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.

Link to landing page referenced by identifier. Service Protocol: Link to landing page referenced by identifier. Link Function: information-- dc:identifier.

This map shows the median household income in the U.S. in 2017 in a multiscale map by country, state, county, ZIP Code, tract, and block group. Median household income is estimated for 2017 in current dollars, including an adjustment for inflation or cost-of-living increases.The pop-up is configured to include the following information for each geography level:Median household incomeMedian household income by age of householderCount of households by income level (Householder age 15 to 24)Count of households by income level (Householder age 25 to 34)Count of households by income level (Householder age 35 to 44)Count of households by income level (Householder age 45 to 54)Count of households by income level (Householder age 55 to 64)Count of households by income level (Householder age 65 to 74)Count of households by income level (Householder age 75 plus)The data shown is from Esri's 2017 Updated Demographic estimates using Census 2010 geographies. The map adds increasing level of detail as you zoom in, from state, to county, to ZIP Code, to tract, to block group data. Esri's U.S. Updated Demographic (2017/2022) Data - Population, age, income, sex, race, home value, and marital status are among the variables included in the database. Each year, Esri's Data Development team employs its proven methodologies to update more than 2,000 demographic variables for a variety of U.S. geographies.Data Note: The median household income value divides the distribution of household income into two equal parts. Pareto interpolation is used if the median falls in an income interval other than the first or last. For the lowest interval, <$10,000, linear interpolation is used. If the median falls in the upper income interval of $500,000+, it is represented by the value of $500,001.

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.

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.

At 7.99 U.S. dollars, Switzerland has the most expensive Big Macs in the world, according to the January 2025 Big Mac index. Concurrently, the cost of a Big Mac was 5.79 dollars in the U.S., and 5.95 U.S. dollars in the Euro area. What is the Big Mac index? The Big Mac index, published by The Economist, is a novel way of measuring whether the market exchange rates for different countries’ currencies are overvalued or undervalued. It does this by measuring each currency against a common standard – the Big Mac hamburger sold by McDonald’s restaurants all over the world. Twice a year the Economist converts the average national price of a Big Mac into U.S. dollars using the exchange rate at that point in time. As a Big Mac is a completely standardized product across the world, the argument goes that it should have the same relative cost in every country. Differences in the cost of a Big Mac expressed as U.S. dollars therefore reflect differences in the purchasing power of each currency. Is the Big Mac index a good measure of purchasing power parity? Purchasing power parity (PPP) is the idea that items should cost the same in different countries, based on the exchange rate at that time. This relationship does not hold in practice. Factors like tax rates, wage regulations, whether components need to be imported, and the level of market competition all contribute to price variations between countries. The Big Mac index does measure this basic point – that one U.S. dollar can buy more in some countries than others. There are more accurate ways to measure differences in PPP though, which convert a larger range of products into their dollar price. Adjusting for PPP can have a massive effect on how we understand a country’s economy. The country with the largest GDP adjusted for PPP is China, but when looking at the unadjusted GDP of different countries, the U.S. has the largest economy.

This feature service contains census tract data from the American Community Survey: 5-year Estimates Subject Tables for Gallatin County, MT. The attributes come from the Financial Characteristics table (S2503). Processing Notes:Data was downloaded from the U.S. Census Bureau, imported into FME, and joined with TIGER/Line geometry 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 household20kto35k: 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 $75,000Under_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 all census tracts in Gallatin County, MTAdditional LinksU.S. Census BureauU.S. Census Bureau American Community Survey (ACS)About the American Community Survey

In March 2025, inflation amounted to 2.4 percent, while wages grew by 4.3 percent. The inflation rate has not exceeded the rate of wage growth since January 2023. Inflation in 2022 The high rates of inflation in 2022 meant that the real terms value of American wages took a hit. Many Americans report feelings of concern over the economy and a worsening of their financial situation. The inflation situation in the United States is one that was experienced globally in 2022, mainly due to COVID-19 related supply chain constraints and disruption due to the Russian invasion of Ukraine. The monthly inflation rate for the U.S. reached a 40-year high in June 2022 at 9.1 percent, and annual inflation for 2022 reached eight percent. Without appropriate wage increases, Americans will continue to see a decline in their purchasing power. Wages in the U.S. Despite the level of wage growth reaching 6.7 percent in the summer of 2022, it has not been enough to curb the impact of even higher inflation rates. The federally mandated minimum wage in the United States has not increased since 2009, meaning that individuals working minimum wage jobs have taken a real terms pay cut for the last twelve years. There are discrepancies between states - the minimum wage in California can be as high as 15.50 U.S. dollars per hour, while a business in Oklahoma may be as low as two U.S. dollars per hour. However, even the higher wage rates in states like California and Washington may be lacking - one analysis found that if minimum wage had kept up with productivity, the minimum hourly wage in the U.S. should have been 22.88 dollars per hour in 2021. Additionally, the impact of decreased purchasing power due to inflation will impact different parts of society in different ways with stark contrast in average wages due to both gender and race.

Assisted Living Waiver (ALW) eligible individuals are those who are enrolled in Medi-Cal and meet the level of care provided in a nursing facility due to their medical needs. Individuals with Medi-Cal benefits that include a share of cost may not enroll in the ALW. This dataset contains the provider number, provider legal name, provider business name, capacity per provider enrollment, provider physical location, provider counties and provider phone number of facilities enrolled in the ALW program. Data as of 1/1/2023

In economics, the inflation rate is a measure of the change in price of a basket of goods. The most common measure being the consumer price index. It is the percentage rate of change in price level over time, and also indicates the rate of decrease in the purchasing power of money. The annual rate of inflation for 2023, was 4.1 percent higher in the United States when compared to the previous year. More information on inflation and the consumer price index can be found on our dedicated topic page. Additionally, the monthly rate of inflation in the United States can be accessed here. Inflation and purchasing power Inflation is a key economic indicator, and gives economists and consumers alike a look at changes in prices in the wider economy. For example, if an average pair of socks costs 100 dollars one year and 105 dollars the following year, the inflation rate is five percent. This means the amount of goods an individual can purchase with a unit of currency has decreased. This concept is often referred to as purchasing power. The data presents the average rate of inflation in a year, whereas the monthly measure of inflation measures the change in prices compared with prices one year ago. For example, monthly inflation in the U.S. reached a peak in June 2022 at 9.1 percent. This means that prices were 9.1 percent higher than they were in June of 2021. The purchasing power is the extent to which a person has available funds to make purchases. The Big Mac Index has been published by The Economist since 1986 and exemplifies purchasing power on a global scale, allowing us to see note the differences between different countries currencies. Switzerland for example, has the most expensive Big Mac in the world, costing consumers 6.71 U.S. dollars as of July 2022, whereas a Big Mac cost 5.15 dollars in the United States, and 4.77 dollars in the Euro area. One of the most important tools in influencing the rate of inflation is interest rates. The Federal Reserve of the United States has the capacity to make changes to the federal interest rate . Changes to the rate of inflation are thought to be an imbalance between supply and demand. After COVID-19 related lockdowns came to an end there was a sudden increase in demand for goods and services with consumers having more funds than usual thanks to reduced spending during lockdown and government funded economic support. Additionally, supply-chain related bottlenecks also due to lockdowns around the world and the Russian invasion of Ukraine meant that there was a decrease in the supply of goods and services. By increasing the interest rate, the Federal Reserve aims to reduce spending, and thus bring demand back into balance with supply.

Overburdened Communities Census Tracts web layer configured in Map Viewer Classic for the EV Publicly Available application. (Current Version)This layer represents the overall ranking for Environmental Exposures, Environmental Effects, Socioeconomic Factors and Sensitive Populations. More information is available here https://fortress.wa.gov/doh/wtnibl/WTNIBL/.This layer uses 2010 Census Tracts based on the current version of the Washington Tracking Network's Environmental Health Disparities data.The source data is derived from the Environmental Health Disparities map displayed on WTN's Information by Location (IBL) tool. The data on the map include 19 indicators and are divided into four themes:Environmental Exposures (PM2.5-diesel emissions; ozone concentration; PM2.5 Concentration; proximity to heavy traffic roadways; toxic release from facilities (RSEI model))Environmental Effects (lead risk from housing; proximity to hazardous waste treatment, storage, and disposal facilities (TSDFs); proximity to National Priorities List sites (Superfund Sites); proximity to Risk Management Plan (RMP) facilities; wastewater discharge)Sensitive Populations (death from cardiovascular disease; low birth weight)Socioeconomic Factors (limited English; no high school diploma; poverty; race - people of color; transportation expense; unaffordable housing; unemployed)Learn about how the Environmental Health Disparities map is being used to support Washington's clean energy transformation.Washington State Department of Health provides an index of Environmental Health Disparities for all the census tracts in Washington. Both deciles (ranks 1 - 10) and quintiles (ranks 1 - 5) have been calculated for cardiovascular disease, low birth weight, people without a high school diploma, people who speak English less than "very well" or "not at all", people living at or below 185% of federal poverty level, people of color, transportation costs, unemployment, housing costs, people exposed to air pollution near busy road ways, exposure to diesel emissions, exposure to average ozone, exposure to particulate matter, exposure to toxic releases, proximity to hazardous waste generators, exposure to lead, proximity to Superfund sites, proximity to facilities with highly toxic substances, proximity to wastewater discharge, general environmental exposure, general environmental effects, general sensitive populations, general socioeconomic factors, and overall environmental health disparities. Please see the Washington environmental health disparities page for more information: https://www.doh.wa.gov/DataandStatisticalReports/WashingtonTrackingNetworkWTN/InformationbyLocation/WashingtonEnvironmentalHealthDisparitiesMap The map was a collaborative project that took several years to develop. It went live to the public in January of 2019. Those involved in the initial collaboration include: University of Washington's Department of Environmental and Occupational Health Sciences, Front and Centered, Washington State Department of Health, Washington State Department of Ecology, and Puget Sound Clean Air Agency. The effort included listening sessions with communities in Washington State. The communities gave input that informed development of the map. Since the map was published, several laws and rules highlight it as a resource. Healthy Environment for All (HEAL) Act, passed in 2021, led to the first dedicated, ongoing state funding to maintain and update the map. The HEAL Act (RCW 43.70.815) requires DOH to: Further develop the EHD map, engaging with communities, tribes, researcher, and EJ CouncilTrack changes in disparities over time Perform a comprehensive evaluation every three yearsExpand online video trainings and guidance on how to use the EHD mapProvide support and consultation to state agencies on how to use the EHD map\DOH continues to add data to the EHD map to reflect additional health risks. DOH is currently working with partners to develop indicators for: wildfire smoke, asthma, tree canopy and greenspace, water quality, pesticide exposure, redlining index, and a group of climate change indicators.The EHD map is a living tool. Developing and improving it is an ongoing process, incorporating feedback and new data. The map will never fully reflect communities’ experiences and should not be used to replace community engagement or tribal consultation. If you have feedback about how we could improve the map, please contact us at EHDmap@doh.wa.gov.

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

Symbols in bright yellow represent areas where more seniors with burdensome housing costs are renters, whereas symbols that are blue represent areas with more owners. Map has national coverage but opens in Milwaukee. Use the map's bookmarks or the search bar to view other cities. Bookmarks include what are generally thought of as "affordable" cities - Fresno, Salt Lake City, New Orleans, Albuquerque, El Paso, Tusla, Raleigh, Milwaukee - but yet there are many seniors whose housing costs are 30 percent or more of their income. "The burden of housing costs combined with climbing health care expenses can significantly reduce financial security at older ages" according to the Urban Institute. The number of senior households is projected to grow in the coming years, making the issue of economic security for seniors even more pressing.Housing costs are defined as burdensome if they exceed 30 percent of monthly income, a widely-used definition by HUD and others in affordable housing discussions. For owners, monthly housing costs include payments for mortgages and all other debts on the property; real estate taxes; fire, hazard, and flood insurance; utilities; fuels; and condominium or mobile home fees.For renters, monthly housing costs include contract rent plus the estimated average monthly cost of utilities (electricity, gas, and water and sewer) and fuels (oil, coal, kerosene, wood, etc.) if these are paid by the renter.Income is defined as the sum of wage/salary income; net self-employment income; interest/dividends/net rental/royalty income/income from estates & trusts; Social Security/Railroad Retirement income; Supplemental Security Income (SSI); public assistance/welfare payments; retirement/survivor/disability pensions; & all other income.Only households with a householder who is 65 and over are included in these maps. The householder is a person in whose name the home is owned, being bought, or rented, and how answers the questionnaire as person 1.This map is multi-scale, with data for states, counties, and tracts. This map uses these hosted feature layers containing the most recent American Community Survey data. These layers are part of the ArcGIS Living Atlas, and are updated every year when the American Community Survey releases new estimates, so values in the map always reflect the newest data available.

The average transaction price of new housing in Europe was the highest in Norway, whereas existing homes were the most expensive in Austria. Since there is no central body that collects and tracks transaction activity or house prices across the whole continent or the European Union, not all countries are included. To compile the ranking, the source weighed the transaction prices of residential properties in the most important cities in each country based on data from their national offices. For example, in Germany, the cities included were Munich, Hamburg, Frankfurt, and Berlin. House prices have been soaring, with Sweden topping the ranking Considering the RHPI of houses in Europe (the price index in real terms, which measures price changes of single-family properties adjusted for the impact of inflation), however, the picture changes. Sweden, Luxembourg and Norway top this ranking, meaning residential property prices have surged the most in these countries. Real values were calculated using the so-called Personal Consumption Expenditure Deflator (PCE), This PCE uses both consumer prices as well as consumer expenditures, like medical and health care expenses paid by employers. It is meant to show how expensive housing is compared to the way of living in a country. Home ownership highest in Eastern Europe The home ownership rate in Europe varied from country to country. In 2020, roughly half of all homes in Germany were owner-occupied whereas home ownership was at nearly 97 percent in Romania or around 90 percent in Slovakia and Lithuania. These numbers were considerably higher than in France or Italy, where homeowners made up 65 percent and 72 percent of their respective populations.For more information on the topic of property in Europe, visit the following pages as a starting point for your research: real estate investments in Europe and residential real estate in Europe.

Amsterdam is set to maintain its position as Europe's most expensive city for apartment rentals in 2025, with median costs reaching 2,500 euros per month for a furnished one-bedroom unit. This figure is double the rent in Prague and significantly higher than other major European capitals like Paris, Berlin, and Madrid. The stark difference in rental costs across European cities reflects broader economic trends, housing policies, and the complex interplay between supply and demand in urban centers. Factors driving rental costs across Europe The disparity in rental prices across European cities can be attributed to various factors. In countries like Switzerland, Germany, and Austria, a higher proportion of the population lives in rental housing. This trend contributes to increased demand and potentially higher living costs in these nations. Conversely, many Eastern and Southern European countries have homeownership rates exceeding 90 percent, which may help keep rental prices lower in those regions. Housing affordability and market dynamics The relationship between housing prices and rental rates varies significantly across Europe. As of 2024, countries like Turkey, Iceland, Portugal, and Hungary had the highest house price to rent ratio indices. This indicates a widening gap between property values and rental costs since 2015. The affordability of homeownership versus renting differs greatly among European nations, with some countries experiencing rapid increases in property values that outpace rental growth. These market dynamics influence rental costs and contribute to the diverse rental landscape observed across European cities.