100+ datasets found
  1. T

    CONSUMER PRICE INDEX WITH FIXED INTEREST RATE by Country Dataset

    • tradingeconomics.com
    csv, excel, json, xml
    Updated May 20, 2024
    + more versions
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    TRADING ECONOMICS (2024). CONSUMER PRICE INDEX WITH FIXED INTEREST RATE by Country Dataset [Dataset]. https://tradingeconomics.com/country-list/consumer-price-index-with-fixed-interest-rate
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    json, excel, csv, xmlAvailable download formats
    Dataset updated
    May 20, 2024
    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
    2025
    Area covered
    World
    Description

    This dataset provides values for CONSUMER PRICE INDEX WITH FIXED INTEREST RATE reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

  2. Consumer prices; price index 1900 = 100

    • data.overheid.nl
    • cbs.nl
    • +1more
    atom, json
    Updated Feb 13, 2025
    + more versions
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    Centraal Bureau voor de Statistiek (Rijk) (2025). Consumer prices; price index 1900 = 100 [Dataset]. https://data.overheid.nl/en/dataset/6e398518-b888-4610-ac7d-be94a3e93200
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    json(KB), atom(KB)Available download formats
    Dataset updated
    Feb 13, 2025
    Dataset provided by
    Statistics Netherlands
    License

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

    Description

    This table presents the Consumer price index (CPI) with reference year 1900 = 100. This index series is an estimation and has been constructed by multiplying the year-on-year mutations of several index series from different reference periods with the overlapping index from the previous reference period. The index shows the price change of the goods and services purchased by an average Dutch household in one year. Annual rate of change is measured as the year on-year change of the CPI, expressed as a percentage. The annual rate of change in this series may differ from the officially published annual rate of change as a result of rounding differences.

    Data available from: 1900

    Status of the figures: The yearly figures are provisional when first published. Definitive figures are provided in the second version. Disparities between provisional and definitive figures must be attributed to new or updated source material that has become available.

    Changes compared with previous version: Data on the most recent period have been added and/or adjustments have been implemented.

    When will new figures be published? New figures are available at the beginning of the year.

  3. 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
    West Bank, Palestine
    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

  4. Consumer Price Data and Measures Explained

    • clevelandfed.org
    csv
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    Federal Reserve Bank of Cleveland, Consumer Price Data and Measures Explained [Dataset]. https://www.clevelandfed.org/center-for-inflation-research/consumer-price-data
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    csvAvailable download formats
    Dataset authored and provided by
    Federal Reserve Bank of Clevelandhttps://www.clevelandfed.org/
    Description

    Learn the differences between the consumer price index (CPI) and the personal consumption expenditures (PCE) price index. Find out what measures are used to gauge underlying inflation, or the long-term trend in prices, such as median and trimmed-mean inflation rates and core inflation.

  5. Consumer Price Index

    • kaggle.com
    Updated Jun 27, 2017
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    US Bureau of Labor Statistics (2017). Consumer Price Index [Dataset]. https://www.kaggle.com/datasets/bls/consumer-price-index/discussion
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jun 27, 2017
    Dataset provided by
    Kaggle
    Authors
    US Bureau of Labor Statistics
    License

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

    Description

    Context:

    The Bureau of Labor Statistics defines the Consumer Price Index (CPI) as “a statistical measure of change, over time, of the prices of goods and services in major expenditure groups--such as food, housing, apparel, transportation, and medical care--typically purchased by urban consumers. Essentially, it compares the cost of a sample of goods and services in a specific month relative to the cost of the same "market basket" in an earlier reference period.

    Make sure to read the cu.txt for more descriptive summaries on each data file and how to use the unique identifiers.

    Content:

    This dataset was collected June 27th, 2017 and may not be up-to-date.

    The revised CPI introduced by the BLS in 1998 includes indexes for two populations; urban wage earners and clerical workers (CW), and all urban consumers (CU). This dataset covers all urban consumers (CU).

    The Consumer Price Index (CPI) is a statistical measure of change, over time, of the prices of goods and services in major expenditure groups--such as food, housing, apparel, transportation, and medical care--typically purchased by urban consumers. Essentially, it compares the cost of a sample "market basket" of goods and services in a specific month relative to the cost of the same "market basket" in an earlier reference period. This reference period is designated as the base period.

    As a result of the 1998 revision, both the CW and the CU utilize updated expenditure weights based upon data tabulated from three years (1982, 1983, and 1984) of the Consumer Expenditure Survey and incorporate a number of technical improvements, including an updated and revised item structure.

    To construct the two indexes, prices for about 100,000 items and data on about 8,300 housing units are collected in a sample of 91 urban places. Comparison of indexes for individual CMSA's or cities show only the relative change over time in prices between locations. These indexes cannot be used to measure interarea differences in price levels or living costs.

    Summary Data Available: U.S. average indexes for both populations are available for about 305 consumer items and groups of items. In addition, over 100 of the indexes have been adjusted for seasonality. The indexes are monthly with some beginning in 1913. Semi-annual indexes have been calculated for about 100 items for comparison with semi-annual areas mentioned below. Semi-annual indexes are available from 1984 forward.

    Area indexes for both populations are available for 26 urban places. For each area, indexes are published for about 42 items and groups. The indexes are published monthly for three areas, bimonthly for eleven areas, and semi-annually for 12 urban areas.

    Regional indexes for both populations are available for four regions with about 55 items and groups per region. Beginning with January 1987, indexes are monthly, with some beginning as early as 1966. Semi-annual indexes have been calculated for about 42 items for comparison with semi-annual areas mentioned above. Semi-annual indexes have been calculated for about 42 items in the 27 urban places for comparison with semi-annual areas.

    City-size indexes for both populations are available for three size classes with about 55 items and groups per class. Beginning with January 1987, indexes are monthly and most begin in 1977. Semi-annual indexes have been calculated for about 42 items for comparison with semi-annual areas mentioned below.

    Region/city-size indexes for both populations are available cross classified by region and city-size class. For each of 13 cross calculations, about 42 items and groups are available. Beginning with January 1987, indexes are monthly and most begin in 1977. Semi-annual indexes have been calculated for about 42 items in the 26 urban places for comparison with semi-annual areas.

    Frequency of Observations: U.S. city average indexes, some area indexes, and regional indexes, city-size indexes, and region/city-size indexes for both populations are monthly. Other area indexes for both populations are bimonthly or semi-annual.

    Annual Averages: Annual averages are available for all unadjusted series in the CW and CU.

    Base Periods: Most indexes have a base period of 1982-1984 = 100. Other indexes, mainly those which have been added to the CPI program with the 1998 revision, are based more recently. The base period value is 100.0, except for the "Purchasing Power" values (AAOR and SAOR) where the base period value is 1.000.

    Data Characteristics: Indexes are stored to one decimal place, except for the "Purchasing Power" values which are stored to three decimal places.

    References: BLS Handbook of Methods, Chapter 17, "Consumer Price Index", BLS Bulletin 2285, April 1988.

    Acknowledgements:

    This dataset was taken directly from the U.S. Bureau of Labor Statistics web...

  6. d

    Inter-city indexes of price differentials of consumer goods and services,...

    • datasets.ai
    • www150.statcan.gc.ca
    • +2more
    21, 55, 8
    Updated Sep 1, 2024
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    Statistics Canada | Statistique Canada (2024). Inter-city indexes of price differentials of consumer goods and services, annual [Dataset]. https://datasets.ai/datasets/ee949112-5d13-420a-98a9-ec5822e026b3
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    8, 21, 55Available download formats
    Dataset updated
    Sep 1, 2024
    Dataset authored and provided by
    Statistics Canada | Statistique Canada
    Description

    Annual indexes of price differences between 15 cities in all provinces and territories, as of October of the previous year, for a selection of products (goods and services) from the Consumer Price Index (CPI) purchased by consumers in each of the 15 cities. The combined city average index is 100.

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

    • statista.com
    • tokrwards.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.

  8. Consumer Price Index (CPI)

    • catalog.data.gov
    • s.cnmilf.com
    • +1more
    Updated May 16, 2022
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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

  9. Consumer Price Index 2023 - West Bank and Gaza

    • pcbs.gov.ps
    Updated Mar 10, 2024
    + more versions
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    Palestinian Central Bureau of Statistics (2024). Consumer Price Index 2023 - West Bank and Gaza [Dataset]. https://www.pcbs.gov.ps/PCBS-Metadata-en-v5.2/index.php/catalog/729
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    Dataset updated
    Mar 10, 2024
    Dataset authored and provided by
    Palestinian Central Bureau of Statisticshttp://pcbs.gov.ps/
    Time period covered
    2023
    Area covered
    Palestine, West Bank
    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

  10. 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
    Palestine, West Bank
    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

  11. n

    Consumer Price Index (CPI)

    • db.nomics.world
    Updated Aug 30, 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 30, 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.

  12. The reconciliation of the differences between the Consumer Price Index and...

    • ckan.publishing.service.gov.uk
    Updated Mar 20, 2012
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    ckan.publishing.service.gov.uk (2012). The reconciliation of the differences between the Consumer Price Index and the Implied Price Deflator - Dataset - data.gov.uk [Dataset]. https://ckan.publishing.service.gov.uk/dataset/the_reconciliation_of_the_differences_between_the_consumer_price_index_and_the_implied_price_deflato
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    Dataset updated
    Mar 20, 2012
    Dataset provided by
    CKANhttps://ckan.org/
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Description

    The Consumer Prices Index (CPI) is the preferred measure of inflation used in the application of monetary policy by the Bank of England. Within the System of National Accounts, and subsequently the ESA, the preferred measure of inflation is the Implied Price Deflator (IPD). Historically, the indices have behaved broadly similar, however since around 2007 Q4 the divergence in the indices has increased and become more volatile. The plan for this article is to cover the conceptual and scope differences between the CPI and Household Final Consumption Expenditure Implied Price Deflator. There will be an empirical analysis on how and why the two indices differ over time. Source agency: Office for National Statistics Designation: National Statistics Language: English Alternative title: The differences between the CPI and the Implied Price Deflator

  13. Import prices - manufacturing

    • data.europa.eu
    csv, html, tsv, xml
    Updated May 2, 2016
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    Eurostat (2016). Import prices - manufacturing [Dataset]. https://data.europa.eu/data/datasets/1zos8rnbabsub1dzgjvxmw?locale=en
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    csv(3982), tsv(1615), xml(9600), xml(3454), htmlAvailable download formats
    Dataset updated
    May 2, 2016
    Dataset authored and provided by
    Eurostathttps://ec.europa.eu/eurostat
    License

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

    Description

    The industrial import price index (IPI) measures the monthly transaction price development of imported goods purchased from non-domestic areas by domestic residents. IPI permits monthly monitoring of prices for different categories of products or group of products. They are also a means to distinguish real growth of imports from price changes in the foreign trade statistics and in the national accounts. Data are compiled according to the Classification of Products by Activity (CPA). The breakdowns are based on aggregates derived from the MIGs (Main Industrial Groupings). Industrial import prices are compiled as a fixed base year Laspeyres type price-index (except for Luxembourg). The current base year is 2021 (Index 2021 =100). Indexes, as well as both growth rates with respect to the previous month (M/M-1) and with respect to the corresponding month of the previous year (M/M-12) are compiled from raw data.

  14. w

    Price index figures on the production of buildings, 2000 - 2016

    • data.wu.ac.at
    • cbs.nl
    • +1more
    atom feed, json
    Updated Jul 11, 2018
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    Centraal Bureau voor de Statistiek (2018). Price index figures on the production of buildings, 2000 - 2016 [Dataset]. https://data.wu.ac.at/schema/data_overheid_nl/ZjkwZGE5ZTctNDk3MC00NjE3LTlmMzYtMzQ1NDQ1MzM0YzEx
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    json, atom feedAvailable download formats
    Dataset updated
    Jul 11, 2018
    Dataset provided by
    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
    4b165ac763d4953abca7d82e01c8577ff7741933
    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.

  15. g

    Development Economics Data Group - Inflation, end of period consumer prices,...

    • gimi9.com
    Updated Oct 1, 2002
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    (2002). Development Economics Data Group - Inflation, end of period consumer prices, Index | gimi9.com [Dataset]. https://gimi9.com/dataset/worldbank_imf_weo_pcpie/
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    Dataset updated
    Oct 1, 2002
    License

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

    Description

    Expressed in end of the period, not annual average data. A consumer price index (CPI) measures changes in the prices of goods and services that households consume. Such changes affect the real purchasing power of consumers' incomes and their welfare. As the prices of different goods and services do not all change at the same rate, a price index can only reflect their average movement. A price index is typically assigned a value of unity, or 100, in some reference period and the values of the index for other periods of time are intended to indicate the average proportionate, or percentage, change in prices from this price reference period. Price indices can also be used to measure differences in price levels between different cities, regions or countries at the same point in time. [CPI Manual 2004, Introduction] For euro countries, consumer prices are calculated based on harmonized prices.

  16. H

    Replication data for: A Cost-of-Living Dynamic Price Index, with an...

    • dataverse.harvard.edu
    Updated Dec 17, 2008
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    Ricardo Reis (2008). Replication data for: A Cost-of-Living Dynamic Price Index, with an Application to Indexing Retirement Accounts [Dataset]. http://doi.org/10.7910/DVN/L1C8R3
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Dec 17, 2008
    Dataset provided by
    Harvard Dataverse
    Authors
    Ricardo Reis
    License

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

    Time period covered
    1970 - 2004
    Description

    If a consumer wishes to protect her retirement account from the risk of price changes in order to sustain a stable standard of living, then what price index should the account be indexed to? This paper constructs a dynamic price index (DPI) that answers this question. Unlike the existing theory on price indices (which is static and certain), the DPI measures the cost of living for a consumer who lives for many periods and faces uncertainty. The first contribution of this research is to define this price index and study its theoretical properties. Like static price indices, the DPI is: independent of wealth, homogeneous of degree 1 in all prices, and higher if prices rise at a faster rate. Unlike static price indices, the DPI: is forward-looking, is affected by intertemporal substitution, responds by more to persistent shocks, includes assets prices, and distinguishes between durable and non-durable goods prices. The second contribution of the paper is to construct a DPI for the United States from 1970 to 2004. It differs markedly from the CPI in that: it is less serially correlated, more volatile, and a large part of its movements are driven by changes in the prices of houses and bonds. Both in theory and in practice, this paper finds that considering dynamics, intertemporal smoothing and uncertainty leads to a novel and strikingly different measure of the cost of living.

  17. F

    Producer Price Index by Commodity: All Commodities

    • fred.stlouisfed.org
    json
    Updated Sep 10, 2025
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    (2025). Producer Price Index by Commodity: All Commodities [Dataset]. https://fred.stlouisfed.org/series/PPIACO
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    jsonAvailable download formats
    Dataset updated
    Sep 10, 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: All Commodities (PPIACO) from Jan 1913 to Aug 2025 about commodities, PPI, inflation, price index, indexes, price, and USA.

  18. Consumer Price Index by geography, all-items, monthly, percentage change,...

    • www150.statcan.gc.ca
    Updated Sep 16, 2025
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    Government of Canada, Statistics Canada (2025). Consumer Price Index by geography, all-items, monthly, percentage change, not seasonally adjusted, Canada, provinces, Whitehorse, Yellowknife and Iqaluit [Dataset]. http://doi.org/10.25318/1810000401-eng
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    Dataset updated
    Sep 16, 2025
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    Monthly indexes and percentage changes for all components and special aggregates of the Consumer Price Index (CPI), not seasonally adjusted, for Canada, provinces, Whitehorse, Yellowknife and Iqaluit. Data are presented for the corresponding month of the previous year, the previous month and the current month. The base year for the index is 2002=100.

  19. 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

  20. g

    Elementary index bias: evidence for the euro area from a large scanner...

    • datasearch.gesis.org
    155305
    Updated Apr 9, 2019
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    Gábor-Tóth, Eniko; Vermeulen, Philip (2019). Elementary index bias: evidence for the euro area from a large scanner dataset [Dataset]. http://doi.org/10.15456/ger.2018346.155305
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    155305Available download formats
    Dataset updated
    Apr 9, 2019
    Dataset provided by
    da|ra (Registration agency for social science and economic data)
    Authors
    Gábor-Tóth, Eniko; Vermeulen, Philip
    License

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

    Description

    We provide evidence on the effect of elementary index choice on inflation measurement in the euro area. Using scanner data for 15,844 individual items from 42 product categories and 10 euro area countries, we compute product category level elementary price indexes using eight different elementary index formulas. Measured inflation outcomes of the different index formulas are compared with the Fisher ideal index to quantify elementary index bias. We have three main findings. First, elementary index bias is quite variable across product categories, countries and index formulas. Second, a comparison of elementary index formulas with and without expenditure weights shows that a shift from price only indexes to expenditure weighted indexes would entail at the product level multiple percentage points differences in measured price changes. And finally, we show that elementary index bias is quantitatively more important than upper level substitution bias.

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TRADING ECONOMICS (2024). CONSUMER PRICE INDEX WITH FIXED INTEREST RATE by Country Dataset [Dataset]. https://tradingeconomics.com/country-list/consumer-price-index-with-fixed-interest-rate

CONSUMER PRICE INDEX WITH FIXED INTEREST RATE by Country Dataset

CONSUMER PRICE INDEX WITH FIXED INTEREST RATE by Country Dataset (2025)

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json, excel, csv, xmlAvailable download formats
Dataset updated
May 20, 2024
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
2025
Area covered
World
Description

This dataset provides values for CONSUMER PRICE INDEX WITH FIXED INTEREST RATE reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

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