100+ datasets found
  1. Consumer Price Index (CPI)

    • catalog.data.gov
    • s.cnmilf.com
    • +1more
    Updated May 16, 2022
    + more versions
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    Bureau of Labor Statistics (2022). Consumer Price Index (CPI) [Dataset]. https://catalog.data.gov/dataset/consumer-price-index-cpi-ee18b
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    Dataset updated
    May 16, 2022
    Dataset provided by
    Bureau of Labor Statisticshttp://www.bls.gov/
    Description

    The Consumer Price Index (CPI) is a measure of the average change over time in the prices paid by urban consumers for a market basket of consumer goods and services. Indexes are available for the U.S. and various geographic areas. Average price data for select utility, automotive fuel, and food items are also available. Prices for the goods and services used to calculate the CPI are collected in 75 urban areas throughout the country and from about 23,000 retail and service establishments. Data on rents are collected from about 43,000 landlords or tenants. More information and details about the data provided can be found at http://www.bls.gov/cpi

  2. 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.

  3. U.S. projected Consumer Price Index 2010-2029

    • statista.com
    Updated Aug 21, 2024
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    Statista (2024). U.S. projected Consumer Price Index 2010-2029 [Dataset]. https://www.statista.com/statistics/244993/projected-consumer-price-index-in-the-united-states/
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    Dataset updated
    Aug 21, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    In 2023, the U.S. Consumer Price Index was 309.42, and is projected to increase to 352.27 by 2029. The base period was 1982-84. The monthly CPI for all urban consumers in the U.S. can be accessed here. After a time of high inflation, the U.S. inflation rateis projected fall to two percent by 2027. United States Consumer Price Index ForecastIt is projected that the CPI will continue to rise year over year, reaching 325.6 in 2027. The Consumer Price Index of all urban consumers in previous years was lower, and has risen every year since 1992, except in 2009, when the CPI went from 215.30 in 2008 to 214.54 in 2009. The monthly unadjusted Consumer Price Index was 296.17 for the month of August in 2022. The U.S. CPI measures changes in the price of consumer goods and services purchased by households and is thought to reflect inflation in the U.S. as well as the health of the economy. The U.S. Bureau of Labor Statistics calculates the CPI and defines it as, "a measure of the average change over time in the prices paid by urban consumers for a market basket of consumer goods and services." The BLS records the price of thousands of goods and services month by month. They consider goods and services within eight main categories: food and beverage, housing, apparel, transportation, medical care, recreation, education, and other goods and services. They aggregate the data collected in order to compare how much it would cost a consumer to buy the same market basket of goods and services within one month or one year compared with the previous month or year. Given that the CPI is used to calculate U.S. inflation, the CPI influences the annual adjustments of many financial institutions in the United States, both private and public. Wages, social security payments, and pensions are all affected by the CPI.

  4. Research series Consumer price index electricity and gas

    • cbs.nl
    xlsx
    Updated Jun 30, 2023
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    Centraal Bureau voor de Statistiek (2023). Research series Consumer price index electricity and gas [Dataset]. https://www.cbs.nl/en-gb/custom/2023/26/research-series-consumer-price-index-electricity-and-gas
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    xlsxAvailable download formats
    Dataset updated
    Jun 30, 2023
    Dataset provided by
    Statistics Netherlands
    Authors
    Centraal Bureau voor de Statistiek
    License

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

    Area covered
    The Netherlands
    Description

    The tables presented in this file are a supplement to the article “CBS switches to new method for calculating energy prices in the CPI”, published on 30 June 2023. The article presents the results of the research carried out by Statistics Netherlands (CBS) in order to develop new energy prices for the Consumer price index (CPI).

  5. Replication dataset and calculations for PIIE WP 25-3 Modernizing price...

    • piie.com
    Updated Jan 23, 2025
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    Daniel E. Sichel; Christopher Mackie (2025). Replication dataset and calculations for PIIE WP 25-3 Modernizing price measurement and evaluating recent critiques of the consumer price index by Daniel E. Sichel and Christopher Mackie (2025). [Dataset]. https://www.piie.com/publications/working-papers/2025/modernizing-price-measurement-and-evaluating-recent-critiques
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    Dataset updated
    Jan 23, 2025
    Dataset provided by
    Peterson Institute for International Economicshttp://www.piie.com/
    Authors
    Daniel E. Sichel; Christopher Mackie
    Description

    This data package includes the underlying data to replicate the charts, tables, and calculations presented in Modernizing price measurement and evaluating recent critiques of the consumer price index, PIIE Working Paper 25-3.

    If you use the data, please cite as:

    Sichel, Daniel E., and Christopher Mackie. 2025. Modernizing price measurement and evaluating recent critiques of the consumer price index. PIIE Working Paper 25-3. Washington: Peterson Institute for International Economics.

  6. u

    Data from: Personal Inflation Calculator

    • zivahub.uct.ac.za
    xlsx
    Updated Aug 9, 2018
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    Darian Sagnelli (2018). Personal Inflation Calculator [Dataset]. http://doi.org/10.25375/uct.6882941.v1
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    xlsxAvailable download formats
    Dataset updated
    Aug 9, 2018
    Dataset provided by
    University of Cape Town
    Authors
    Darian Sagnelli
    License

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

    Description

    Inflation rates experienced by different groups of consumers within a country vary. This is because the prices of goods and services and the expenditure patterns of consumers differ. The published inflation rate is used for important decisions regarding the preservation of consumer purchasing power. These include the adjustment of social grants and minimum wages by government and the benchmarking of returns by investors when making investment decisions. It is thus vital that inflation is measured accurately to ensure the purchasing power of consumers is preserved. Current measures of inflation published by Stats SA are applicable to typical consumers and are not relevant to each individual. This resource supplements a study that seeks to provide a publicly available model that can be used by consumers to calculate their personal rate of inflation.

  7. C

    Chile CPI: Housing: Hardware: Calculator

    • ceicdata.com
    Updated Jan 15, 2025
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    CEICdata.com (2025). Chile CPI: Housing: Hardware: Calculator [Dataset]. https://www.ceicdata.com/en/chile/consumer-price-index-greater-santiago-dec1998100/cpi-housing-hardware-calculator
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    Dataset updated
    Jan 15, 2025
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Jan 1, 2008 - Dec 1, 2008
    Area covered
    Chile
    Variables measured
    Consumer Prices
    Description

    Chile Consumer Price Index (CPI): Housing: Hardware: Calculator data was reported at 24,832.770 1998=100 in Dec 2008. This records an increase from the previous number of 24,608.830 1998=100 for Nov 2008. Chile Consumer Price Index (CPI): Housing: Hardware: Calculator data is updated monthly, averaging 24,642.810 1998=100 from Dec 1998 (Median) to Dec 2008, with 121 observations. The data reached an all-time high of 26,104.340 1998=100 in Mar 2003 and a record low of 23,585.500 1998=100 in Apr 2000. Chile Consumer Price Index (CPI): Housing: Hardware: Calculator data remains active status in CEIC and is reported by National Institute of Statistics. The data is categorized under Global Database’s Chile – Table CL.I014: Consumer Price Index: Greater Santiago: Dec1998=100.

  8. Adjusted price index, monthly percentage change

    • www150.statcan.gc.ca
    • open.canada.ca
    • +1more
    Updated May 9, 2022
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    Government of Canada, Statistics Canada (2022). Adjusted price index, monthly percentage change [Dataset]. http://doi.org/10.25318/1810027101-eng
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    Dataset updated
    May 9, 2022
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    1-month change in the Adjusted price index based on monthly adjusted consumer expenditure basket weights created by Statistics Canada, in partnership with the Bank of Canada. The Adjusted price index has been updated to incorporate the 2020 basket weights and is now based on a Similarity-linked Fisher price index formula. The expenditure data covers all goods and services in the Consumer Price Index.

  9. n

    Consumer Price Index (CPI)

    • db.nomics.world
    Updated Aug 29, 2025
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    DBnomics (2025). Consumer Price Index (CPI) [Dataset]. https://db.nomics.world/IMF/CPI
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    Dataset updated
    Aug 29, 2025
    Dataset provided by
    International Monetary Fund
    Authors
    DBnomics
    Description

    Consumer price indexes (CPIs) are index numbers that measure changes in the prices of goods and services purchased or otherwise acquired by households, which households use directly, or indirectly, to satisfy their own needs and wants. In practice, most CPIs are calculated as weighted averages of the percentage price changes for a specified set, or ‘‘basket’’, of consumer products, the weights reflecting their relative importance in household consumption in some period. CPIs are widely used to index pensions and social security benefits. CPIs are also used to index other payments, such as interest payments or rents, or the prices of bonds. CPIs are also commonly used as a proxy for the general rate of inflation, even though they measure only consumer inflation. They are used by some governments or central banks to set inflation targets for purposes of monetary policy. The price data collected for CPI purposes can also be used to compile other indices, such as the price indices used to deflate household consumption expenditures in national accounts, or the purchasing power parities used to compare real levels of consumption in different countries.

    In an effort to further coordinate and harmonize the collection of CPI data, the international organizations agreed that the International Monetary Fund (IMF) and the Organisation for Economic Cooperation and Development (OECD) would assume responsibility for the international collection and dissemination of national CPI data. Under this data collection initiative, countries are reporting the aggregate all items index; more detailed indexes and weights for 12 subgroups of consumption expenditure (according to the so-called COICOP-classification), and detailed metadata. These detailed data represent a valuable resource for data users throughout the world and this portal would not be possible without the ongoing cooperation of all reporting countries. In this effort, the OECD collects and validates the data for their member countries, including accession and key partner countries, whereas the IMF takes care of the collection of data for all other countries.

  10. T

    United States Consumer Price Index (CPI)

    • tradingeconomics.com
    • fa.tradingeconomics.com
    • +13more
    csv, excel, json, xml
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    TRADING ECONOMICS, United States Consumer Price Index (CPI) [Dataset]. https://tradingeconomics.com/united-states/consumer-price-index-cpi
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    xml, csv, excel, jsonAvailable download formats
    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 - Jul 31, 2025
    Area covered
    United States
    Description

    Consumer Price Index CPI in the United States increased to 323.05 points in July from 322.56 points in June 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.

  11. Consumer Price Index 2022 - West Bank and Gaza

    • pcbs.gov.ps
    Updated May 18, 2023
    + more versions
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    Palestinian Central Bureau of Statistics (2023). Consumer Price Index 2022 - West Bank and Gaza [Dataset]. https://www.pcbs.gov.ps/PCBS-Metadata-en-v5.2/index.php/catalog/717
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    Dataset updated
    May 18, 2023
    Dataset authored and provided by
    Palestinian Central Bureau of Statisticshttp://pcbs.gov.ps/
    Time period covered
    2022
    Area covered
    Gaza Strip, West Bank, Gaza
    Description

    Abstract

    The Consumer price surveys primarily provide the following: Data on CPI in Palestine covering the West Bank, Gaza Strip and Jerusalem J1 for major and sub groups of expenditure. Statistics needed for decision-makers, planners and those who are interested in the national economy. Contribution to the preparation of quarterly and annual national accounts data.

    Consumer Prices and indices are used for a wide range of purposes, the most important of which are as follows: Adjustment of wages, government subsidies and social security benefits to compensate in part or in full for the changes in living costs. To provide an index to measure the price inflation of the entire household sector, which is used to eliminate the inflation impact of the components of the final consumption expenditure of households in national accounts and to dispose of the impact of price changes from income and national groups. Price index numbers are widely used to measure inflation rates and economic recession. Price indices are used by the public as a guide for the family with regard to its budget and its constituent items. Price indices are used to monitor changes in the prices of the goods traded in the market and the consequent position of price trends, market conditions and living costs. However, the price index does not reflect other factors affecting the cost of living, e.g. the quality and quantity of purchased goods. Therefore, it is only one of many indicators used to assess living costs. It is used as a direct method to identify the purchasing power of money, where the purchasing power of money is inversely proportional to the price index.

    Geographic coverage

    Palestine West Bank Gaza Strip Jerusalem

    Analysis unit

    The target population for the CPI survey is the shops and retail markets such as grocery stores, supermarkets, clothing shops, restaurants, public service institutions, private schools and doctors.

    Universe

    The target population for the CPI survey is the shops and retail markets such as grocery stores, supermarkets, clothing shops, restaurants, public service institutions, private schools and doctors.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    A non-probability purposive sample of sources from which the prices of different goods and services are collected was updated based on the establishment census 2017, in a manner that achieves full coverage of all goods and services that fall within the Palestinian consumer system. These sources were selected based on the availability of the goods within them. It is worth mentioning that the sample of sources was selected from the main cities inside Palestine: Jenin, Tulkarm, Nablus, Qalqiliya, Ramallah, Al-Bireh, Jericho, Jerusalem, Bethlehem, Hebron, Gaza, Jabalia, Dier Al-Balah, Nusseirat, Khan Yunis and Rafah. The selection of these sources was considered to be representative of the variation that can occur in the prices collected from the various sources. The number of goods and services included in the CPI is approximately 730 commodities, whose prices were collected from 3,200 sources. (COICOP) classification is used for consumer data as recommended by the United Nations System of National Accounts (SNA-2008).

    Sampling deviation

    Not apply

    Mode of data collection

    Computer Assisted Personal Interview [capi]

    Research instrument

    A tablet-supported electronic form was designed for price surveys to be used by the field teams in collecting data from different governorates, with the exception of Jerusalem J1. The electronic form is supported with GIS, and GPS mapping technique that allow the field workers to locate the outlets exactly on the map and the administrative staff to manage the field remotely. The electronic questionnaire is divided into a number of screens, namely: First screen: shows the metadata for the data source, governorate name, governorate code, source code, source name, full source address, and phone number. Second screen: shows the source interview result, which is either completed, temporarily paused or permanently closed. It also shows the change activity as incomplete or rejected with the explanation for the reason of rejection. Third screen: shows the item code, item name, item unit, item price, product availability, and reason for unavailability. Fourth screen: checks the price data of the related source and verifies their validity through the auditing rules, which was designed specifically for the price programs. Fifth screen: saves and sends data through (VPN-Connection) and (WI-FI technology).

    In case of the Jerusalem J1 Governorate, a paper form has been designed to collect the price data so that the form in the top part contains the metadata of the data source and in the lower section contains the price data for the source collected. After that, the data are entered into the price program database.

    Cleaning operations

    The price survey forms were already encoded by the project management depending on the specific international statistical classification of each survey. After the researcher collected the price data and sent them electronically, the data was reviewed and audited by the project management. Achievement reports were reviewed on a daily and weekly basis. Also, the detailed price reports at data source levels were checked and reviewed on a daily basis by the project management. If there were any notes, the researcher was consulted in order to verify the data and call the owner in order to correct or confirm the information.

    At the end of the data collection process in all governorates, the data will be edited using the following process: Logical revision of prices by comparing the prices of goods and services with others from different sources and other governorates. Whenever a mistake is detected, it should be returned to the field for correction. Mathematical revision of the average prices for items in governorates and the general average in all governorates. Field revision of prices through selecting a sample of the prices collected from the items.

    Response rate

    Not apply

    Sampling error estimates

    The findings of the survey may be affected by sampling errors due to the use of samples in conducting the survey rather than total enumeration of the units of the target population, which increases the chances of variances between the actual values we expect to obtain from the data if we had conducted the survey using total enumeration. The computation of differences between the most important key goods showed that the variation of these goods differs due to the specialty of each survey. The variance of the key goods in the computed and disseminated CPI survey that was carried out on the Palestine level was for reasons related to sample design and variance calculation of different indicators since there was a difficulty in the dissemination of results by governorates due to lack of weights. Non-sampling errors are probable at all stages of data collection or data entry. Non-sampling errors include: Non-response errors: the selected sources demonstrated a significant cooperation with interviewers; so, there wasn't any case of non-response reported during 2019. Response errors (respondent), interviewing errors (interviewer), and data entry errors: to avoid these types of errors and reduce their effect to a minimum, project managers adopted a number of procedures, including the following: More than one visit was made to every source to explain the objectives of the survey and emphasize the confidentiality of the data. The visits to data sources contributed to empowering relations, cooperation, and the verification of data accuracy. Interviewer errors: a number of procedures were taken to ensure data accuracy throughout the process of field data compilation: Interviewers were selected based on educational qualification, competence, and assessment. Interviewers were trained theoretically and practically on the questionnaire. Meetings were held to remind interviewers of instructions. In addition, explanatory notes were supplied with the surveys. A number of procedures were taken to verify data quality and consistency and ensure data accuracy for the data collected by a questioner throughout processing and data entry (knowing that data collected through paper questionnaires did not exceed 5%): Data entry staff was selected from among specialists in computer programming and were fully trained on the entry programs. Data verification was carried out for 10% of the entered questionnaires to ensure that data entry staff had entered data correctly and in accordance with the provisions of the questionnaire. The result of the verification was consistent with the original data to a degree of 100%. The files of the entered data were received, examined, and reviewed by project managers before findings were extracted. Project managers carried out many checks on data logic and coherence, such as comparing the data of the current month with that of the previous month, and comparing the data of sources and between governorates. Data collected by tablet devices were checked for consistency and accuracy by applying rules at item level to be checked.

    Data appraisal

    Other technical procedures to improve data quality: Seasonal adjustment processes and estimations of non-available items' prices: Under each category, a number of common items are used in Palestine to calculate the price levels and to represent the commodity within the commodity group. Of course, it is

  12. g

    Monthly price indices of consumer goods and services from 1982 | gimi9.com

    • gimi9.com
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    Monthly price indices of consumer goods and services from 1982 | gimi9.com [Dataset]. https://gimi9.com/dataset/eu_https-dane-gov-pl-pl-dataset-2055-miesieczne-wskazniki-cen-towarow-i-uslug-konsumpcy
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    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    Price index of consumer goods and services is calculated on the basis of the results of: - surveys on prices of consumer goods and services on the retail market, - surveys on household budgets, providing data on average expenditures on consumer goods and services; these data are then used for compilation of a weight system. Calculating price index of consumer goods and services is done on the basis of the Classification of Individual Consumption by Purpose (COICOP) adapted for the use of Harmonized Indices of Consumer Prices (HICP). The price index of a representative in the region included in the price survey results from relating its average monthly price to an average annual price from the previous yea The all-Polish price index of a representative included in the survey is calculated as geometric mean of price indices from all regions. Calculating price indices of groups of consumer goods and services at the lowest level of weight system aggregation is done on the basis of price indices of the representatives included in price survey in a given group by using geometric mean. They are then used by applying weight system to calculate indices of higher level of aggregation up to the price index of total consumer goods and services. price index is calculated in line with the Laspeyress’s formula by applying weights from the year preceding the reference year.

  13. g

    Price index figures on the production of buildings, 2000 - 2016 | gimi9.com

    • gimi9.com
    Updated May 3, 2025
    + more versions
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    (2025). Price index figures on the production of buildings, 2000 - 2016 | gimi9.com [Dataset]. https://gimi9.com/dataset/nl_4507-price-index-figures-on-the-production-of-buildings--2000---2016/
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    Dataset updated
    May 3, 2025
    License

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

    Description

    Index figures on production prices of dwellings and other buildings reflect the relation between the output value and the output volume and can be used to convert the value of construction output from current prices to fixed prices. The output price index is derived from the series "New dwellings; output indices 2000=100". From the 2nd quarter 2009 on, the figures of the series 2005 = 100 are used and linked to the series 2000 = 100. Statistics Netherlands publishes data on the value of construction output. The volume of construction output, however, cannot be deduced from the value, which is subject to price changes. The price index on the building costs of new dwellings eliminates the effect of price changes. The price index on construction output is calculated by distributing the value of the output (current prices) over the quarters essential to the price setting of the building project. Subsequently, the quarterly output is calculated in fixed prices by using the price index on the building costs of new dwellings. The index figure of the output price is the sum of the current prices divided by the sum of the fixed prices (*100). Possibilities for selection: - Total construction - Total construction of new dwellings/buildings - New dwellings - New buildings in the private sector - New buildings in the non-commercial sector - Total other buildings - Other dwellings - Other buildings in the private sector - Other buildings in the non-commercial sector Data available from 1st quarter 2000 till 4th quarter 2016 Frequency: discontinued Status of the figures: The figures of 2016 are provisional. Since this table has been discontinued, the data will not become definitive. Changes as of January 29 2018 None, this table is discontinued. When will new figures become available? This table is succeeded by Production on buildings; price index 2015 = 100. See paragraph 3. Linking recommendation If you want to compile long-term series with linked price indices on production of buildings, you can link the figures on price level 1995 with the figures on price level 2000. For that, the percentage change from the 2nd quarter 2005 with the 1st quarter 2005 must be calculated, as the price index for the 1st quarter 2005 is the last figure published on price level 1995. This change must then be adjusted to the figures for the 1st quarter 2005 of the series 1995. The 2nd quarter index of the linked series is calculated by calculating the difference between the 1st quarter 2005 and the 2nd quarter 2005 according to the series on price level 2000 and multiplying this by the index for the 1st quarter 2005 according to the series on price level 1995. In the example: (119/120) x 148=147 (rounded). For the 3rd quarter 2005 the index is calculated analogously, where because of rounding problems the first quarter figures must be used for the link.

  14. I

    Israel IL: CPI: Local Source Base Year: Clothing and Footwear

    • ceicdata.com
    Updated Sep 8, 2021
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    CEICdata.com (2021). Israel IL: CPI: Local Source Base Year: Clothing and Footwear [Dataset]. https://www.ceicdata.com/en/israel/consumer-price-index-oecd-member-annual/il-cpi-local-source-base-year-clothing-and-footwear
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    Dataset updated
    Sep 8, 2021
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Dec 1, 2011 - Dec 1, 2022
    Area covered
    Israel
    Variables measured
    Consumer Prices
    Description

    Israel IL: Consumer Price Index (CPI): Local Source Base Year: Clothing and Footwear data was reported at 90.467 2020=100 in 2022. This records a decrease from the previous number of 95.092 2020=100 for 2021. Israel IL: Consumer Price Index (CPI): Local Source Base Year: Clothing and Footwear data is updated yearly, averaging 119.871 2020=100 from Dec 1985 (Median) to 2022, with 38 observations. The data reached an all-time high of 167.358 2020=100 in 1997 and a record low of 53.850 2020=100 in 1985. Israel IL: Consumer Price Index (CPI): Local Source Base Year: Clothing and Footwear data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Israel – Table IL.OECD.MEI: Consumer Price Index: COICOP 1999: OECD Member: Annual. The CPI measures the change in prices which consumer pay for fixed market basket of consumption goods and services. Price coverage: Prices include applicable taxes (VAT) and fees on the products at the time of sale. Cash payments are the basis for the price survey. Monthly installment payment and credit card interest are excluded. Price collection procedure: The data collection methods are adapted according to the specific characteristics of the CPI classes. The main price surveys are: Computer Assisted Telephone Interviews (CATI), conducted by the CBS staff at the central office; Computer Assisted Personal Interviews (CAPI) by field collectors with handheld personal computers (HPC) and Direct Data Entry (DDE) into the database. Also for some special items Internet is used either in parallel with CAPI or as a part of DDE collection. The CPI includes a measure of rented housing Owner Occupied Housing (OOH) is included in the CPI and is calculated using rental equivalent method. The method for imputation of OOH is based on stratified average prices of contracts that are subject to renewal. In order to reduce variance in the monthly series, two month moving averages are compared each month. However, the method for OOH still leaves room for quality differences to play role in month-to-month average price changes. The method relies on successful stratification of apartments to groups whose relative price changes are as similar as possible. While the stratification is based on apartment location and number of rooms, some quality characteristics may experience month-to-month variation. Treatment of own account production is not included Goods and services sold illegally, second hand goods, goods and services partially or totally subsidized by the government and financial transactions are not included. Insurance: Insurance of personal transport and Health insurance (private and provided by the Government) are included. Treatment of missing items: Price changes for missing observations are imputed based on the price movements of other observations of the same item. Selection of replacement items: Products that become permantely unavailable are replaced in the sample and enumerators select a replacement possessing as many of the same quality characteristics as possible. Prices from previous period are sought for the replacement item for linking purpose. Treatment of quality change: There are two types of replacement approach: comparable and non-comparable. If a new product possesses the previously defined important characteristics of the old product, the new product is defined as comparable and a minor quality change is regarded as price change. Otherwise, if a significant quality change is introduced, the new product is defined as not comparable. The breakage in price series is treated by the linking method. Explicit quality adjustments are usually not performed. Hedonic methods are being considered but not yet implemented. In some cases, where the product cycle is short and new versions with improved quality characteristics are frequently introduced, the overlap method may give biased estimates. Introduction of new products: New items are introduced when the market basket is updated. New products are introduced into the sample as they gain significant market share. Business and professional periodicles are closely followed to gain information on new products that are gaining consumer demand. Seasonal items: Missing prices for seasonal products are imputed. Certain procedures are in place to avoid too early reintroduction of seasonal products back to the index. For price changes a bridge method is used when the items are reintroduced to the collection. Index series are also calculated and released in seasonally adjusted form.; Index series starts in November 1985

  15. g

    Quarterly price indices of consumer goods and services from 1995 | gimi9.com...

    • gimi9.com
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    Quarterly price indices of consumer goods and services from 1995 | gimi9.com [Dataset]. https://gimi9.com/dataset/eu_https-dane-gov-pl-pl-dataset-2053-kwartalne-wskazniki-cen-towarow-i-uslug-konsumpcyj/
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    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    Price index of consumer goods and services is calculated on the basis of the results of: - surveys on prices of consumer goods and services on the retail market, - surveys on household budgets, providing data on average expenditures on consumer goods and services; these data are then used for compilation of a weight system. Calculating price index of consumer goods and services is done on the basis of the Classification of Individual Consumption by Purpose (COICOP) adapted for the use of Harmonized Indices of Consumer Prices (HICP). The price index of a representative in the region included in the price survey results from relating its average monthly price to an average annual price from the previous yea The all-Polish price index of a representative included in the survey is calculated as geometric mean of price indices from all regions. Calculating price indices of groups of consumer goods and services at the lowest level of weight system aggregation is done on the basis of price indices of the representatives included in price survey in a given group by using geometric mean. They are then used by applying weight system to calculate indices of higher level of aggregation up to the price index of total consumer goods and services. price index is calculated in line with the Laspeyress’s formula by applying weights from the year preceding the reference year.

  16. Consumer Price Index 2024 - West Bank and Gaza

    • pcbs.gov.ps
    Updated Feb 19, 2025
    + more versions
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    Palestinian Central Bureau of Statistics (2025). Consumer Price Index 2024 - West Bank and Gaza [Dataset]. https://www.pcbs.gov.ps/PCBS-Metadata-en-v5.2/index.php/catalog/732
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    Dataset updated
    Feb 19, 2025
    Dataset authored and provided by
    Palestinian Central Bureau of Statisticshttp://pcbs.gov.ps/
    Time period covered
    2024
    Area covered
    Palestine, Gaza Strip, West Bank, Gaza
    Description

    Abstract

    The Consumer price surveys primarily provide the following: Data on CPI in Palestine covering the West Bank, Gaza Strip and Jerusalem J1 for major and sub groups of expenditure. Statistics needed for decision-makers, planners and those who are interested in the national economy. Contribution to the preparation of quarterly and annual national accounts data.

    Consumer Prices and indices are used for a wide range of purposes, the most important of which are as follows: Adjustment of wages, government subsidies and social security benefits to compensate in part or in full for the changes in living costs. To provide an index to measure the price inflation of the entire household sector, which is used to eliminate the inflation impact of the components of the final consumption expenditure of households in national accounts and to dispose of the impact of price changes from income and national groups. Price index numbers are widely used to measure inflation rates and economic recession. Price indices are used by the public as a guide for the family with regard to its budget and its constituent items. Price indices are used to monitor changes in the prices of the goods traded in the market and the consequent position of price trends, market conditions and living costs. However, the price index does not reflect other factors affecting the cost of living, e.g. the quality and quantity of purchased goods. Therefore, it is only one of many indicators used to assess living costs. It is used as a direct method to identify the purchasing power of money, where the purchasing power of money is inversely proportional to the price index.

    Geographic coverage

    Palestine West Bank Gaza Strip Jerusalem

    Analysis unit

    The target population for the CPI survey is the shops and retail markets such as grocery stores, supermarkets, clothing shops, restaurants, public service institutions, private schools and doctors.

    Universe

    The target population for the CPI survey is the shops and retail markets such as grocery stores, supermarkets, clothing shops, restaurants, public service institutions, private schools and doctors.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    A non-probability purposive sample of sources from which the prices of different goods and services are collected was updated based on the establishment census 2017, in a manner that achieves full coverage of all goods and services that fall within the Palestinian consumer system. These sources were selected based on the availability of the goods within them. It is worth mentioning that the sample of sources was selected from the main cities inside Palestine: Jenin, Tulkarm, Nablus, Qalqiliya, Ramallah, Al-Bireh, Jericho, Jerusalem, Bethlehem, Hebron, Gaza, Jabalia, Dier Al-Balah, Nusseirat, Khan Yunis and Rafah. The selection of these sources was considered to be representative of the variation that can occur in the prices collected from the various sources. The number of goods and services included in the CPI is approximately 730 commodities, whose prices were collected from 3,200 sources. (COICOP) classification is used for consumer data as recommended by the United Nations System of National Accounts (SNA-2008).

    Sampling deviation

    Not apply

    Mode of data collection

    Computer Assisted Personal Interview [capi]

    Research instrument

    A tablet-supported electronic form was designed for price surveys to be used by the field teams in collecting data from different governorates, with the exception of Jerusalem J1. The electronic form is supported with GIS, and GPS mapping technique that allow the field workers to locate the outlets exactly on the map and the administrative staff to manage the field remotely. The electronic questionnaire is divided into a number of screens, namely: First screen: shows the metadata for the data source, governorate name, governorate code, source code, source name, full source address, and phone number. Second screen: shows the source interview result, which is either completed, temporarily paused or permanently closed. It also shows the change activity as incomplete or rejected with the explanation for the reason of rejection. Third screen: shows the item code, item name, item unit, item price, product availability, and reason for unavailability. Fourth screen: checks the price data of the related source and verifies their validity through the auditing rules, which was designed specifically for the price programs. Fifth screen: saves and sends data through (VPN-Connection) and (WI-FI technology).

    In case of the Jerusalem J1 Governorate, a paper form has been designed to collect the price data so that the form in the top part contains the metadata of the data source and in the lower section contains the price data for the source collected. After that, the data are entered into the price program database.

    Cleaning operations

    The price survey forms were already encoded by the project management depending on the specific international statistical classification of each survey. After the researcher collected the price data and sent them electronically, the data was reviewed and audited by the project management. Achievement reports were reviewed on a daily and weekly basis. Also, the detailed price reports at data source levels were checked and reviewed on a daily basis by the project management. If there were any notes, the researcher was consulted in order to verify the data and call the owner in order to correct or confirm the information.

    At the end of the data collection process in all governorates, the data will be edited using the following process: Logical revision of prices by comparing the prices of goods and services with others from different sources and other governorates. Whenever a mistake is detected, it should be returned to the field for correction. Mathematical revision of the average prices for items in governorates and the general average in all governorates. Field revision of prices through selecting a sample of the prices collected from the items.

    Response rate

    Not apply

    Sampling error estimates

    The findings of the survey may be affected by sampling errors due to the use of samples in conducting the survey rather than total enumeration of the units of the target population, which increases the chances of variances between the actual values we expect to obtain from the data if we had conducted the survey using total enumeration. The computation of differences between the most important key goods showed that the variation of these goods differs due to the specialty of each survey. The variance of the key goods in the computed and disseminated CPI survey that was carried out on the Palestine level was for reasons related to sample design and variance calculation of different indicators since there was a difficulty in the dissemination of results by governorates due to lack of weights. Non-sampling errors are probable at all stages of data collection or data entry. Non-sampling errors include: Non-response errors: the selected sources demonstrated a significant cooperation with interviewers; so, there wasn't any case of non-response reported during 2019. Response errors (respondent), interviewing errors (interviewer), and data entry errors: to avoid these types of errors and reduce their effect to a minimum, project managers adopted a number of procedures, including the following: More than one visit was made to every source to explain the objectives of the survey and emphasize the confidentiality of the data. The visits to data sources contributed to empowering relations, cooperation, and the verification of data accuracy. Interviewer errors: a number of procedures were taken to ensure data accuracy throughout the process of field data compilation: Interviewers were selected based on educational qualification, competence, and assessment. Interviewers were trained theoretically and practically on the questionnaire. Meetings were held to remind interviewers of instructions. In addition, explanatory notes were supplied with the surveys. A number of procedures were taken to verify data quality and consistency and ensure data accuracy for the data collected by a questioner throughout processing and data entry (knowing that data collected through paper questionnaires did not exceed 5%): Data entry staff was selected from among specialists in computer programming and were fully trained on the entry programs. Data verification was carried out for 10% of the entered questionnaires to ensure that data entry staff had entered data correctly and in accordance with the provisions of the questionnaire. The result of the verification was consistent with the original data to a degree of 100%. The files of the entered data were received, examined, and reviewed by project managers before findings were extracted. Project managers carried out many checks on data logic and coherence, such as comparing the data of the current month with that of the previous month, and comparing the data of sources and between governorates. Data collected by tablet devices were checked for consistency and accuracy by applying rules at item level to be checked.

    Data appraisal

    Other technical procedures to improve data quality: Seasonal adjustment processes and estimations of non-available items' prices: Under each category, a number of common items are used in Palestine to calculate the price levels and to represent the commodity within the commodity group. Of course, it is

  17. d

    Miesięczne wskaźniki cen towarów i usług konsumpcyjnych od 1982 roku

    • dane.gov.pl
    none
    Updated Dec 17, 2024
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    Główny Urząd Statystyczny (2024). Miesięczne wskaźniki cen towarów i usług konsumpcyjnych od 1982 roku [Dataset]. https://dane.gov.pl/en/dataset/2055
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    noneAvailable download formats
    Dataset updated
    Dec 17, 2024
    Dataset authored and provided by
    Główny Urząd Statystyczny
    License

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

    Description

    Price index of consumer goods and services is calculated on the basis of the results of:
    - surveys on prices of consumer goods and services on the retail market,
    - surveys on household budgets, providing data on average expenditures on consumer goods and services; these data are then used for compilation of a weight system.

    Calculating price index of consumer goods and services is done on the basis of the Classification of Individual Consumption by Purpose (COICOP) adapted for the use of Harmonized Indices of Consumer Prices (HICP).

    The price index of a representative in the region included in the price survey results from relating its average monthly price to an average annual price from the previous yea The all-Polish price index of a representative included in the survey is calculated as geometric mean of price indices from all regions. Calculating price indices of groups of consumer goods and services at the lowest level of weight system aggregation is done on the basis of price indices of the representatives included in price survey in a given group by using geometric mean. They are then used by applying weight system to calculate indices of higher level of aggregation up to the price index of total consumer goods and services. price index is calculated in line with the Laspeyress’s formula by applying weights from the year preceding the reference year.

  18. e

    Quarterly price indices of consumer goods and services from 1995

    • data.europa.eu
    html
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    Główny Urząd Statystyczny, Quarterly price indices of consumer goods and services from 1995 [Dataset]. https://data.europa.eu/data/datasets/https-dane-gov-pl-pl-dataset-2053-kwartalne-wskazniki-cen-towarow-i-uslug-konsumpcyj?locale=no
    Explore at:
    html(0)Available download formats
    Dataset authored and provided by
    Główny Urząd Statystyczny
    Description

    Price index of consumer goods and services is calculated on the basis of the results of:
    - surveys on prices of consumer goods and services on the retail market,
    - surveys on household budgets, providing data on average expenditures on consumer goods and services; these data are then used for compilation of a weight system.

    Calculating price index of consumer goods and services is done on the basis of the Classification of Individual Consumption by Purpose (COICOP) adapted for the use of Harmonized Indices of Consumer Prices (HICP).

    The price index of a representative in the region included in the price survey results from relating its average monthly price to an average annual price from the previous yea The all-Polish price index of a representative included in the survey is calculated as geometric mean of price indices from all regions. Calculating price indices of groups of consumer goods and services at the lowest level of weight system aggregation is done on the basis of price indices of the representatives included in price survey in a given group by using geometric mean. They are then used by applying weight system to calculate indices of higher level of aggregation up to the price index of total consumer goods and services. price index is calculated in line with the Laspeyress’s formula by applying weights from the year preceding the reference year.

  19. S

    Sweden Consumer Price Index: Shadow

    • ceicdata.com
    Updated May 25, 2018
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    CEICdata.com (2018). Sweden Consumer Price Index: Shadow [Dataset]. https://www.ceicdata.com/en/sweden/consumer-price-index-fixed-and-shadow-1980100
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    Dataset updated
    May 25, 2018
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Mar 1, 2024 - Feb 1, 2025
    Area covered
    Sweden
    Variables measured
    Consumer Prices
    Description

    Consumer Price Index: Shadow data was reported at 416.200 1980=100 in Mar 2025. This records a decrease from the previous number of 419.080 1980=100 for Feb 2025. Consumer Price Index: Shadow data is updated monthly, averaging 273.640 1980=100 from Jan 1980 (Median) to Mar 2025, with 543 observations. The data reached an all-time high of 419.080 1980=100 in Feb 2025 and a record low of 95.300 1980=100 in Jan 1980. Consumer Price Index: Shadow data remains active status in CEIC and is reported by Statistics Sweden. The data is categorized under Global Database’s Sweden – Table SE.I005: Consumer Price Index: Fixed and Shadow: 1980=100. Shadow Index is being used to calculate CPI. The shadow index numbers are adjusted to take into account certain inadequacies in the basic data on prices or in the methods used for calculating fixed index numbers. [COVID-19-IMPACT]

  20. T

    Taiwan Consumer Price Index CPI Growth

    • ceicdata.com
    Updated Jan 15, 2021
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    CEICdata.com (2021). Taiwan Consumer Price Index CPI Growth [Dataset]. https://www.ceicdata.com/en/indicator/taiwan/consumer-price-index-cpi-growth
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    Dataset updated
    Jan 15, 2021
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Mar 1, 2024 - Feb 1, 2025
    Area covered
    Taiwan
    Description

    Key information about Taiwan Consumer Price Index CPI growth

    • Taiwan Consumer Price Index (CPI) growth was measured at 2.2 % YoY in Feb 2025, compared with a rate of 2.0 % in the previous month.
    • Taiwan Consumer Price Index growth data is updated monthly, available from Jan 1960 to Feb 2025, with an averaged number of 2.0 % YoY.
    • The data reached an all-time high of 61.1 % YoY in Mar 1974 and a record low of -3.1 % YoY in Oct 1970.

    CEIC calculates Consumer Price Index Growth from monthly Consumer Price Index. The Directorate-General of Budget, Accounting and Statistics, Executive Yuan provides Consumer Price Index with base 2021=100. Consumer Price Index Growth prior to January 1982 is calculated from Consumer Price Index with base 2016=100.

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Bureau of Labor Statistics (2022). Consumer Price Index (CPI) [Dataset]. https://catalog.data.gov/dataset/consumer-price-index-cpi-ee18b
Organization logo

Consumer Price Index (CPI)

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Dataset updated
May 16, 2022
Dataset provided by
Bureau of Labor Statisticshttp://www.bls.gov/
Description

The Consumer Price Index (CPI) is a measure of the average change over time in the prices paid by urban consumers for a market basket of consumer goods and services. Indexes are available for the U.S. and various geographic areas. Average price data for select utility, automotive fuel, and food items are also available. Prices for the goods and services used to calculate the CPI are collected in 75 urban areas throughout the country and from about 23,000 retail and service establishments. Data on rents are collected from about 43,000 landlords or tenants. More information and details about the data provided can be found at http://www.bls.gov/cpi

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