United States CBO Projection:(CPI) Consumer Price IndexU: Less Food & Energy: QoQ data was reported at 2.369 % in Dec 2029. This records an increase from the previous number of 2.364 % for Sep 2029. United States CBO Projection:(CPI) Consumer Price IndexU: Less Food & Energy: QoQ data is updated quarterly, averaging 2.317 % from Jun 2011 (Median) to Dec 2029, with 75 observations. The data reached an all-time high of 2.667 % in Sep 2020 and a record low of 1.372 % in Dec 2012. United States CBO Projection:(CPI) Consumer Price IndexU: Less Food & Energy: QoQ data remains active status in CEIC and is reported by Congressional Budget Office. The data is categorized under Global Database’s United States – Table US.I004: Consumer Price Index: Urban: Projection: Congressional Budget Office.

United States CBO Projection: Consumer Price Index (CPI): Urban Less Food & Energy: YoY data was reported at 2.357 % in 2028. This records an increase from the previous number of 2.345 % for 2027. United States CBO Projection: Consumer Price Index (CPI): Urban Less Food & Energy: YoY data is updated yearly, averaging 2.343 % from Dec 2012 (Median) to 2028, with 17 observations. The data reached an all-time high of 2.683 % in 2020 and a record low of 1.770 % in 2013. United States CBO Projection: Consumer Price Index (CPI): Urban Less Food & Energy: YoY data remains active status in CEIC and is reported by Congressional Budget Office. The data is categorized under Global Database’s United States – Table US.I004: Consumer Price Index: Urban: Projection: Congressional Budget Office.

1. New Taipei City Consumer Price Index (CPI)2. Unit: %3. For detailed explanations of each category, please refer to the New Taipei City Consumer Price Statistics Monthly Report (website: http://www.bas.ntpc.gov.tw/home.jsp?idODE) or contact the Statistical Office for inquiries.

The Department of Treasury and Finance (DTF) monitors economic conditions in the Victorian economy and prepares forecasts of the main economic indicators of those conditions twice yearly for the current and four-ensuing years (the out-years). The economic forecasts underpin the Government's fiscal outlook presented in the Budget and Budget Update. The key economic indicators forecast growth in real gross state product (GSP) and the level of nominal GSP; growth in employment and the unemployment rate; growth in wages; growth in consumer prices (the CPI) and population growth. For further information refer to the Macroeconomic indicators methodology for making forecasts of macro-economic indicators.

United States CBO Projection: Consumer Price Index (CPI): Urban data was reported at 328.637 1982-1984=100 in Dec 2029. This records an increase from the previous number of 326.717 1982-1984=100 for Sep 2029. United States CBO Projection: Consumer Price Index (CPI): Urban data is updated quarterly, averaging 268.979 1982-1984=100 from Dec 2012 (Median) to Dec 2029, with 69 observations. The data reached an all-time high of 328.637 1982-1984=100 in Dec 2029 and a record low of 231.227 1982-1984=100 in Dec 2012. United States CBO Projection: Consumer Price Index (CPI): Urban data remains active status in CEIC and is reported by Congressional Budget Office. The data is categorized under Global Database’s United States – Table US.I004: Consumer Price Index: Urban: Projection: Congressional Budget Office.

The Department of Treasury and Finance (DTF) monitors economic conditions in the Victorian economy and prepares forecasts of the main economic indicators of those conditions twice yearly for the current and four-ensuing years (the out-years). The economic forecasts underpin the Government's fiscal outlook presented in the Budget and Budget Update. The key economic indicators forecast growth in real gross state product (GSP) and the level of nominal GSP; growth in employment and the unemployment rate; growth in wages; growth in consumer prices (the CPI) and population growth. For further information refer to the Macroeconomic indicators methodology for making forecasts of macro-economic indicators.

Consumer Price Index (CPI) (Basic Classification Index) monthly index

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.

The purpose of this article is to give the estimated effects on the Consumer Prices Index and Retail Prices Index resulting from duty and taxation changes announced in the Budget.

This article is simply a helpful guide to users of the CPI and RPI. The Office for National Statistics (ONS) accepts no liability whatsoever for losses of any kind arising as a result of reliance on this note.

Source agency: Office for National Statistics

Designation: National Statistics

Language: English

Alternative title: Budget

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

United States CBO Projection:(CPI) Consumer Price IndexU: Less Food & Energy: Annual data was reported at 334.595 1982-1984=100 in 2029. This records an increase from the previous number of 326.902 1982-1984=100 for 2028. United States CBO Projection:(CPI) Consumer Price IndexU: Less Food & Energy: Annual data is updated yearly, averaging 270.654 1982-1984=100 from Dec 2011 (Median) to 2029, with 19 observations. The data reached an all-time high of 334.595 1982-1984=100 in 2029 and a record low of 224.992 1982-1984=100 in 2011. United States CBO Projection:(CPI) Consumer Price IndexU: Less Food & Energy: Annual data remains active status in CEIC and is reported by Congressional Budget Office. The data is categorized under Global Database’s United States – Table US.I004: Consumer Price Index: Urban: Projection: Congressional Budget Office. Refer to Series ID 41090601 for the actual figures from Bureau of Labor Statistics

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

The Department of Treasury and Finance (DTF) monitors economic conditions in the Victorian economy and prepares forecasts of the main economic indicators of those conditions twice yearly for the current and four-ensuing years (the out-years). The economic forecasts underpin the Government's fiscal outlook presented in the Budget and Budget Update.
The key economic indicators forecast growth in real gross state product (GSP) and the level of nominal GSP; growth in employment and the unemployment rate; growth in wages; growth in consumer prices (the CPI) and population growth.
For further information refer to the Macroeconomic indicators methodology for making forecasts of macro-economic indicators.

1. URL link to the CPI statistics dataset in XML format2. Purpose of collection: for batch downloading3. Data collection method: Consolidate URL links to the CPI dataset in XML format

The Consumer Price Index of the United Kingdom was 138.5 in the second quarter of 2025, indicating that consumer prices have increased by 38.5 percent when compared with the first quarter of 2015. As of June 2025, the inflation rate for the CPI was 3.6 percent, an uptick from March, when prices were rising by 2.6 percent. A long period of elevated inflation between 2021 and 2023 peaked in October 2022 and saw prices increase by over 20 percent in just three years. Uptick in inflation expected in 2025 In late 2024, the UK's main economic forecaster, the Office for Budget Responsibility, predicted that the annual inflation rate for 2025 would average out at around 2.6 percent. In March 2025, however, the OBR revised this figure upward, with annual inflation now expected to be 3.2 percent. This uptick in inflation is predicted to peak in the third quarter of the year at 3.7 percent before falling to two percent by the second quarter of 2026. Although this period of higher inflation is predicted to be far less severe than in 2022, it will no doubt put further pressure on households already struggling with their cost of living. Cost of living woes continue The share of UK households reporting that their cost of living was increasing has been steadily rising since Summer 2024. At that time, less than half of UK households reported rising costs, down from 91 percent two years earlier. As of March 2025, however, 59 percent of households said their costs were rising, the highest figure since 2023. Of these households, 93 percent reported that their food shop was increasing, with three quarters of them reporting higher energy costs. With higher inflation predicted in 2025, the pressure on UK households will likely continue, although a crisis on the scale of 2021-2023 will hopefully be avoided.

In 2020 the Consumer Price Index (CPI) rate of the United Kingdom is expected to be between *** percent and *** percent, according to forecasts from three different institutions, the Office for Budget Responsibility, the International Monetary Fund, and the The National Institute of Economic and Social Research. CPI measures the rate of change to market basket price levels of consumer goods and services purchased by households.

United States CBO Projection:(CPI) Consumer Price IndexU: Annual data was reported at 325.772 1982-1984=100 in 2029. This records an increase from the previous number of 318.264 1982-1984=100 for 2028. United States CBO Projection:(CPI) Consumer Price IndexU: Annual data is updated yearly, averaging 263.055 1982-1984=100 from Dec 2011 (Median) to 2029, with 19 observations. The data reached an all-time high of 325.772 1982-1984=100 in 2029 and a record low of 224.960 1982-1984=100 in 2011. United States CBO Projection:(CPI) Consumer Price IndexU: Annual data remains active status in CEIC and is reported by Congressional Budget Office. The data is categorized under Global Database’s United States – Table US.I004: Consumer Price Index: Urban: Projection: Congressional Budget Office. Refer to Series ID 41060801 for the actual figures from the Bureau of Labor Statistics

Record the statistical data of the consumer price index in this city according to special categories.

United States CBO Projection:(CPI) Consumer Price IndexU: QoQ data was reported at 2.371 % in Dec 2029. This records an increase from the previous number of 2.367 % for Sep 2029. United States CBO Projection:(CPI) Consumer Price IndexU: QoQ data is updated quarterly, averaging 2.348 % from Jun 2011 (Median) to Dec 2029, with 75 observations. The data reached an all-time high of 4.291 % in Jun 2011 and a record low of -0.050 % in Dec 2014. United States CBO Projection:(CPI) Consumer Price IndexU: QoQ data remains active status in CEIC and is reported by Congressional Budget Office. The data is categorized under Global Database’s United States – Table US.I004: Consumer Price Index: Urban: Projection: Congressional Budget Office.

Consumer Price Index Time Series Statistics for Taipei City