Consumer Price Index CPI in the United States increased to 323.05 points in July from 322.56 points in June 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.

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

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.

Case Shiller Home Price Index in the United States increased to 342.97 points in May from 341.55 points in April 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.

The residential statistics were compiled from information in caveats lodged at the option stage with the Singapore Land Registry, supplemented with Stamp Duty data from the Inland Revenue Authority of Singapore, as well as data provided by developers for new sales. A caveat is normally lodged by a purchaser to protect his/her interest of a property shortly after the option to purchase is exercised. The prices in 2009-Q1 are used as the base reference price of the index. The indices are compiled based on a Stratified Hedonic Regression method. The value of properties transacted in the past 5 quarters are used as weights. The weights are revised every 3 years. The latest revision was in 2015-Q1.

The commercial statistics were compiled from information in caveats lodged at the option stage with the Singapore Land Registry. A caveat is normally lodged by a purchaser to protect his/her interest of a property shortly after the option to purchase is exercised. The prices in 1998-Q4 are used as the base reference price of the index (i.e. the index for 1998-Q4 assumes a value of 100).The indices are compiled based on a Moving Average weight method, whereby the value of properties transacted in the past 12 quarters are used as weights.

Housing Index in the United States decreased to 434.40 points in May from 435.10 points in April of 2025. This dataset provides the latest reported value for - United States House Price Index MoM Change - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The Wage Price Index measures changes in the price of labour services resulting from market pressures, and is unaffected by changes in the quality or quantity of work performed. It is unaffected by changes in the composition of the labour force, hours worked, or changes in characteristics of employees (e.g. work performance). Information about the wage price indexes has been released for each quarter since September 1997. Individual indexes are published for various combinations of state and territory, public and private sectors, and broad industry groups.

Time series data for the statistic Consumer Price Index, All items, Percentage change, Previous period and country Dominica. Indicator Definition:Consumer Price Index, All items, Percentage change, Previous periodThe indicator "Consumer Price Index, All items, Percentage change, Previous period" stands at 0.0082 as of 1/31/2025. Regarding the One-Year-Change of the series, the current value constitutes an increase of 0.185 compared to the value the year prior.The Serie's long term average value is 0.143. It's latest available value, on 1/31/2025, is -0.135 lower, compared to it's long term average value.The Serie's change from it's minimum value, on 12/31/2017, to it's latest available value, on 1/31/2025, is +4.04 .The Serie's change from it's maximum value, on 7/31/2003, to it's latest available value, on 1/31/2025, is -2.56 .

Analysis of ‘Home Price Index’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/PythonforSASUsers/hpindex on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Context

The Federal Housing Finance Agency House Price Index (HPI) is a broad measure of the movement of single-family house prices. The HPI is a weighted, repeat-sales index, meaning that it measures average price changes in repeat sales or refinancings on the same properties. The technical methodology for devising the index, collection, and publishing the data is at: http://www.fhfa.gov/PolicyProgramsResearch/Research/PaperDocuments/1996-03_HPI_TechDescription_N508.pdf

Content

Contains monthly and quarterly time series from January 1991 to August 2016 for the U.S., state, and MSA categories. Analysis variables are the aggregate non-seasonally adjusted value and seasonally adjusted index values. The index value is 100 beginning January 1991.

Acknowledgements

This data is found on Data.gov

Inspiration

Can this data be combined with the corresponding census growth projections either at the state or MSA level to forecast 24 months out the highest and lowest home index values?

--- Original source retains full ownership of the source dataset ---

The available data collection compiles the most important price indices of living costs published in official price statistics. The price indices for the standard of living are to show, in which measure the haouseholds’ standard of living increased or decreased in price due to price alteration, but unaffected by changes by consumers’ behaviour. Therefore, the consumer price indices are to measure the pure price development, isolated from changes in quantity or quality. Basis of the index is the supposition, that the structure of private households’ consumer expenditures doesn’t have changed since the basis-year (Laspeyres-Index). The consumer price index covers groups of goods, which are bought and/or used by the private households. The private households’ expenditure structure is the basis of this price index, therefore the index is to be regarded as a “purchase price index” for private ultimate consumer. Aim of the consumer price statistics is – as it is the aim of the whole official price statistics – the registration of price changes. Therefore their most important results are price indices to a certain base year and not average prices in absolute height. Furthermore, living-cost price indices informs about the percental increas or decrease of the goods’ and achievments’ prices (in relation to a base year). Topics List of data-tables in the search- and downloadsystem HISTAT: A. Living-cost price index of all private households and living-cost price index by household-types (1948-2001). B. Living-cost price index by consumption-groups and main groups; structure by goods, achievements and use of dwellings; structuring by COICOP; housing rents, motorist-price index (1948-2001); C. Consumer prices since 1881; Cost of living since 1924; Price index for nutrition (1881-1913); Realm index figures for living-cost: blue-colour-worker-households with 5 persons by consumption groups (1924-1944); D. Monthly values: Living-cost-price index of all private households (1962-2001); Living-cost-price index of a 4-persons-household with middle income (1950-2001), base years: 1913/14, 1938 = 100 (1948-1994); E. Living-cost price index: international tables (1960-2001). Die vorliegende Datensammlung bündelt die wichtigsten Preisindizes für die Lebenshaltung aus der amtlichen Preisstatistik. Die Preisindizes für die Lebenshaltung sollen zeigen, in welchem Maße sich die Lebenshaltung der Haushalte infolge von Preisänderungen, aber unbeeinflusst von Änderungen im Konsumverhalten, verteuert oder verbilligt hat. Die Preisindizes für die Lebenshaltung sollen damit die reine Preisentwicklung, isoliert von Mengen- oder Qualitätsänderungen, messen. Dem Index liegt die Annahme zugrunde, dass sich die Struktur der Verbrauchsausgaben der privaten Haushalte seit dem Basisjahr nicht verändert hat (Laspeyres-Index). Der Preisindex für die Lebenshaltung umfasst Gütergruppen, die von den privaten Haushalten gekauft bzw. verbraucht werden. Ihm liegt die Ausgabenstruktur der privaten Haushalte zugrunde, er ist daher als ein „Einkaufspreisindex“ für den privaten Letztverbraucher anzusehen. Die Statistik der Verbraucherpreise ist – wie die gesamte amtliche Preisstatistik – in erster Linie auf den Nachweis von Preisänderungen abgestellt. Deshalb sind ihre wichtigsten Ergebnisse Preisindizes zu einem bestimmten Basisjahr und nicht Durchschnittspreise in absoluter Höhe. Preisindizes für die Lebenshaltung geben darüber Auskunft, um wie viel Prozent sich die Preise für die Waren und Leistungen der Lebenshaltung erhöht oder verringert haben (gegenüber einem Basisjahr). Themen: Verzeichnis der Daten-Tabellen im Recherche- und Downloadsystem HISTAT: A. Preisindex für die Lebenshaltung aller privaten Haushalte und Preisindex für die Lebenshaltung gegliedert nach Haushaltstypen (1948-2001); B. Preisindex für die Lebenshaltung nach Bedarfs- und Hauptgruppen; Gliederung nach Waren, Leistungen und Wohnungsnutzung; Gliederung nach der COICOP; Wohnungsmieten; Kraftfahrer – Preisindex (1948 – 2001); C. Verbraucherpreise seit 1881; Lebenshaltungskosten seit 1924; Preisindex für Ernährung (1881-1913); Reichsindexziffern für die Lebenshaltungskosten: 5-Personen-Arbeiterhaushalt nach Bedarfsgruppen (1924-1944); D. Monatswerte: Preisindex für die Lebenshaltung aller privaten Haushalte (1962-2001); Preisindex für die Lebenshaltung eines 4-Personen-Haushalts mit mittlerem Einkommen (1950-2001), Basisjahre: 1913/14, 1938 = 100 (1948-1994); E. Preisindex für die Lebenshaltung: Internationale Tabellen (1960-2001). Sources: 1881 – 1913: Average of 10 indexvalues of different publications; nutrition only. Since 1914: Published data of official price-statistics (Statistical Office of the German Empire; Federal Statistical Office of FRG). Quellen: 1881 – 1913: Durchschnitt aus 10 Indexziffern verschiedener Autoren; nur Ernährung. Ab 1914: Veröffentlichte Daten der amtlichen Preisstatistik (Statistisches Reichsamt; Statistisches Bundesamt Wiesbaden).

Saudi Arabia SA: Import Unit Value Index data was reported at 144.217 2000=100 in 2016. This records a decrease from the previous number of 144.431 2000=100 for 2015. Saudi Arabia SA: Import Unit Value Index data is updated yearly, averaging 144.217 2000=100 from Dec 2000 (Median) to 2016, with 17 observations. The data reached an all-time high of 162.099 2000=100 in 2014 and a record low of 98.867 2000=100 in 2002. Saudi Arabia SA: Import Unit Value Index data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Saudi Arabia – Table SA.World Bank.WDI: Trade Index. Import unit value indices come from UNCTAD's trade database. Unit value indices are based on data reported by countries that demonstrate consistency under UNCTAD quality controls, supplemented by UNCTAD’s estimates using the previous year’s trade values at the Standard International Trade Classification three-digit level as weights. To improve data coverage, especially for the latest periods, UNCTAD constructs a set of average prices indexes at the three-digit product classification of the Standard International Trade Classification revision 3 using UNCTAD’s Commodity Price Statistics, interna¬tional and national sources, and UNCTAD secretariat estimates.; ; United Nations Conference on Trade and Development, Handbook of Statistics and data files. (http://unctadstat.unctad.org); ;

Time series data for the statistic Consumer Price Index, All items, Percentage change, Previous period and country Kuwait. Indicator Definition:Consumer Price Index, All items, Percentage change, Previous periodThe indicator "Consumer Price Index, All items, Percentage change, Previous period" stands at 0.293 as of 6/30/2025. Regarding the One-Year-Change of the series, the current value constitutes an increase of 0.0683 compared to the value the year prior.The Serie's long term average value is 0.237. It's latest available value, on 6/30/2025, is 0.0559 higher, compared to it's long term average value.The Serie's change from it's minimum value, on 3/31/2018, to it's latest available value, on 6/30/2025, is +0.6477 .The Serie's change from it's maximum value, on 9/30/2021, to it's latest available value, on 6/30/2025, is -1.03 .

Value of Import Value of Export Deflator of Import Deflator of Export Import Price Index Export Price Index

Albania Import Unit Value Index data was reported at 159.500 2015=100 in 2023. This records an increase from the previous number of 113.500 2015=100 for 2022. Albania Import Unit Value Index data is updated yearly, averaging 102.900 2015=100 from Dec 2005 (Median) to 2023, with 19 observations. The data reached an all-time high of 159.500 2015=100 in 2023 and a record low of 83.900 2015=100 in 2005. Albania Import Unit Value Index data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Albania – Table AL.World Bank.WDI: Trade Index. Import unit value indices come from UNCTAD's trade database. Unit value indices are based on data reported by countries that demonstrate consistency under UNCTAD quality controls, supplemented by UNCTAD’s estimates using the previous year’s trade values at the Standard International Trade Classification three-digit level as weights. To improve data coverage, especially for the latest periods, UNCTAD constructs a set of average prices indexes at the three-digit product classification of the Standard International Trade Classification revision 3 using UNCTAD’s Commodity Price Statistics, interna¬tional and national sources, and UNCTAD secretariat estimates.;United Nations Conference on Trade and Development, Handbook of Statistics and data files. (http://unctadstat.unctad.org);;

Vietnam VN: Export Unit Value Index data was reported at 188.908 2000=100 in 2016. This records a decrease from the previous number of 193.493 2000=100 for 2015. Vietnam VN: Export Unit Value Index data is updated yearly, averaging 166.395 2000=100 from Dec 2000 (Median) to 2016, with 17 observations. The data reached an all-time high of 220.302 2000=100 in 2011 and a record low of 93.705 2000=100 in 2001. Vietnam VN: Export Unit Value Index data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Vietnam – Table VN.World Bank.WDI: Trade Index. Export unit value indices come from UNCTAD's trade database. Unit value indices are based on data reported by countries that demonstrate consistency under UNCTAD quality controls, supplemented by UNCTAD’s estimates using the previous year’s trade values at the Standard International Trade Classification three-digit level as weights. To improve data coverage, especially for the latest periods, UNCTAD constructs a set of average prices indexes at the three-digit product classification of the Standard International Trade Classification revision 3 using UNCTAD’s Commodity Price Statistics, interna¬tional and national sources, and UNCTAD secretariat estimates.; ; United Nations Conference on Trade and Development, Handbook of Statistics and data files. (http://unctadstat.unctad.org); ;

This table shows the consumer price index for all households (CPI), split up into an index for frequent "out-of-pocket" purchases (FROOPP) and less frequent or "non-out-of-pocket" purchased items (non-FROOPP). Frequent purchased items are purchases that are typically done at least monthly. Out-of-pocket purchases are those that are considered to be typically paid for by the consumer directly and actively. This table also includes the monthly and yearly price developments.

The FROOPP and non-FROOPP are special extracts of the CPI. The corresponding CPI weights and prices are used to calculate both indices. The segmentation used is derived from the FROOPP-classification of Eurostat.

Data available from: January 2006 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 as of 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.

When will new figures be published? Not applicable.

Moldova MD: Import Unit Value Index data was reported at 129.186 2000=100 in 2016. This records a decrease from the previous number of 138.166 2000=100 for 2015. Moldova MD: Import Unit Value Index data is updated yearly, averaging 138.166 2000=100 from Dec 2000 (Median) to 2016, with 17 observations. The data reached an all-time high of 176.567 2000=100 in 2011 and a record low of 100.000 2000=100 in 2002. Moldova MD: Import Unit Value Index data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Moldova – Table MD.World Bank.WDI: Trade Index. Import unit value indices come from UNCTAD's trade database. Unit value indices are based on data reported by countries that demonstrate consistency under UNCTAD quality controls, supplemented by UNCTAD’s estimates using the previous year’s trade values at the Standard International Trade Classification three-digit level as weights. To improve data coverage, especially for the latest periods, UNCTAD constructs a set of average prices indexes at the three-digit product classification of the Standard International Trade Classification revision 3 using UNCTAD’s Commodity Price Statistics, interna¬tional and national sources, and UNCTAD secretariat estimates.; ; United Nations Conference on Trade and Development, Handbook of Statistics and data files. (http://unctadstat.unctad.org); ;

Consumer Price Index CPI in Germany increased to 122.20 points in July from 121.80 points in June of 2025. This dataset provides the latest reported value for - Germany Consumer Price Index (CPI) - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Consumer Price Index CPI in Israel increased to 103.50 points in July from 103.10 points in June of 2025. This dataset provides the latest reported value for - Israel Consumer Price Index (CPI) - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.