provides key statistics on the private rental market in Victoria. The major source for the statistics presented in the Rental Report is the Residential Tenancies Bond Authority which collects data on all rental bonds lodged under the Residential Tenancies Act 1997.

As of January 2025, the rent for a two-bedroom apartment in Hawaii was about 120 U.S. dollars higher than in California. The states of Hawaii and California ranked as the most expensive within the United States for apartment renters. Conversely, an apartment in Arkansas was almost three times more affordable than one in Hawaii.In 2025, the average monthly rent in the U.S. declined slightly. Nevertheless, in rents increased in most states, with West Virginia registering the highest growth.

The housing affordability measure illustrates the relationship between income and housing costs. A household that spends 30% or more of its collective monthly income to cover housing costs is considered to be “housing cost-burden[ed].”[1] Those spending between 30% and 49.9% of their monthly income are categorized as “moderately housing cost-burden[ed],” while those spending more than 50% are categorized as “severely housing cost-burden[ed].”[2]

How much a household spends on housing costs affects the household’s overall financial situation. More money spent on housing leaves less in the household budget for other needs, such as food, clothing, transportation, and medical care, as well as for incidental purchases and saving for the future.

The estimated housing costs as a percentage of household income are categorized by tenure: all households, those that own their housing unit, and those that rent their housing unit.

Throughout the period of analysis, the percentage of housing cost-burdened renter households in Champaign County was higher than the percentage of housing cost-burdened homeowner households in Champaign County. All three categories saw year-to-year fluctuations between 2005 and 2023, and none of the three show a consistent trend. However, all three categories were estimated to have a lower percentage of housing cost-burdened households in 2023 than in 2005.

Data on estimated housing costs as a percentage of monthly income was sourced from the U.S. Census Bureau’s American Community Survey (ACS) 1-Year Estimates, which are released annually.

As with any datasets that are estimates rather than exact counts, it is important to take into account the margins of error (listed in the column beside each figure) when drawing conclusions from the data.

Due to the impact of the COVID-19 pandemic, instead of providing the standard 1-year data products, the Census Bureau released experimental estimates from the 1-year data in 2020. This includes a limited number of data tables for the nation, states, and the District of Columbia. The Census Bureau states that the 2020 ACS 1-year experimental tables use an experimental estimation methodology and should not be compared with other ACS data. For these reasons, and because data is not available for Champaign County, no data for 2020 is included in this Indicator.

For interested data users, the 2020 ACS 1-Year Experimental data release includes a dataset on Housing Tenure.

[1] Schwarz, M. and E. Watson. (2008). Who can afford to live in a home?: A look at data from the 2006 American Community Survey. U.S. Census Bureau.

[2] Ibid.

Sources: U.S. Census Bureau; American Community Survey, 2023 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using data.census.gov; (17 October 2024).; U.S. Census Bureau; American Community Survey, 2022 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using data.census.gov; (22 September 2023).; U.S. Census Bureau; American Community Survey, 2021 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using data.census.gov; (30 September 2022).; U.S. Census Bureau; American Community Survey, 2019 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using data.census.gov; (10 June 2021).; U.S. Census Bureau; American Community Survey, 2018 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using data.census.gov; (10 June 2021).;U.S. Census Bureau; American Community Survey, 2017 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2016 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (14 September 2017).; U.S. Census Bureau; American Community Survey, 2015 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (19 September 2016).; U.S. Census Bureau; American Community Survey, 2014 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2013 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2012 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2011 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2010 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2009 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2008 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; 16 March 2016).; U.S. Census Bureau; American Community Survey, 2007 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2006 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2005 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).

The Rental Report time series dataset provides detailed time-series statistics for some key Rental Report data from the March quarter of 2000 to the December quarter of 2017. This specific dataset presents statistics on affordable 3 bedroom rental properties by the 2016 Local Government Areas geographic level. Affordable rental properties are those within 30 per cent of gross income for low-income households. The rental thresholds are taken from the household incomes for whom that number of bedrooms is a minimum: For one-bedroom properties, we have taken the income of singles on Newstart allowance; For two-bedroom properties, we have taken a single parent pensioner with one child aged under 5;

Number of affordable housing starts (seasonally adjusted)

How the figure is calculated:

Total reported numbers of starts under the relevant programmes within the reporting period. Because delivery is seasonal and reflects funding profiles, with more starts and completions being reported in the second six months than are reported in the first six months, the current figures are compared back to the equivalent period of the year before rather than the preceding six months.

Why is this indicator in the business plan?

These are the most timely indicators on affordable housing delivery. Increasing the supply of affordable housing is a key part of DCLG policy.

How often is it updated?

Bi-annually, approximately June and November.

Where does the data come from?

Homes and Communities Agency (HCA) - Investment Management System and other programme information. Published figures are at http://www.homesandcommunities.co.uk/housing-statistics.

Greater London Authority (GLA) - Investment Management System and other programme information. Published figures are at http://www.london.gov.uk/priorities/housing-land/increasing-housing-supply/gla-affordable-housing-statistics.

What area does the headline figure cover?

England

Are further breakdowns of the data available?

Yes, can be split by type (social rent, affordable rent, intermediate rent, Low Cost Home Ownership) and by local authority area.

What does a change in this indicator show?

An increase in this indicator is good and shows more new affordable houses are being started through the HCA and GLA.

Time Lag

Published within two months of the end of the reporting period.

Next available update

June 2015.

Type of Data

Official Statistics.

Robustness and data limitations

• Does not include all affordable housing starts and completions because some will be delivered outside the HCA and GLA roles.
• Delivery is seasonal and reflects funding profiles. Delivery tends to be lower in the first six months than the last six months of the year and therefore comparisons with the previous six-monthly period are not usually appropriate.
• A small number of the affordable housing starts reported by the HCA over this period are actually located in London (the Get Britain Building programme in London is administered by the HCA on behalf of the GLA).

With effect from 1 April 2014, affordable housing starts on site include the starts on site for new build homes purchased at completion. These have not been reported historically

Links to Further Information

http://www.homesandcommunities.co.uk/housing-statistics

http://www.london.gov.uk/priorities/housing-land/increasing-housing-supply/gla-affordable-housing-statistics

Contact Details

CorporatePerformance@communities.gsi.gov.uk

Housing Rental Platform Market Outlook

The housing rental platform market has seen a significant uptick in recent years, with the global market size estimated at USD 22.6 billion in 2023. The market is projected to grow at a robust CAGR of 12.4% from 2024 to 2032, reaching an estimated USD 72.4 billion by 2032. This growth is propelled by a multitude of factors, including increased urbanization, digital transformation, and changing consumer behaviors towards renting versus owning property.

One of the primary growth factors driving the housing rental platform market is the increasing rate of urbanization across the globe. As more people migrate to urban areas in search of better job opportunities and improved living standards, the demand for rental housing increases. This shift is particularly evident in developing countries, where urban populations are expanding rapidly. Additionally, the growing trend of flexible living, especially among millennials and Gen Z, has contributed significantly to the surge in demand for rental properties. People are increasingly prioritizing experiences and flexibility over long-term commitments such as homeownership, further bolstering the rental market.

Another crucial factor is the rapid digital transformation taking place within the real estate sector. Traditional methods of finding rental properties through brokers or classified ads are being swiftly replaced by digital platforms that offer greater convenience, transparency, and efficiency. Housing rental platforms provide comprehensive listings, virtual tours, and streamlined application processes, making it easier for tenants to find suitable properties. Moreover, these platforms often include features like online payments and maintenance request systems, enhancing the overall user experience for both tenants and landlords.

Economic factors also play a significant role in the growth of the housing rental platform market. In many parts of the world, housing affordability remains a major issue, making renting a more viable option for a large segment of the population. Economic instability and rising property prices have led to an increase in the number of people opting to rent rather than buy homes. Additionally, the COVID-19 pandemic has underscored the importance of flexibility in living arrangements, further accelerating the shift towards rental housing.

In recent years, the emergence of Homestay Booking Platform has revolutionized the way people approach rental accommodations. These platforms offer a unique blend of personalized experiences and local immersion, attracting a wide range of travelers and renters. Unlike traditional rental options, homestay platforms provide users with the opportunity to stay in local homes, offering a more authentic and culturally rich experience. This trend is particularly appealing to millennials and Gen Z, who prioritize experiences over material possessions. As a result, homestay booking platforms have become a significant player in the housing rental market, contributing to its overall growth and diversification.

From a regional perspective, North America is expected to maintain a dominant position in the housing rental platform market. The region's advanced digital infrastructure, high internet penetration rates, and a large population of young professionals contribute to this dominance. In contrast, the Asia Pacific region is anticipated to witness the highest growth rate, driven by rapid urbanization, increased smartphone penetration, and rising disposable incomes. Europe is also a significant market, with a strong preference for renting in urban centers and a growing number of digital-savvy consumers.

Property Type Analysis

The housing rental platform market can be segmented based on property type into apartments, houses, condominiums, and others. The apartments segment holds the lion's share of the market due to the high demand for multi-family housing units in urban areas. Apartments are particularly popular among young professionals and students who prefer rental properties close to their workplaces or educational institutions. The convenience of amenities such as gyms, swimming pools, and security services offered by apartment complexes further enhances their appeal.

Houses form another significant segmen

Housing Affordability Supply and Demand Data. Number of South Australian households paying more than 30% of their household income on housing (rent or mortgage) broken down by very low, low and moderate income brackets. This dataset relates to section 4, Housing Stress, of the Affordability master reports produced by the SA Housing Authority. Each master report covers one Local Government Area and is entitled ‘Housing Affordability – Demand and Supply by Local Government Area’. The Demand for Supply for LGA reports are available online at: https://data.sa.gov.au/data/dataset/housing-affordability-demand-and-supply-by-local-government-area Explanatory Notes: Data sourced from the Australian Bureau of Statistics (ABS), Census for Population and Housing and it is updated every 5 years in line with the ABS Census. The nature of the income imputation means that the reported proportion may significantly overstate the true proportion. Census housing stress data is best used in comparing results over Censuses (ie did it increase or decrease in an area) rather than using it to ascertain what proportion of households were in rental stress. Income bands are based on household income. High income households can also experience rental stress. These households are included in the total but not identified separately. Data is representative of households in very low, low and moderate income brackets. Please note that there are small random adjustments made to all cell values to protect the confidentiality of data. These adjustments may cause the sum of rows or columns to differ by small amounts from table totals.

Build-to-Rent Finance Market Outlook

According to our latest research, the global Build-to-Rent Finance market size reached USD 85.7 billion in 2024, demonstrating robust expansion driven by rising institutional investment and evolving housing demands. With a compound annual growth rate (CAGR) of 10.4% forecasted from 2025 to 2033, the market is projected to achieve a value of USD 210.5 billion by 2033. This strong growth trajectory is fueled by increasing urbanization, a shift toward rental housing preferences, and enhanced access to innovative financing models, as per our latest research insights.

One of the primary growth factors propelling the Build-to-Rent Finance market is the surge in urban populations and the resultant demand for high-quality rental housing. Urbanization has led to a significant increase in the number of individuals and families seeking flexible housing solutions that do not require long-term ownership commitments. This trend is particularly pronounced among younger demographics and transient professionals who prioritize mobility and convenience. The build-to-rent (BTR) model, supported by tailored financing arrangements, addresses these evolving needs by providing professionally managed, purpose-built rental properties. As cities continue to grow and housing affordability becomes a pressing issue, the market is expected to expand further, with developers and investors leveraging innovative finance structures to meet surging demand.

Another critical driver for the Build-to-Rent Finance market is the growing participation of institutional investors and real estate funds. These entities are increasingly attracted to the stable, long-term returns offered by BTR assets, particularly in comparison to more volatile commercial real estate sectors. The influx of institutional capital has led to larger-scale developments and the adoption of sophisticated financing mechanisms, such as debt syndication, equity partnerships, and mezzanine loans. This institutional involvement not only ensures the financial viability of BTR projects but also enhances the professionalism and operational efficiency of the sector. As a result, the market is witnessing a shift from fragmented, small-scale investments to large, master-planned communities financed through diverse and innovative channels.

Additionally, the evolution of financing models within the Build-to-Rent Finance market is playing a pivotal role in its expansion. Traditional financing methods are being complemented by creative structures such as joint ventures, public-private partnerships, and green financing options. These models enable developers to access capital more efficiently, mitigate risks, and align interests among multiple stakeholders. The flexibility and customization of these financing arrangements are particularly appealing in a dynamic real estate environment marked by fluctuating interest rates and regulatory changes. Furthermore, the integration of sustainability and technology into BTR developments is attracting ESG-focused investors, further broadening the market’s capital base and supporting long-term growth.

From a regional perspective, North America and Europe currently dominate the Build-to-Rent Finance market, accounting for the majority of global investments and transactions. These regions benefit from mature financial systems, well-established rental markets, and supportive regulatory frameworks that encourage institutional participation. However, Asia Pacific is emerging as a significant growth engine, driven by rapid urbanization, rising middle-class populations, and increasing investor interest in alternative real estate assets. The Middle East & Africa and Latin America are also witnessing gradual adoption of the BTR model, supported by demographic shifts and government initiatives to boost housing supply. As the market matures globally, regional variations in financing preferences and regulatory environments will continue to shape its evolution.

Financing Type Analysis

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This dataset contains Housing Affordability Supply and Demand Data broken down by very low, low and moderate income brackets. This dataset relates to section 4, Housing Stress, of the Affordability master reports produced by the SA Housing Authority. Each master report covers one Local Government Area and is entitled Housing Affordability Demand and Supply by Local Government Area. Explanatory Notes: Data sourced from the Australian Bureau of Statistics (ABS), Census for Population and Housing …Show full descriptionThis dataset contains Housing Affordability Supply and Demand Data broken down by very low, low and moderate income brackets. This dataset relates to section 4, Housing Stress, of the Affordability master reports produced by the SA Housing Authority. Each master report covers one Local Government Area and is entitled Housing Affordability Demand and Supply by Local Government Area. Explanatory Notes: Data sourced from the Australian Bureau of Statistics (ABS), Census for Population and Housing and it is updated every 5 years in line with the ABS Census. The nature of the income imputation means that the reported proportion may significantly overstate the true proportion. Census housing stress data is best used in comparing results over Censuses (ie did it increase or decrease in an area) rather than using it to ascertain what proportion of households were in rental stress. Income bands are based on household income. High income households can also experience rental stress. These households are included in the total but not identified separately. Data is representative of households in very low, low and moderate income brackets. Please note that there are small random adjustments made to all cell values to protect the confidentiality of data. These adjustments may cause the sum of rows or columns to differ by small amounts from table totals. Field Definitions: LGA Name: 2011 Local Government Areas are an ABS approximation of officially gazetted LGAs as defined by each State and Territory Local Government Department. The boundaries produced for LGAs are constructed from allocations of whole Mesh Blocks and reviewed annually. Tenure Type: This is a consolidation of the census tenure and landlord types. The following definitions have been used: Rented: Private and not stated, this is comprised of rented dwellings (excluding rent free) where the Landlord type is a Real Estate Agent, Person not in the same household or where the Landlord type is not stated Rented: Other, this is comprised of rented dwellings (excluding rent free) where the Landlord type is Employer (Govt or other), Housing cooperative,community,church group, or Residential park (incl caravan parks and marinas) Rented: TOTAL, this is comprised of the sum of Rented: Public, Rented: Private and not stated, and Rented: Other landlord. Please note that this field should be excluded when summing the total households Other tenure types: this is comprised of dwellings that are owned outright, occupied rent free, occupied under a life tenure scheme, other tenure types and tenure type not stated. Total Households: this is comprised of the sum of Being purchased (incl rent,buy), Rented: TOTAL and Other tenure types. Total - Includes all South Australian households. Source: The data was downloaded from data.sa.gov.au and spatialised by the Adelaide Data Hub using the ABS 2011 Local Government Areas dataset. Copyright attribution: Government of South Australia - SA Housing Authority, (2014): . Accessed from AURIN Portal on 12/3/2020. Licence type: Creative Commons Attribution 4.0 International (CC BY 4.0)

Build‑to‑Rent Payments Market Outlook

According to our latest research, the global Build-to-Rent Payments market size reached USD 3.41 billion in 2024, with a robust year-on-year growth trend. The market is expected to expand at a CAGR of 13.2% from 2025 to 2033, reaching a forecasted value of USD 10.06 billion by 2033. This growth trajectory is underpinned by the increasing adoption of digital payment solutions, the proliferation of build-to-rent (BTR) developments, and the growing need for seamless, secure, and efficient rent collection and management processes across the globe. As per our latest research, the surge in institutional investments in the build-to-rent sector, combined with the evolving preferences of tenants for flexible and tech-enabled living experiences, is fueling the expansion of the Build-to-Rent Payments market.

One of the primary growth factors driving the Build-to-Rent Payments market is the rapid digital transformation occurring within the real estate and property management sectors. The adoption of advanced payment technologies, such as online and mobile payments, has significantly enhanced the efficiency and transparency of rent collection and disbursement processes. Property managers and landlords are increasingly leveraging automated payment platforms to reduce manual errors, minimize late payments, and provide tenants with a convenient and user-friendly payment experience. Furthermore, the integration of payment gateways with property management software is streamlining operations and enabling real-time tracking of transactions, which is particularly beneficial for large-scale Build-to-Rent portfolios. This digital shift is not only improving cash flow management for property owners but also elevating tenant satisfaction, thereby strengthening the long-term prospects of the market.

Another key driver propelling the Build-to-Rent Payments market is the evolving demographic and lifestyle trends among urban populations, particularly among millennials and Gen Z renters. These cohorts are exhibiting a marked preference for rental housing options that offer flexibility, community amenities, and seamless digital experiences. The Build-to-Rent model, which emphasizes professionally managed rental communities, is gaining traction in major metropolitan areas worldwide. As a result, there is a growing demand for integrated payment solutions that can handle recurring payments, automate reminders, and facilitate secure transactions. The increasing prevalence of contactless and mobile payment methods, alongside the rise of digital wallets and fintech innovations, is further accelerating the adoption of electronic payment systems within the BTR segment.

The Build-to-Rent Payments market is also benefiting from heightened investor interest in the BTR real estate segment. Institutional investors, private equity firms, and real estate developers are channeling significant capital into purpose-built rental communities, recognizing their potential for stable, long-term returns. This influx of investment is fostering the development of large-scale BTR projects, which in turn necessitate robust and scalable payment infrastructure to manage high transaction volumes and diverse tenant profiles. The ability to customize payment workflows, generate detailed financial reports, and ensure compliance with local regulations is becoming a critical differentiator for payment solution providers in this market. As the BTR ecosystem continues to mature, the demand for innovative payment technologies that can support complex operational requirements is expected to intensify.

From a regional perspective, North America currently leads the Build-to-Rent Payments market, accounting for the largest share in 2024, followed closely by Europe and Asia Pacific. The United States and Canada have witnessed a surge in BTR developments, particularly in urban centers where housing affordability challenges and shifting lifestyle preferences are driving rental demand. In Europe, the United Kingdom, Germany, and the Netherlands are emerging as key markets, with institutional investors actively participating in the BTR space. Meanwhile, the Asia Pacific region is experiencing rapid urbanization and a growing middle-class population, creating fertile ground for the expansion of BTR projects and associated payment solutions. Latin America and the Middle East & Africa are also showing promising growth prospects, albeit from a smaller base, as developers and investors recognize the potential of the BTR model

Rents in Germany continued to increase in all seven major cities in 2024. The average rent per square meter in Munich was approximately **** euros — the highest in the country. Conversely, Düsseldorf had the most affordable rent, at approximately **** euros per square meter. But how does renting compare to buying? According to the house price to rent ratio, house prices in Germany have risen faster than rents, making renting more affordable than buying. Affordability of housing in Germany In 2023, Germany was among the European countries with a relatively high house price to income ratio in Europe. The indicator compares the affordability of housing across OECD countries and is calculated as the nominal house prices divided by nominal disposable income per head, with 2015 chosen as a base year. Between 2012 and 2022, property prices in the country rose much faster than income, with the house price to income index peaking at *** index points at the beginning of 2022. Slower house price growth in the following years has led to the index declining, as incomes catch up. Nevertheless, homebuyers in 2024 faced significantly higher mortgage interest rates, contributing to a higher final cost. How much does buying a property in Germany cost? Just as with renting, Munich was the most expensive city for newly built apartments. In 2024, the cost per square meter in Munich was almost ***** euros pricier than in the runner-up city, Frankfurt. Detached and semi-detached houses are usually more expensive. The price gap between Munich and the second most expensive city, Stuttgart, was nearly ***** euros per square meter.

Portugal, Canada, and the United States were the countries with the highest house price to income ratio in 2024. In all three countries, the index exceeded 130 index points, while the average for all OECD countries stood at 116.2 index points. The index measures the development of housing affordability and is calculated by dividing nominal house price by nominal disposable income per head, with 2015 set as a base year when the index amounted to 100. An index value of 120, for example, would mean that house price growth has outpaced income growth by 20 percent since 2015. How have house prices worldwide changed since the COVID-19 pandemic? House prices started to rise gradually after the global financial crisis (2007–2008), but this trend accelerated with the pandemic. The countries with advanced economies, which usually have mature housing markets, experienced stronger growth than countries with emerging economies. Real house price growth (accounting for inflation) peaked in 2022 and has since lost some of the gain. Although, many countries experienced a decline in house prices, the global house price index shows that property prices in 2023 were still substantially higher than before COVID-19. Renting vs. buying In the past, house prices have grown faster than rents. However, the home affordability has been declining notably, with a direct impact on rental prices. As people struggle to buy a property of their own, they often turn to rental accommodation. This has resulted in a growing demand for rental apartments and soaring rental prices.

Rent‑to‑Own Platforms Market Outlook

According to our latest research, the global rent-to-own platforms market size reached USD 6.8 billion in 2024, demonstrating robust expansion driven by digital transformation and rising consumer demand for flexible financing. The market is projected to grow at a CAGR of 10.2% from 2025 to 2033, reaching an estimated USD 16.2 billion by 2033. This growth trajectory is underpinned by the increasing adoption of online business models, the proliferation of e-commerce, and evolving consumer preferences for ownership alternatives in both developed and emerging markets.

The primary growth driver for the rent-to-own platforms market is the shifting consumer mindset toward asset utilization rather than outright ownership. In an era marked by economic uncertainty and the growing gig economy, consumers are increasingly seeking flexible and affordable access to high-value products such as electronics, appliances, and automobiles. Rent-to-own platforms offer a compelling value proposition by enabling users to acquire essential goods without the burden of significant upfront capital. This model is particularly attractive to younger demographics, urban dwellers, and individuals with limited access to traditional credit, propelling the market’s expansion across various sectors.

Technological advancements and digital integration have also played a pivotal role in the market’s evolution. The proliferation of smartphones, the rise of digital payment solutions, and the integration of artificial intelligence in customer onboarding and risk assessment have streamlined the rent-to-own process, making it more accessible and efficient. Online platforms now offer seamless user experiences, from product selection and contract management to payment tracking and customer support. The ability to leverage data analytics for personalized offers and risk mitigation further enhances the appeal of rent-to-own services, fostering greater trust and repeat engagement among consumers.

Another significant factor fueling the rent-to-own platforms market is the expansion of product offerings and business models. Leading players are diversifying their portfolios beyond traditional consumer electronics and furniture to include appliances, automobiles, and even niche categories such as fitness equipment and home improvement tools. The emergence of hybrid business models—blending online convenience with offline touchpoints—caters to a broader customer base, including those who prefer in-person interactions. Moreover, the integration of flexible payment options, such as subscriptions and lease-to-own arrangements, provides customers with tailored solutions that align with their financial circumstances, further driving market penetration.

Regionally, North America continues to dominate the rent-to-own platforms market, accounting for the largest revenue share in 2024, followed closely by Europe and the Asia Pacific. The North American market benefits from high consumer awareness, mature digital infrastructure, and supportive regulatory frameworks. Meanwhile, rapid urbanization, rising disposable incomes, and increasing smartphone penetration are accelerating adoption rates in Asia Pacific, positioning the region as a key growth engine over the forecast period. Latin America and the Middle East & Africa, though comparatively nascent, are witnessing steady uptake due to growing fintech ecosystems and unbanked populations seeking alternative credit solutions.

Product Type Analysis

The product type segment of the rent-to-own platforms market is diverse, encompassing consumer electronics, furniture, appliances, automobiles, and other specialized categories. Consumer electronics remain the most significant contributor to market revenue, driven by the relentless pace of technological innovation and the high replacement rate of devices such as smartphones, laptops, and gaming consoles. Rent-to-own platforms have capitalized