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

Index figures on production prices of dwellings and other buildings reflect the relation between the output value and the output volume and can be used to convert the value of construction output from current prices to fixed prices. The output price index is derived from the series "New dwellings; output indices 2000=100". From the 2nd quarter 2009 on, the figures of the series 2005 = 100 are used and linked to the series 2000 = 100. Statistics Netherlands publishes data on the value of construction output. The volume of construction output, however, cannot be deduced from the value, which is subject to price changes. The price index on the building costs of new dwellings eliminates the effect of price changes. The price index on construction output is calculated by distributing the value of the output (current prices) over the quarters essential to the price setting of the building project. Subsequently, the quarterly output is calculated in fixed prices by using the price index on the building costs of new dwellings. The index figure of the output price is the sum of the current prices divided by the sum of the fixed prices (*100). Possibilities for selection: - Total construction - Total construction of new dwellings/buildings - New dwellings - New buildings in the private sector - New buildings in the non-commercial sector - Total other buildings - Other dwellings - Other buildings in the private sector - Other buildings in the non-commercial sector Data available from 1st quarter 2000 till 4th quarter 2016 Frequency: discontinued Status of the figures: The figures of 2016 are provisional. Since this table has been discontinued, the data will not become definitive. Changes as of January 29 2018 None, this table is discontinued. When will new figures become available? This table is succeeded by Production on buildings; price index 2015 = 100. See paragraph 3. Linking recommendation If you want to compile long-term series with linked price indices on production of buildings, you can link the figures on price level 1995 with the figures on price level 2000. For that, the percentage change from the 2nd quarter 2005 with the 1st quarter 2005 must be calculated, as the price index for the 1st quarter 2005 is the last figure published on price level 1995. This change must then be adjusted to the figures for the 1st quarter 2005 of the series 1995. The 2nd quarter index of the linked series is calculated by calculating the difference between the 1st quarter 2005 and the 2nd quarter 2005 according to the series on price level 2000 and multiplying this by the index for the 1st quarter 2005 according to the series on price level 1995. In the example: (119/120) x 148=147 (rounded). For the 3rd quarter 2005 the index is calculated analogously, where because of rounding problems the first quarter figures must be used for the link.

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

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

GDP: Intermediate Inputs (II): Quantity Index (QI): saar data was reported at 128.550 2009=100 in Mar 2018. This records an increase from the previous number of 127.303 2009=100 for Dec 2017. GDP: Intermediate Inputs (II): Quantity Index (QI): saar data is updated quarterly, averaging 112.841 2009=100 from Mar 2005 (Median) to Mar 2018, with 53 observations. The data reached an all-time high of 128.550 2009=100 in Mar 2018 and a record low of 99.244 2009=100 in Jun 2009. GDP: Intermediate Inputs (II): Quantity Index (QI): saar 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.A030: NIPA 2013: GDP by Industry: Intermediate Inputs: Seasonally Adjusted at Annual Rates: Quantity Index.

As of 2022, Israel had the highest price level index among listed countries, amounting to 138, with 100 being the average of OECD countries. Switzerland and Iceland followed on the places behind. On the other hand, Turkey and India had the lowest price levels compared to the OECD average. This price index shows differences in price levels in different countries. Another very popular index indicating the value of money is the Big Mac index, showing how much a Big Mac costs in different countries. This list was also topped by Switzerland in 2023.

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 GDP: Value Added (VA): Quantity Index (QI): saar data was reported at 120.481 2009=100 in Mar 2018. This records an increase from the previous number of 119.889 2009=100 for Dec 2017. United States GDP: Value Added (VA): Quantity Index (QI): saar data is updated quarterly, averaging 104.178 2009=100 from Mar 2005 (Median) to Mar 2018, with 53 observations. The data reached an all-time high of 120.481 2009=100 in Mar 2018 and a record low of 97.783 2009=100 in Mar 2005. United States GDP: Value Added (VA): Quantity Index (QI): saar 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.A024: NIPA 2013: GDP by Industry: Value Added: Seasonally Adjusted at Annual Rates: Quantity Index.

United States GDP: Gross Output (GO): Quantity Index (QI): saar data was reported at 122.764 2009=100 in Mar 2018. This records an increase from the previous number of 121.935 2009=100 for Dec 2017. United States GDP: Gross Output (GO): Quantity Index (QI): saar data is updated quarterly, averaging 108.007 2009=100 from Mar 2005 (Median) to Mar 2018, with 53 observations. The data reached an all-time high of 122.764 2009=100 in Mar 2018 and a record low of 99.453 2009=100 in Jun 2009. United States GDP: Gross Output (GO): Quantity Index (QI): saar 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.A027: NIPA 2013: GDP by Industry: Gross Output: Seasonally Adjusted at Annual Rates: Quantity Index.

Consumer Price Index CPI in the United States increased to 321.47 points in May from 320.80 points in April of 2025. This dataset provides the latest reported value for - United States Consumer Price Index (CPI) - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

GDP: VA: QI: saar: Pvt: Retail Trade data was reported at 126.954 2009=100 in Mar 2018. This records an increase from the previous number of 126.063 2009=100 for Dec 2017. GDP: VA: QI: saar: Pvt: Retail Trade data is updated quarterly, averaging 107.961 2009=100 from Mar 2005 (Median) to Mar 2018, with 53 observations. The data reached an all-time high of 126.954 2009=100 in Mar 2018 and a record low of 99.434 2009=100 in Sep 2009. GDP: VA: QI: saar: Pvt: Retail Trade 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.A024: NIPA 2013: GDP by Industry: Value Added: Seasonally Adjusted at Annual Rates: Quantity Index.

Consumer Price Index (CPI) in India, May, 2025 The most recent value is 193 index points as of May 2025, an increase compared to the previous value of 192.6 index points. Historically, the average for India from January 2011 to May 2025 is 140.6514 index points. The minimum of 88.4 index points was recorded in February 2011, while the maximum of 196.8 index points was reached in October 2024. | TheGlobalEconomy.com

The Consumer price index (CPI) all households, calculated by Statistics Netherlands, measures the average price changes of goods and services purchased by households. The index is an important criterion for inflation, frequently used by trade and industry, employers' organisations, trade unions and government. The index is for instance, used to make adjustments to wages, tax tablesand index-linked rent increases, annuities, etc.

Data available from: January 1996 till December 2015

Status of the figures: The figures in this table are final.

Changes as of 18 May 2016: None, this table is stopped.

Changes from 7 January 2016: New figures added.

Changes from 10 December 2015: On 1 October 2015, the points system for the pricing of rental homes was adjusted by the Dutch national government. As a direct consequence, rental prices of a limited number of dwellings were reduced, which had a downward effect on the average rental price. The effect of this decrease on the rental price indices and imputed rent value could not be determined in time because housing associations announced the impact of rent adjustments only in November. For this reason, the figures of the groups 04100 ‘Actual rentals for housing’ and 04200 ‘Imputed rent value’ over October 2015 have now been adjusted.

The figures of the groups 061100 ‘Pharmaceutical products’, 061200 ‘Other medical products, equipment’, 072200 ‘Fuels and lubricants’ and 083000 ‘Telephone and internet services’ over the months June through September 2015 have been corrected. This has no impact on the headline indices.

The derived CPI decreased by 0.01 index point over August 2015.

When will new figures be published? Not applicable. This table is succeeded by Consumer prices; price index 2015=100. See paragraph 3.

In 2024, Turkey had the highest inflation-adjusted house price index out of the ** European countries under observation, making it the country where house prices have increased the most since 2010. In Turkey, the house price index exceeded *** index points in the fourth quarter of 2024, showing an increase in real terms of *** percent since 2010, the baseline year for the index. Iceland and Estonia completed the top three, with an index value of *** and *** index points. In the past year, however, many European countries saw house prices decline in real terms. Where can I find other metrics on different housing markets in Europe? To assess the valuation in different housing markets, one can compare the house-price-to-income ratios of different countries worldwide. These ratios are calculated by dividing nominal house prices by nominal disposable income per head. There are also ratios that look at how residential property prices relate to domestic rents, such as the house-price-to-rent ratio for the United Kingdom. Unfortunately, these numbers are not available in a European overview. An overview of the price per square meter of an apartment in the EU-28 countries is available, however. One region, different markets An important trait of the European housing market is that there is not one market, but multiple. Property policy in Europe lies with the domestic governments, not with the European Union. This leads to significant differences between European countries, which shows in, for example, the homeownership rate (the share of owner-occupied dwellings of all homes). These differences also lead to another problem: the availability of data. Non-Europeans might be surprised to see that house price statistics vary in depth, as every country has their own methodology and no European body exists that tracks this data for the whole continent.

GDP: II: QI: saar: Pvt: Transportation and Warehousing data was reported at 124.268 2009=100 in Mar 2018. This records an increase from the previous number of 122.285 2009=100 for Dec 2017. GDP: II: QI: saar: Pvt: Transportation and Warehousing data is updated quarterly, averaging 115.087 2009=100 from Mar 2005 (Median) to Mar 2018, with 53 observations. The data reached an all-time high of 129.736 2009=100 in Dec 2014 and a record low of 97.037 2009=100 in Dec 2009. GDP: II: QI: saar: Pvt: Transportation and Warehousing 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.A030: NIPA 2013: GDP by Industry: Intermediate Inputs: Seasonally Adjusted at Annual Rates: Quantity Index.

From 1994 onwards The consumer price index, which takes into account price trends of all goods and services, forms the basis of another index: the health index. This health index has been calculated since January 1994 (introduced by the Royal Decree of 24 December 1993). The value of this index is determined by removing a number of products from the consumer price index product basket, in particular alcoholic beverages (bought in a shop or consumed in a bar), tobacco products and motor fuels except for LPG. What is the purpose of the health index? The health index is used for the indexation of housing rents. The health index is defined in the Law of 23 April 2015 on employment promotion (Belgian Official Journal of 27 April 2015). The smoothed health index, also called smoothed index (the average value of the health indexes of the last 4 months) is used as a basis for the indexation of retirement pensions, social security benefits and some salaries and wages. Public wages and social benefits are indexed as soon as the smoothed index reaches a given value, called the central index. The smoothed index is also called moving average. In order to perform a 2% index jump (laid down in the Law of 23 April 2015 on employment promotion), the smoothed health index has been temporarily blocked at its value of March 2015 (100.66). The smoothed health index was then reduced by 2% from April 2015. When the reduced smoothed health index (also called the reference index) had increased again by 2% or in other words when it had exceeded the value of 100.66, the index was no longer blocked. It occurred in April 2016. Since April 2016 the smoothed health index is calculated in the same manner as the reference index and therefore corresponds to the arithmetical mean of the health indexes of the last 4 months multiplied by a factor of 0.98. More information All health indices from 1994 onward can be found through our index-search. Simply enter the desired year and month to view the consumer price index and the health index on all available bases. Health index: list of excluded products (PDF, 83.29 Kb) More information on the index link to public services wages and pensions can be found on the website of the Wages Service of the FPS Finances:https://persopoint.be/fr/services/administration-des-salaires/principes-generaux-de-l-index. The table below shows the health index of the 13 most recent available months. be.STAT allows you to search from 1994 onward. Purpose and brief description The health index was introduced in January 1994 (by Royal Decree of 24 December 1993 implementing the law of 6 January 1989 on the safeguarding of the country's competitiveness) and is derived from the consumer price index. The value of the health index is obtained by excluding a number of products from the product and service basket from the consumer price index, in particular alcoholic beverages (bought in the shop or consumed in a café), tobacco products and motor fuels (with the exception of LPG). Population Belgian private households Frequency Monthly Timing of publication The results are available on the penultimate working day of the reference period Remarks Remark Confidentiality consumer price indices - Although the headings are published in the index and are therefore generally known, the exact definition of the goods and services is kept secret. This confidentiality is required to prevent attempts to manipulate the index, by resolute actions on certain goods and services. The confidentiality of the definitions guarantees the index objectiveness. Metadata Consumer price index - Health index.pdf

Case Shiller Home Price Index in the United States increased to 341.48 points in April from 338.39 points in March of 2025. This dataset provides the latest reported value for - United States S&P Case-Shiller Home Price Index - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

This is the unadjusted median house priced for residential property sales (transactions) in the area for a 12 month period with April in the middle (year-ending September). These figures have been produced by the ONS (Office for National Statistics) using the Land Registry (LR) Price Paid data on residential dwelling transactions.

The LR Price Paid data are comprehensive in that they capture changes of ownership for individual residential properties which have sold for full market value and covers both cash sales and those involving a mortgage.

The median is the value determined by putting all the house sales for a given year, area and type in order of price and then selecting the price of the house sale which falls in the middle. The median is less susceptible to distortion by the presence of extreme values than is the mean. It is the most appropriate average to use because it best takes account of the skewed distribution of house prices.

Note that a transaction occurs when a change of freeholder or leaseholder takes place regardless of the amount of money involved and a property can transact more than once in the time period.

The LR records the actual price for which the property changed hands. This will usually be an accurate reflection of the market value for the individual property, but it is not always the case. In order to generate statistics that more accurately reflect market values, the LR has excluded records of houses that were not sold at market value from the dataset. The remaining data are considered a good reflection of market values at the time of the transaction. For full details of exclusions and more information on the methodology used to produce these statistics please see http://www.ons.gov.uk/peoplepopulationandcommunity/housing/qmis/housepricestatisticsforsmallareasqmi

The LR Price Paid data are not adjusted to reflect the mix of houses in a given area. Fluctuations in the types of house that are sold in that area can cause differences between the median transactional value of houses and the overall market value of houses. Therefore these statistics differ to the new UK House Price Index (HPI) which reports mix-adjusted average house prices and house price indices.

If, for a given year, for house type and area there were fewer than 5 sales records in the LR Price Paid data, the house price statistics are not reported. Data is Powered by LG Inform Plus and automatically checked for new data on the 3rd of each month.

In August 2024, the global producer price index (PPI)/ wholesale price index inflation (WPI), excluding the U.S., stood at 174.01. In the United States, the index value amounted to 165.3. The PPI/WPI inflation tracks changes in the level of prices received by domestic producers for their goods and services. Consumer habits and price increases As of August 2024, consumers considered rising prices and inflation to be their biggest worry. Consumers are expressing this worry in numerous ways. Globally, over 20 percent of consumers have said they would shop less and seek cheaper options in response to price increases. Moreover, nearly 70 percent of surveyed consumers globally reduced their gift giving to extended family and friends during the holiday season in 2023 to stretch their budgets further. Impact of inflation on emerging economies Notably, emerging economies have a higher WPI value than advanced economies. Between 2021 and 2022, the average inflation rate in developing and emerging economies increased from 5.9 percent to 9.8 percent, before falling slightly to 8.34 percent in 2023. The countries with the highest inflation rates in 2023 include many developing and emerging economies, such as Zimbabwe, Argentina, Turkey, and Suriname.

United States - Value Added by Industry: Information (Chain-Type Price Index) was 94.33300 Index 2009=100 in October of 2024, according to the United States Federal Reserve. Historically, United States - Value Added by Industry: Information (Chain-Type Price Index) reached a record high of 124.52700 in January of 2005 and a record low of 91.75400 in July of 2023. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Value Added by Industry: Information (Chain-Type Price Index) - last updated from the United States Federal Reserve on June of 2025.