66 datasets found
  1. Cost of living index in the U.S. 2024, by state

    • statista.com
    Updated May 27, 2025
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    Statista (2025). Cost of living index in the U.S. 2024, by state [Dataset]. https://www.statista.com/statistics/1240947/cost-of-living-index-usa-by-state/
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    Dataset updated
    May 27, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2024
    Area covered
    United States
    Description

    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.

  2. Data from: Cost of Living in the United States, 1917-1919

    • icpsr.umich.edu
    ascii, sas, spss
    Updated Feb 16, 1992
    + more versions
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    United States Department of Labor. Bureau of Labor Statistics (1992). Cost of Living in the United States, 1917-1919 [Dataset]. http://doi.org/10.3886/ICPSR08299.v5
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    ascii, sas, spssAvailable download formats
    Dataset updated
    Feb 16, 1992
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    United States Department of Labor. Bureau of Labor Statistics
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/8299/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/8299/terms

    Time period covered
    1917 - 1919
    Area covered
    United States
    Description

    This collection contains data obtained from families of wage earners or salaried workers in industrial locales scattered throughout the United States. The purpose of the survey was to estimate the cost of living of a "typical" American family. The completed questionnaires contain information about income sources and family expenditures including specific quantities and costs of food, housing, clothing, fuel, furniture, and miscellaneous household items for the calendar year. Demographic characteristics recorded for each household member include relationship to head, age, sex, occupation, weeks spent in the household and employed, wage rate, and total earnings.

  3. Data and Code for: Measuring the Cost of Living in Mexico and the U.S.

    • openicpsr.org
    Updated Oct 24, 2021
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    David Argente; Chang-Tai Hsieh; Munseob Lee (2021). Data and Code for: Measuring the Cost of Living in Mexico and the U.S. [Dataset]. http://doi.org/10.3886/E153241V1
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    Dataset updated
    Oct 24, 2021
    Dataset provided by
    American Economic Associationhttp://www.aeaweb.org/
    Authors
    David Argente; Chang-Tai Hsieh; Munseob Lee
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Mexico, United States
    Description

    We use a dataset with prices and spending on consumer packaged goods matched at the barcode-level across the US and Mexico to measure the price index in Mexico relative to the US. Mexican prices relative to the US are 23% lower compared to the International Comparisons Project's (ICP) price index. We decompose the 23% gap into the biases from imputation, sampling, quality, and variety. Quality bias increases Mexican prices by 48%. Imputation, sampling, and variety bias lowers Mexican prices by 11%, 13%, and 33%, respectively.

  4. T

    Vital Signs: Poverty - Bay Area (2022)

    • data.bayareametro.gov
    application/rdfxml +5
    Updated Jan 3, 2023
    + more versions
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    (2023). Vital Signs: Poverty - Bay Area (2022) [Dataset]. https://data.bayareametro.gov/dataset/Vital-Signs-Poverty-Bay-Area-2022-/g2wq-gn4h
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    xml, csv, json, application/rssxml, application/rdfxml, tsvAvailable download formats
    Dataset updated
    Jan 3, 2023
    Area covered
    San Francisco Bay Area
    Description

    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.

  5. Consumer reactions to the cost of living crisis in the U.S. 2023

    • statista.com
    Updated Jun 5, 2023
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    Statista (2023). Consumer reactions to the cost of living crisis in the U.S. 2023 [Dataset]. https://www.statista.com/statistics/1384081/consumer-reactions-to-the-cost-of-living-crisis-in-the-us/
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    Dataset updated
    Jun 5, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Apr 19, 2023 - Apr 24, 2023
    Area covered
    United States
    Description

    Around 64 percent of U.S. consumers spend less on non-essentials amidst the ongoing cost of living crisis in 2023. This is according to a survey conducted by We are Social and Statista Q, which shows that rising inflation rates have caused around a similar percentage of customers to pay more attention to bargains, good deals, or offers (when going shopping). Furthermore, around 39 percent of U.S. consumers do not go out for dinner/lunch anymore to deal with the situation.

  6. US Cost of Living Dataset (1877 Counties)

    • kaggle.com
    Updated Feb 17, 2024
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    asaniczka (2024). US Cost of Living Dataset (1877 Counties) [Dataset]. http://doi.org/10.34740/kaggle/ds/3832881
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 17, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    asaniczka
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Area covered
    United States
    Description

    The US Family Budget Dataset provides insights into the cost of living in different US counties based on the Family Budget Calculator by the Economic Policy Institute (EPI).

    This dataset offers community-specific estimates for ten family types, including one or two adults with zero to four children, in all 1877 counties and metro areas across the United States.

    Interesting Task Ideas:

    1. See how family budgets compare to the federal poverty line and the Supplemental Poverty Measure in different counties.
    2. Look into the money challenges faced by different types of families using the budgets provided.
    3. Find out which counties have the most affordable places to live, food, transportation, healthcare, childcare, and other things people need.
    4. Explore how the average income of families relates to the overall cost of living in different counties.
    5. Investigate how family size affects the estimated budget and find counties where bigger families have higher costs.
    6. Create visuals showing how the cost of living varies across different states and big cities.
    7. Check whether specific counties are affordable for families of different sizes and types.
    8. Use the dataset to compare living standards and economic security in different US counties.

    If you find this dataset valuable, don't forget to hit the upvote button! 😊💝

    Checkout my other datasets

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    Photo by Alev Takil on Unsplash

  7. Cost of living index in India 2024, by city

    • statista.com
    Updated Jun 23, 2025
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    Statista (2025). Cost of living index in India 2024, by city [Dataset]. https://www.statista.com/statistics/1399330/india-cost-of-living-index-by-city/
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    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    India
    Description

    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.

  8. D

    Replication Data for: Product Variety, the Cost of Living and Welfare Across...

    • test.dataverse.nl
    pdf, zip
    Updated Feb 3, 2022
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    A. Cavallo; R.C. Feenstra; R.C. Inklaar; A. Cavallo; R.C. Feenstra; R.C. Inklaar (2022). Replication Data for: Product Variety, the Cost of Living and Welfare Across Countries [Dataset]. http://doi.org/10.34894/7RCSFZ
    Explore at:
    pdf(128041), zip(177370749)Available download formats
    Dataset updated
    Feb 3, 2022
    Dataset provided by
    DataverseNL (test)
    Authors
    A. Cavallo; R.C. Feenstra; R.C. Inklaar; A. Cavallo; R.C. Feenstra; R.C. Inklaar
    License

    https://tdvnl.dans.knaw.nl/api/datasets/:persistentId/versions/1.1/customlicense?persistentId=doi:10.34894/7RCSFZhttps://tdvnl.dans.knaw.nl/api/datasets/:persistentId/versions/1.1/customlicense?persistentId=doi:10.34894/7RCSFZ

    Description

    Cavallo, A., Feenstra, R.C., & Inklaar, R.C., (2022). Product Variety, the Cost of Living and Welfare Across Countries. American Economic Journal: Macroeconomics, forthcoming

  9. H

    Replication Data for: The Fading American Dream: Trends in Absolute Income...

    • dataverse.harvard.edu
    • search.dataone.org
    Updated Feb 23, 2022
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    Raj Chetty; David Grusky; Maximilian Hell; Nathaniel Hendren; Robert Manduca; Jimmy Narang (2022). Replication Data for: The Fading American Dream: Trends in Absolute Income Mobility Since 1940 [Dataset]. http://doi.org/10.7910/DVN/B9TEWM
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 23, 2022
    Dataset provided by
    Harvard Dataverse
    Authors
    Raj Chetty; David Grusky; Maximilian Hell; Nathaniel Hendren; Robert Manduca; Jimmy Narang
    License

    https://dataverse.harvard.edu/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.7910/DVN/B9TEWMhttps://dataverse.harvard.edu/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.7910/DVN/B9TEWM

    Description

    This dataset contains replication files for "The Fading American Dream: Trends in Absolute Income Mobility Since 1940" by Raj Chetty, David Grusky, Maximilian Hell, Nathaniel Hendren, Robert Manduca, and Jimmy Narang. For more information, see https://opportunityinsights.org/paper/the-fading-american-dream/. A summary of the related publication follows. One of the defining features of the “American Dream” is the ideal that children have a higher standard of living than their parents. We assess whether the U.S. is living up to this ideal by estimating rates of “absolute income mobility” – the fraction of children who earn more than their parents – since 1940. We measure absolute mobility by comparing children’s household incomes at age 30 (adjusted for inflation using the Consumer Price Index) with their parents’ household incomes at age 30. We find that rates of absolute mobility have fallen from approximately 90% for children born in 1940 to 50% for children born in the 1980s. Absolute income mobility has fallen across the entire income distribution, with the largest declines for families in the middle class. These findings are unaffected by using alternative price indices to adjust for inflation, accounting for taxes and transfers, measuring income at later ages, and adjusting for changes in household size. Absolute mobility fell in all 50 states, although the rate of decline varied, with the largest declines concentrated in states in the industrial Midwest, such as Michigan and Illinois. The decline in absolute mobility is especially steep – from 95% for children born in 1940 to 41% for children born in 1984 – when we compare the sons’ earnings to their fathers’ earnings. Why have rates of upward income mobility fallen so sharply over the past half-century? There have been two important trends that have affected the incomes of children born in the 1980s relative to those born in the 1940s and 1950s: lower Gross Domestic Product (GDP) growth rates and greater inequality in the distribution of growth. We find that most of the decline in absolute mobility is driven by the more unequal distribution of economic growth rather than the slowdown in aggregate growth rates. When we simulate an economy that restores GDP growth to the levels experienced in the 1940s and 1950s but distributes that growth across income groups as it is distributed today, absolute mobility only increases to 62%. In contrast, maintaining GDP at its current level but distributing it more broadly across income groups – at it was distributed for children born in the 1940s – would increase absolute mobility to 80%, thereby reversing more than two-thirds of the decline in absolute mobility. These findings show that higher growth rates alone are insufficient to restore absolute mobility to the levels experienced in mid-century America. Under the current distribution of GDP, we would need real GDP growth rates above 6% per year to return to rates of absolute mobility in the 1940s. Intuitively, because a large fraction of GDP goes to a small fraction of high-income households today, higher GDP growth does not substantially increase the number of children who earn more than their parents. Of course, this does not mean that GDP growth does not matter: changing the distribution of growth naturally has smaller effects on absolute mobility when there is very little growth to be distributed. The key point is that increasing absolute mobility substantially would require more broad-based economic growth. We conclude that absolute mobility has declined sharply in America over the past half-century primarily because of the growth in inequality. If one wants to revive the “American Dream” of high rates of absolute mobility, one must have an interest in growth that is shared more broadly across the income distribution.

  10. T

    Vital Signs: Poverty - by metro (2022)

    • data.bayareametro.gov
    application/rdfxml +5
    Updated Jan 3, 2023
    + more versions
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    (2023). Vital Signs: Poverty - by metro (2022) [Dataset]. https://data.bayareametro.gov/dataset/Vital-Signs-Poverty-by-metro-2022-/bnmj-wqz3
    Explore at:
    application/rssxml, csv, application/rdfxml, tsv, json, xmlAvailable download formats
    Dataset updated
    Jan 3, 2023
    Description

    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.

  11. Annual costs of long-term care services in the U.S. in 2024, by type

    • statista.com
    • ai-chatbox.pro
    Updated Jun 27, 2025
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    Statista (2025). Annual costs of long-term care services in the U.S. in 2024, by type [Dataset]. https://www.statista.com/statistics/310446/annual-median-rate-of-long-term-care-services-in-the-us/
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    Dataset updated
    Jun 27, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jul 2024 - Dec 2024
    Area covered
    United States
    Description

    In 2024, the annual median cost for long-term care in the United States ranged from ****** to ******* U.S. dollars, depending on the type of service. This significant financial burden highlights the importance of planning for future healthcare needs, as many older adults may face substantial out-of-pocket costs for extended care services. Nursing homes and assisted living facilities Nursing homes represent the most expensive long-term care option, with private rooms costing an estimated ****** U.S. dollars per month in 2024. Semi-private rooms are slightly more affordable at ***** U.S. dollars monthly. Assisted living facilities offer a less costly alternative, with annual expenses for a private room averaging ****** U.S. dollars. However, these costs can vary dramatically by location, with states like Hawaii, Alaska, and Washington D.C. commanding the highest prices for assisted living accommodations. Home care services and future projections For those preferring to receive care at home, the hourly rates for long-term home care services in 2024 were ** U.S. dollars for homemaker services and ** U.S. dollars for home health aide services. These costs are expected to rise significantly in the coming decades, with projections suggesting home health aide services could approach *** U.S. dollars per hour by 2060. The increasing expense of long-term care is evident across all service types, with assisted living facilities experiencing a ** percent cost increase from 2023 to 2024, while nursing home rates for semi-private and private rooms rose by * and * percent, respectively.

  12. Cheapest and most expensive countries to live in Latin America 2023

    • statista.com
    • ai-chatbox.pro
    Updated Jul 5, 2024
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    Statista (2024). Cheapest and most expensive countries to live in Latin America 2023 [Dataset]. https://www.statista.com/statistics/1375636/cheapest-most-expensive-countries-latin-america/
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    Dataset updated
    Jul 5, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Mar 2023
    Area covered
    Latin America, Americas, LAC
    Description

    According to a recent study, Colombia had the lowest monthly cost of living in Latin America with 546 U.S. dollars needed for basic living. In contrast, four countries had a cost of living above one thousand dollars, Costa Rica, Chile, Panama and Uruguay. In 2022, the highest minimum wage in the region was recorded by Ecuador with 425 dollars per month.

    Can Latin Americans survive on a minimum wage? Even if most countries in Latin America have instated laws to guarantee citizens a basic income, these minimum standards are often not enough to meet household needs. For instance, it was estimated that almost 22 million people in Mexico lacked basic housing services. Salary levels also vary greatly among Latin American economies. In 2022, the average net monthly salary in Brazil was lower than Ecuador's minimum wage.

    What can a minimum wage afford in Latin America? Latin American real wages have generally risen in the past decade. However, consumers in this region still struggle to afford non-basic goods, such as tech products. Recent estimates reveal that, in order to buy an iPhone, Brazilian residents would have to work more than two months to be able to pay for it. A gaming console, on the other hand, could easily cost a Latin American worker several minimum wages.

  13. Typical price of single-family homes in the U.S. 2020-2024, by state

    • statista.com
    • ai-chatbox.pro
    Updated Jun 20, 2025
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    Statista (2025). Typical price of single-family homes in the U.S. 2020-2024, by state [Dataset]. https://www.statista.com/statistics/1041708/typical-home-value-single-family-homes-usa-by-state/
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    Dataset updated
    Jun 20, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    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.

  14. Monthly residential utility costs, by state U.S. 2023

    • statista.com
    Updated Jun 20, 2025
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    Statista (2025). Monthly residential utility costs, by state U.S. 2023 [Dataset]. https://www.statista.com/statistics/1108684/monthly-utility-costs-usa-state/
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    Dataset updated
    Jun 20, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States
    Description

    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.

  15. T

    United States Consumer Price Index (CPI)

    • tradingeconomics.com
    • fa.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jul 15, 2025
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    TRADING ECONOMICS (2025). United States Consumer Price Index (CPI) [Dataset]. https://tradingeconomics.com/united-states/consumer-price-index-cpi
    Explore at:
    xml, csv, excel, jsonAvailable download formats
    Dataset updated
    Jul 15, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 31, 1950 - Jun 30, 2025
    Area covered
    United States
    Description

    Consumer Price Index CPI in the United States increased to 322.56 points in June from 321.46 points in May of 2025. This dataset provides the latest reported value for - United States Consumer Price Index (CPI) - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  16. Share of people who believe that the cost of living is the main issue...

    • statista.com
    Updated Jul 18, 2025
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    Statista (2025). Share of people who believe that the cost of living is the main issue Australia 2025 [Dataset]. https://www.statista.com/statistics/1534807/australia-share-of-people-who-believe-the-cost-of-living-is-the-main-issue/
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    Dataset updated
    Jul 18, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Mar 2024 - Mar 2025
    Area covered
    Australia
    Description

    According to a survey conducted among adults in Australia in March 2025, ** percent of the respondents surveyed in September believed that the cost of living is the chief issue that Australia is facing. This represented a ***** percent decrease in those citing the cost of living as the main issue compared to March of the previous year.

  17. U.S. annual consumer spending 2023, by type

    • statista.com
    Updated Oct 23, 2024
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    Statista (2024). U.S. annual consumer spending 2023, by type [Dataset]. https://www.statista.com/statistics/247407/average-annual-consumer-spending-in-the-us-by-type/
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    Dataset updated
    Oct 23, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States
    Description

    In 2023, the average consumer unit in the United States spent about 9,985 U.S. dollars on food. Americans spent the most on housing, at 25,436 U.S. dollars, reflecting around one third of annual expenditure. The total average U.S. consumer spending amounted to 77,280 U.S. dollars.

  18. D

    Senior Co-Housing Market Research Report 2033

    • dataintelo.com
    csv, pdf, pptx
    Updated Jun 28, 2025
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    Dataintelo (2025). Senior Co-Housing Market Research Report 2033 [Dataset]. https://dataintelo.com/report/senior-co-housing-market
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    pdf, pptx, csvAvailable download formats
    Dataset updated
    Jun 28, 2025
    Authors
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Senior Co-Housing Market Outlook



    According to our latest research, the global senior co-housing market size reached USD 8.2 billion in 2024, driven by the growing demand for innovative housing solutions among older adults. The market is projected to exhibit a robust compound annual growth rate (CAGR) of 7.1% from 2025 to 2033, reaching a forecasted value of USD 15.3 billion by 2033. This sustained growth is primarily attributed to the rising aging population, increasing preference for community-centric living arrangements, and the continuous evolution of senior care models worldwide.




    One of the primary growth drivers for the senior co-housing market is the rapidly aging global population. As life expectancy continues to rise, more individuals are reaching retirement age, resulting in a substantial increase in the number of people aged 55 and above. This demographic shift has created a pressing need for alternative living arrangements that offer not only affordability but also foster social interaction and community engagement. Traditional senior housing options often fall short in providing the desired sense of autonomy and companionship, making co-housing an attractive alternative. Furthermore, the prevalence of chronic diseases and the desire for aging in place have prompted seniors and their families to seek out living environments that balance independence with access to supportive services, fueling the adoption of co-housing models.




    Another significant factor contributing to market expansion is the changing attitudes toward aging and retirement. Modern seniors are increasingly seeking active, meaningful lifestyles post-retirement, emphasizing social connections, shared responsibilities, and mutual support. The senior co-housing market addresses these preferences by offering shared living spaces, communal resources, and collaborative decision-making frameworks. This model resonates particularly well with the Baby Boomer generation, which values autonomy and social engagement. Moreover, the economic benefits associated with co-housing, such as reduced living costs and shared amenities, further enhance its appeal in regions facing rising housing prices and limited affordable senior living options.




    Technological advancements and supportive government policies are also playing a pivotal role in shaping the senior co-housing market. Innovations in health monitoring, security, and smart home technologies have made it easier to integrate supportive care services into co-housing communities, enhancing safety and quality of life for residents. Additionally, several governments and non-profit organizations are actively promoting senior co-housing through regulatory incentives, funding, and awareness campaigns. These efforts are fostering the development of new co-housing projects and enabling the scaling of existing models, thereby accelerating market growth across developed and emerging economies alike.




    Regionally, Europe and North America continue to dominate the senior co-housing market due to their advanced healthcare infrastructure, high awareness levels, and favorable policy environments. Europe, in particular, has a long-standing tradition of collaborative housing, while North America is witnessing a surge in innovative co-housing projects tailored to the needs of older adults. Meanwhile, the Asia Pacific region is emerging as a lucrative market, driven by rapid urbanization, changing family structures, and a burgeoning aging population. Latin America and the Middle East & Africa are also experiencing gradual growth, supported by increasing investments in senior care infrastructure and evolving cultural attitudes toward elder care.



    Housing Type Analysis



    The senior co-housing market is segmented by housing type into shared apartments, co-operative housing, cluster housing, and others, each catering to distinct preferences and community dynamics among older adults. Shared apartments have gained significant traction, particularly in urban centers, as they offer an affordable and flexible solution for seniors seeking companionship and reduced living expenses. These arrangements typically involve private bedrooms with shared common areas such as kitchens and living rooms, fostering a sense of community while maintaining personal privacy. The popularity of shared apartments is bolstered by rising urban housing costs and the desire among seniors to avoid social isolation, making this segme

  19. Student Micro-Apartment Market Research Report 2033

    • growthmarketreports.com
    csv, pdf, pptx
    Updated Jun 29, 2025
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    Growth Market Reports (2025). Student Micro-Apartment Market Research Report 2033 [Dataset]. https://growthmarketreports.com/report/student-micro-apartment-market
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    csv, pptx, pdfAvailable download formats
    Dataset updated
    Jun 29, 2025
    Dataset authored and provided by
    Growth Market Reports
    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Student Micro-Apartment Market Outlook




    According to our latest research, the global student micro-apartment market size reached USD 9.2 billion in 2024 and is projected to grow at a robust CAGR of 8.4% from 2025 to 2033, attaining a forecasted market value of USD 18.8 billion by 2033. This significant growth is primarily driven by the increasing demand for affordable, flexible, and well-located student housing solutions in urban centers worldwide, as higher education enrollment continues to surge and urbanization intensifies.




    One of the primary growth factors propelling the student micro-apartment market is the ongoing surge in global student mobility. As more students pursue higher education abroad, particularly in countries like the United States, United Kingdom, Australia, and Canada, the demand for compact, cost-effective, and conveniently located accommodation near educational institutions has soared. These micro-apartments offer students a blend of privacy, affordability, and community living, making them an attractive alternative to traditional dormitories and private rentals. Additionally, the rising costs of urban real estate have made large-scale student housing projects less viable, pushing developers to focus on micro-apartments that maximize space efficiency while minimizing rental costs.




    Another key driver is the evolving lifestyle preferences of Generation Z and Millennial students, who prioritize sustainability, flexibility, and connectivity in their living arrangements. Student micro-apartments are designed to cater to these preferences by incorporating smart technology, energy-efficient appliances, and communal amenities such as study lounges, gyms, and social spaces. The modular nature of many micro-apartment projects enables rapid construction, scalability, and adaptability to changing student needs, further fueling market growth. Moreover, universities and private developers are increasingly partnering to offer purpose-built student accommodations (PBSA), integrating micro-apartments into campus master plans to enhance student satisfaction and retention.




    The market is also benefiting from the expansion of higher education institutions into secondary and tertiary cities, especially in emerging economies across Asia Pacific and Latin America. These regions are witnessing a boom in university enrollments, driven by favorable demographic trends and government initiatives to improve access to education. As a result, there is a heightened need for affordable student housing options that can be quickly deployed and managed efficiently. The growing acceptance of alternative rental models, such as co-living and shared micro-apartments, is further diversifying the market landscape, attracting investment from real estate funds, institutional investors, and proptech startups.




    Regionally, Europe and North America remain the largest markets for student micro-apartments, accounting for a combined share of over 60% of global revenues in 2024. However, the Asia Pacific region is emerging as the fastest-growing market, with a projected CAGR of over 10% during the forecast period. Countries like China, India, and Australia are experiencing unprecedented growth in international student inflows and domestic university enrollments, driving robust demand for modern, affordable student housing solutions. Meanwhile, Middle East & Africa and Latin America are gradually catching up, supported by urbanization, rising middle-class incomes, and strategic investments in educational infrastructure.





    Apartment Type Analysis




    The student micro-apartment market is segmented by apartment type into studio, loft, shared, modular, and others, each catering to distinct student preferences and budget considerations. Studio apartments remain the most popular choice, offering a self-contained living space that combines bedroom, kitchenette, and bathroom facilities in a compact footprint. This format appeals to studen

  20. U.S. consumer Price Index of all urban consumers 1992-2024

    • statista.com
    Updated Feb 10, 2025
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    Statista (2025). U.S. consumer Price Index of all urban consumers 1992-2024 [Dataset]. https://www.statista.com/statistics/190974/unadjusted-consumer-price-index-of-all-urban-consumers-in-the-us-since-1992/
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    Dataset updated
    Feb 10, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    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.

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Statista (2025). Cost of living index in the U.S. 2024, by state [Dataset]. https://www.statista.com/statistics/1240947/cost-of-living-index-usa-by-state/
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Cost of living index in the U.S. 2024, by state

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Dataset updated
May 27, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
2024
Area covered
United States
Description

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.

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