Consumer Price Index CPI in India increased to 197.30 points in October from 197 points in September of 2025. This dataset provides - India Consumer Price Index (CPI) - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Graph and download economic data for Consumer Price Index: Services Less Housing National Definition for Austria (CPSELR02ATM661N) from Jan 1966 to May 2018 about Austria, services, CPI, housing, price index, indexes, and price.

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

The Consumer Price Index (CPI) is a measure that examines the weighted average of prices of a basket of consumer goods and services, such as transportation, food, and medical care. It is calculated by taking price changes for each item in the predetermined basket and averaging them. Prices are collected periodically, and the CPI is often used to measure inflation, reflecting the cost of living. The CPI is typically set against a base year. The index is set to 100 in the base year, and changes in the CPI indicate price changes compared to that year. A typical household might purchase a wide range of products and services. Items in the basket are weighted according to their importance or share in total household spending. The Inflation Rate is the percentage increase in the general level of prices for goods and services over a period of time. It indicates how much prices have risen over a specific period, typically a year. Higher inflation decreases the purchasing power of money, meaning consumers can buy less with the same amount of money.It reflects the overall health of an economy. Moderate inflation is expected in a growing economy, but hyperinflation can indicate economic instability. The Inflation Rate is calculated using the following formula: Inflation Rate (%) = ((CPI in Current Year−CPI in Previous Year)/ (CPI in Previous Year))×100

San Marino Consumer Price Index (CPI): % Change data was reported at 1.046 % in 2017. This records an increase from the previous number of 0.574 % for 2016. San Marino Consumer Price Index (CPI): % Change data is updated yearly, averaging 1.890 % from Dec 2004 (Median) to 2017, with 14 observations. The data reached an all-time high of 4.293 % in 2008 and a record low of 0.146 % in 2015. San Marino Consumer Price Index (CPI): % Change data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s San Marino – Table SM.World Bank.WDI: Inflation. Inflation as measured by the consumer price index reflects the annual percentage change in the cost to the average consumer of acquiring a basket of goods and services that may be fixed or changed at specified intervals, such as yearly. The Laspeyres formula is generally used.; ; International Monetary Fund, International Financial Statistics and data files.; Median;

PCE: PI: saar: Less Formula Effect (LFE) data was reported at -0.100 % Point in Mar 2025. This records a decrease from the previous number of -0.060 % Point for Dec 2024. PCE: PI: saar: Less Formula Effect (LFE) data is updated quarterly, averaging -0.160 % Point from Mar 2002 (Median) to Mar 2025, with 93 observations. The data reached an all-time high of 0.550 % Point in Jun 2020 and a record low of -0.590 % Point in Sep 2005. PCE: PI: saar: Less Formula Effect (LFE) data remains active status in CEIC and is reported by Bureau of Economic Analysis. The data is categorized under Global Database’s United States – Table US.I048: PCE Price Index and CPI Reconciliation: NIPA 2023: Quarterly.

AT: CPI: Local Source Base Year: All Items data was reported at 120.267 2020=100 in 2023. This records an increase from the previous number of 111.550 2020=100 for 2022. AT: CPI: Local Source Base Year: All Items data is updated yearly, averaging 55.823 2020=100 from Dec 1958 (Median) to 2023, with 66 observations. The data reached an all-time high of 120.267 2020=100 in 2023 and a record low of 14.452 2020=100 in 1958. AT: CPI: Local Source Base Year: All Items 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 Austria – Table AT.OECD.MEI: Consumer Price Index: COICOP 1999: OECD Member: Annual. The Austrian CPI measure price changes in a fixed basket of goods and services bought in Austria for the purpose of consumption by all Austrian households, foreign visitors and residents in institutional households. The prices used in the CPI calculation are the transaction prices actually paid by consumers including taxes less any general discounts, rebates or subsidies. Method of collection: Personal visits and mail questionnaire, paper collection forms, centrally collected prices by mail and telephone. Treatment of rentals for housing: Apartments rent abroad are included. Treatment of Owner-Occupied Housing: Regular payments for Owner occupied flats are included (payment approach), initial payments are excluded. House construction goods and services and major repairs are included. The purchase of a house and other real estate (land prices, housing agents) are not included. Treatment of missing prices: Prices are adjusted by the rate of change of the other price observations of the same product. If product offers are not available any more a new product offer is selected as replacement immediately after three months at latest. Treatment of quality changes: Quantity adjustment for food, Expert Judgment adjustment method e.g. for clothing, Option pricing method for durables and cars, Hedonic method for notebooks. Introduction of new products: New products are selected with respect to demand (turnover) and availability and they are introduced every December. New models and varieties are implemented by replacement as soon as they become relevant. Treatment of seasonal items: When a product offer disappears for seasonal non-availability, it is not replaced but its price relative is excluded from calculation. The index is then calculated with the rest of available prices. If the seasonal variety becomes available again the respective price relative is included in the calculation again (after potential quality adjustment). For a minority of products which would not at all be available in whole Austria the last prices are carried forward (e.g. schools and theatres in summer or public baths in winter).; Index series starts in January 1958

Comoros KM: Consumer Price Index (CPI): % Change data was reported at -4.295 % in 2013. This records a decrease from the previous number of 6.315 % for 2012. Comoros KM: Consumer Price Index (CPI): % Change data is updated yearly, averaging 3.533 % from Dec 2001 (Median) to 2013, with 13 observations. The data reached an all-time high of 6.315 % in 2012 and a record low of -4.295 % in 2013. Comoros KM: Consumer Price Index (CPI): % Change data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Comoros – Table KM.World Bank.WDI: Inflation. Inflation as measured by the consumer price index reflects the annual percentage change in the cost to the average consumer of acquiring a basket of goods and services that may be fixed or changed at specified intervals, such as yearly. The Laspeyres formula is generally used.;International Monetary Fund, International Financial Statistics and data files.;Median;

Palau PW: Inflation: Consumer Price Index data was reported at 1.280 % in 2017. This records an increase from the previous number of -1.042 % for 2016. Palau PW: Inflation: Consumer Price Index data is updated yearly, averaging 3.297 % from Dec 2002 (Median) to 2017, with 16 observations. The data reached an all-time high of 11.966 % in 2008 and a record low of -1.301 % in 2002. Palau PW: Inflation: Consumer Price Index data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Palau – Table PW.World Bank.WDI: Inflation. Inflation as measured by the consumer price index reflects the annual percentage change in the cost to the average consumer of acquiring a basket of goods and services that may be fixed or changed at specified intervals, such as yearly. The Laspeyres formula is generally used.; ; International Monetary Fund, International Financial Statistics and data files.; Median;

Graph and download economic data for Consumer Price Index: Services Less Housing National Definition for Portugal (CPSELR02PTM661N) from Jan 1991 to May 2018 about Portugal, CPI, services, housing, price index, indexes, and price.

Explore the latest data on Saudi Arabia's Consumer Price Index (CPI) and Inflation Rate. Access comprehensive information and analysis on economic trends in Saudi Arabia.

Saudi Arabia CPI, Saudi Arabia Inflation Rate

Saudi ArabiaFollow data.kapsarc.org for timely data to advance energy economics research..Note:- Data found here from January 2018 till January 2020 was 2013 base year CPI calculation- Data found here from October 2009 till December 2017 was 2007 base year CPI calculation.You can find Saudi Arabia Inflation Rate with the latest 2018 base year on KAPSARC Dataportal.

Yemen YE: Consumer Price Index (CPI): % Change data was reported at 8.105 % in 2014. This records a decrease from the previous number of 10.968 % for 2013. Yemen YE: Consumer Price Index (CPI): % Change data is updated yearly, averaging 11.493 % from Dec 1991 (Median) to 2014, with 24 observations. The data reached an all-time high of 55.081 % in 1995 and a record low of 2.177 % in 1997. Yemen YE: Consumer Price Index (CPI): % Change data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Yemen – Table YE.World Bank.WDI: Inflation. Inflation as measured by the consumer price index reflects the annual percentage change in the cost to the average consumer of acquiring a basket of goods and services that may be fixed or changed at specified intervals, such as yearly. The Laspeyres formula is generally used.; ; International Monetary Fund, International Financial Statistics and data files.; Median;

Sao Tome and Principe ST: Consumer Price Index (CPI): % Change data was reported at 5.431 % in 2016. This records an increase from the previous number of 5.246 % for 2015. Sao Tome and Principe ST: Consumer Price Index (CPI): % Change data is updated yearly, averaging 13.006 % from Dec 1997 (Median) to 2016, with 20 observations. The data reached an all-time high of 50.493 % in 1998 and a record low of 5.246 % in 2015. Sao Tome and Principe ST: Consumer Price Index (CPI): % Change data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Sao Tome and Principe – Table ST.World Bank: Inflation. Inflation as measured by the consumer price index reflects the annual percentage change in the cost to the average consumer of acquiring a basket of goods and services that may be fixed or changed at specified intervals, such as yearly. The Laspeyres formula is generally used.; ; International Monetary Fund, International Financial Statistics and data files.; Median;

Montenegro ME: Consumer Price Index (CPI): % Change data was reported at 2.380 % in 2017. This records an increase from the previous number of -0.271 % for 2016. Montenegro ME: Consumer Price Index (CPI): % Change data is updated yearly, averaging 2.652 % from Dec 2006 (Median) to 2017, with 12 observations. The data reached an all-time high of 8.759 % in 2008 and a record low of -0.711 % in 2014. Montenegro ME: Consumer Price Index (CPI): % Change data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Montenegro – Table ME.World Bank.WDI: Inflation. Inflation as measured by the consumer price index reflects the annual percentage change in the cost to the average consumer of acquiring a basket of goods and services that may be fixed or changed at specified intervals, such as yearly. The Laspeyres formula is generally used.; ; International Monetary Fund, International Financial Statistics and data files.; Median;

Guinea GN: Consumer Price Index (CPI): % Change data was reported at 8.915 % in 2017. This records an increase from the previous number of 8.173 % for 2016. Guinea GN: Consumer Price Index (CPI): % Change data is updated yearly, averaging 15.225 % from Dec 2005 (Median) to 2017, with 13 observations. The data reached an all-time high of 34.695 % in 2006 and a record low of 4.684 % in 2009. Guinea GN: Consumer Price Index (CPI): % Change data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Guinea – Table GN.World Bank.WDI: Inflation. Inflation as measured by the consumer price index reflects the annual percentage change in the cost to the average consumer of acquiring a basket of goods and services that may be fixed or changed at specified intervals, such as yearly. The Laspeyres formula is generally used.; ; International Monetary Fund, International Financial Statistics and data files.; Median;

United States PCE: PI: Less Formula Effect: Housing data was reported at 0.000 Point in May 2013. This stayed constant from the previous number of 0.000 Point for Apr 2013. United States PCE: PI: Less Formula Effect: Housing data is updated monthly, averaging 0.000 Point from Jan 2002 (Median) to May 2013, with 137 observations. United States PCE: PI: Less Formula Effect: Housing data remains active status in CEIC and is reported by Bureau of Economic Analysis. The data is categorized under Global Database’s United States – Table US.A273: NIPA 2009: PCE Price Index and CPI Reconciliation.

United States PCE: PI: Qtr: Less Formula Effect data was reported at -0.050 Point in Mar 2013. This records an increase from the previous number of -0.160 Point for Dec 2012. United States PCE: PI: Qtr: Less Formula Effect data is updated quarterly, averaging -0.160 Point from Mar 2002 (Median) to Mar 2013, with 45 observations. The data reached an all-time high of 0.710 Point in Dec 2008 and a record low of -0.450 Point in Sep 2005. United States PCE: PI: Qtr: Less Formula Effect data remains active status in CEIC and is reported by Bureau of Economic Analysis. The data is categorized under Global Database’s USA – Table US.A139: NIPA 2009: Personal Consumption Expenditure Price Index and CPI Reconciliation: Quarterly.

Tajikistan TJ: Consumer Price Index (CPI): % Change data was reported at 6.005 % in 2016. This records an increase from the previous number of 5.715 % for 2015. Tajikistan TJ: Consumer Price Index (CPI): % Change data is updated yearly, averaging 7.117 % from Dec 2001 (Median) to 2016, with 16 observations. The data reached an all-time high of 38.592 % in 2001 and a record low of 5.010 % in 2013. Tajikistan TJ: Consumer Price Index (CPI): % Change data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Tajikistan – Table TJ.World Bank.WDI: Inflation. Inflation as measured by the consumer price index reflects the annual percentage change in the cost to the average consumer of acquiring a basket of goods and services that may be fixed or changed at specified intervals, such as yearly. The Laspeyres formula is generally used.; ; International Monetary Fund, International Financial Statistics and data files.; Median;

United States PCE: PI: Less Formula Effect (LFE) data was reported at -0.020 Point in May 2018. This records a decrease from the previous number of -0.010 Point for Apr 2018. United States PCE: PI: Less Formula Effect (LFE) data is updated monthly, averaging -0.010 Point from Jan 2002 (Median) to May 2018, with 197 observations. The data reached an all-time high of 0.080 Point in Nov 2008 and a record low of -0.120 Point in Sep 2005. United States PCE: PI: Less Formula Effect (LFE) data remains active status in CEIC and is reported by Bureau of Economic Analysis. The data is categorized under Global Database’s USA – Table US.A060: NIPA 2013: Personal Consumption Expenditure Price Index and CPI Reconciliation: Monthly.

Graph and download economic data for Consumer Price Index: Services Less Housing National Definition for Portugal (CPSELR02PTQ661N) from Q1 1991 to Q1 2018 about Portugal, CPI, services, housing, price index, indexes, and price.