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.

As of mid-2024, Montevideo ranked as the second Latin American and Caribbean metropolis with the highest cost of living index. The Uruguayan capital obtained an index score of 54.1, only second to Port of Spain, in Trinidad and Tobago, with 56.4 points. Monterrey and Panama City were the third and fourth most expensive cities to live in Latin America and the Caribbean that year, with scores surpassing 45 points each.

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.

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
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 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.

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!

This feature service contains data from the American Community Survey: 5-year Estimates Subject Tables for the greater Bozeman, MT area. The attributes come from the Financial Characteristics table (S2503). Processing Notes:Data was downloaded from the U.S. Census Bureau and imported into FME to create an AGOL Feature Service. Each attribute has been given an abbreviated alias name derived from the American Community Survey (ACS) categorical descriptions. The Data Dictionary below includes all given ACS attribute name aliases. For example: Rent_35kto50k_20to29pcnt is equal to the percentage of the population living in a renter-occupied household, with an annual household income of $35,000 to $50,000, spending between 20% to 29% of their income on housing costs in the past 12 months. Data DictionaryACS_EST_YR: American Community Survey 5-Year Estimate Subject Tables data yearGEO_ID: Census Bureau geographic identifierNAME: Specified geographyOwn: Percent of population living in an Owner-occupied householdRent: Percent of population living in a Renter-occupied householdAnnual Household Income20kto35k: Annual household income of $20,000 to $34,99935kto50k: Annual household income of $35,000 to $49,99950kto75k: Annual household income of $50,000 to $74,999Over75k: Annual household income of over $75,000Housing Cost BurdenUnder_20pcnt: Monthly housing costs under 20% of household income in the past 12 months20to29pcnt: Monthly housing costs of 20-29% of household income in the past 12 months30pcntOrMore: Monthly housing costs of over 30% of household income in the past 12 monthsDownload ACS Financial Characteristics data for the greater Bozeman, MT areaAdditional LinksU.S. Census BureauU.S. Census Bureau American Community Survey (ACS)About the American Community Survey

Annual indexes of price differences between 15 cities in all provinces and territories, as of October of the previous year, for a selection of products (goods and services) from the Consumer Price Index (CPI) purchased by consumers in each of the 15 cities. The combined city average index is 100.

Real Estate Sales 730 Days

City of Hartford real estate sales for the past 2 years

By [source]

About this dataset

This dataset contains data on City of Hartford real estate sales for the last two years, with comprehensive records including property ID, parcel ID, sale date, sale price and more. This dataset is continuously updated each night and sourced from an official reliable source. The columns in this dataset include LocationStartNumber, ApartmentUnitNumber, StreetNameAndWay, LandSF TotalFinishedArea, LivingUnits ,OwnerLastName OwnerFirstName ,PrimaryGrantor ,SaleDate SalePrice ,TotalAppraisedValue and LegalReference - all valuable information to anyone wishing to understand the recent market trends and developments in the City of Hartford real estate industry. With this data providing detailed insights into what properties are selling at what time frame and for how much money – let’s see what secrets we can learn from examining the City of Hartford real estate activity!

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How to use the dataset

This dataset contains helpful information about homes sold in the Hartford area over the past two years. This data can be used to analyze trends in real estate markets, as well as monitor sales activity for various areas.

In order to use this dataset, you will need knowledge of EDA (Exploratory Data Analysis) such as data cleaning and data visualization techniques. You will also need a basic understanding of SQL queries and Python scripting language.

The first step is to familiarize yourself with the columns and information contained within the dataset by analyzing descriptive statistics like mean, min, max etc. Next you can filter or “slice” the data based on certain criteria or variables that interest you - such as sale date range, location (by street name or zip code), sale price range, type of dwelling unit etc. After using various filters for analysis it is important to take an error-check step by looking for outliers or any discrepancies that may exist - this will ensure more accuracy in results when plotting graphs and visualizing trends via software tools like Tableau and Power BI etc.

Next you can conduct exploratory analysis through plot visualizations of relationships between buyer characteristics (first & last name) vs prices over time; living units vs square footage stats; average price per bedroom/bathroom ratio comparisons etc – all while taking into account external factors such as seasonal changeovers that could affect pricing fluctuations during given intervals across multiple neighborhoods - use interactive maps if available ets. At this point it's easy to compile insightful reports containing commonalities amongst buyers and begin generalizing your findings with extrapolations which allow us gain a better understanding of current market conditions across different demographic spectrums being compared ie traditional Vs luxury properties – all made possible simply through dedicated research with datasets like these!

Research Ideas

• Analyzing market trends in the City of Hartford's real estate industry by tracking sale prices and appraised values over time to identify regions who are being under or over valued.
• Conducting a predictive analysis project to predict future sales prices, annual appreciation rates, and key features associated with residential properties such as total finished area and living units for investment purposes.
• Studying the impact of local zoning laws on property ownership and development by comparing sale dates, primary grantors, legal references, street names and ways in a given area over time

Acknowledgements

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

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: real-estate-sales-730-days-1.csv | Column name | Description | |:------------------------|:---------------------------------------------------------------| | LocationStartNumber | The starting number of the location of the property. (Integer) | | ApartmentUnitNumber | The apartment unit number of the property. (Integer) | | StreetNameAndWay | The st...

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

As of September 2024, Mumbai had the highest cost of living among other cities in the country, with an index value of ****. Gurgaon, a satellite city of Delhi and part of the National Capital Region (NCR) followed it with an index value of ****.  What is cost of living? The cost of living varies depending on geographical regions and factors that affect the cost of living in an area include housing, food, utilities, clothing, childcare, and fuel among others. The cost of living is calculated based on different measures such as the consumer price index (CPI), living cost indexes, and wage price index. CPI refers to the change in the value of consumer goods and services. The wage price index, on the other hand, measures the change in labor services prices due to market pressures. Lastly, the living cost indexes calculate the impact of changing costs on different households. The relationship between wages and costs determines affordability and shifts in the cost of living. Mumbai tops the list Mumbai usually tops the list of most expensive cities in India. As the financial and entertainment hub of the country, Mumbai offers wide opportunities and attracts talent from all over the country. It is the second-largest city in India and has one of the most expensive real estates in the world.

Context

Washington, D.C. is the capital of the United States. Washington's population is approaching 700,000 people, and has been growing since 2000 following a half-century of population decline. The city is highly segregated and features a high cost of living. In 2017, the average price of a single family home in the district was $649,000. This dataset provides insight on the housing stock of the district.

Content

The residential property descriptions and address point information is current as of July 2018 and is provided by D.C. Geographic Information System.

The raw_census_tracts_in_2010.csv provides contextual information for regions throughout D.C. and can be joined with the main DC_Property_data.csv dataset through the tract value. Census tract shapefiles are also included to serve mapping visualizations.

Acknowledgements

All data is available at Open Data D.C.. The residential and address point data is managed by the Office of the Chief Technology Officer

Distribution Liability: data terms and conditions

The banner photograph is provided by Caleb Wright.

Click here for research on the effects of land use planning and gentrification on Portland’s communities of color and other vulnerable populations. Economic Vulnerability Assessment:This map identifies census tracts in Portland where residents are more vulnerable to changing economic conditions, making resisting displacement more difficult. These areas have residents who are more likely to:Be "housing cost-burdened", meaning they pay 30% or more of their income on housing costs.Belong to communities of color, particularly Black and Indigenous communities.Lack college degrees, andHave Lower Incomes.This dataset provides an update to the vulnerability risk analysis that Dr. Lisa Bates prepared for the Bureau of Planning and Sustainability in 2012.This latest dataset includes the following changes in methodology:Low income households were replaced with a size-adjusted median household income. This helps account for how different household sizes experience living with different incomes.Renter households were replaced with households that are housing cost-burdened (pay 30%+ on housing costs). This acknowledges that homeowners who pay a high percentage of their income on housing can be vulnerable to displacement as well.A new variable, Black and Indigenous population, was added to better incorporate past harms to these communities.The vulnerability score was rescaled from 0 to 100. A score of 60 or greater is considered a vulnerable tract.Data sources: U.S. Census Bureau, 2022 ACS 5-year estimates, Tables B25106, B25010, B03002, B19013, B15002. Prepared Summer 2024 by the Portland Bureau of Planning and Sustainability.Download dataset from City of Portland Open Data siteAbout the Bureau of Planning and SustainabilityThe Portland Bureau of Planning and Sustainability (BPS) develops creative and practical solutions to enhance Portland’s livability, preserve distinctive places and plan for a resilient future.Need more information about this data? Email bpsgis@portlandoregon.gov-- Additional Information: Category: Planning Purpose: Map the areas susceptible to gentrification pressure. Update Frequency: Yearly-- Metadata Link: https://www.portlandmaps.com/metadata/index.cfm?&action=DisplayLayer&LayerID=54141

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.

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.

Monthly indexes and percentage changes for major components and special aggregates of the Consumer Price Index (CPI), not seasonally adjusted, for Canada, provinces, Whitehorse, Yellowknife and Iqaluit. Data are presented for the corresponding month of the previous year, the previous month and the current month. The base year for the index is 2002=100.

In 2024, the consumer price index (CPI) was 315.61. Data represents U.S. city averages. The monthly inflation rate for the United States can be found here. United States urban Consumer Price Index (CPI) The U.S. Consumer Price Index is a measure of change in the price of consumer goods and services purchased by households. The CPI is defined by the United States Bureau of Labor Statistics as "a measure of the average change over time in the prices paid by urban consumers for a market basket of consumer goods and services." To calculate the CPI, the Bureau of Labor Statistics considers the price of goods and services from various categories: housing, transportation, apparel, food & beverage, medical care, recreation, education and other/uncategorized. The CPI is a useful measure, as it indicates how the cost of urban living in the United States has changed over time, compared to a base period. CPI is also used to calculate inflation, or change in the purchasing power of money. According to the U.S. Bureau of Labor Statistics, the U.S. urban CPI has been rising steadily since 1992. As of 2023, the CPI was 304.7, up from 233 ten years earlier and up from 184 twenty years earlier. This indicates the extent to which, compared to a base period 1982-1984 = 100, the price of various goods and services has risen.

In January 2025, the unadjusted consumer price index (CPI) of all items for urban consumers in the United States amounted to about 317.67. The data represents U.S. city averages. The base period was 1982-84=100. The CPI is defined by the United States Bureau of Labor Statistics as “a measure of the average change over time in the prices paid by urban consumers for a market basket of consumer goods and services”. The annual consumer price index for urban consumers in the U.S. can be accessed here. Consumer Price Index The Consumer Price Index (CPI) began in 1919 under the Bureau of Labor Statistics and is published every month. The CPI for all urban consumers includes urban households in Metropolitan Statistical Areas and regions with over 2,500 inhabitants, as well as non-farm consumers living in rural regions. This index was established in 1978 and includes about 80 percent of the U.S. population. The monthly CPI of urban consumers in the United States increased from 292.3 in May 2022 to 304.13 in 2023. Inflation tends not to impact everyone equally for a variety of reasons, including geography - CPI often differs between regions, with a high of 287.49 in the Western region as of 2021. There are also disparities in inflation between income quartiles, in which inflation is generally felt more heavily by lower income households. The annual CPI in the United States has increased steadily over the past two decades, from 140.3 in 1992 to 292.56 in 2022. A forecast of the CPI expects this positive trend to continue, reaching 325.6 by 2027. As of March 2023, the CPI of the nation’s education had increased by 3.5 percent. Further, in the same month costs of recreation, rent, housing, medical care, and food and beverages, gasoline, and transportation increased. Comparatively, the CPI in Hong Kong reached 103.3 in 2022.

In January 2025, prices had increased by three percent compared to January 2024 according to the 12-month percentage change in the consumer price index — the monthly inflation rate for goods and services in the United States. The data represents U.S. city averages. In economics, the inflation rate is a measure of the change in price level over time. The rate of decrease in the purchasing power of money is approximately equal. A projection of the annual U.S. inflation rate can be accessed here and the actual annual inflation rate since 1990 can be accessed here. InflationOne of the most important economic indicators is the development of the Consumer Price Index in a country. The change in this price level of goods and services is defined as the rate of inflation. The inflationary situation in the United States had been relatively severe in 2022 due to global events relating to COVID-19, supply chain restrains, and the Russian invasion of Ukraine. More information on U.S. inflation may be found on our dedicated topic page. The annual inflation rate in the United States has increased from 3.2 percent in 2011 to 8.3 percent in 2022. This means that the purchasing power of the U.S. dollar has weakened in recent years. The purchasing power is the extent to which a person has available funds to make purchases. According to the data published by the International Monetary Fund, the U.S. Consumer Price Index (CPI) was about 258.84 in 2020 and is forecasted to grow up to 325.6 by 2027, compared to the base period from 1982 to 1984. The monthly percentage change in the Consumer Price Index (CPI) for urban consumers in the United States was 0.1 percent in March 2023 compared to the previous month. In 2022, countries all around the world are experienced high levels of inflation. Although Brazil already had an inflation rate of 8.3 percent in 2021, compared to the previous year, while the inflation rate in China stood at 0.85 percent.