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

    • catalog.data.gov
    • cloud.csiss.gmu.edu
    • +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. G

    Adjusted price index, monthly percentage change

    • ouvert.canada.ca
    • www150.statcan.gc.ca
    • +1more
    csv, html, xml
    Updated May 26, 2025
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    Statistics Canada (2025). Adjusted price index, monthly percentage change [Dataset]. https://ouvert.canada.ca/data/dataset/df557744-2cc8-4eda-bc19-a67b7e75e15f
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    html, csv, xmlAvailable download formats
    Dataset updated
    May 26, 2025
    Dataset provided by
    Statistics Canada
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    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.

  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. 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
    CEIC Data
    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.

  5. 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.

  6. e

    Kwartalne wskaźniki cen towarów i usług konsumpcyjnych od 1995 roku

    • data.europa.eu
    html
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    Główny Urząd Statystyczny, Kwartalne wskaźniki cen towarów i usług konsumpcyjnych od 1995 roku [Dataset]. https://data.europa.eu/data/datasets/https-dane-gov-pl-pl-dataset-2053-kwartalne-wskazniki-cen-towarow-i-uslug-konsumpcyj?locale=it
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    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.

  7. Consumer Price Index 2021 - 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 2021 - West Bank and Gaza [Dataset]. https://www.pcbs.gov.ps/PCBS-Metadata-en-v5.2/index.php/catalog/711
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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
    2021
    Area covered
    West Bank, Gaza Strip, Palestine, 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. For example, for the CPI, the variation between its goods was very low, except in some cases such as banana, tomato, and cucumber goods that had a high coefficient of variation during 2019 due to the high oscillation in their prices. 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

  8. El Salvador SV: Wholesale Price Index

    • ceicdata.com
    Updated Mar 18, 2018
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    CEICdata.com (2018). El Salvador SV: Wholesale Price Index [Dataset]. https://www.ceicdata.com/en/el-salvador/inflation/sv-wholesale-price-index
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    Dataset updated
    Mar 18, 2018
    Dataset provided by
    CEIC Data
    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, 2005 - Dec 1, 2016
    Area covered
    El Salvador
    Variables measured
    Consumer Prices
    Description

    El Salvador SV: Wholesale Price Index data was reported at 108.446 2010=100 in 2016. This records a decrease from the previous number of 111.345 2010=100 for 2015. El Salvador SV: Wholesale Price Index data is updated yearly, averaging 42.663 2010=100 from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 114.438 2010=100 in 2011 and a record low of 5.573 2010=100 in 1962. El Salvador SV: Wholesale Price Index data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s El Salvador – Table SV.World Bank.WDI: Inflation. Wholesale price index refers to a mix of agricultural and industrial goods at various stages of production and distribution, including import duties. The Laspeyres formula is generally used.; ; International Monetary Fund, International Financial Statistics and data files.; ;

  9. e

    Consumer price index

    • data.europa.eu
    excel xls, excel xlsx +1
    Updated Feb 9, 2018
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    North Gate II & III - INS (STATBEL - Statistics Belgium) (2018). Consumer price index [Dataset]. https://data.europa.eu/data/datasets/78b06e72e3614d1019d54adf9ff84d7f4b23c35f?locale=en
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    excel xlsx, excel xls, pdfAvailable download formats
    Dataset updated
    Feb 9, 2018
    Dataset authored and provided by
    North Gate II & III - INS (STATBEL - Statistics Belgium)
    Description

    Purpose and brief description The consumer price index is an economic indicator whose main task is to objectively reflect the price evolution over time for a basket of goods and services purchased by households and considered representative of their consumer habits. The index does not necessarily measure the price level of this basket for a specific period of time, but rather the fluctuation between two periods, the first one acting as basis for comparison. Moreover, this difference in the price level is not measured in absolute, but in relative terms. The consumer price index can be determined as a hundred times the ratio between the observed prices of a range of goods and services at a given time and the prices of the same goods and services, observed under the same circumstances during the reference period, chosen as basis for comparison. Price observations always take place in the same regions. Since 2014, the consumer price index has been a chain index in which the weighting reference period is regularly shifted and prices and quantities are no longer compared between the current period and a fixed reference period, but the current period is compared with an intermediate period. By multiplying these short-term indices, and so creating a chain, we get a long-term series with a fixed reference period. Population Belgian private households Data collection method and possible sampling Survey technique applied using a computer, based on the use of electronic questionnaires and laptops. Frequency Monthly. Timing of publication The results are available on the penultimate working day of the reference period. Definitions Weight (CPI): The weight represents the importance of the goods and services included in the CPI in the total expenditure patterns of the households. Weights are determined based on the household budget survey. Consumer price index (CPI): The consumer price index is an economic indicator whose main task is to objectively reflect the price evolution over time for a basket of goods and services purchased by households and considered representative of their consumer habits. Health index: The health index is derived from the consumer price index and has been published since January 1994. The current value of this index is determined by removing a number of products from the consumer price index product basket, in particular alcoholic beverages (bought in a shop or consumed in a bar), tobacco products and motor fuels except for LPG. Inflation: Inflation is defined as the ratio between the value of the consumer price index of a given month and the index of the same month the year before. Therefore, inflation measures the rhythm of the evolution of the overall price level. Consumer price index without petroleum products: This index is calculated by removing the following products from the consumer price index: butane, propane, liquid fuels and motor fuels. Consumer price index without energy products: This index is calculated by removing the following products from the consumer price index: electricity, natural gas, butane, propane, liquid fuels, solid fuels and motor fuels. Smoothed index: The smoothed health index, also called smoothed index (the average value of the health indexes of the last 4 months) is used as a basis for the indexation of retirement pensions, social security benefits and some salaries and wages. Public wages and social benefits are indexed as soon as the smoothed index reaches a given value, called the central index. The smoothed index is also called moving average. In order to perform a 2% index jump (laid down in the Law of 23 April 2015 on employment promotion), the smoothed health index has been temporarily blocked at its value of March 2015 (100.66). The smoothed health index was then reduced by 2% from April 2015. When the reduced smoothed health index (also called the reference index) had increased again by 2% or in other words when it had exceeded the value of 100.66, the index was no longer blocked. It occurred in April 2016. Since April 2016 the smoothed health index is calculated in the same manner as the reference index and therefore corresponds to the arithmetical mean of the health indexes of the last 4 months multiplied by a factor of 0.98. The central index is a predetermined threshold value against which the smoothed health index is compared. If the central index is reached or exceeded, there is an indexation of the wages and salaries or benefits. This indexation is proportional to the percentage between the old and the new central index. For the public sector and social benefits, the difference between the central indices always amounts to 2 %. Therefore, a 2 % indexation is applied every time the central index is reached. There are also collective labour agreements according to which the difference between the central indices amounts to 1 % or 1.5 %. The reaching of a central index then leads to an indexation of 1 % or 1,5 %. See also: https://bosa.belgium.

  10. T

    United States - Producer Price Index by Commodity: Processed Foods and...

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Apr 22, 2020
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    TRADING ECONOMICS (2020). United States - Producer Price Index by Commodity: Processed Foods and Feeds: Formula Feeds [Dataset]. https://tradingeconomics.com/united-states/producer-price-index-by-commodity-for-processed-foods-and-feeds-formula-feeds-fed-data.html
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    json, csv, excel, xmlAvailable download formats
    Dataset updated
    Apr 22, 2020
    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 1, 1976 - Dec 31, 2025
    Area covered
    United States
    Description

    United States - Producer Price Index by Commodity: Processed Foods and Feeds: Formula Feeds was 258.48200 Index 1982=100 in March of 2025, according to the United States Federal Reserve. Historically, United States - Producer Price Index by Commodity: Processed Foods and Feeds: Formula Feeds reached a record high of 301.55000 in September of 2022 and a record low of 44.20000 in February of 1962. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Producer Price Index by Commodity: Processed Foods and Feeds: Formula Feeds - last updated from the United States Federal Reserve on July of 2025.

  11. F

    Producer Price Index by Commodity: Processed Foods and Feeds: Formula Feeds

    • fred.stlouisfed.org
    json
    Updated Jun 12, 2025
    + more versions
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    (2025). Producer Price Index by Commodity: Processed Foods and Feeds: Formula Feeds [Dataset]. https://fred.stlouisfed.org/series/WPU0293
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    jsonAvailable download formats
    Dataset updated
    Jun 12, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    Graph and download economic data for Producer Price Index by Commodity: Processed Foods and Feeds: Formula Feeds (WPU0293) from Jan 1962 to May 2025 about processed, food, commodities, PPI, inflation, price index, indexes, price, and USA.

  12. T

    United States Consumer Price Index (CPI)

    • tradingeconomics.com
    • fa.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jun 11, 2025
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    TRADING ECONOMICS (2025). 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 updated
    Jun 11, 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 - May 31, 2025
    Area covered
    United States
    Description

    Consumer Price Index CPI in the United States increased to 321.47 points in May from 320.80 points in April 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.

  13. Hong Kong SAR, China Consumer Price Index (B): YoY

    • ceicdata.com
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    CEICdata.com, Hong Kong SAR, China Consumer Price Index (B): YoY [Dataset]. https://www.ceicdata.com/en/hong-kong/consumer-price-index-b-1009910100/consumer-price-index-b-yoy
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    Dataset provided by
    CEIC Data
    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, 2016 - Dec 1, 2016
    Area covered
    Hong Kong
    Variables measured
    Consumer Prices
    Description

    Hong Kong Consumer Price Index (B): YoY data was reported at 1.400 % in Dec 2016. This stayed constant from the previous number of 1.400 % for Nov 2016. Hong Kong Consumer Price Index (B): YoY data is updated monthly, averaging 4.600 % from Jul 1975 (Median) to Dec 2016, with 498 observations. The data reached an all-time high of 19.300 % in Feb 1980 and a record low of -6.900 % in Sep 1999. Hong Kong Consumer Price Index (B): YoY data remains active status in CEIC and is reported by Census and Statistics Department. The data is categorized under Global Database’s Hong Kong SAR – Table HK.I032: Consumer Price Index (B): 10/09-9/10=100. According to the source, Composite Consumer Price Index (B) of more than 1 decimal place are used in the calculation to derive the year-on-year rates of change. Furthermore, the year-on-year rates of change before October 2010 were derived using the index series in the base periods at that time (for instance the 2004/05-based index series), compared with the index a year earlier in the same base period. Rebased from Oct2009-Sep2010=100 to Oct2014-Sep2015=100 Replacement series ID: 376217877

  14. 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.

  15. Housing Price Index Weights

    • data.europa.eu
    csv, json
    Updated Feb 3, 2025
    + more versions
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    Valstybės duomenų agentūra (2025). Housing Price Index Weights [Dataset]. https://data.europa.eu/88u/dataset/https-data-gov-lt-datasets-2521-
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    csv, jsonAvailable download formats
    Dataset updated
    Feb 3, 2025
    Dataset provided by
    State Data Agency of Lithuaniahttps://vda.lrv.lt/
    Authors
    Valstybės duomenų agentūra
    License

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

    Description

    The package includes the weights of the house price index. “Weight” means the percentage or promil of the relative share of household monetary expenditure for the purchase of land-based housing belonging to the basic population of the CCI. The higher the weight, the greater the impact of a change in the price level of a land-based housing classification on the price development of a higher level of land-based housing classification. “Weight reference period” means the period during which the weight of the index is calculated. The following procedures for checking and editing the statistics received are carried out: rejecting transactions in which the purchased dwellings are unfit for life due to a lack of completion (< 80%), analysing the purchase-sale transaction data of the dwellings attributed to each basic whole compared to the previous quarters. The editing and validation of data shall be carried out using a computer program for checking price statistics. The resulting price trends are compared to the trends in house prices recorded by real estate agencies. Information on factors influencing changes in house prices is regularly monitored in the press, surveys and reports published by other companies and institutions. The main source of statistical data for the calculation of the CCI is the data of the Real Property Register of the Centre of Registers of the SE and the databases of transactions. Source data is obtained quarterly. The BKI base period is 2015 (2015: 100). Another change to the CCI base period is foreseen for 2026, the former time line will be converted into a new index base period and published after calculation in QI 2026. CCI

  16. U

    United States PPI: Weights: PO: AF: Formula Feeds

    • ceicdata.com
    Updated Feb 15, 2025
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    CEICdata.com (2025). United States PPI: Weights: PO: AF: Formula Feeds [Dataset]. https://www.ceicdata.com/en/united-states/producer-price-index-by-commodities-weights/ppi-weights-po-af-formula-feeds
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    Dataset updated
    Feb 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
    Dec 1, 2013 - Dec 1, 2024
    Area covered
    United States
    Description

    United States PPI: Weights: PO: Formula Feeds data was reported at 0.413 % in 2024. This records a decrease from the previous number of 0.432 % for 2023. United States PPI: Weights: PO: Formula Feeds data is updated yearly, averaging 0.381 % from Dec 2007 (Median) to 2024, with 18 observations. The data reached an all-time high of 0.469 % in 2022 and a record low of 0.266 % in 2007. United States PPI: Weights: PO: Formula Feeds data remains active status in CEIC and is reported by U.S. Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.I068: Producer Price Index: by Commodities: Weights.

  17. Consumer Price Index 2019 - West Bank and Gaza

    • pcbs.gov.ps
    Updated Dec 26, 2021
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    Palestinian Central Bureau of Statistics (2021). Consumer Price Index 2019 - West Bank and Gaza [Dataset]. https://www.pcbs.gov.ps/PCBS-Metadata-en-v5.2/index.php/catalog/704
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    Dataset updated
    Dec 26, 2021
    Dataset authored and provided by
    Palestinian Central Bureau of Statisticshttp://pcbs.gov.ps/
    Time period covered
    2019
    Area covered
    West Bank, Gaza Strip, Palestine, 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. For example, for the CPI, the variation between its goods was very low, except in some cases such as banana, tomato, and cucumber goods that had a high coefficient of variation during 2019 due to the high oscillation in their prices. 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

  18. 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.

  19. U

    United States PCE: PI: Less Formula Effect: Elec, Gas, Fuel Oil & Oth HH...

    • ceicdata.com
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    CEICdata.com, United States PCE: PI: Less Formula Effect: Elec, Gas, Fuel Oil & Oth HH Fuels [Dataset]. https://www.ceicdata.com/en/united-states/nipa-2009-personal-consumption-expenditure-price-index-and-cpi-reconciliation-monthly
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    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
    Jun 1, 2012 - May 1, 2013
    Area covered
    United States
    Variables measured
    Gross Domestic Product
    Description

    PCE: PI: Less Formula Effect: Elec, Gas, Fuel Oil & Oth HH Fuels data was reported at 0.000 Point in May 2013. This records a decrease from the previous number of 0.010 Point for Apr 2013. PCE: PI: Less Formula Effect: Elec, Gas, Fuel Oil & Oth HH Fuels data is updated monthly, averaging 0.000 Point from Jan 2002 (Median) to May 2013, with 137 observations. The data reached an all-time high of 0.010 Point in Apr 2013 and a record low of -0.030 Point in Sep 2005. PCE: PI: Less Formula Effect: Elec, Gas, Fuel Oil & Oth HH Fuels data remains active status in CEIC and is reported by Bureau of Economic Analysis. The data is categorized under Global Database’s United States – Table US.A273: NIPA 2009: PCE Price Index and CPI Reconciliation.

  20. t

    Formula Effect: All items RPI, Index (CDID: CRFT) Month | Consumer price...

    • timeseriesexplorer.com
    Updated May 22, 2024
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    Time Series Explorer (2024). Formula Effect: All items RPI, Index (CDID: CRFT) Month | Consumer price inflation time series [Dataset]. https://www.timeseriesexplorer.com/01b6e047c438ee6884a03036ef736dce/3c1757e5454f844e878803b14076c832/
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    Dataset updated
    May 22, 2024
    Dataset provided by
    Office for National Statistics
    Time Series Explorer
    Description

    (CDID: CRFT) Month - Consumer price inflation time series Time series data for public sector finances and important fiscal aggregates, based on the new European System of Accounts 2010: ESA10 framework.

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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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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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