66 datasets found
  1. d

    CPI 3.12 Family Team Meetings FY2015-2024

    • catalog.data.gov
    • data.texas.gov
    Updated Feb 25, 2025
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    data.austintexas.gov (2025). CPI 3.12 Family Team Meetings FY2015-2024 [Dataset]. https://catalog.data.gov/dataset/cpi-3-12-family-team-meetings-fy2013-2022
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    Dataset updated
    Feb 25, 2025
    Dataset provided by
    data.austintexas.gov
    Description

    A Family Team Meeting (FTM) is a family-centered rapid response meeting CPI uses to try and prevent a removal by engaging caregivers, parents and extended family and friends to address child safety concerns. An FTM is not limited to an investigation and can occur at any point or stage in which CPI or CPS is involved with a family. More information at www.dfps.texas.gov

  2. Switzerland CPI: RC: CR: Recreation Service: Meetings

    • ceicdata.com
    • dr.ceicdata.com
    Updated Dec 15, 2024
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    CEICdata.com (2024). Switzerland CPI: RC: CR: Recreation Service: Meetings [Dataset]. https://www.ceicdata.com/en/switzerland/consumer-price-index-december-2005100/cpi-rc-cr-recreation-service-meetings
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    Dataset updated
    Dec 15, 2024
    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, 2010 - Dec 1, 2010
    Area covered
    Switzerland
    Variables measured
    Consumer Prices
    Description

    Switzerland Consumer Price Index (CPI): RC: CR: Recreation Service: Meetings data was reported at 107.401 Dec2005=100 in Dec 2010. This records a decrease from the previous number of 107.462 Dec2005=100 for Nov 2010. Switzerland Consumer Price Index (CPI): RC: CR: Recreation Service: Meetings data is updated monthly, averaging 76.657 Dec2005=100 from Dec 1982 (Median) to Dec 2010, with 337 observations. The data reached an all-time high of 107.462 Dec2005=100 in Nov 2010 and a record low of 47.046 Dec2005=100 in Jan 1983. Switzerland Consumer Price Index (CPI): RC: CR: Recreation Service: Meetings data remains active status in CEIC and is reported by Swiss Federal Statistical Office. The data is categorized under Global Database’s Switzerland – Table CH.I006: Consumer Price Index: December 2005=100.

  3. w

    Consumer Price Indices

    • data360.worldbank.org
    Updated Aug 18, 2020
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    (2020). Consumer Price Indices [Dataset]. https://data360.worldbank.org/en/dataset/FAO_CP
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    Dataset updated
    Aug 18, 2020
    License

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

    Time period covered
    2000 - 2024
    Description

    The FAOSTAT monthly Food CPI and General CPI database was based on the ILO CPI data until December 2014. In 2014, IMF-ILO-FAO agreed to transfer global CPI data compilation from ILO to IMF. Upon agreement, CPIs for all items and its sub components originates from the International Monetary Fund (IMF), and the UN Statistics Division(UNSD) for countries not covered by the IMF. However, due to a limited time coverage from IMF and UNSD for a number of countries, the Organisation for Economic Co-operation and Development (OECD), Central Bank of Western African States (BCEAO), Eastern Caribbean Central Bank (ECCB), UNdata, United Nations Conference on Trade and Development (UNCTAD) and national statistical office website data are used for missing historical data from IMF and UNSD food CPI.

    The FAO CPI dataset for all items(or general CPI) and the Food CPI, consists of a complete and consistent set of time series from January 2000 onwards. Data gaps on monthly Food CPI and General CPI are filled using statistical estimation procedures to have full data coverage for all countries for Food CPI and for General CPI. These indices measure the price change between the current and reference periods of the average basket of goods and services purchased by households. The General CPI is typically used to measure and monitor inflation, set monetary policy targets, index social benefits such as pensions and unemployment benefits, and to escalate thresholds and credits in the income tax systems and wages in public and private wage contracts. The FAOSTAT monthly Food CPI inflation rates are annual year-over-year inflation or percentage change over corresponding month of the previous year.

    The data included in Data360 is a subset of the data available from the source. Please refer to the source for complete data and methodology details.

    This collection includes only a subset of indicators from the source dataset.

  4. T

    United States CPI Core Core

    • tradingeconomics.com
    • ru.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated May 15, 2025
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    TRADING ECONOMICS (2025). United States CPI Core Core [Dataset]. https://tradingeconomics.com/united-states/cpi-core-core
    Explore at:
    json, excel, xml, csvAvailable download formats
    Dataset updated
    May 15, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Jan 31, 1968 - May 31, 2025
    Area covered
    United States
    Description

    CPI Core Core in the United States increased to 1.90 percent in May from 1.80 percent in April of 2025. This dataset provides - United States CPI Core Core- actual values, historical data, forecast, chart, statistics, economic calendar and news.

  5. d

    CPI 5.2 Alternative Response Stages - Timeliness of Initial Contact...

    • catalog.data.gov
    • data.texas.gov
    Updated Feb 25, 2025
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    data.austintexas.gov (2025). CPI 5.2 Alternative Response Stages - Timeliness of Initial Contact FY2015-2024 [Dataset]. https://catalog.data.gov/dataset/cpi-5-2-alternative-response-stages-timeliness-of-initial-contact-fy2015-2022
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    Dataset updated
    Feb 25, 2025
    Dataset provided by
    data.austintexas.gov
    Description

    ABOUT THIS CHART Child Protective Investigations (CPI) conducts either a traditional investigation or Alternative Response (AR). Traditional investigations and Alternative Response require caseworkers to assess safety and take needed actions to protect a child while assessing any risk of abuse or neglect in the foreseeable future. AR cases present a less adversarial more collaborative approach to working with families by allowing for family engagement along with other community supports to ensure child safety. AR differs from traditional investigations in that AR cases are Priority 2 cases involving victims who are age 6 or older, there is no substantiation of allegations, no entry of perpetrators into the Central Registry (a repository for reports of child abuse and neglect), and there is a heightened focus on guiding the family to plan for safety in a way that works for them and therefore sustains safety. Alternative response is timely if the first face-to-face meeting with the family and children in the household occurs within five days of an AR stage being opened and will involve working with the family to conduct safety and family assessments. AR cases can remain open for up to 60 days with a one-time 20-day extension, if appropriate. Should CPI staff identify services to improve general family functioning and overall protective actions within the standard AR case time frame, the caseworker will provide support in linking the family to existing resources within the community. A description of Alternative Response and how it differs from a traditional investigation and priority response times are in the glossary. Alterative Response has been fully implemented in Regions 1, 2, 3, 4, 5, 6B, 7, 8, 9, 10 and 11. AR in Region 6A is in the implementation stage. Full state implementation is anticipated in March 2021. Region 6A is Harris County and Region 6B is Region 6 excluding Harris County. This dashboard addresses the Texas Family Code Section 264.017 (b) (6).

  6. Monthly inflation rate and Federal Reserve interest rate in the U.S....

    • statista.com
    • ai-chatbox.pro
    Updated Jun 23, 2025
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    Statista (2025). Monthly inflation rate and Federal Reserve interest rate in the U.S. 2018-2025 [Dataset]. https://www.statista.com/statistics/1312060/us-inflation-rate-federal-reserve-interest-rate-monthly/
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    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 2018 - Mar 2024
    Area covered
    United States
    Description

    The inflation rate in the United States declined significantly between June 2022 and May 2025, despite rising inflationary pressures towards the end of 2024. The peak inflation rate was recorded in June 2022, at *** percent. In August 2023, the Federal Reserve's interest rate hit its highest level during the observed period, at **** percent, and remained unchanged until September 2024, when the Federal Reserve implemented its first rate cut since September 2021. By January 2025, the rate dropped to **** percent, signalling a shift in monetary policy. What is the Federal Reserve interest rate? The Federal Reserve interest rate, or the federal funds rate, is the rate at which banks and credit unions lend to and borrow from each other. It is one of the Federal Reserve's key tools for maintaining strong employment rates, stable prices, and reasonable interest rates. The rate is determined by the Federal Reserve and adjusted eight times a year, though it can be changed through emergency meetings during times of crisis. The Fed doesn't directly control the interest rate but sets a target rate. It then uses open market operations to influence rates toward this target. Ways of measuring inflation Inflation is typically measured using several methods, with the most common being the Consumer Price Index (CPI). The CPI tracks the price of a fixed basket of goods and services over time, providing a measure of the price changes consumers face. At the end of 2023, the CPI in the United States was ****** percent, up from ****** a year earlier. A more business-focused measure is the producer price index (PPI), which represents the costs of firms.

  7. T

    United States Core Inflation Rate

    • tradingeconomics.com
    • id.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Apr 10, 2025
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    TRADING ECONOMICS (2025). United States Core Inflation Rate [Dataset]. https://tradingeconomics.com/united-states/core-inflation-rate
    Explore at:
    excel, csv, json, xmlAvailable download formats
    Dataset updated
    Apr 10, 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
    Feb 28, 1957 - May 31, 2025
    Area covered
    United States
    Description

    Core consumer prices in the United States increased 2.80 percent in May of 2025 over the same month in the previous year. This dataset provides - United States Core Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  8. 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
    Explore at:
    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

  9. d

    Consumer Price Index

    • data.gov.tw
    xml
    + more versions
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    Directorate General of Budget, Accounting and Statistics, Executive Yuan, R.O.C., Consumer Price Index [Dataset]. https://data.gov.tw/en/datasets/6019
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    xmlAvailable download formats
    Dataset authored and provided by
    Directorate General of Budget, Accounting and Statistics, Executive Yuan, R.O.C.
    License

    https://data.gov.tw/licensehttps://data.gov.tw/license

    Description

    The basic classification of the Consumer Price Index in Taiwan includes categories such as food, clothing, housing, transportation and communication, medical care, education and entertainment, and miscellaneous expenses.

  10. 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
    Explore at:
    Dataset updated
    May 18, 2023
    Dataset authored and provided by
    Palestinian Central Bureau of Statisticshttp://pcbs.gov.ps/
    Time period covered
    2021
    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. Consumer Price Data and Measures Explained

    • clevelandfed.org
    csv
    Updated May 1, 2025
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    Federal Reserve Bank of Cleveland (2025). Consumer Price Data and Measures Explained [Dataset]. https://www.clevelandfed.org/center-for-inflation-research/consumer-price-data
    Explore at:
    csvAvailable download formats
    Dataset updated
    May 1, 2025
    Dataset authored and provided by
    Federal Reserve Bank of Clevelandhttps://www.clevelandfed.org/
    Description

    We explain how measures of consumer prices are computed and what the differences are between the consumer price index (CPI) and the personal consumption expenditures (PCE) price index. We also explain various measures used to gauge underlying inflation, or the long-term trend in prices, such as median and trimmed-mean inflation rates and core inflation.

  12. Inflation rate in the UK 2015-2025

    • statista.com
    • ai-chatbox.pro
    Updated Jun 18, 2025
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    Statista (2025). Inflation rate in the UK 2015-2025 [Dataset]. https://www.statista.com/statistics/306648/inflation-rate-consumer-price-index-cpi-united-kingdom-uk/
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    Dataset updated
    Jun 18, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 2015 - May 2025
    Area covered
    United Kingdom
    Description

    The UK inflation rate was 3.4 percent in May 2025, down from 3.5 percent in the previous month, and the fastest rate of inflation since February 2024. Between September 2022 and March 2023, the UK experienced seven months of double-digit inflation, which peaked at 11.1 percent in October 2022. Due to this long period of high inflation, UK consumer prices have increased by over 20 percent in the last three years. As of the most recent month, prices were rising fastest in the communications sector, at 6.1 percent, but were falling in both the furniture and transport sectors, at -0.3 percent and -0.6 percent respectively.
    The Cost of Living Crisis High inflation is one of the main factors behind the ongoing Cost of Living Crisis in the UK, which, despite subsiding somewhat in 2024, is still impacting households going into 2025. In December 2024, for example, 56 percent of UK households reported their cost of living was increasing compared with the previous month, up from 45 percent in July, but far lower than at the height of the crisis in 2022. After global energy prices spiraled that year, the UK's energy price cap increased substantially. The cap, which limits what suppliers can charge consumers, reached 3,549 British pounds per year in October 2022, compared with 1,277 pounds a year earlier. Along with soaring food costs, high-energy bills have hit UK households hard, especially lower income ones that spend more of their earnings on housing costs. As a result of these factors, UK households experienced their biggest fall in living standards in decades in 2022/23. Global inflation crisis causes rapid surge in prices The UK's high inflation, and cost of living crisis in 2022 had its origins in the COVID-19 pandemic. Following the initial waves of the virus, global supply chains struggled to meet the renewed demand for goods and services. Food and energy prices, which were already high, increased further in 2022. Russia's invasion of Ukraine in February 2022 brought an end to the era of cheap gas flowing to European markets from Russia. The war also disrupted global food markets, as both Russia and Ukraine are major exporters of cereal crops. As a result of these factors, inflation surged across Europe and in other parts of the world, but typically declined in 2023, and approached more usual levels by 2024.

  13. g

    World Bank - Consumer Price Indices

    • gimi9.com
    Updated Aug 18, 2020
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    (2020). World Bank - Consumer Price Indices [Dataset]. https://gimi9.com/dataset/worldbank_fao_cp/
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    Dataset updated
    Aug 18, 2020
    License

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

    Description

    šŸ³ļøā€šŸŒˆ International Organization English The FAOSTAT monthly Food CPI and General CPI database was based on the ILO CPI data until December 2014. In 2014, IMF-ILO-FAO agreed to transfer global CPI data compilation from ILO to IMF. Upon agreement, CPIs for all items and its sub components originates from the International Monetary Fund (IMF), and the UN Statistics Division(UNSD) for countries not covered by the IMF. However, due to a limited time coverage from IMF and UNSD for a number of countries, the Organisation for Economic Co-operation and Development (OECD), Central Bank of Western African States (BCEAO), Eastern Caribbean Central Bank (ECCB), UNdata, United Nations Conference on Trade and Development (UNCTAD) and national statistical office website data are used for missing historical data from IMF and UNSD food CPI. The FAO CPI dataset for all items(or general CPI) and the Food CPI, consists of a complete and consistent set of time series from January 2000 onwards. Data gaps on monthly Food CPI and General CPI are filled using statistical estimation procedures to have full data coverage for all countries for Food CPI and for General CPI. These indices measure the price change between the current and reference periods of the average basket of goods and services purchased by households. The General CPI is typically used to measure and monitor inflation, set monetary policy targets, index social benefits such as pensions and unemployment benefits, and to escalate thresholds and credits in the income tax systems and wages in public and private wage contracts. The FAOSTAT monthly Food CPI inflation rates are annual year-over-year inflation or percentage change over corresponding month of the previous year. The data included in Data360 is a subset of the data available from the source. Please refer to the source for complete data and methodology details. This collection includes only a subset of indicators from the source dataset.

  14. T

    Italy Consumer Price Index (CPI)

    • tradingeconomics.com
    • ru.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Aug 18, 2015
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    TRADING ECONOMICS (2015). Italy Consumer Price Index (CPI) [Dataset]. https://tradingeconomics.com/italy/consumer-price-index-cpi
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    xml, excel, json, csvAvailable download formats
    Dataset updated
    Aug 18, 2015
    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, 1957 - Jun 30, 2025
    Area covered
    Italy
    Description

    Consumer Price Index CPI in Italy remained unchanged at 122.60 points in May. This dataset provides the latest reported value for - Italy Consumer Price Index (CPI) - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  15. CPI inflation rate for goods and services in the UK 2015-2025

    • statista.com
    Updated Jun 18, 2025
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    Statista (2025). CPI inflation rate for goods and services in the UK 2015-2025 [Dataset]. https://www.statista.com/statistics/285202/rpi-goods-and-services/
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    Dataset updated
    Jun 18, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 2015 - May 2025
    Area covered
    United Kingdom
    Description

    In May 2025, the UK inflation rate for goods was two percent and 4.7 percent for services. Prices for goods accelerated significantly, sharply between in 2021 and 2022 before falling in 2023. By comparison, prices for services initially grew at a more moderate rate, but have also not fallen as quickly. The overall CPI inflation rate for the UK reached a recent high of 11.1 percent in October 2022 and remained in double-figures until April 2023, when it fell to 8.7 percent. As of this month, the UK's inflation rate was 2.6 percent, down from 2.8 percent in the previous month. Sectors driving high inflation In late 2024, communication was the sector with the highest inflation rate, with prices increasing by 6.1 percent as of December 2024. During the recent period of high inflation that eased in 2023, food and energy prices were particular high, with housing and energy inflation far higher than in any other sector, peaking at 26.6 percent towards the end of 2022. High food and energy prices since 2021 have been one of the main causes of the cost of living crisis in the UK, especially for low-income households that spend a higher share of their income on these categories. This is likely one of the factors driving increasing food bank usage in the UK, which saw approximately 3.12 million people use a food bank in 2023/24, compared with 1.9 million just before the COVID-19 pandemic. The global inflation crisis The UK has not been alone in suffering rapid price increases since 2021. After the start of the COVID-19 pandemic, a series of economic and geopolitical shocks had a dramatic impact on the global economy. A global supply chain crisis failed to meet rising demand in 2021, leading to the beginning of an Inflation Crisis, which was only exacerbated by Russia's invasion of Ukraine in February 2022. The war directly influenced the prices of food and energy, as both countries were major exporters of important crops. European imports of hydrocarbons from Russia were also steadily reduced throughout 2022 and 2023, resulting in higher energy prices throughout the year.

  16. 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

  17. Inflation Nowcasting

    • clevelandfed.org
    json
    Updated Mar 10, 2017
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    Federal Reserve Bank of Cleveland (2017). Inflation Nowcasting [Dataset]. https://www.clevelandfed.org/indicators-and-data/inflation-nowcasting
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    jsonAvailable download formats
    Dataset updated
    Mar 10, 2017
    Dataset authored and provided by
    Federal Reserve Bank of Clevelandhttps://www.clevelandfed.org/
    License

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

    Description

    The Federal Reserve Bank of Cleveland provides daily ā€œnowcastsā€ of inflation for two popular price indexes, the price index for personal consumption expenditures (PCE) and the Consumer Price Index (CPI). These nowcasts give a sense of where inflation is today. Released each business day.

  18. B

    Conference Board of Canada, CPI by Provinces, 1972-2018 (Millions $) [Excel...

    • borealisdata.ca
    • search.dataone.org
    Updated Oct 24, 2024
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    Conference Board of Canada (2024). Conference Board of Canada, CPI by Provinces, 1972-2018 (Millions $) [Excel file] [Dataset]. http://doi.org/10.5683/SP3/QPDSIO
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Oct 24, 2024
    Dataset provided by
    Borealis
    Authors
    Conference Board of Canada
    License

    https://borealisdata.ca/api/datasets/:persistentId/versions/1.4/customlicense?persistentId=doi:10.5683/SP3/QPDSIOhttps://borealisdata.ca/api/datasets/:persistentId/versions/1.4/customlicense?persistentId=doi:10.5683/SP3/QPDSIO

    Time period covered
    1972 - 2018
    Area covered
    Canada
    Description

    Quarterly data from 1972-2018 (projection) of CPI by provinces

  19. South Korea KR: CPI: Local Source Base Year: Communication

    • ceicdata.com
    Updated Dec 15, 2023
    + more versions
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    CEICdata.com (2023). South Korea KR: CPI: Local Source Base Year: Communication [Dataset]. https://www.ceicdata.com/en/korea/consumer-price-index-coicop-1999-oecd-member-quarterly/kr-cpi-local-source-base-year-communication
    Explore at:
    Dataset updated
    Dec 15, 2023
    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
    Mar 1, 2021 - Dec 1, 2023
    Area covered
    South Korea
    Variables measured
    Consumer Prices
    Description

    South Korea Consumer Price Index (CPI): Local Source Base Year: Communication data was reported at 101.227 2020=100 in Dec 2023. This records an increase from the previous number of 101.047 2020=100 for Sep 2023. South Korea Consumer Price Index (CPI): Local Source Base Year: Communication data is updated quarterly, averaging 119.431 2020=100 from Mar 1985 (Median) to Dec 2023, with 156 observations. The data reached an all-time high of 169.167 2020=100 in Sep 1988 and a record low of 96.140 2020=100 in Dec 2020. South Korea Consumer Price Index (CPI): Local Source Base Year: Communication 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 South Korea – Table KR.OECD.MEI: Consumer Price Index: COICOP 1999: OECD Member: Quarterly. The Consumer price index is produced by collecting the prices of goods and services and its result is used as basic data for government financial policies and as deflator of other economic indices, such as Household Income & Expenditure and National Account. Type of prices: Actual transaction prices exclude abnormal prices such as temporarily irregular prices caused by disaster or similar conditions, discounts due to volume transactions, goods sold on an installment basis and second-hand articles. Tax: Sales taxes are included. Method of collection: Most collection is done by personal visit and some are collected centrally for items such as electric charges, whose prices are the same throughout the country. Rents are collected from households as part of the LFS (Labor Force Survey). Treatment of rentals for housing: the index includes a measure of rentals for housing. Treatment of Owner-occupied housing: It is not included in the CPI main index but it is provided as a complementary index. Treatment of missing prices: When a price observation is temporarily unavailable in a given month, its price is imputed by the price movements of similar products of the same item in the same geographic area. Treatment of quality changes: For minor quality differences (such as changes in packaging, style,...) a direct adjustment for the price difference is applied. For significant quality differences, the splicing (overlap) method is used. Introduction of new products: New items are introduced at the time weights are updated. it means once every five years. Selection of replacement items: When a specific variety is permanently unavailable in an outlet, another product in the same outlet that most closely meets the specifications of the previous variety is selected as a replacement. Treatment of seasonal items: For items such as fresh fish, fruit, and vegetables that are not available on the market during the off-season, the last available prices are used to calculate the index until new prices are available.; Index series starts in January 1985

  20. South Korea KR: CPI: Local Source Base Year: Health

    • ceicdata.com
    Updated Dec 15, 2023
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    South Korea KR: CPI: Local Source Base Year: Health [Dataset]. https://www.ceicdata.com/en/korea/consumer-price-index-coicop-1999-oecd-member-quarterly/kr-cpi-local-source-base-year-health
    Explore at:
    Dataset updated
    Dec 15, 2023
    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
    Mar 1, 2021 - Dec 1, 2023
    Area covered
    South Korea
    Variables measured
    Consumer Prices
    Description

    South Korea Consumer Price Index (CPI): Local Source Base Year: Health data was reported at 102.753 2020=100 in Dec 2023. This records an increase from the previous number of 102.513 2020=100 for Sep 2023. South Korea Consumer Price Index (CPI): Local Source Base Year: Health data is updated quarterly, averaging 81.567 2020=100 from Mar 1985 (Median) to Dec 2023, with 156 observations. The data reached an all-time high of 102.753 2020=100 in Dec 2023 and a record low of 36.073 2020=100 in Mar 1985. South Korea Consumer Price Index (CPI): Local Source Base Year: Health 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 South Korea – Table KR.OECD.MEI: Consumer Price Index: COICOP 1999: OECD Member: Quarterly. The Consumer price index is produced by collecting the prices of goods and services and its result is used as basic data for government financial policies and as deflator of other economic indices, such as Household Income & Expenditure and National Account. Type of prices: Actual transaction prices exclude abnormal prices such as temporarily irregular prices caused by disaster or similar conditions, discounts due to volume transactions, goods sold on an installment basis and second-hand articles. Tax: Sales taxes are included. Method of collection: Most collection is done by personal visit and some are collected centrally for items such as electric charges, whose prices are the same throughout the country. Rents are collected from households as part of the LFS (Labor Force Survey). Treatment of rentals for housing: the index includes a measure of rentals for housing. Treatment of Owner-occupied housing: It is not included in the CPI main index but it is provided as a complementary index. Treatment of missing prices: When a price observation is temporarily unavailable in a given month, its price is imputed by the price movements of similar products of the same item in the same geographic area. Treatment of quality changes: For minor quality differences (such as changes in packaging, style,...) a direct adjustment for the price difference is applied. For significant quality differences, the splicing (overlap) method is used. Introduction of new products: New items are introduced at the time weights are updated. it means once every five years. Selection of replacement items: When a specific variety is permanently unavailable in an outlet, another product in the same outlet that most closely meets the specifications of the previous variety is selected as a replacement. Treatment of seasonal items: For items such as fresh fish, fruit, and vegetables that are not available on the market during the off-season, the last available prices are used to calculate the index until new prices are available.; Index series starts in January 1985

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data.austintexas.gov (2025). CPI 3.12 Family Team Meetings FY2015-2024 [Dataset]. https://catalog.data.gov/dataset/cpi-3-12-family-team-meetings-fy2013-2022

CPI 3.12 Family Team Meetings FY2015-2024

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Dataset updated
Feb 25, 2025
Dataset provided by
data.austintexas.gov
Description

A Family Team Meeting (FTM) is a family-centered rapid response meeting CPI uses to try and prevent a removal by engaging caregivers, parents and extended family and friends to address child safety concerns. An FTM is not limited to an investigation and can occur at any point or stage in which CPI or CPS is involved with a family. More information at www.dfps.texas.gov

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