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.

The house price to income index in Europe declined in almost all European countries in 2023, indicating that income grew faster than house prices. Portugal, Luxembourg, and the Netherlands led the house price to income index ranking in 2023, with values exceeding *** index points. Romania, Bulgaria, and Finland were on the other side of the spectrum, with less than 100 index points. The house price to income ratio is an indicator for the development of housing affordability 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. A ratio higher than 100 means that the nominal house price growth since 2015 has outpaced the nominal disposable income growth, and housing is therefore comparatively less affordable. In 2023, the OECD average stood at ***** index points.

This service shows the proportion of average total income of households which is spent on shelter costs by census subdivision. The data is from the Census Profile, Statistics Canada Catalogue no. 98-316-X2016001. Shelter-cost-to-income ratio is calculated for private households living in owned or rented dwellings who reported a total household income greater than zero. Private households living in band housing, located on an agricultural operation that is operated by a member of the household, and households who reported a zero or negative total household income are excluded. The relatively high shelter-costs-to-household income ratios for some households may have resulted from the difference in the reference period for shelter costs and household total income data. The reference period for shelter cost data is 2016, while household total income is reported for the year 2015. As well, for some households, the 2015 household total income may represent income for only part of a year. For additional information refer to the 2016 Census Dictionary for 'Total income' and 'Shelter cost'. To have a cartographic representation of the ecumene with this socio-economic indicator, it is recommended to add as the first layer, the “NRCan - 2016 population ecumene by census subdivision” web service, accessible in the data resources section below.

Shelter-cost-to-income ratio by tenure for Canada, provinces and territories, census metropolitan areas and census agglomerations. Includes household total income groups, household type including census family structure, housing suitability and dwelling condition.

Portugal, the Netherlands and Austria are among the countries where house prices grew the most in comparison to income since 2015. In the fourth quarter of 2024, the house price to income ratio in the Netherlands and Austria exceeded *** index points, indicating that since 2015, house price growth has outpaced income growth by ** percent. In Portugal, the index amounted to *** index points in the same period. This was not the case in all countries in the ranking: In Finland, Bulgaria, and Romania, the opposite trend was observed, showing that incomes grew faster than house prices. The house price to income ratio is calculated as the nominal house prices divided by nominal income per capita, with 2015 chosen as the base year of the index. The ratio signifies the development of housing affordability, with higher figures meaning housing is more unaffordable. There are other indices, such as RHPI (or house price indices corrected by inflation rates) which look at this as well.

Number of persons by shelter-cost-to-income ratio, tenure, First Nations people living off reserve, Métis and Inuit and gender, Canada, provinces and territories.

The house price-to-income ratio in Australia was ***** as of the fourth quarter of 2024. This ratio, calculated by dividing nominal house prices by nominal disposable income per head, increased from the previous quarter. The price-to-income ratio can be used to measure housing affordability in a specific area. Australia's property bubble There has been considerable debate over the past decade about whether Australia is in a property bubble or not. A property bubble refers to a sharp increase in the price of property that is disproportional to income and rental prices, followed by a decline. In Australia, rising house prices have undoubtedly been an issue for many potential homeowners, pricing them out of the market. Along with the average house price, high mortgage interest rates have exacerbated the issue. Is the homeownership dream out of reach? Housing affordability has varied across the different states and territories in Australia. In 2024, the median value of residential houses was the highest in Sydney compared to other major Australian cities, with Brisbane becoming an increasingly expensive city. Nonetheless, expected interest rate cuts in 2025, alongside the expansion of initiatives to improve Australia's dwelling stock, social housing supply, and first-time buyer accessibility to properties, may start to improve the situation. These encompass initiatives such as the Australian government's Help to Buy scheme and the Housing Australia Future Fund Facility (HAFFF) and National Housing Accord Facility (NHAF) programs.

Quality of Life Index (higher is better) is an estimation of overall quality of life by using an empirical formula which takes into account purchasing power index (higher is better), pollution index (lower is better), house price to income ratio (lower is better), cost of living index (lower is better), safety index (higher is better), health care index (higher is better), traffic commute time index (lower is better) and climate index (higher is better).

Current formula (written in Java programming language):

index.main = Math.max(0, 100 + purchasingPowerInclRentIndex / 2.5 - (housePriceToIncomeRatio * 1.0) - costOfLivingIndex / 10 + safetyIndex / 2.0 + healthIndex / 2.5 - trafficTimeIndex / 2.0 - pollutionIndex * 2.0 / 3.0 + climateIndex / 3.0);

For details how purchasing power (including rent) index, pollution index, property price to income ratios, cost of living index, safety index, climate index, health index and traffic index are calculated please look up their respective pages.

Formulas used in the past

Formula used between June 2017 and Decembar 2017

We decided to decrease weight from costOfLivingIndex in this formula:

index.main = Math.max(0, 100 + purchasingPowerInclRentIndex / 2.5 - (housePriceToIncomeRatio * 1.0) - costOfLivingIndex / 5 + safetyIndex / 2.0 + healthIndex / 2.5 - trafficTimeIndex / 2.0 - pollutionIndex * 2.0 / 3.0 + climateIndex / 3.0);

The World Happiness 2017, which ranks 155 countries by their happiness levels, was released at the United Nations at an event celebrating International Day of Happiness on March 20th. The report continues to gain global recognition as governments, organizations and civil society increasingly use happiness indicators to inform their policy-making decisions. Leading experts across fields – economics, psychology, survey analysis, national statistics, health, public policy and more – describe how measurements of well-being can be used effectively to assess the progress of nations. The reports review the state of happiness in the world today and show how the new science of happiness explains personal and national variations in happiness.

The scores are based on answers to the main life evaluation question asked in the poll. This question, known as the Cantril ladder, asks respondents to think of a ladder with the best possible life for them being a 10 and the worst possible life being a 0 and to rate their own current lives on that scale. The scores are from nationally representative samples for 2017 and use the Gallup weights to make the estimates representative. The columns following the happiness score estimate the extent to which each of six factors – economic production, social support, life expectancy, freedom, absence of corruption, and generosity – contribute to making life evaluations higher in each country than they are in Dystopia, a hypothetical country that has values equal to the world’s lowest national averages for each of the six factors. They have no impact on the total score reported for each country, but they do explain why some countries rank higher than others.

Quality of life index, link: https://www.numbeo.com/quality-of-life/indices_explained.jsp

Happiness store, link: https://www.kaggle.com/unsdsn/world-happiness/home

The US Family Budget Dataset provides insights into the cost of living in different US counties based on the Family Budget Calculator by the Economic Policy Institute (EPI).

This dataset offers community-specific estimates for ten family types, including one or two adults with zero to four children, in all 1877 counties and metro areas across the United States.

Interesting Task Ideas:

1. See how family budgets compare to the federal poverty line and the Supplemental Poverty Measure in different counties.
2. Look into the money challenges faced by different types of families using the budgets provided.
3. Find out which counties have the most affordable places to live, food, transportation, healthcare, childcare, and other things people need.
4. Explore how the average income of families relates to the overall cost of living in different counties.
5. Investigate how family size affects the estimated budget and find counties where bigger families have higher costs.
6. Create visuals showing how the cost of living varies across different states and big cities.
7. Check whether specific counties are affordable for families of different sizes and types.
8. Use the dataset to compare living standards and economic security in different US counties.

If you find this dataset valuable, don't forget to hit the upvote button! 😊💝

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This statistic shows the median household income in the United States from 1990 to 2023 in 2023 U.S. dollars. The median household income was 80,610 U.S. dollars in 2023, an increase from the previous year. Household incomeThe median household income depicts the income of households, including the income of the householder and all other individuals aged 15 years or over living in the household. Income includes wages and salaries, unemployment insurance, disability payments, child support payments received, regular rental receipts, as well as any personal business, investment, or other kinds of income received routinely. The median household income in the United States varies from state to state. In 2020, the median household income was 86,725 U.S. dollars in Massachusetts, while the median household income in Mississippi was approximately 44,966 U.S. dollars at that time. Household income is also used to determine the poverty line in the United States. In 2021, about 11.6 percent of the U.S. population was living in poverty. The child poverty rate, which represents people under the age of 18 living in poverty, has been growing steadily over the first decade since the turn of the century, from 16.2 percent of the children living below the poverty line in year 2000 to 22 percent in 2010. In 2021, it had lowered to 15.3 percent. The state with the widest gap between the rich and the poor was New York, with a Gini coefficient score of 0.51 in 2019. The Gini coefficient is calculated by looking at average income rates. A score of zero would reflect perfect income equality and a score of one indicates a society where one person would have all the money and all other people have nothing.

There is more to housing affordability than the rent or mortgage you pay. Transportation costs are the second-biggest budget item for most families, but it can be difficult for people to fully factor transportation costs into decisions about where to live and work. The Location Affordability Index (LAI) is a user-friendly source of standardized data at the neighborhood (census tract) level on combined housing and transportation costs to help consumers, policymakers, and developers make more informed decisions about where to live, work, and invest. Compare eight household profiles (see table below) —which vary by household income, size, and number of commuters—and see the impact of the built environment on affordability in a given location while holding household demographics constant.*$11,880 for a single person household in 2016 according to US Dept. of Health and Human Services: https://aspe.hhs.gov/computations-2016-poverty-guidelinesThis layer is symbolized by the percentage of housing and transportation costs as a percentage of income for the Median-Income Family profile, but the costs as a percentage of income for all household profiles are listed in the pop-up:Also available is a gallery of 8 web maps (one for each household profile) all symbolized the same way for easy comparison: Median-Income Family, Very Low-Income Individual, Working Individual, Single Professional, Retired Couple, Single-Parent Family, Moderate-Income Family, and Dual-Professional Family.An accompanying story map provides side-by-side comparisons and additional context.--Variables used in HUD's calculations include 24 measures such as people per household, average number of rooms per housing unit, monthly housing costs (mortgage/rent as well as utility and maintenance expenses), average number of cars per household, median commute distance, vehicle miles traveled per year, percent of trips taken on transit, street connectivity and walkability (measured by block density), and many more.To learn more about the Location Affordability Index (v.3) visit: https://www.hudexchange.info/programs/location-affordability-index/. There you will find some background and an FAQ page, which includes the question:"Manhattan, San Francisco, and downtown Boston are some of the most expensive places to live in the country, yet the LAI shows them as affordable for the typical regional household. Why?" These areas have some of the lowest transportation costs in the country, which helps offset the high cost of housing. The area median income (AMI) in these regions is also high, so when costs are shown as a percent of income for the typical regional household these neighborhoods appear affordable; however, they are generally unaffordable to households earning less than the AMI.Date of Coverage: 2012-2016 Date Released: March 2019Date Downloaded from HUD Open Data: 4/18/19Further Documentation:LAI Version 3 Data and MethodologyLAI Version 3 Technical Documentation_**The documentation below is in reference to this items placement in the NM Supply Chain Data Hub. The documentation is of use to understanding the source of this item, and how to reproduce it for updates**

Title: Location Affordability Index - NMCDC Copy

Summary: This layer contains the Location Affordability Index from U.S. Dept. of Housing and Urban Development (HUD) - standardized household, housing, and transportation cost estimates by census tract for 8 household profiles.

Notes: This map is copied from source map: https://nmcdc.maps.arcgis.com/home/item.html?id=de341c1338c5447da400c4e8c51ae1f6, created by dianaclavery_uo, and identified in Living Atlas.

Prepared by: dianaclavery_uo, copied by EMcRae_NMCDC

Source: This map is copied from source map: https://nmcdc.maps.arcgis.com/home/item.html?id=de341c1338c5447da400c4e8c51ae1f6, created by dianaclavery_uo, and identified in Living Atlas. Check the source documentation or other details above for more information about data sources.

Feature Service: https://nmcdc.maps.arcgis.com/home/item.html?id=447a461f048845979f30a2478b9e65bb

UID: 73

Data Requested: Family income spent on basic need

Method of Acquisition: Search for Location Affordability Index in the Living Atlas. Make a copy of most recent map available. To update this map, copy the most recent map available. In a new tab, open the AGOL Assistant Portal tool and use the functions in the portal to copy the new maps JSON, and paste it over the old map (this map with item id

Date Acquired: Map copied on May 10, 2022

Priority rank as Identified in 2022 (scale of 1 being the highest priority, to 11 being the lowest priority): 6

Tags: PENDING

Number of persons by shelter-cost-to-income ratio, tenure, First Nations people living off reserve, Métis and Inuit and gender, Canada, provinces and territories.

This is the proportion of children aged under 16 (0-15) living in families in absolute low income during the year. The figures are based on the count of children aged under 16 (0-15) living in the area derived from ONS mid-year population estimates. The count of children refers to the age of the child at 30 June of each year.

Low income is a family whose equivalised income is below 60 per cent of median household incomes. Gross income measure is Before Housing Costs (BHC) and includes contributions from earnings, state support, and pensions. Equivalisation adjusts incomes for household size and composition, taking an adult couple with no children as the reference point. For example, the process of equivalisation would adjust the income of a single person upwards, so their income can be compared directly to the standard of living for a couple.

Absolute low income is income Before Housing Costs (BHC) in the reference year in comparison with incomes in 2010/11 adjusted for inflation. A family must have claimed one or more of Universal Credit, Tax Credits, or Housing Benefit at any point in the year to be classed as low income in these statistics. Children are dependent individuals aged under 16; or aged 16 to 19 in full-time non-advanced education. The count of children refers to the age of the child at 31 March of each year.

Data are calibrated to the Households Below Average Income (HBAI) survey regional estimates of children in low income but provide more granular local area information not available from the HBAI. For further information and methodology on the construction of these statistics, visit this link. Totals may not sum due to rounding.

Data is Powered by LG Inform Plus and automatically checked for new data on the 3rd of each month.

Between April 2008 and March 2024, households from the Pakistani and Bangladeshi ethnic groups were the most likely to live in low income out of all ethnic groups, before and after housing costs.

Percentage of the population living in a household where total housing costs (net of housing allowances) represent more than 40% of the total disposable household income (net of housing allowances).

Low-income cut-offs, after tax (LICO-AT) - The Low-income cut-offs, after tax refers to an income threshold, defined using 1992 expenditure data, below which economic families or persons not in economic families would likely have devoted a larger share of their after-tax income than average to the necessities of food, shelter and clothing. More specifically, the thresholds represented income levels at which these families or persons were expected to spend 20 percentage points or more of their after-tax income than average on food, shelter and clothing. These thresholds have been adjusted to current dollars using the all-items Consumer Price Index (CPI).The LICO-AT has 35 cut-offs varying by seven family sizes and five different sizes of area of residence to account for economies of scale and potential differences in cost of living in communities of different sizes. These thresholds are presented in Table 4.3 Low-income cut-offs, after tax (LICO-AT - 1992 base) for economic families and persons not in economic families, 2015, Dictionary, Census of Population, 2016.When the after-tax income of an economic family member or a person not in an economic family falls below the threshold applicable to the person, the person is considered to be in low income according to LICO-AT. Since the LICO-AT threshold and family income are unique within each economic family, low-income status based on LICO-AT can also be reported for economic families.Return to footnote1referrerFootnote 2Low-income status - The income situation of the statistical unit in relation to a specific low-income line in a reference year. Statistical units with income that is below the low-income line are considered to be in low income.For the 2016 Census, the reference period is the calendar year 2015 for all income variables.Return to footnote2referrerFootnote 3The low-income concepts are not applied in the territories and in certain areas based on census subdivision type (such as Indian reserves). The existence of substantial in-kind transfers (such as subsidized housing and First Nations band housing) and sizeable barter economies or consumption from own production (such as product from hunting, farming or fishing) could make the interpretation of low-income statistics more difficult in these situations.Return to footnote3referrerFootnote 4Prevalence of low income - The proportion or percentage of units whose income falls below a specified low-income line.

Table showing the country rankings based in the different metrics analysed

Expenditure on rent by renters and mortgages by mortgage holders, by region and age from the Living Costs and Food Survey for the financial year ending 2022. Data is presented as a proportion of total expenditure and a proportion of disposable income.

This indicator is defined as the ratio of the average house price (detached, semi-detached, terraced, flat/maisonette) in a local authority to the average, gross, full time annual earnings in a local authority. The purpose of this indicator is to monitor progress towards improving housing opportunities and affordable housing. It measures the relationship between average full time earnings and average house prices within an area and therefore provides an indication of how affordable housing is in that area. The ratio using residence based earnings information measures how affordable housing is for those living in the area, the indicator using workplace earnings information measures how affordable local housing is for those working in the area. The two together provide a picture of the different circumstances of those living or working in an area. Monitored over time this indicator will measure how quickly housing costs are increasing relative to the increase in average earnings. The indicator has limitations as it does not measure the affordability of privately rented or social housing. In addition, it only measures the income of people working full time and excludes part time workers, those who are self-employed and those claiming benefits. Information on those claiming benefits are measured by indicators 1.1, 1.2, 1.3 and 1.6 in the local basket of inequalities indicators. Nevertheless this indicator provides an indication of the overall housing opportunities in an area. This indicator has been discontinued and so there will be no further updates. Legacy unique identifier: P01086

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GapMinder collects data from a handful of sources, including the Institute for Health Metrics and Evaluation, the US Census Bureau’s International Database, the United Nations Statistics Division, and the World Bank.

Variable Name & Description of Indicator:

• country: Unique Identifier
• incomeperperson: Gross Domestic Product per capita in constant 2000 US$. The inflation but not the differences in the cost of living between countries has been taken into account.
• Internetuserate: Internet users (per 100 people) Internet users are people with access to the worldwide network.
• urbanrate: Urban population (% of total) Urban population refers to people living in urban areas as defined by national statistical offices (calculated using World Bank population estimates and urban ratios from the United Nations World Urbanization Prospects)

More information is available at www.gapminder.org