7 datasets found
  1. Cost of Living Index 2022

    • kaggle.com
    Updated May 28, 2022
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    Ankan Hore (2022). Cost of Living Index 2022 [Dataset]. https://www.kaggle.com/datasets/ankanhore545/cost-of-living-index-2022
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 28, 2022
    Dataset provided by
    Kaggle
    Authors
    Ankan Hore
    Description

    Cost of Living Index (Excl. Rent) is a relative indicator of consumer goods prices, including groceries, restaurants, transportation and utilities. Cost of Living Index does not include accommodation expenses such as rent or mortgage. If a city has a Cost of Living Index of 120, it means Numbeo has estimated it is 20% more expensive than New York (excluding rent).

    Please refer further to: https://www.numbeo.com/cost-of-living/cpi_explained.jsp for motivation and methodology.

    All credits to https://www.numbeo.com .

    This dataset would surely help socio-economic researchers to analyse and get deeper insights regarding the life of people country-wise.

    Thanks to @andradaolteanu for the motivation! Upwards and onwards...

  2. Cost of living indices Singapore 2024, by category

    • statista.com
    • ai-chatbox.pro
    Updated Jun 23, 2025
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    Statista (2025). Cost of living indices Singapore 2024, by category [Dataset]. https://www.statista.com/statistics/1551867/singapore-cost-of-living-index-by-category/
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    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    Singapore
    Description

    In 2024, Singapore's cost of living index was at ****, compared to that of New York City as a base of 100. This meant that Singapore was about ** percent more affordable than New York City. With a local purchasing power index of ***, residents with an average salary in Singapore are able to afford more goods and services compared to the base city of New York City. In that year, Singapore had the highest cost of living index in Asia.

  3. U.S. Consumer Price Index for selected U.S. cities 2024

    • statista.com
    Updated Mar 5, 2025
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    Statista (2025). U.S. Consumer Price Index for selected U.S. cities 2024 [Dataset]. https://www.statista.com/statistics/245014/consumer-price-index-for-selected-us-cities/
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    Dataset updated
    Mar 5, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2024
    Area covered
    United States
    Description

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

  4. New York Housing cost index

    • knoema.es
    csv, json, sdmx, xls
    Updated Mar 17, 2025
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    Knoema (2025). New York Housing cost index [Dataset]. https://knoema.es/atlas/Vereinigte-Staaten-von-Amerika/New-York/topics/Income-and-Welfare/Cost-of-Living/Housing-cost-index?view=snowflake
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    csv, sdmx, json, xlsAvailable download formats
    Dataset updated
    Mar 17, 2025
    Dataset authored and provided by
    Knoemahttp://knoema.com/
    Time period covered
    Jan 1, 2021 - Jul 1, 2024
    Area covered
    Nueva York
    Variables measured
    Housing cost index
    Description

    170,2 (Index, higher means higher cost of living) in 2024Q3.

  5. New York Grocery cost index

    • knoema.es
    csv, json, sdmx, xls
    Updated Mar 17, 2025
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    Knoema (2025). New York Grocery cost index [Dataset]. https://knoema.es/atlas/Estados-Unidos-de-Am%C3%A9rica/New-York/topics/Income-and-Welfare/Cost-of-Living/Grocery-cost-index
    Explore at:
    sdmx, csv, xls, jsonAvailable download formats
    Dataset updated
    Mar 17, 2025
    Dataset authored and provided by
    Knoemahttp://knoema.com/
    Time period covered
    Jan 1, 2021 - Jul 1, 2024
    Area covered
    Nueva York
    Variables measured
    Grocery cost index
    Description

    103,8 (Index, higher means higher cost of living) in 2024Q3.

  6. M

    New York County Real Mean Household Wages (2009-2023)

    • macrotrends.net
    csv
    Updated Jun 30, 2025
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    MACROTRENDS (2025). New York County Real Mean Household Wages (2009-2023) [Dataset]. https://www.macrotrends.net/4968/new-york-county-real-mean-household-wages
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    csvAvailable download formats
    Dataset updated
    Jun 30, 2025
    Dataset authored and provided by
    MACROTRENDS
    License

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

    Time period covered
    2009 - 2023
    Area covered
    United States
    Description

    The observation for 2020 is missing because the U.S. Census Bureau released experimental estimates (https://www.census.gov/programs-surveys/acs/data/experimental-data.html) instead of the standard 1-year data products for the 2020 American Community Survey (ACS). There was no 2020 experimental data provided for the American Community Survey (ACS) 1-year variable S1901_C01_013E.

    Mean household income, American Community Survey (ACS) 1-year variable S1901_C01_013E, is adjusted by CPI (https://fred.stlouisfed.org/series/CPIAUCSL) where the price index is re-based to 1999 dollars. Then the series is adjusted for cost of living using regional price parities (RPP) from the U.S. Bureau of Economic Analysis' Real Personal Income for States and Metropolitan Areas (https://fred.stlouisfed.org/release?rid=403&soid=18). Finally to approximate the wage, the series is divided by (52 * 40), which assumes there are 52 weeks in a year and 40 work hours in a week. Note that household income can include additional sources of income beyond wages. See page 83 in the ACS's Subject Definitions (https://www2.census.gov/programs-surveys/acs/tech_docs/subject_definitions/2019_ACSSubjectDefinitions.pdf) for more information.

    ACS 1-year estimates are not available for all geographic areas. If a county is not included in the 1-year estimates for a given year, the series will not revise or there will be a missing observation. See the Areas Published (https://www.census.gov/programs-surveys/acs/geography-acs/areas-published.html) for more details about the geographies included in the ACS 1-year estimates.

    The RPP used to calculate this series is NYNMPRPPALL (https://fred.stlouisfed.org/series/NYNMPRPPALL). If the RPP for the region is zero or missing for a given year, the series will not revise or there will be a missing observation.

  7. Big Mac index worldwide 2025

    • statista.com
    • tiktok-play.menuridamusic.com
    • +1more
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    Statista, Big Mac index worldwide 2025 [Dataset]. https://www.statista.com/statistics/274326/big-mac-index-global-prices-for-a-big-mac/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 2025
    Area covered
    Worldwide
    Description

    At **** 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 **** dollars in the U.S., and **** 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.

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Click to copy link
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Ankan Hore (2022). Cost of Living Index 2022 [Dataset]. https://www.kaggle.com/datasets/ankanhore545/cost-of-living-index-2022
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Cost of Living Index 2022

Analyse the Cost of Living Index for each country in 2022

Explore at:
CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
Dataset updated
May 28, 2022
Dataset provided by
Kaggle
Authors
Ankan Hore
Description

Cost of Living Index (Excl. Rent) is a relative indicator of consumer goods prices, including groceries, restaurants, transportation and utilities. Cost of Living Index does not include accommodation expenses such as rent or mortgage. If a city has a Cost of Living Index of 120, it means Numbeo has estimated it is 20% more expensive than New York (excluding rent).

Please refer further to: https://www.numbeo.com/cost-of-living/cpi_explained.jsp for motivation and methodology.

All credits to https://www.numbeo.com .

This dataset would surely help socio-economic researchers to analyse and get deeper insights regarding the life of people country-wise.

Thanks to @andradaolteanu for the motivation! Upwards and onwards...

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