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.
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Data on resident buyers who are persons that purchased a residential property in a market sale and filed their T1 tax return form: number of and incomes of residential property buyers, sale price, price-to-income ratio by the number of buyers as part of a sale, age groups, first-time home buyer status, buyer characteristics (sex, family type, immigration status, period of immigration, admission category).
The house price to income ratio in Canada peaked in the second quarter of 2022, followed by a decline until the second quarter of 2025. The ratio 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. Canada's index score in the second quarter of 2025 amounted to *****, which means that house price growth has outpaced income growth by almost **** percent since 2015. Canadian home prices continue to grow House prices in Canada have steadily increased over the past decade, despite a very mild decline in 2023. This trend is forecast to continue until 2026, albeit at a lower rate than in the period between 2019 and 2022. In British Columbia, which has consistently been the most expensive province for housing, the average house price is expected to reach nearly *** million Canadian dollars in 2026. The rising homeownership costs have also affected rents. In 2024, the average two-bedroom apartment rent in Vancouver exceeded ***** Canadian dollars. Canadian incomes on the rise Incomes in Canada have steadily risen since 2000 and show no signs of slowing down in the near future. This should improve housing affordability, as long as home price growth slows down.
The average resale house price in Canada was forecast to reach nearly ******* Canadian dollars in 2026, according to a January forecast. In 2024, house prices increased after falling for the first time since 2019. One of the reasons for the price correction was the notable drop in transaction activity. Housing transactions picked up in 2024 and are expected to continue to grow until 2026. British Columbia, which is the most expensive province for housing, is projected to see the average house price reach *** million Canadian dollars in 2026. Affordability in Vancouver Vancouver is the most populous city in British Columbia and is also infamously expensive for housing. In 2023, the city topped the ranking for least affordable housing market in Canada, with the average homeownership cost outweighing the average household income. There are a multitude of reasons for this, but most residents believe that foreigners investing in the market cause the high housing prices. Victoria housing market The capital of British Columbia is Victoria, where housing prices are also very high. The price of a single family home in Victoria's most expensive suburb, Oak Bay was *** million Canadian dollars in 2024.
Average and median market, total and after-tax income of individuals by visible minority group, Indigenous group and immigration status, Canada and provinces.
The house price for Ontario is forecast to decrease by eight percent in 2023, followed by a minor increase of one percent in 2024. From roughly 932,000 Canadian dollars, the average house price in Canada's second most expensive province for housing is expected to fall to 861,000 Canadian dollars in 2024. After British Columbia, Ontario is Canada's most expensive province for housing. Ontario Ontario is the most populated province in Canada, located on the eastern-central side of the country. It is an English speaking province. To the south, it borders American states Minnesota, Michigan, Ohio, Pennsylvania, and New York. Its provincial capital and largest city is Toronto. It is also home to Canada’s national capital, Ottawa. Furthermore, a large part of Ontario’s economy comes from manufacturing, as it is the leading manufacturing province in Canada. The population of Ontario has been steadily increasing since 2000. The population in 2018 was an estimated 14.3 million people. The median total family income in 2016 came to 83,160 Canadian dollars. Ontario housing market The number of housing units sold in Ontario is projected to rise until 2024. Additionally, the average home prices in Ontario have significantly increased since 2007.
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Data on resident buyers who are persons that purchased a residential property in a market sale and filed their T1 tax return form: number of and incomes of residential property buyers, sale price, price-to-income ratio by the number of buyers as part of a sale, age groups, first-time home buyer status, buyer characteristics (sex, family type, immigration status, period of immigration, admission category).
https://borealisdata.ca/api/datasets/:persistentId/versions/1.2/customlicense?persistentId=doi:10.5683/SP2/NYATT1https://borealisdata.ca/api/datasets/:persistentId/versions/1.2/customlicense?persistentId=doi:10.5683/SP2/NYATT1
This dataset includes Statistics Canada table 46-10-0050-01, titled "Total family income and owner characteristics at the residential property level by income quintiles". The dataset has been split up into three tables: Table A includes the number of properties and average assessment value of properties by the owner's income quintile, the property type (eg. detached house, condominium), and by family type (lone-parent family, couple family, and other census family). Table B includes includes the number of properties and average assessment value of properties by the owner's income quintile, the property type (eg. detached house, condominium), and by pension income categories (eg. whether or not the owner of the property is receiving a pension). Table C includes includes includes the number of properties and average assessment value of properties by the owner's income quintile, the property type (eg. detached house, condominium), and by residency participation types (eg. whether the property is owned by resident owners only or a mix of resident and non-resident owners). The tables have been edited to include only geographies from British Columbia and to have the unique ID numbers added to the Census Subdivisions and Census Metropolitan Areas. The tables are available in CSV and Excel Workbook format. Definitions and notes are included at the bottom of the spreadsheet. This data set was collected as part of the Canadian Housing Statistics Program by Statistics Canada. Geographies: Abbotsford-Mission, census metropolitan area, Abbotsford, Mission, Kelowna, census metropolitan area, Central Okanagan, Central Okanagan J, Kelowna, Lake Country, Peachland, West Kelowna, Vancouver, census metropolitan area, Anmore, Belcarra, Bowen Island, Burnaby, Coquitlam, Delta, Langley, city, Langley, municipal district, Lions Bay, Maple Ridge, Metro Vancouver A, New Westminster, North Vancouver, city, North Vancouver, municipal district, Pitt Meadows, Port Coquitlam, Port Moody, Richmond, Surrey, Vancouver, West Vancouver, White Rock, Victoria, census metropolitan area, Central Saanich, Colwood, Esquimalt, Highlands, Juan de Fuca (Part 1), Langford, Metchosin, North Saanich, Oak Bay, Saanich, Sidney, Sooke, Victoria, View Royal, British Columbia, outside of census metropolitan areas, Alberni-Clayoquot A, Alberni-Clayoquot B, Alberni-Clayoquot C, Alberni-Clayoquot D, Alberni-Clayoquot E, Alberni-Clayoquot F, Alert Bay, Armstrong, Ashcroft, Barriere, Bulkley-Nechako A, Bulkley-Nechako B, Bulkley-Nechako C, Bulkley-Nechako D, Bulkley-Nechako E, Bulkley-Nechako F, Bulkley-Nechako G, Burns Lake, Cache Creek, Campbell River, Canal Flats, Cariboo A, Cariboo B, Cariboo C, Cariboo D, Cariboo E, Cariboo F, Cariboo G, Cariboo H, Cariboo I, Cariboo J, Cariboo K, Cariboo L, Castlegar, Central Coast A, Central Coast C, Central Coast D, Central Coast E, Central Kootenay A, Central Kootenay B, Central Kootenay C, Central Kootenay D, Central Kootenay E, Central Kootenay F, Central Kootenay G, Central Kootenay H, Central Kootenay I, Central Kootenay J, Central Kootenay K, Chase, Chetwynd, Chilliwack, Clearwater, Clinton, Coldstream, Columbia-Shuswap A, Columbia-Shuswap B, Columbia-Shuswap C, Columbia-Shuswap D, Columbia-Shuswap E, Columbia-Shuswap F, Comox, Comox Valley A, Comox Valley B (Lazo North), Comox Valley C (Puntledge - Black Creek), Courtenay, Cowichan Valley A, Cowichan Valley B, Cowichan Valley C, Cowichan Valley D, Cowichan Valley E, Cowichan Valley F, Cowichan Valley G, Cowichan Valley H, Cowichan Valley I, Cranbrook, Creston, Cumberland, Dawson Creek, Duncan, East Kootenay A, East Kootenay B, East Kootenay C, East Kootenay E, East Kootenay F, East Kootenay G, Elkford, Enderby, Fernie, Fort St. James, Fort St. John, Fraser Lake, Fraser Valley A, Fraser Valley B, Fraser Valley C, Fraser Valley D, Fraser Valley E, Fraser Valley F, Fraser Valley G, Fraser Valley H, Fraser-Fort George A, Fraser-Fort George C, Fraser-Fort George D, Fraser-Fort George E, Fraser-Fort George F, Fraser-Fort George G, Fraser-Fort George H, Fruitvale, Gibsons, Gold River, Golden, Grand Forks, Granisle, Greenwood, Harrison Hot Springs, Hazelton, Hope, Houston, Hudson's Hope, Invermere, Juan de Fuca (Part 2), Kamloops, Kaslo, Kent, Keremeos, Kimberley, Kitimat, Kitimat-Stikine A, Kitimat-Stikine B, Kitimat-Stikine C (Part 1), Kitimat-Stikine C (Part 2), Kitimat-Stikine D, Kitimat-Stikine E, Kitimat-Stikine F, Kootenay Boundary A, Kootenay Boundary B / Lower Columbia-Old-Glory, Kootenay Boundary C / Christina Lake, Kootenay Boundary D / Rural Grand Forks, Kootenay Boundary E / West Boundary, Ladysmith, Lake Cowichan, Lantzville, Lillooet, Logan Lake, Lumby, Lytton, Mackenzie, Masset, McBride, Merritt, Midway, Montrose, Mount Waddington A, Mount Waddington B, Mount Waddington C, Mount Waddington D, Nakusp, Nanaimo, Nanaimo A, Nanaimo B, Nanaimo C, Nanaimo E, Nanaimo F, Nanaimo G, Nanaimo H, Nelson, New Denver, New Hazelton, North Coast A, North Coast C,...
https://borealisdata.ca/api/datasets/:persistentId/versions/3.1/customlicense?persistentId=doi:10.5683/SP3/LCXVCRhttps://borealisdata.ca/api/datasets/:persistentId/versions/3.1/customlicense?persistentId=doi:10.5683/SP3/LCXVCR
Note: Data on gender diverse households (formerly "2SLGBTQ+" households) has been added as of March 28th, 2025. For more information, please visit HART.ubc.ca. Housing Assessment Resource Tools (HART) This dataset contains 18 tables which draw upon data from the 2021 Canadian Census of Population. The tables are a custom order and contain data pertaining to core housing need and characteristics of households and dwellings. This custom order was placed in collaboration with Housing, Infrastructure and Communities Canada to fill data gaps in their Housing Needs Assessment Template. 17 of the tables each cover a different geography in Canada: one for Canada as a whole, one for all Canadian census divisions (CD), and 15 for all census subdivisions (CSD) across Canada. The 18th table contains the median income for all geographies. Statistics Canada used these median incomes as the "area median household income (AMHI)," from which they derived some of the data fields within the Shelter Costs/Household Income dimension. The dataset is in Beyond 20/20 (.ivt) format. The Beyond 20/20 browser is required in order to open it. This software can be freely downloaded from the Statistics Canada website: https://www.statcan.gc.ca/eng/public/beyond20-20 (Windows only). For information on how to use Beyond 20/20, please see: http://odesi2.scholarsportal.info/documentation/Beyond2020/beyond20-quickstart.pdf https://wiki.ubc.ca/Library:Beyond_20/20_Guide Custom order from Statistics Canada includes the following dimensions and data fields: Geography: - Country of Canada, all CDs & Country as a whole - All 10 Provinces (Newfoundland, Prince Edward Island (PEI), Nova Scotia, New Brunswick, Quebec, Ontario, Manitoba, Saskatchewan, Alberta, and British Columbia), all CSDs & each Province as a whole - All 3 Territories (Nunavut, Northwest Territories, Yukon), all CSDs & each Territory as a whole *- Data on gender diverse households is only available for geographies (provinces, territories, CDs, CSDs) with a population count greater than 50,000. Data Quality and Suppression: - The global non-response rate (GNR) is an important measure of census data quality. It combines total non-response (households) and partial non-response (questions). A lower GNR indicates a lower risk of non-response bias and, as a result, a lower risk of inaccuracy. The counts and estimates for geographic areas with a GNR equal to or greater than 50% are not published in the standard products. The counts and estimates for these areas have a high risk of non-response bias, and in most cases, should not be released. - Area suppression is used to replace all income characteristic data with an 'x' for geographic areas with populations and/or number of households below a specific threshold. If a tabulation contains quantitative income data (e.g., total income, wages), qualitative data based on income concepts (e.g., low income before tax status) or derived data based on quantitative income variables (e.g., indexes) for individuals, families or households, then the following rule applies: income characteristic data are replaced with an 'x' for areas where the population is less than 250 or where the number of private households is less than 40. Source: Statistics Canada - When showing count data, Statistics Canada employs random rounding in order to reduce the possibility of identifying individuals within the tabulations. Random rounding transforms all raw counts to random rounded counts. Reducing the possibility of identifying individuals within the tabulations becomes pertinent for very small (sub)populations. All counts greater than 10 are rounded to a base of 5, meaning they will end in either 0 or 5. The random rounding algorithm controls the results and rounds the unit value of the count according to a predetermined frequency. Counts ending in 0 or 5 are not changed. Counts less than 10 are rounded to a base of 10, meaning they will be rounded to either 10 or Zero. Universe: Private Households in Non-farm Non-band Off-reserve Occupied Private Dwellings with Income Greater than zero. Households examined for Core Housing Need: Private, non-farm, non-reserve, owner- or renter-households with incomes greater than zero and shelter-cost-to-income ratios less than 100% are assessed for 'Core Housing Need.' Non-family Households with at least one household maintainer aged 15 to 29 attending school are considered not to be in Core Housing Need, regardless of their housing circumstances. Data Fields: Tenure Including Presence of Mortgage and Subsidized Housing; Household size (7) 1. Total - Private households by tenure including presence of mortgage payments and subsidized housing 2. Owner 3. With mortgage 4. Without mortgage 5. Renter 6. Subsidized housing 7. Not subsidized housing Housing indicators in Core Housing Universe (12) 1. Total - Private Households by core housing need status 2. Households examined for core housing need 3. Households in core...
https://borealisdata.ca/api/datasets/:persistentId/versions/2.0/customlicense?persistentId=doi:10.5683/SP3/KW09ZAhttps://borealisdata.ca/api/datasets/:persistentId/versions/2.0/customlicense?persistentId=doi:10.5683/SP3/KW09ZA
For more information, please visit HART.ubc.ca. Housing Assessment Resource Tools (HART) This dataset includes 18 tables which draw upon data from the 2006 Census of Canada. The tables are a custom order and contains data pertaining to core housing need and characteristics of households. 16 of the tables each cover a different geography in Canada: one for Canada as a whole, one for all Canadian census divisions (CD), and 14 for all census subdivisions (CSD) across Canada. The last two tables contains the median income for all geographies. Statistics Canada used these median incomes as the "area median household income (AMHI)," from which they derived some of the variables within the Shelter Costs/Household Income dimension. Included alongside the data tables is a guide to HART's housing need assessment methodology. This guide is intended to support independent use of HART's custom data both to allow for transparent verification of our analysis, as well as supporting efforts to utilize the data for analysis beyond what HART did. There are many variables in the data order that we did not use that may be of value for others. The dataset is in Beyond 20/20 (.ivt) format. The Beyond 20/20 browser is required in order to open it. This software can be freely downloaded from the Statistics Canada website: https://www.statcan.gc.ca/eng/public/beyond20-20 (Windows only). For information on how to use Beyond 20/20, please see: http://odesi2.scholarsportal.info/documentation/Beyond2020/beyond20-quickstart.pdf https://wiki.ubc.ca/Library:Beyond_20/20_Guide Custom order from Statistics Canada includes the following dimensions and variables: Geography: - Country of Canada, all CDs & Country as a whole - All 10 Provinces (Newfoundland, Prince Edward Island (PEI), Nova Scotia, New Brunswick, Quebec, Ontario, Manitoba, Saskatchewan, Alberta, and British Columbia), all CSDs & each Province as a whole - All 3 Territories (Nunavut, Northwest Territories, Yukon), all CSDs & each Territory as a whole The global non-response rate (GNR) is an important measure of census data quality. It combines total non-response (households) and partial non-response (questions). A lower GNR indicates a lower risk of non-response bias and, as a result, a lower risk of inaccuracy. The counts and estimates for geographic areas with a GNR equal to or greater than 50% are not published in the standard products. The counts and estimates for these areas have a high risk of non-response bias, and in most cases, should not be released. Universe: Full Universe: Private Households in Non-farm Non-band Off-reserve Occupied Private Dwellings with Income Greater than zero. Households examined for Core Housing Need: Private, non-farm, non-reserve, owner- or renter-households with incomes greater than zero and shelter-cost-to-income ratios less than 100% are assessed for 'Core Housing Need.' Non-family Households with at least one household maintainer aged 15 to 29 attending school are considered not to be in Core Housing Need, regardless of their housing circumstances. Variables: Housing indicators in Core Housing Universe (3) 1. Total - Private Households by core housing need status 2. Households examined for core housing need 3. Households in core housing need Tenure Including Presence of Mortgage and Subsidized Housing; Household size (11) 1. Total - Household tenure and mortgage status 2. Owners 3. With mortgage 4. Without mortgage 5. Renters 6. Total - Household size 7. 1 person 8. 2 persons 9. 3 persons 10. 4 persons 11. 5 or more persons Shelter costs groups/statistics (20) 1. Total – Private households by household income proportion to AMHI_1 2. Households with income 20% or under of area median household income (AMHI) 3. Households with income 21% to 50% of AMHI 4. Households with income 51% to 80% of AMHI 5. Households with income 81% to 120% of AMHI 6. Households with income 121% or over of AMHI 7. Total – Private households by household income proportion to AMHI_2 8. Households with income 30% and under of AMHI 9. Households with income 31% to 60% of AMHI 10. Households with income 61% or more of AMHI 11. Total – Private households by shelter cost proportion to AMHI_1 12. Households with shelter cost 0.5% and under of AMHI 13. Households with shelter cost 0.6% to 1.25% of AMHI 14. Households with shelter cost 1.26% to 2% of AMHI 15. Households with shelter cost 2.1% to 3% of AMHI 16. Households with shelter cost 3.1% or over of AMHI 17. Total – Private households by shelter cost proportion to AMHI_2 18. Households with shelter cost 0.75% or under of AMHI 19. Households with shelter cost 0.76% to 1.5% of AMHI 20. Households with shelter cost greater than or equal to 1.6% of AMHI Selected characteristics of the households (47) 1.Total - Household type 2. Census-family households 3. One-census-family households 4. Couple-family households 5. With children 6. Without children 7. Lone-parent-family households 8. Multiple-family households...
This table is part of a series of tables that present a portrait of Canada based on the various census topics. The tables range in complexity and levels of geography. Content varies from a simple overview of the country to complex cross-tabulations; the tables may also cover several censuses.
RE/MAX Canada brokers and agents in 24 key markets across the country were asked to provide their analysis on local market activity and housing affordability trends for the first half of 2022. Toronto, ON and Kelowna, BC (July 20, 2022) — RE/MAX® Canada’s 2022 Housing Affordability Report reveals that 68 per cent of Canadians are willing to make at least one sacrifice to buy a home they can afford, according to a Leger survey commissioned by RE/MAX Canada. The most common concession is relocation, as identified by 64 per cent of survey respondents – a trend that continues to reign as a primary influence in local housing markets across the country, say RE/MAX brokers. This is followed by 56 per cent indicating they would be willing to sacrifice the type of home they purchased; purchasing a home under co-ownership with family and friends, as identified by 29 per cent of survey respondents; and renting a part of their home for additional income, at 27 per cent. According to the same Leger survey, 43 per cent of Canadians said the high price of real estate in their area was a barrier to entry into the market. This is up one per cent from last year. Other hurdles include a higher cost of living (35 per cent); a shortfall in salary (24 per cent, down two per cent from 2021); market volatility (24 per cent); and rising interest rates (24 per cent, up six per cent from 2021).
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Net-Interest-Income Time Series for H&R Real Estate Investment Trust. H&R REIT is one of Canada's largest real estate investment trusts with total assets of approximately $10.5 billion as at March 31, 2025. H&R REIT has ownership interests in a Canadian and U.S. portfolio comprised of high-quality residential, industrial, office and retail properties comprising over 25.6 million square feet. H&R's strategy is to create a simplified, growth-oriented business focused on residential and industrial properties in order to create sustainable long-term value for unitholders. H&R plans to sell its office and retail properties as market conditions permit. H&R's target is to be a leading owner, operator and developer of residential and industrial properties, creating value through redevelopment and greenfield development in prime locations within Toronto and high growth U.S. sunbelt and gateway cities.
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This dataset includes one dataset which was custom ordered from Statistics Canada.The table includes information on housing suitability and shelter-cost-to-income ratio by number of bedrooms, housing tenure, age of primary household maintainer, household type, and income quartile ranges for census subdivisions in British Columbia. The dataset is in Beyond 20/20 (.ivt) format. The Beyond 20/20 browser is required in order to open it. This software can be freely downloaded from the Statistics Canada website: https://www.statcan.gc.ca/eng/public/beyond20-20 (Windows only). For information on how to use Beyond 20/20, please see: http://odesi2.scholarsportal.info/documentation/Beyond2020/beyond20-quickstart.pdf https://wiki.ubc.ca/Library:Beyond_20/20_Guide Custom order from Statistics Canada includes the following dimensions and variables: Geography: Non-reserve CSDs in British Columbia - 299 geographies The global non-response rate (GNR) is an important measure of census data quality. It combines total non-response (households) and partial non-response (questions). A lower GNR indicates a lower risk of non-response bias and, as a result, a lower risk of inaccuracy. The counts and estimates for geographic areas with a GNR equal to or greater than 50% are not published in the standard products. The counts and estimates for these areas have a high risk of non-response bias, and in most cases, should not be released. Housing Tenure Including Presence of Mortgage (5) 1. Total – Private non-band non-farm off-reserve households with an income greater than zero by housing tenure 2. Households who own 3. With a mortgage1 4. Without a mortgage 5. Households who rent Notes: 1) Presence of mortgage - Refers to whether the owner households reported mortgage or loan payments for their dwelling. 2015 Before-tax Household Income Quartile Ranges (5) 1. Total – Private households by quartile ranges1, 2, 3 2. Count of households under or at quartile 1 3. Count of households between quartile 1 and quartile 2 (median) (including at quartile 2) 4. Count of households between quartile 2 (median) and quartile 3 (including at quartile 3) 5. Count of households over quartile 3 Notes: 1) A private household will be assigned to a quartile range depending on its CSD-level location and depending on its tenure (owned and rented). Quartile ranges for owned households in a specific CSD are delimited by the 2015 before-tax income quartiles of owned households with an income greater than zero and residing in non-farm off-reserve dwellings in that CSD. Quartile ranges for rented households in a specific CSD are delimited by the 2015 before-tax income quartiles of rented households with an income greater than zero and residing in non-farm off-reserve dwellings in that CSD. 2) For the income quartiles dollar values (the delimiters) please refer to Table 1. 3) Quartiles 1 to 3 are suppressed if the number of actual records used in the calculation (not rounded or weighted) is less than 16. For cases in which the renters’ quartiles or the owners’ quartiles (figures from Table 1) of a CSD are suppressed the CSD is assigned to a quartile range depending on the provincial renters’ or owners’ quartile figures. Number of Bedrooms (Unit Size) (6) 1. Total – Private households by number of bedrooms1 2. 0 bedrooms (Bachelor/Studio) 3. 1 bedroom 4. 2 bedrooms 5. 3 bedrooms 6. 4 bedrooms Note: 1) Dwellings with 5 bedrooms or more included in the total count only. Housing Suitability (6) 1. Total - Housing suitability 2. Suitable 3. Not suitable 4. One bedroom shortfall 5. Two bedroom shortfall 6. Three or more bedroom shortfall Note: 1) 'Housing suitability' refers to whether a private household is living in suitable accommodations according to the National Occupancy Standard (NOS); that is, whether the dwelling has enough bedrooms for the size and composition of the household. A household is deemed to be living in suitable accommodations if its dwelling has enough bedrooms, as calculated using the NOS. 'Housing suitability' assesses the required number of bedrooms for a household based on the age, sex, and relationships among household members. An alternative variable, 'persons per room,' considers all rooms in a private dwelling and the number of household members. Housing suitability and the National Occupancy Standard (NOS) on which it is based were developed by Canada Mortgage and Housing Corporation (CMHC) through consultations with provincial housing agencies. Shelter-cost-to-income-ratio (4) 1. Total – Private non-band non-farm off-reserve households with an income greater than zero 2. Spending less than 30% of households total income on shelter costs 3. Spending 30% or more of households total income on shelter costs 4. Spending 50% or more of households total income on shelter costs Note: 'Shelter-cost-to-income ratio' refers to the proportion of average total income of household which is spent on shelter costs. Household Statistics (8) 1....
Housing Assessment Resource Tools (HART) This dataset contains 2 tables and 5 files which draw upon data from the 2021 Census of Canada. The tables are a custom order and contain data pertaining to older adults and housing need. The 2 tables have 6 dimensions in common and 1 dimension that is unique to each table. Table 1's unique dimension is the "Ethnicity / Indigeneity status" dimension which contains data fields related to visible minority and Indigenous identity within the population in private households. Table 2's unique dimension is "Structural type of dwelling and Period of Construction" which contains data fields relating to the structural type and period of construction of the dwelling. Each of the two tables is then split into multiple files based on geography. Table 1 has two files: Table 1.1 includes Canada, Provinces and Territories (14 geographies), CDs of NWT (6), CDs of Yukon (1) and CDs of Nunavut (3); and Table 1.2 includes Canada and the CMAs of Canada (44). Table 2 has three files: Table 2.1 includes Canada, Provinces and Territories (14), CDs of NWT (6), CDs of Yukon (1) and CDs of Nunavut (3); Table 2.2 includes Canada and the CMAs of Canada excluding Ontario and Quebec (20 geographies); and Table 2.3 includes Canada and the CMAs of Canada that are in Ontario and Quebec (25 geographies). The dataset is in Beyond 20/20 (.ivt) format. The Beyond 20/20 browser is required in order to open it. This software can be freely downloaded from the Statistics Canada website: https://www.statcan.gc.ca/eng/public/beyond20-20 (Windows only). For information on how to use Beyond 20/20, please see: http://odesi2.scholarsportal.info/documentation/Beyond2020/beyond20-quickstart.pdf https://wiki.ubc.ca/Library:Beyond_20/20_Guide Custom order from Statistics Canada includes the following dimensions and data fields: Geography: - Country of Canada as a whole - All 10 Provinces (Newfoundland, Prince Edward Island (PEI), Nova Scotia, New Brunswick, Quebec, Ontario, Manitoba, Saskatchewan, Alberta, and British Columbia) as a whole - All 3 Territories (Nunavut, Northwest Territories, Yukon), as a whole as well as all census divisions (CDs) within the 3 territories - All 43 census metropolitan areas (CMAs) in Canada Data Quality and Suppression: - The global non-response rate (GNR) is an important measure of census data quality. It combines total non-response (households) and partial non-response (questions). A lower GNR indicates a lower risk of non-response bias and, as a result, a lower risk of inaccuracy. The counts and estimates for geographic areas with a GNR equal to or greater than 50% are not published in the standard products. The counts and estimates for these areas have a high risk of non-response bias, and in most cases, should not be released. - Area suppression is used to replace all income characteristic data with an 'x' for geographic areas with populations and/or number of households below a specific threshold. If a tabulation contains quantitative income data (e.g., total income, wages), qualitative data based on income concepts (e.g., low income before tax status) or derived data based on quantitative income variables (e.g., indexes) for individuals, families or households, then the following rule applies: income characteristic data are replaced with an 'x' for areas where the population is less than 250 or where the number of private households is less than 40. Source: Statistics Canada - When showing count data, Statistics Canada employs random rounding in order to reduce the possibility of identifying individuals within the tabulations. Random rounding transforms all raw counts to random rounded counts. Reducing the possibility of identifying individuals within the tabulations becomes pertinent for very small (sub)populations. All counts are rounded to a base of 5, meaning they will end in either 0 or 5. The random rounding algorithm controls the results and rounds the unit value of the count according to a predetermined frequency. Counts ending in 0 or 5 are not changed. Universe: Full Universe: Population aged 55 years and over in owner and tenant households with household total income greater than zero in non-reserve non-farm private dwellings. Definition of Households examined for Core Housing Need: Private, non-farm, non-reserve, owner- or renter-households with incomes greater than zero and shelter-cost-to-income ratios less than 100% are assessed for 'Core Housing Need.' Non-family Households with at least one household maintainer aged 15 to 29 attending school are considered not to be in Core Housing Need, regardless of their housing circumstances. Data Fields: Table 1: Age / Gender (12) 1. Total – Population 55 years and over 2. Men+ 3. Women+ 4. 55 to 64 years 5. Men+ 6. Women+ 7. 65+ years 8. Men+ 9. Women+ 10. 85+ 11. Men+ 12. Women+ Housing indicators (13) 1. Total – Private Households by core housing need status 2. Households below one standard only...
Survey of Household Spending (SHS), average household spending, Canada, regions and provinces.
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
This table is part of a series of tables that present a portrait of Canada based on the various census topics. The tables range in complexity and levels of geography. Content varies from a simple overview of the country to complex cross-tabulations; the tables may also cover several censuses.
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
This table is part of a series of tables that present a portrait of Canada based on the various census topics. The tables range in complexity and levels of geography. Content varies from a simple overview of the country to complex cross-tabulations; the tables may also cover several censuses.
This table provides data on core housing need and costs for the 3 largest visible minority groups in each region. Learn more about visible minority households in core housing need with data on: number and average incomes shelter costs shelter-cost-to-income ratios (STIRs) This data is organized by: region and minority group for Canada the provinces and territories selected Census Metropolitan Areas (CMAs)
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
This table is part of a series of tables that present a portrait of Canada based on the various census topics. The tables range in complexity and levels of geography. Content varies from a simple overview of the country to complex cross-tabulations; the tables may also cover several censuses.
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.