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.

This map uses a two-color thematic shading to emphasize where areas experience the least to the most affordable housing across the US. This web map is part of the How Affordable is the American Dream story map.

Esri’s Housing Affordability Index (HAI) is a powerful tool to analyze local real estate markets. Esri’s housing affordability index measures the financial ability of a typical household to purchase an existing home in an area. A HAI of 100 represents an area that on average has sufficient household income to qualify for a loan on a home valued at the median home price. An index greater than 100 suggests homes are easily afforded by the average area resident. A HAI less than 100 suggests that homes are less affordable. The housing affordability index is not applicable in areas with no households or in predominantly rental markets . Esri’s home value estimates cover owner-occupied homes only. For a full demographic analysis of US growth refer to Esri's Trending in 2017: The Selectivity of Growth.

The pop-up is configured to show the following 2017 demographics for each County and ZIP Code:

Total Households 2010-17 Annual Pop Change Median Age Percent Owner-Occupied Housing Units Median Household Income Median Home Value Housing Affordability Index Share of Income to Mortgage

In 2024, the annual cost for a private room in an assisted living facility in the U.S. amounted to 70,800 U.S. dollars - the national median price. However, cost varied greatly from one state to another. The least expensive states for a private room in assisted living were South Dakota, and Mississippi. While the most expensive states for assisted living were Hawaii and Alaska.

In 2019, the state of California had the least affordable child care.The cost of care is presented as a percentage of state median income for a two-parent family. About 18 percent of the median income of a two-parent family had to be spent for full-time care for an infant in a child care center.

Graph and download economic data for Housing Affordability Index (Fixed) (FIXHAI) from Apr 2024 to Apr 2025 about fixed, housing, indexes, and USA.

In 2024, the western island state of Hawaii offered the most affordable homeowners' insurance in the United States. Homeowners in Hawaii paid an annual average of 515 U.S. dollars for insurance coverage. On the other hand, Oklahoma, Texas, and Nebraska were among the least affordable states for homeowners insurance. Who are the leading providers of homeowners insurance in the United States? State Farm, headquartered in Bloomington, Illinois, maintained its position as a market leader in home insurance due to its extensive network of agents, strong financial stability, and consistently high customer satisfaction ratings. Other leading providers of homeowners insurance in the United States included Allstate Corporation and Liberty Mutual. These companies dominate the market by offering comprehensive coverage options, competitive pricing, and reliable claims services, making them the preferred choice for millions of homeowners. How has U.S. homeownership changed since the financial crisis? Since the global financial crisis, the homeownership rate in the United States has seen a significant decline. Before the crisis, homeownership peaked at approximately 69 percent in the mid-2000s. Following the downturn, it dropped significantly, reaching lows around 64 percent by the mid-2010s. In recent years, homeownership has seen a modest recovery, but levels remain below the pre-crisis peak, as rising costs and market constraints continue to pose challenges for many.

The Housing Affordability Data System (HADS) is a set of files derived from the 1985 and later national American Housing Survey (AHS) and the 2002 and later Metro AHS. This system categorizes housing units by affordability and households by income, with respect to the Adjusted Median Income, Fair Market Rent (FMR), and poverty income. It also includes housing cost burden for owner and renter households. These files have been the basis for the worst case needs tables since 2001. The data files are available for public use, since they were derived from AHS public use files and the published income limits and FMRs. These dataset give the community of housing analysts the opportunity to use a consistent set of affordability measures. The most recent year HADS is available as a Public Use File (PUF) is 2013. For 2015 and beyond, HADS is only available as an IUF and can no longer be released on a PUF. Those seeking access to more recent data should reach to the listed point of contact.

In 2024, the annual cost for a private room in an assisted living facility in the U.S. amounted to 70,800 U.S. dollars. However, costs varied greatly from one state to another. The most expensive states for a private room in assisted living was found in Hawaii, followed by Alaska and DC.

First launched by the U.S. Department of Housing and Urban Development (HUD) and Department of Transportation (DOT) in November 2013, the Location Affordability Index (LAI) provides ubiquitous, standardized household housing and transportation cost estimates for all 50 states and the District of Columbia. Because what is affordable is different for everyone, users can choose among eight household profiles—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.

Version 3 updates the constituent data sets with 2012-2016 American Community Survey data and makes several methodological tweaks, most notably moving to modeling at the Census tract level rather at the block group. As with Version 2, the inputs to the simultaneous equation model (SEM) include six endogenous variables—housing costs, car ownership, and transit usage for both owners and renters—and 18 exogenous variables, with vehicle miles traveled still modeled separately due to data limitations.To learn more about the Location Affordability Index (v.3) visit: https://www.hudexchange.info/programs/location-affordability-index/, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. Date of Coverage: 2012-2016 Data Dictionary: DD_Location Affordability Indev v.3.0LAI Version 3 Data and MethodologyLAI Version 3 Technical Documentation

This web map shows the potential relationship between Esri's housing affordability index (HAI) and median household income in the United States for CBSA metropolitan and micropolitan statistical areas. It also shows Total Household Growth between 2010-2018. The data can be used to determine the impact between income earned in relationship to housing affordability. For example;Which areas experience very affordable housing and earn high median household incomesWhich areas experience affordable housing but earn relatively low median household incomesWhich areas experience the least affordable housing but earn relatively high median household incomesWhich areas experience the least affordable housing along and below US median household incomes

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.

First launched by the U.S. Department of Housing and Urban Development (HUD) and Department of Transportation (DOT) in November 2013, the Location Affordability Index (LAI) provides ubiquitous, standardized household housing and transportation cost estimates at the Census block-group level for the majority of the populated area of the United States. Because what is affordable is different for everyone, users can choose among eight household profiles—which vary by household income, size, and number of commuters—and see the impact of the built environment on affordability in a given neighborhood location while holding household demographics constant.

In Version 1, these estimates were originally generated with data from several federal sources and vehicle miles traveled (VMT) data from Illinois EPA using separate OLS regression models for household housing costs, VMT, car ownership, and transit usage. Version 2, in addition to updating all the constituent data sources, represents a significant a methodological and technical advance from Version 1, modelling auto ownership, housing costs, and transit usage for both homeowners and renters are concurrently using simultaneous equation modeling (SEM) to capture the interrelationship of these factors. The inputs to the SEM include these six endogenous variables and 18 exogenous variables, with VMT still modeled separately due to data limitations.

To learn more about the Location Affordability Index (v.2.0) visit: https://www.hudexchange.info/programs/location-affordability-index/, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. Data Dictionary: DD_Location Affordability Indev v.2.0 Date of Coverage: 2008-2012

The housing affordability measure illustrates the relationship between income and housing costs. A household that spends 30% or more of its collective monthly income to cover housing costs is considered to be “housing cost-burden[ed].”[1] Those spending between 30% and 49.9% of their monthly income are categorized as “moderately housing cost-burden[ed],” while those spending more than 50% are categorized as “severely housing cost-burden[ed].”[2]

How much a household spends on housing costs affects the household’s overall financial situation. More money spent on housing leaves less in the household budget for other needs, such as food, clothing, transportation, and medical care, as well as for incidental purchases and saving for the future.

The estimated housing costs as a percentage of household income are categorized by tenure: all households, those that own their housing unit, and those that rent their housing unit.

Throughout the period of analysis, the percentage of housing cost-burdened renter households in Champaign County was higher than the percentage of housing cost-burdened homeowner households in Champaign County. All three categories saw year-to-year fluctuations between 2005 and 2023, and none of the three show a consistent trend. However, all three categories were estimated to have a lower percentage of housing cost-burdened households in 2023 than in 2005.

Data on estimated housing costs as a percentage of monthly income was sourced from the U.S. Census Bureau’s American Community Survey (ACS) 1-Year Estimates, which are released annually.

As with any datasets that are estimates rather than exact counts, it is important to take into account the margins of error (listed in the column beside each figure) when drawing conclusions from the data.

Due to the impact of the COVID-19 pandemic, instead of providing the standard 1-year data products, the Census Bureau released experimental estimates from the 1-year data in 2020. This includes a limited number of data tables for the nation, states, and the District of Columbia. The Census Bureau states that the 2020 ACS 1-year experimental tables use an experimental estimation methodology and should not be compared with other ACS data. For these reasons, and because data is not available for Champaign County, no data for 2020 is included in this Indicator.

For interested data users, the 2020 ACS 1-Year Experimental data release includes a dataset on Housing Tenure.

[1] Schwarz, M. and E. Watson. (2008). Who can afford to live in a home?: A look at data from the 2006 American Community Survey. U.S. Census Bureau.

[2] Ibid.

Sources: U.S. Census Bureau; American Community Survey, 2023 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using data.census.gov; (17 October 2024).; U.S. Census Bureau; American Community Survey, 2022 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using data.census.gov; (22 September 2023).; U.S. Census Bureau; American Community Survey, 2021 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using data.census.gov; (30 September 2022).; U.S. Census Bureau; American Community Survey, 2019 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using data.census.gov; (10 June 2021).; U.S. Census Bureau; American Community Survey, 2018 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using data.census.gov; (10 June 2021).;U.S. Census Bureau; American Community Survey, 2017 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2016 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (14 September 2017).; U.S. Census Bureau; American Community Survey, 2015 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (19 September 2016).; U.S. Census Bureau; American Community Survey, 2014 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2013 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2012 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2011 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2010 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2009 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2008 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; 16 March 2016).; U.S. Census Bureau; American Community Survey, 2007 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2006 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2005 American Community Survey 1-Year Estimates, Table B25106; generated by CCRPC staff; using American FactFinder; (16 March 2016).

In the United States, Hawaii was the state with the most expensive housing, with the typical value of single-family homes in the 35th to 65th percentile range exceeding ******* U.S. dollars. Unsurprisingly, Hawaii also ranked top as the state with the highest cost of living. Meanwhile, a property was the least expensive in West Virginia, where it cost under ******* U.S. dollars to buy the typical single-family home. Single-family home prices increased across most states in the United States between December 2023 and December 2024, except in Louisiana, Florida, and the District of Colombia. According to the Federal Housing Association, house appreciation in 13 states exceeded **** percent in 2023.

In the United States, a private room in a nursing home facility came with a cost of 127,750 U.S. dollars per year in 2024. However, the costs for private rooms in the US varied greatly from one state to another. That year, the annual cost for a private room in Alaska stood at 364,452 U.S. dollars, roughly three times the national average. The second-most expensive state for a private room in nursing home facilities was Oregon, followed by DC.

The graph illustrates the most expensive drugs in the United States for the year 2024. The x-axis lists the drug names, including Lenmeldy***, Hemgenix*, Elevidys*, Skysona*, Zynteglo*, Zolgensma*, Myalept**, Danyelza**, Zokinvy**, and Kimmtrak**, while the y-axis represents the cost of each drug in U.S. dollars. Among these, Lenmeldy*** stands as the most costly medication at $4,250,000, followed by Hemgenix* at $3,500,000 and Elevidys* at $3,200,000. The prices gradually decrease with Skysona* priced at $3,000,000, Zynteglo* at $2,800,000, and Zolgensma* at $2,100,000. The remaining drugs—Myalept** ($1,300,000), Danyelza** and Zokinvy** (each at $1,200,000), and Kimmtrak** ($1,100,000)—are comparatively less expensive but still among the highest-priced medications available. The data reveals a significant disparity in drug costs, with the top-priced drug being nearly four times more expensive than the least expensive one listed. This steep decline from the highest to the lowest cost highlights the wide range of prices within the most expensive pharmaceuticals in the U.S. for 2024. The information is effectively represented in a bar graph format, which clearly showcases the differences in drug prices and emphasizes the concentration of costs among the top-tier medications.

Graph and download economic data for Median Sales Price of Houses Sold for the United States (MSPUS) from Q1 1963 to Q1 2025 about sales, median, housing, and USA.

More than one minimum wage job was required to afford two-bedroom housing in all states in the United States in 2024. At mean wage, Hawaii was the most expensive state requiring renters to hold about two full-time jobs at a mean wage to afford two-bedroom housing. The fair market rent value of two bedroom housing in Hawaii ranked fourth most expensive among all states in the United States in 2024.

A table listing the average electricity rates (kWh) of all 50 U.S. states as of March 2025.

The annual cost for home health services in the U.S. was 77,792 US dollars in 2024, yet varied greatly from one state to another. In that year, the most expensive U.S. state for home health aide was South Dakota, with annual cost over 100 thousand U.S. dollars.