Of the most populous cities in the U.S., San Jose, California had the highest annual income requirement at 288,953 U.S. dollars annually for homeowners to have an affordable and comfortable life in 2024. This can be compared to Houston, Texas, where homeowners needed an annual income of 87,991 U.S. dollars in 2024.

West Virginia and Kansas had the lowest cost of living across all U.S. states, with composite costs being half of those found in Hawaii. This was according to a composite index that compares prices for various goods and services on a state-by-state basis. In West Virginia, the cost of living index amounted to **** — well below the national benchmark of 100. Virginia— which had an index value of ***** — was only slightly above that benchmark. Expensive places to live included Hawaii, Massachusetts, and California. Housing costs in the U.S. Housing is usually the highest expense in a household’s budget. In 2023, the average house sold for approximately ******* U.S. dollars, but house prices in the Northeast and West regions were significantly higher. Conversely, the South had some of the least expensive housing. In West Virginia, Mississippi, and Louisiana, the median price of the typical single-family home was less than ******* U.S. dollars. That makes living expenses in these states significantly lower than in states such as Hawaii and California, where housing is much pricier. What other expenses affect the cost of living? Utility costs such as electricity, natural gas, water, and internet also influence the cost of living. In Alaska, Hawaii, and Connecticut, the average monthly utility cost exceeded *** U.S. dollars. That was because of the significantly higher prices for electricity and natural gas in these states.

In 2024, the CPI in U.S. cities averaged at 313.7. However, the CPI for the New York-Newark-Jersey City metropolitan area amounted to about 334.21. Prices in New York City were significantly higher than the U.S. average. Nonetheless, the San Diego-Carlsbad area ranked first with a CPI of 373.32.The monthly inflation rate for the United States can be found here.

This table contains data on the percent of households paying more than 30% (or 50%) of monthly household income towards housing costs for California, its regions, counties, cities/towns, and census tracts. Data is from the U.S. Department of Housing and Urban Development (HUD), Consolidated Planning Comprehensive Housing Affordability Strategy (CHAS) and the U.S. Census Bureau, American Community Survey (ACS). The table is part of a series of indicators in the [Healthy Communities Data and Indicators Project of the Office of Health Equity] Affordable, quality housing is central to health, conferring protection from the environment and supporting family life. Housing costs—typically the largest, single expense in a family's budget—also impact decisions that affect health. As housing consumes larger proportions of household income, families have less income for nutrition, health care, transportation, education, etc. Severe cost burdens may induce poverty—which is associated with developmental and behavioral problems in children and accelerated cognitive and physical decline in adults. Low-income families and minority communities are disproportionately affected by the lack of affordable, quality housing. More information about the data table and a data dictionary can be found in the Attachments.

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

VITAL SIGNS INDICATOR Poverty (EQ5)

FULL MEASURE NAME The share of the population living in households that earn less than 200 percent of the federal poverty limit

LAST UPDATED December 2018

DESCRIPTION Poverty refers to the share of the population living in households that earn less than 200 percent of the federal poverty limit, which varies based on the number of individuals in a given household. It reflects the number of individuals who are economically struggling due to low household income levels.

DATA SOURCE U.S Census Bureau: Decennial Census http://www.nhgis.org (1980-1990) http://factfinder2.census.gov (2000)

U.S. Census Bureau: American Community Survey Form C17002 (2006-2017) http://api.census.gov

METHODOLOGY NOTES (across all datasets for this indicator) The U.S. Census Bureau defines a national poverty level (or household income) that varies by household size, number of children in a household, and age of householder. The national poverty level does not vary geographically even though cost of living is different across the United States. For the Bay Area, where cost of living is high and incomes are correspondingly high, an appropriate poverty level is 200% of poverty or twice the national poverty level, consistent with what was used for past equity work at MTC and ABAG. For comparison, however, both the national and 200% poverty levels are presented.

For Vital Signs, the poverty rate is defined as the number of people (including children) living below twice the poverty level divided by the number of people for whom poverty status is determined. Poverty rates do not include unrelated individuals below 15 years old or people who live in the following: institutionalized group quarters, college dormitories, military barracks, and situations without conventional housing. The household income definitions for poverty change each year to reflect inflation. The official poverty definition uses money income before taxes and does not include capital gains or noncash benefits (such as public housing, Medicaid, and food stamps). For the national poverty level definitions by year, see: https://www.census.gov/hhes/www/poverty/data/threshld/index.html For an explanation on how the Census Bureau measures poverty, see: https://www.census.gov/hhes/www/poverty/about/overview/measure.html

For the American Community Survey datasets, 1-year data was used for region, county, and metro areas whereas 5-year rolling average data was used for city and census tract.

To be consistent across metropolitan areas, the poverty definition for non-Bay Area metros is twice the national poverty level. Data were not adjusted for varying income and cost of living levels across the metropolitan areas.

D.C.'s median rent for a one bedroom apartment stands at $2,495, significantly higher than the national median rent of approximately $1,567. Click on different U.S. cities to see the median rent for a one bedroom apartment2.The map on the left side shows the percentage of people by census tract that are considered "cost burdened" by housing costs, by paying 30% or more of their household income on rent and utilities3. The map on the right side shows the median household income by census tract4. You can click on the "list" icon in the lower left corner to see the map legend, and meanings of map symbology. Areas that are cost burdened are often areas with the lowest median household incomes. There are also areas in wards where median incomes are high, but the cost of living is also high, leading to a greater cost burden.

This table contains data on the living wage and the percent of families with incomes below the living wage for California, its counties, regions and cities/towns. Living wage is the wage needed to cover basic family expenses (basic needs budget) plus all relevant taxes; it does not include publicly provided income or housing assistance. The percent of families below the living wage was calculated using data from the Living Wage Calculator and the U.S. Census Bureau, American Community Survey. The table is part of a series of indicators in the Healthy Communities Data and Indicators Project of the Office of Health Equity. The living wage is the wage or annual income that covers the cost of the bare necessities of life for a worker and his/her family. These necessities include housing, transportation, food, childcare, health care, and payment of taxes. Low income populations and non-white race/ethnic have disproportionately lower wages, poorer housing, and higher levels of food insecurity. More information about the data table and a data dictionary can be found in the About/Attachments section.

VITAL SIGNS INDICATOR
Poverty (EQ5)

FULL MEASURE NAME
The share of the population living in households that earn less than 200 percent of the federal poverty limit

LAST UPDATED
January 2023

DESCRIPTION
Poverty refers to the share of the population living in households that earn less than 200 percent of the federal poverty limit, which varies based on the number of individuals in a given household. It reflects the number of individuals who are economically struggling due to low household income levels.

DATA SOURCE
U.S Census Bureau: Decennial Census - http://www.nhgis.org
1980-2000

U.S. Census Bureau: American Community Survey - https://data.census.gov/
2007-2021
Form C17002

CONTACT INFORMATION
vitalsigns.info@mtc.ca.gov

METHODOLOGY NOTES (across all datasets for this indicator)
The U.S. Census Bureau defines a national poverty level (or household income) that varies by household size, number of children in a household, and age of householder. The national poverty level does not vary geographically even though cost of living is different across the United States. For the Bay Area, where cost of living is high and incomes are correspondingly high, an appropriate poverty level is 200% of poverty or twice the national poverty level, consistent with what was used for past equity work at MTC and ABAG. For comparison, however, both the national and 200% poverty levels are presented.

For Vital Signs, the poverty rate is defined as the number of people (including children) living below twice the poverty level divided by the number of people for whom poverty status is determined. The household income definitions for poverty change each year to reflect inflation. The official poverty definition uses money income before taxes and does not include capital gains or non-cash benefits (such as public housing, Medicaid and food stamps).

For the national poverty level definitions by year, see: US Census Bureau Poverty Thresholds - https://www.census.gov/data/tables/time-series/demo/income-poverty/historical-poverty-thresholds.html.

For an explanation on how the Census Bureau measures poverty, see: How the Census Bureau Measures Poverty - https://www.census.gov/topics/income-poverty/poverty/guidance/poverty-measures.html.

American Community Survey (ACS) 1-year data is used for larger geographies – Bay counties and most metropolitan area counties – while smaller geographies rely upon 5-year rolling average data due to their smaller sample sizes. Note that 2020 data uses the 5-year estimates because the ACS did not collect 1-year data for 2020.

To be consistent across metropolitan areas, the poverty definition for non-Bay Area metros is twice the national poverty level. Data were not adjusted for varying income and cost of living levels across the metropolitan areas.

This Cost of International Education dataset compiles detailed financial information for students pursuing higher education abroad. It covers multiple countries, cities, and universities around the world, capturing the full tuition and living expenses spectrum alongside key ancillary costs. With standardized fields such as tuition in USD, living-cost indices, rent, visa fees, insurance, and up-to-date exchange rates, it enables comparative analysis across programs, degree levels, and geographies. Whether you’re a prospective international student mapping out budgets, an educational consultant advising on affordability, or a researcher studying global education economics, this dataset offers a comprehensive foundation for data-driven insights.

Description

Potential Uses

• Budget Planning Prospective students can filter by country, program level, or university to forecast total expenses and compare across destinations.
• Policy Analysis Educational policymakers and NGOs can assess the affordability of international education and design support programs.
• Economic Research Economists can correlate living-cost indices and tuition levels with enrollment rates or student demographics.
• University Benchmarking Institutions can benchmark their fees and ancillary costs against peer universities worldwide.

Notes on Data Collection & Quality

• Currency Conversions All monetary values are unified to USD using contemporaneous exchange rates to facilitate direct comparison.
• Living Cost Index Derived from reputable city-index publications (e.g., Numbeo, Mercer) to standardize disparate cost-of-living metrics.
• Data Currency Exchange rates and fee schedules should be periodically updated to reflect market fluctuations and policy changes.

Feel free to explore, visualize, and extend this dataset for deeper insights into the true cost of studying abroad!

As of March 2024, the cost of living in Bogota was the highest among major Colombian cities. In total, the average cost per month amounted to 883 U.S. dollars. Cartagena followed in the ranking, with a monthly cost of living of 877 U.S. dollars at that time.

Apartment prices in Tel Aviv are the highest among the major cities in Israel. In the first quarter of 2023, the average cost of dwellings in Tel Aviv amounted to over 4.2 million Israeli shekels (roughly 1.13 million U.S. dollars). That was a slight rise compared to the previous quarter. The average price of apartments in the city slightly fluctuated but overall increased during the observed period. Due to the high housing prices in the city, many who wish to live in the city can afford only rented housing. The The number of households  living in rented dwellings in Tel Aviv amounted to 110,000 in 2020, making it the most common type of residency that year.  

High demand for housing in Tel Aviv 

Tel Aviv is the financial and cultural capital of Israel. Important companies in the Israeli economy and most of the influential cultural institutions in Israel are located in the city. As a result, many are interested in living in the city permanently, so housing prices remain high and even rise. Tel Aviv is the most important city in the Israeli high-tech industry, one of the most essential industries in the Israeli economy. As a result, many of the industry workers live in the city. In 2022, StartupBlink ranked Tel Aviv first in its list of leading cities for startups in Israel, with a score of 54.89. 

Residence in Jerusalem and Haifa is more affordable 

Jerusalem, the largest city in Israel, offers more affordable housing than Tel Aviv. In the first quarter of 2023, the aaverage price of apartments in Jerusalem amounted to just over 2.5 million Israeli shekels (around 673,000 U.S. dollars). Although the price is lower than in Tel Aviv, many Israelis hesitate to reside there. Jerusalem has a traditional character; therefore, it has fewer leisure and nightlife options than Tel Aviv can offer. The standard price of dwellings in Haifa, the largest city in the northern part of Israel, is lower than both towns. In the same quarter, it reached almost 1.64 million Israeli shekels (approximately 440,000 U.S. dollars).

Zillow Properties Listing dataset to access detailed real estate listings, including property prices, locations, and features. Popular use cases include market analysis, property valuation, and investment decision-making in the real estate sector.

Use our Zillow Properties Listing Information dataset to access detailed real estate listings, including property features, pricing trends, and location insights. This dataset is perfect for real estate agents, investors, market analysts, and property developers looking to analyze housing markets, identify investment opportunities, and assess property values.

Leverage this dataset to track pricing patterns, compare property features, and forecast market trends across different regions. Whether you're evaluating investment prospects or optimizing property listings, the Zillow Properties dataset offers essential information for making data-driven real estate decisions.

Dataset Features

• zpid: Unique property identifier assigned by Zillow.
• city: The name of the city where the property is located.
• state: The state in which the property is located.
• homeStatus: Indicates the current status of the property
• address: The full address of the property, including street, city, and state.
• isListingClaimedByCurrentSignedInUser: This field shows if the current Zillow user has claimed ownership of the listing.
• isCurrentSignedInAgentResponsible: This field indicates whether the currently signed-in real estate agent is responsible for the listing.
• bedrooms: Number of bedrooms in the property.
• bathrooms: Number of bathrooms in the property.
• price: Current asking price of the property.
• yearBuilt: The year the home was originally constructed.
• streetAddress: Specific street address (usually excludes city/state/zip).
• zipcode: The postal ZIP code of the property.
• isCurrentSignedInUserVerifiedOwner: This field indicates if the signed-in user has verified ownership of the property on Zillow.
• isVerifiedClaimedByCurrentSignedInUser: Indicates whether the user has claimed and verified the listing as the current owner.
• listingDataSource: The original source of the listing. Important for data lineage and trustworthiness.
• longitude: The longitudinal geographic coordinate of the property.
• latitude: The latitudinal geographic coordinate of the property.
• hasBadGeocode: This indicates whether the geolocation data is incorrect or problematic.
• streetViewMetadataUrlMediaWallLatLong: A URL or reference to the Street View media wall based on latitude and longitude.
• streetViewMetadataUrlMediaWallAddress: A similar URL reference to the Street View, but based on the property’s address.
• streetViewServiceUrl: The base URL to Google Street View or similar services. Enables interactive visuals of the property’s surroundings.
• livingArea: Total internal living area of the home, typically in square feet.
• homeType: The category/type of the home.
• lotSize: The size of the entire lot or land the home is situated on.
• lotAreaValue: The numerical value representing the lot area is usually tied to a measurement unit.
• lotAreaUnits: Units in which the lot area is measured (e.g., sqft, acres).
• livingAreaValue: The numeric value of the property's interior living space.
• livingAreaUnitsShort: Abbreviated unit for living area (e.g., sqft), useful for compact displays.
• isUndisclosedAddress: Boolean indicating if the full property address is hidden, typically used for privacy reasons.
• zestimate: Zillow’s estimated market value of the home, generated via its proprietary model.
• rentZestimate: Zillow’s estimated rental price per month, is helpful for rental market analysis.
• currency: Currency used for price, Zestimate, and rent estimate (e.g., USD).
• hideZestimate: Indicates whether the Zestimate is hidden from public view.
• dateSoldString: The date when the property was last sold, in string format (e.g., 2022-06-15).
• taxAssessedValue: The most recent assessed value of the property for tax purposes.
• taxAssessedYear: The year in which the property was last assessed.
• country: The country where the property is located.
• propertyTaxRate: The most recent tax rate.
• photocount: This column provides a photo count of the property.
• isPremierBuilder: Boolean indicating whether the builder is listed as a premier (trusted) builder on Zillow.
• isZillowOwned: Indicates whether the property is owned or managed directly by Zillow.
• ssid: A unique internal Zillow identifier for the listing (not to be confused with network SSID).
• hdpUrl: URL to the home’s detail page on Zillow (Home Details Page).
• tourViewCount: Number of times users have viewed the property tour.
• hasPublicVideo: This

This layer was developed by the Research & Analytics Group of the Atlanta Regional Commission, using data from the U.S. Census Bureau’s American Community Survey 5-year estimates for 2013-2017, to show the number and percentages of migration by city in the Atlanta region.

The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent.

The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2013-2017). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available.

For further explanation of ACS estimates and margin of error, visit Census ACS website.

Naming conventions:

Prefixes:

None

Count

p

Percent

r

Rate

m

Median

a

Mean (average)

t

Aggregate (total)

ch

Change in absolute terms (value in t2 - value in t1)

pch

Percent change ((value in t2 - value in t1) / value in t1)

chp

Change in percent (percent in t2 - percent in t1)

Suffixes:

None

Change over two periods

_e

Estimate from most recent ACS

_m

Margin of Error from most recent ACS

_00

Decennial 2000

Attributes:

SumLevel

Summary level of geographic unit (e.g., County, Tract, NSA, NPU, DSNI, SuperDistrict, etc)

GEOID

Census tract Federal Information Processing Series (FIPS) code

NAME

Name of geographic unit

Planning_Region

Planning region designation for ARC purposes

Acres

Total area within the tract (in acres)

SqMi

Total area within the tract (in square miles)

County

County identifier (combination of Federal Information Processing Series (FIPS) codes for state and county)

CountyName

County Name

Pop1P_e

# Population ages 1 year and over, 2017

Pop1P_m

# Population ages 1 year and over, 2017 (MOE)

SameHouse_e

# Living in the same house as 1 year ago, 2017

SameHouse_m

# Living in the same house as 1 year ago, 2017 (MOE)

pSameHouse_e

% Living in the same house as 1 year ago, 2017

pSameHouse_m

% Living in the same house as 1 year ago, 2017 (MOE)

DiffHouseInUS_e

# Living in a different house in the U.S. 1 year ago, 2017

DiffHouseInUS_m

# Living in a different house in the U.S. 1 year ago, 2017 (MOE)

pDiffHouseInUS_e

% Living in a different house in the U.S. 1 year ago, 2017

pDiffHouseInUS_m

% Living in a different house in the U.S. 1 year ago, 2017 (MOE)

SameCounty_e

# Living in a different house in the same county 1 year ago, 2017

SameCounty_m

# Living in a different house in the same county 1 year ago, 2017 (MOE)

pSameCounty_e

% Living in a different house in the same county 1 year ago, 2017

pSameCounty_m

% Living in a different house in the same county 1 year ago, 2017 (MOE)

DiffCounty_e

# Living in a different county 1 year ago, 2017

DiffCounty_m

# Living in a different county 1 year ago, 2017 (MOE)

pDiffCounty_e

% Living in a different county 1 year ago, 2017

pDiffCounty_m

% Living in a different county 1 year ago, 2017 (MOE)

SameState_e

# Living in a different county, same state 1 year ago, 2017

SameState_m

# Living in a different county, same state 1 year ago, 2017 (MOE)

pSameState_e

% Living in a different county, same state 1 year ago, 2017

pSameState_m

% Living in a different county, same state 1 year ago, 2017 (MOE)

Diff_State_e

# Living in a different state 1 year ago, 2017

Diff_State_m

# Living in a different state 1 year ago, 2017 (MOE)

pDiff_State_e

% Living in a different state 1 year ago, 2017

pDiff_State_m

% Living in a different state 1 year ago, 2017 (MOE)

Abroad_e

# Living abroad 1 year ago, 2017

Abroad_m

# Living abroad 1 year ago, 2017 (MOE)

pAbroad_e

% Living abroad 1 year ago, 2017

pAbroad_m

% Living abroad 1 year ago, 2017 (MOE)

Moved_e

# Moved in the last year, 2017

Moved_m

# Moved in the last year, 2017 (MOE)

pMoved_e

% Moved in the last year, 2017

pMoved_m

% Moved in the last year, 2017 (MOE)

last_edited_date

Last date the feature was edited by ARC

Source: U.S. Census Bureau, Atlanta Regional Commission

Date: 2013-2017

For additional information, please visit the Census ACS website.

Ontario's construction costs 2023, by building type Published by Fernando de Querol Cumbrera, Dec 10, 2024 Ambulatory healthcare was the type of building with the highest construction costs in Ontario (Canada) in 2023. The cost of that type of building ranged from 7,110 to 8,750 Canadian dollars per square meter. Townhouses with mid-end specifications were, along with warehouses, among the cheapest buildings to construct, even though the townhouse sale price in Canada was much higher in 2023 than in a decade earlier. On the other side of the residential spectrum, the construction cost of high-rise buildings with mid-end specifications could reach up to 5,370 Canadian dollars per square meter. The housing sector in Ontario The fast population growth in Toronto, the main city in Ontario, has put pressure on its housing market. From 2001 to 2022, the number of people living in Canada’s largest city increased by over 37 percent. During the past years, house prices in Ontario rose at a similarly fast pace. Combined, these elements signal a strong demand for homes in Toronto and Ontario as a whole. The construction sector has responded to this trend: In 2022, most housing starts in Canada took place in the province of Ontario. That same year, EllisDon Corporation, with headquarters in Mississauga (Ontario), was the second-largest contractor in Canada. One of its largest residential/mixed-use projects under development is the 489-539 King St. West Development, in Toronto. Construction cost in North America Building construction costs in Quebec, the second most populous province in Canada after Ontario, had a similar cost range: Ambulatory healthcare buildings were the most expensive, and warehouses were the cheapest to build. However, enclosed malls and higher education buildings were significantly more expensive in Quebec than in Ontario. Across the border, the cities with the highest residential construction costs in the U.S. were San Francisco for multi-family housing, and New York City for single-family housing. Meanwhile, Los Angeles, San Francisco, and New York had the highest hotel construction costs in the U.S.

Ambulatory healthcare was the type of building with the highest construction costs in Ontario (Canada) in 2023. The cost of that type of building ranged from 7,110 to 8,750 Canadian dollars per square meter. Townhouses with mid-end specifications were, along with warehouses, among the cheapest buildings to construct, even though the townhouse sale price in Canada was much higher in 2023 than in a decade earlier. On the other side of the residential spectrum, the construction cost of high-rise buildings with mid-end specifications could reach up to 5,370 Canadian dollars per square meter. The housing sector in Ontario The fast population growth in Toronto, the main city in Ontario, has put pressure on its housing market. From 2001 to 2022, the number of people living in Canada’s largest city increased by over 37 percent. During the past years, house prices in Ontario rose at a similarly fast pace. Combined, these elements signal a strong demand for homes in Toronto and Ontario as a whole. The construction sector has responded to this trend: In 2022, most housing starts in Canada took place in the province of Ontario. That same year, EllisDon Corporation, with headquarters in Mississauga (Ontario), was the second-largest contractor in Canada. One of its largest residential/mixed-use projects under development is the 489-539 King St. West Development, in Toronto. Construction cost in North America Building construction costs in Quebec, the second most populous province in Canada after Ontario, had a similar cost range: Ambulatory healthcare buildings were the most expensive, and warehouses were the cheapest to build. However, enclosed malls and higher education buildings were significantly more expensive in Quebec than in Ontario. Across the border, the cities with the highest residential construction costs in the U.S. were San Francisco for multi-family housing, and New York City for single-family housing. Meanwhile, Los Angeles, San Francisco, and New York had the highest hotel construction costs in the U.S.

Of the cities who have experienced cost of living increases, the top three are located in Latin America, two in Mexico and one in Costa Rica. Each moved 38, 39, and 48 spots in the ranking respectively since 2022. Due to increases in interest rates, the Mexican peso and Costa Rican colón have both appreciated against the U.S. Dollar. Comparatively, Singapore and Zurich were ranked the most expensive cities in the world.

How many incorporated places are registered in the U.S.?

There were 19,502 incorporated places registered in the United States as of July 31, 2019. 16,410 had a population under 10,000 while, in contrast, only 10 cities had a population of one million or more.

Small-town America

Suffice it to say, almost nothing is more idealized in the American imagination than small-town America. When asked where they would prefer to live, 30 percent of Americans reported that they would prefer to live in a small town. Americans tend to prefer small-town living due to a perceived slower pace of life, close-knit communities, and a more affordable cost of living when compared to large cities.

An increasing population

Despite a preference for small-town life, metropolitan areas in the U.S. still see high population figures, with the New York, Los Angeles, and Chicago metro areas being the most populous in the country. Metro and state populations are projected to increase by 2040, so while some may move to small towns to escape city living, those small towns may become more crowded in the upcoming decades.

Cost of living can vary wildly depending on the city that people live in. Some are hugely expensive while others are comparatively cheaper. This variety can also be seen in the average overnight price of hotels. In September 2023, New York held the highest hotel rate in North America when compared to other selected cities. The average overnight price for a hotel room in New York was 504 U.S. dollars.

Alaska, Hawaii, and Connecticut were the states with the highest average monthly utility costs in the United States in 2023. Residents paid about ****** U.S. dollars for their electricity bills in Hawaii, while the average monthly bill for natural gas came to *** U.S. dollars. This was significantly higher than in any other state. Bigger homes have higher utility costs Despite regional variations, single-family homes in the United States have grown bigger in size since 1975. This trend also means that, unless homeowners invest in energy savings measures, they will have to pay more for their utility costs. Which are the most affordable states to live in? According to the cost of living index, the three most affordable states to live in are Mississippi, Kansas, and Oklahoma. At the other end of the scale are Hawaii, District of Columbia, and New York. The index is based on housing, utilities, grocery items, transportation, health care, and miscellaneous goods and services. To buy a median priced home in Kansas City, a prospective home buyer will have to earn an annual salary of about ****** U.S. dollars.