Core consumer prices in the United States increased 3.10 percent in July of 2025 over the same month in the previous year. This dataset provides - United States Core Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Inflation Rate in Japan decreased to 3.10 percent in July from 3.30 percent in June of 2025. This dataset provides the latest reported value for - Japan Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Graph and download economic data for Inflation, consumer prices for the United States (FPCPITOTLZGUSA) from 1960 to 2024 about consumer, CPI, inflation, price index, indexes, price, and USA.

Inflation Rate in Russia decreased to 8.80 percent in July from 9.40 percent in June of 2025. This dataset provides - Russia Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Inflation Rate in Turkey decreased to 32.95 percent in August from 33.52 percent in July of 2025. This dataset provides the latest reported value for - Turkey Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Inflation Rate in Germany increased to 2.20 percent in August from 2 percent in July of 2025. This dataset provides the latest reported value for - Germany Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

United States Breakeven Inflation: 5-Year data was reported at 2.410 % in 15 May 2025. This records a decrease from the previous number of 2.440 % for 14 May 2025. United States Breakeven Inflation: 5-Year data is updated daily, averaging 1.900 % from Jan 2003 (Median) to 15 May 2025, with 5597 observations. The data reached an all-time high of 3.590 % in 25 Mar 2022 and a record low of 0.140 % in 19 Mar 2020. United States Breakeven Inflation: 5-Year data remains active status in CEIC and is reported by Federal Reserve Bank of St. Louis. The data is categorized under Global Database’s United States – Table US.I: Breakeven Inflation Rate. [COVID-19-IMPACT]

Nigeria’s inflation has been higher than the average for African and Sub-Saharan countries for years now, and even exceeded 16 percent in 2017 – and a real, significant decrease is nowhere in sight. The bigger problem is its unsteadiness, however: An inflation rate that is bouncing all over the place, like this one, is usually a sign of a struggling economy, causing prices to fluctuate, and unemployment and poverty to increase. Nigeria’s economy - a so-called “mixed economy”, which means the market economy is at least in part regulated by the state – is not entirely in bad shape, though. More than half of its GDP is generated by the services sector, namely telecommunications and finances, and the country derives a significant share of its state revenues from oil.

Because it got high

To simplify: When the inflation rate rises, so do prices, and consequently banks raise their interest rates as well to cope and maintain their profit margin. Higher interest rates often cause unemployment to rise. In certain scenarios, rising prices can also mean more panicky spending and consumption among end users, causing debt and poverty. The extreme version of this is called hyperinflation: A rapid increase of prices that is out of control and leads to bankruptcies en masse, devaluation of money and subsequently a currency reform, among other things. But does that mean that low inflation is better? Maybe, but only to a certain degree; the ECB, for example, aspires to maintain an inflation rate of about two percent so as to keep the economy stable. As soon as we reach deflation territory, however, things are starting to look grim again. The best course is a stable inflation rate, to avoid uncertainty and rash actions.

Nigeria today

Nigeria is one of the countries with the largest populations worldwide and also the largest economy in Africa, with its economy growing rapidly after a slump in the aforementioned year 2017. It is slated to be one of the countries with the highest economic growth over the next few decades. Demographic key indicators, like infant mortality rate, fertility rate, and the median age of the population, all point towards a bright future. Additionally, the country seems to make big leaps forward in manufacturing and technological developments, and boasts huge natural resources, including natural gas. All in all, Nigeria and its inflation seem to be on the upswing – or on the path to stabilization, as it were.

Einführung des Euro in Litauen. Themen: Kontakt mit und Nutzung von Euro-Banknoten und -Münzen; Nutzung im eigenen Land, im Ausland oder beides; Wissenstest über den Euro: identisches Aussehen von Euro-Banknoten und -Münzen in jedem Land, Anzahl der bereits den Euro nutzenden Länder, Wahlmöglichkeit des eigenen Landes zur Einführung des Euro, Jahr der Einführung im eigenen Land; Selbsteinschätzung der Informiertheit über den Euro; bevorzugter Zeitpunkt für Informationen zur Euro-Einführung im eigenen Land; Vertrauen in Informationen zur Euro-Einführung von: nationaler bzw. regionaler Regierung oder Behörden, Steuerbehörden, nationaler Zentralbank, europäischen Institutionen, Geschäftsbanken, Journalisten, Gewerkschaften oder Berufsorganisationen, Verbraucherschutzorganisationen; bevorzugte Orte für Informationen über den Euro und die Umstellung; wichtigste Inhalte einer Informationskampagne zum Euro; Bedeutung einzelner Aktionen einer Informationskampagne; Einschätzung der Folgen der Einführung in den bereits den Euro nutzenden Ländern als positiv; Einschätzung der Folgen der Einführung für das eigene Land und für den Befragten persönlich; Zustimmung zur Einführung des Euro im eigenen Land; bevorzugter Zeitpunkt für die Einführung des Euro; erwartete Auswirkungen der Einführung auf die Preise im eigenen Land; erwartete Folgen der Einführung: Erleichterung von Preisvergleichen mit anderen Ländern, Erleichterung von Einkäufen in anderen Ländern, Kostensenkung beim Geldumtausch durch Aufheben von Gebühren, bequemeres Reisen in anderen Ländern, Schutz des eigenen Landes vor den Folgen internationaler Krisen; Vorzüge durch die Einführung des Euro für das eigene Land: niedrigere Zinssätze, solidere öffentliche Finanzen, Verbesserung von Wachstum und Beschäftigung, niedrige Inflationsraten, Stärkung der europäischen Identifikation; Einstellung zu folgenden Aussagen zur Euro-Einführung: Überzeugung, sich persönlich an die neue Währung zu gewöhnen, Besorgnis über missbräuchliche Preisbildung, Verlust der Kontrolle über die nationale Wirtschaftspolitik, Verlust der nationalen Identität. Demographie: Alter; Geschlecht; Staatsangehörigkeit; Alter bei Beendigung der Ausbildung; Beruf; berufliche Stellung; Region; Urbanisierungsgrad; Besitz eines Mobiltelefons; Festnetztelefon im Haushalt; Haushaltszusammensetzung und Haushaltsgröße. Zusätzlich verkodet wurde: Interviewmodus (Mobiltelefon oder Festnetz); Gewichtungsfaktor. Introduction of the euro in Lithuania. Topics: contact with and use of euro banknotes or coins; use of euro banknotes or coins in the own country or abroad; knowledge test on the euro: equal design of euro banknotes and coins in every country, number of countries that already introduced the euro, possibility of the own country to choose whether to introduce the euro or not, year of introduction of the euro in the own country; self-rated knowledge on the euro; preferred time of information about the introduction of the euro in the own country; trust in information about the introduction provided by: national or regional government or authorities, tax administration, national central bank, European institutions, commercial banks, journalists, trade unions or professional organizations, consumer associations; preferred places of information about the euro and the changeover; most important issues to be covered by information campaigns; significance of selected information campaign actions; assessment of the impact of the introduction of the euro in the countries already using the euro as positive; assessment of the impact of the introduction on the own country and on personal life; approval of introducing the euro in the own country; preferred time for introducing the euro; expected impact of the introduction on the prices in the own country; expected impact of the introduction: easier price comparisons with other countries, easier shopping in other countries, save money by eliminating fees of currency exchange in other countries, more convenient travel in other countries, protection of the own country from the effects of international crises; benefits from the adoption of the euro on the own country: lower interest rates, sounder public finances, improvement of growth and employment, ensuring low inflation rates, reinforcement of the place of Europe in the world, strengthening of European identity; approval of the following statements on the impact of the introduction of the euro: confident to adapt to the replacement of the national currency, afraid of abusive price setting, loss of control over national economic policy, loss of national identity. Demography: age; sex; nationality; age at end of education; occupation; professional position; region; type of community; own a mobile phone and fixed (landline) phone; household composition and household size. Additionally coded was: type of phone line; weighting factor. Telephone interview: CATI Litauische Bevölkerung, im Alter von 15 Jahren und älter. Die Befragung umfasst die nationale Bevölkerung sowie die Bürger aller Mitgliedsstaaten der Europäischen Union, die in Litauen wohnhaft sind und über zum Ausfüllen des Fragebogens ausreichende Kenntnis der Landessprache verfügen. Population of Lithuania, aged 15 years and over. The survey covers the national population of citizens as well as the population of citizens of all the European Union Member States who are resident in Lithuania and have a sufficient command of the national language to answer the questionnaire.

The benchmark interest rate in the United States was last recorded at 4.50 percent. This dataset provides the latest reported value for - United States Fed Funds Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

This dataset contains news headlines relevant to key forex pairs: AUDUSD, EURCHF, EURUSD, GBPUSD, and USDJPY. The data was extracted from reputable platforms Forex Live and FXstreet over a period of 86 days, from January to May 2023. The dataset comprises 2,291 unique news headlines. Each headline includes an associated forex pair, timestamp, source, author, URL, and the corresponding article text. Data was collected using web scraping techniques executed via a custom service on a virtual machine. This service periodically retrieves the latest news for a specified forex pair (ticker) from each platform, parsing all available information. The collected data is then processed to extract details such as the article's timestamp, author, and URL. The URL is further used to retrieve the full text of each article. This data acquisition process repeats approximately every 15 minutes.

To ensure the reliability of the dataset, we manually annotated each headline for sentiment. Instead of solely focusing on the textual content, we ascertained sentiment based on the potential short-term impact of the headline on its corresponding forex pair. This method recognizes the currency market's acute sensitivity to economic news, which significantly influences many trading strategies. As such, this dataset could serve as an invaluable resource for fine-tuning sentiment analysis models in the financial realm.

We used three categories for annotation: 'positive', 'negative', and 'neutral', which correspond to bullish, bearish, and hold sentiments, respectively, for the forex pair linked to each headline. The following Table provides examples of annotated headlines along with brief explanations of the assigned sentiment.

Examples of Annotated Headlines


    Forex Pair
    Headline
    Sentiment
    Explanation




    GBPUSD 
    Diminishing bets for a move to 12400 
    Neutral
    Lack of strong sentiment in either direction


    GBPUSD 
    No reasons to dislike Cable in the very near term as long as the Dollar momentum remains soft 
    Positive
    Positive sentiment towards GBPUSD (Cable) in the near term


    GBPUSD 
    When are the UK jobs and how could they affect GBPUSD 
    Neutral
    Poses a question and does not express a clear sentiment


    JPYUSD
    Appropriate to continue monetary easing to achieve 2% inflation target with wage growth 
    Positive
    Monetary easing from Bank of Japan (BoJ) could lead to a weaker JPY in the short term due to increased money supply


    USDJPY
    Dollar rebounds despite US data. Yen gains amid lower yields 
    Neutral
    Since both the USD and JPY are gaining, the effects on the USDJPY forex pair might offset each other


    USDJPY
    USDJPY to reach 124 by Q4 as the likelihood of a BoJ policy shift should accelerate Yen gains 
    Negative
    USDJPY is expected to reach a lower value, with the USD losing value against the JPY


    AUDUSD

RBA Governor Lowe’s Testimony High inflation is damaging and corrosive

    Positive
    Reserve Bank of Australia (RBA) expresses concerns about inflation. Typically, central banks combat high inflation with higher interest rates, which could strengthen AUD.

Moreover, the dataset includes two columns with the predicted sentiment class and score as predicted by the FinBERT model. Specifically, the FinBERT model outputs a set of probabilities for each sentiment class (positive, negative, and neutral), representing the model's confidence in associating the input headline with each sentiment category. These probabilities are used to determine the predicted class and a sentiment score for each headline. The sentiment score is computed by subtracting the negative class probability from the positive one.

Introduction of the euro in the new member states. Topics: contact with and use of euro banknotes or coins; use of euro banknotes or coins in the own country or abroad; knowledge test on the euro: equal design of euro banknotes and coins in every country, number of countries that already introduced the euro, possibility of the own country to choose whether to introduce the euro or not, year of introduction of the euro in the own country; self-rated knowledge on the euro; preferred time of information about the introduction of the euro in the own country; trust in information about the introduction provided by: national government or authorities, tax administrations, national central bank, European institutions, commercial banks, journalists, trade unions or professional organizations, consumer associations; preferred places of information about the euro and the changeover; most important issues to be covered by information campaigns; significance of selected information campaign actions; satisfaction with the replacement of the national currency by the euro; assessment of the impact of the introduction on the own country and on personal life; approval of the introduction of the euro by own friends; preferred time for introducing the euro in the own country; assessment of the impact of the introduction of the euro in the countries already using the euro as positive; expected impact of the introduction on the prices in the own country; assessment of the euro compared to US dollar and Japanese Yen; expected impact of the introduction: easier price comparisons with other countries, easier shopping in other countries, save money by eliminating fees of currency exchange in other countries, more convenient travel in other countries, protection of the own country from the effects of international crises; benefits from the adoption of the euro on the own country: lower interest rates, sounder public finances, reinforcement of the place of Europe in the world, improvement of growth and employment, low inflation rates; approval of the following statements regarding the adoption of the euro: will cause personal inconvenience, concern about abusive price setting during the changeover, loss of control over national economic policy, loss of national identity, strengthening of the feeling of being European. Demography: sex; age; age at end of education; professional position; type of community. Additionally coded was: interviewer ID; language of the interview; country; date of interview; time of the beginning of the interview; duration of the interview; type of phone line; region; weighting factor. Euro-Umstellung im Urteil der neuen EU-Mitgliedsländer. Themen: Kontakt mit sowie Gebrauch von Euro-Münzen und Banknoten; Ort des Gebrauchs (Inland/Ausland); Kenntnistest über die Gestalt der Münzen und Banknoten; Kenntnis der Anzahl der EU-Länder mit Euro-Währung; Wahlfreiheit des Landes über die Einführung des Euro; Kenntnis des Einführungsjahrs im eigenen Land; Selbsteinschätzung der Informiertheit über den Euro; gewünschter Zeitpunkt der Information über die Euro-Einführung; Institutionenvertrauen bei der Information über den Euro; gewünschter Ort der Informationsversorgung über den Euro (z.B. Medien, Banken oder Supermärkten); präferierter Inhalte für eine Informationskampagne: Vorgehen bei der Einführung, Währungswert, Gestalt des Euro, Vorgehen bei der korrekten Umrechnung von der einheimischen Währung in Euro; Auswirkungen auf die persönliche Lohnauszahlung oder das Bankkonto sowie wirtschaftliche und politische Auswirkungen, über duale Preisauszeichnung in Läden und in Rechnungen, Broschüren, Fernseh-, Zeitungs- und Radiowerbung; Zufriedenheit mit der Einführung einer neuen Währung; Einschätzung der Konsequenzen durch die Euro-Einführung für den Befragten persönlich sowie für das eigene Land; Einschätzung der generellen Meinung zum Euro im eigenen Land; gewünschter Einführungszeitpunkt; Einschätzung der Konsequenzen für die Länder, die den Euro bereits eingeführt haben; erwartete Auswirkungen der Euro-Einführung im eigenen Land: Preisanstieg oder Preisstabilität; Vergleichbarkeit des Euro (als internationale Währung) mit dem US-Dollar oder dem japanischen Yen; erwartete Erleichterungen durch den Euro: einfacher Preisvergleich mit anderen Euro-Ländern, Einkäufe in anderen Euro-Ländern, Einsparungen von Umtauschkosten, Reiseerleichterungen, Schutz des Landes vor internationalen Krisen; Vorteile durch den Euro: niedrigere Zinsraten für Kredite, ausgeglichene öffentliche Finanzen, Stärkung des Standorts Europa, Stärkung von Wachstum und Beschäftigung, Sicherung der Preisstabilität, stärkere Identifizierung mit Europa; Nachteile durch die Euro-Einführung: persönliche Unannehmlichkeiten, Betrug bei der Preisumrechnung, nationaler Kontrollverlust über die Wirtschaftspolitik, Identitätsverlust. Demographie: Geschlecht; Alter; Alter bei Beendigung der Ausbildung; berufliche Stellung; Urbanisierungsgrad. Zusätzlich verkodet wurde: Interviewer-ID; Interviewsprache; Land; Interviewdatum; Interviewdauer (Interviewbeginn und Interviewende); Interviewmodus (Mobiltelefon oder Festnetz); Region; Gewichtungsfaktor.

Graph and download economic data for Personal Saving Rate (PSAVERT) from Jan 1959 to Jul 2025 about savings, personal, rate, and USA.

Inflation Rate in Iran increased to 38.90 percent in April from 37.10 percent in March of 2025. This dataset provides the latest reported value for - Iran Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Iceland Breakeven Inflation Rate: Bond Market: 2 Year data was reported at 3.000 % in Dec 2024. This records a decrease from the previous number of 3.900 % for Sep 2024. Iceland Breakeven Inflation Rate: Bond Market: 2 Year data is updated quarterly, averaging 3.717 % from Mar 2003 (Median) to Dec 2024, with 88 observations. The data reached an all-time high of 10.663 % in Dec 2008 and a record low of 1.292 % in Mar 2011. Iceland Breakeven Inflation Rate: Bond Market: 2 Year data remains active status in CEIC and is reported by Central Bank of Iceland. The data is categorized under Global Database’s Iceland – Table IS.I018: Breakeven Inflation Rate (BEI). [COVID-19-IMPACT]

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

Iceland Breakeven Inflation Rate: Bond Market: 10 Year data was reported at 3.800 % in Dec 2024. This records a decrease from the previous number of 4.000 % for Sep 2024. Iceland Breakeven Inflation Rate: Bond Market: 10 Year data is updated quarterly, averaging 3.444 % from Mar 2003 (Median) to Dec 2024, with 88 observations. The data reached an all-time high of 5.892 % in Dec 2008 and a record low of 1.349 % in Dec 2006. Iceland Breakeven Inflation Rate: Bond Market: 10 Year data remains active status in CEIC and is reported by Central Bank of Iceland. The data is categorized under Global Database’s Iceland – Table IS.I018: Breakeven Inflation Rate (BEI). [COVID-19-IMPACT]

Replication files for "Job-to-Job Mobility and Inflation" Authors: Renato Faccini and Leonardo Melosi Review of Economics and Statistics Date: February 2, 2023 -------------------------------------------------------------------------------------------- ORDERS OF TOPICS .Section 1. We explain the code to replicate all the figures in the paper (except Figure 6) .Section 2. We explain how Figure 6 is constructed .Section 3. We explain how the data are constructed SECTION 1 Replication_Main.m is used to reproduce all the figures of the paper except Figure 6. All the primitive variables are defined in the code and all the steps are commented in code to facilitate the replication of our results. Replication_Main.m, should be run in Matlab. The authors tested it on a DELL XPS 15 7590 laptop wih the follwoing characteristics: -------------------------------------------------------------------------------------------- Processor Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz 2.40 GHz Installed RAM 64.0 GB System type 64-bit operating system, x64-based processor -------------------------------------------------------------------------------------------- It took 2 minutes and 57 seconds for this machine to construct Figures 1, 2, 3, 4a, 4b, 5, 7a, and 7b. The following version of Matlab and Matlab toolboxes has been used for the test: -------------------------------------------------------------------------------------------- MATLAB Version: 9.7.0.1190202 (R2019b) MATLAB License Number: 363305 Operating System: Microsoft Windows 10 Enterprise Version 10.0 (Build 19045) Java Version: Java 1.8.0_202-b08 with Oracle Corporation Java HotSpot(TM) 64-Bit Server VM mixed mode -------------------------------------------------------------------------------------------- MATLAB Version 9.7 (R2019b) Financial Toolbox Version 5.14 (R2019b) Optimization Toolbox Version 8.4 (R2019b) Statistics and Machine Learning Toolbox Version 11.6 (R2019b) Symbolic Math Toolbox Version 8.4 (R2019b) -------------------------------------------------------------------------------------------- The replication code uses auxiliary files and save the pictures in various subfolders: \JL_models: It contains the equations describing the model including the observation equations and routine used to solve the model. To do so, the routine in this folder calls other routines located in some fo the subfolders below. \gensystoama: It contains a set of codes that allow us to solve linear rational expectations models. We use the AMA solver. More information are provided in the file AMASOLVE.m. The codes in this subfolder have been developed by Alejandro Justiniano. \filters: it contains the Kalman filter augmented with a routine to make sure that the zero lower bound constraint for the nominal interest rate is satisfied in every period in our sample. \SteadyStateSolver: It contains a set of routines that are used to solved the steady state of the model numerically. \NLEquations: It contains some of the equations of the model that are log-linearized using the symbolic toolbox of matlab. \NberDates: It contains a set of routines that allows to add shaded area to graphs to denote NBER recessions. \Graphics: It contains useful codes enabling features to construct some of the graphs in the paper. \Data: it contains the data set used in the paper. \Params: It contains a spreadsheet with the values attributes to the model parameters. \VAR_Estimation: It contains the forecasts implied by the Bayesian VAR model of Section 2. The output of Replication_Main.m are the figures of the paper that are stored in the subfolder \Figures SECTION 2 The Excel file "Figure-6.xlsx" is used to create the charts in Figure 6. All three panels of the charts (A, B, and C) plot a measure of unexpected wage inflation against the unemployment rate, then fits separate linear regressions for the periods 1960-1985,1986-2007, and 2008-2009. Unexpected wage inflation is given by the difference between wage growth and a measure of expected wage growth. In all three panels, the unemployment rate used is the civilian unemployment rate (UNRATE), seasonally adjusted, from the BLS. The sheet "Panel A" uses quarterly manufacturing sector average hourly earnings growth data, seasonally adjusted (CES3000000008), from the Bureau of Labor Statistics (BLS) Employment Situation report as the measure of wage inflation. The unexpected wage inflation is given by the difference between earnings growth at time t and the average of earnings growth across the previous four months. Growth rates are annualized quarterly values. The sheet "Panel B" uses quarterly Nonfarm Business Sector Compensation Per Hour, seasonally adjusted (COMPNFB), from the BLS Productivity and Costs report as its measure of wage inflation. As in Panel A, expected wage inflation is given by the average wage inflation over the previous four quarters. Growth rates are annualized quarterly values. The sheet "Panel C" uses semiannual manufacturing...

Views on the introduction of the euro. Themes: Contact with and use of euro banknotes and euro coins; use of euro banknotes and euro coins in respondent´s country or abroad; knowledge test of the design of euro coins and banknotes and about the number of EU countries that have introduced the euro; country has a choice to introduce the euro; expected year of introduction in respondent´s country; feeling well informed about the euro; desired time for information on the introduction of the euro; trust in selected institutions or groups regarding their informations on the changeover to the euro; essential issues for the information campaign; essential information campaign actions; positive or negative consequences for those countries that are using the euro already; expected positive or negative consequences of the introduction of the euro for the respondent´s country and for him personally; attitude towards the introduction of the euro; desired time to introduce the euro as new currency; suspected impact of the introduction of the euro on prices in the country; positive aspects of the euro-introduction (easier comparison of prices, easier shopping in other countries that use the euro, save of money by elimination fees of currency exchange, more convenient for traveling, protection of the country from the effects of international crises); positive aspects of the adoption of the euro for the country (will ensure lower interest rates, less debt charges, sounder public finances, improvement of growth and employment, ensure low inflation rates, reinforce the place of Europe in the world, feeling more European); the replacement of the national currency by the euro will cause a lot of inconvenience; concern about abusive price setting during the changeover; adoption of the euro leads to the lose of control over the economic policy of the country; adopting the euro will mean that the country will lose a part of its identity. Demography: Age; gender; age when finished full-time education; occupation and occupational status; region; type of community (degree of urbanization); possession of a mobile phone and a landline phone; number of persons in the household aged 15 years or more (household size). Ansichten über die Einführung des Euro. Themen: Kontakt mit und Verwendung von Euro-Banknoten und Euro-Münzen; Verwendung von Euro-Banknoten und Euro-Münzen im Inland oder im Ausland; Wissenstest über das Design der Euro-Münzen und Euro-Banknoten und über die Zahl der EU-Länder, die den Euro eingeführt haben; Land hat die Wahl, den Euro einzuführen; erwartetes Jahr der Euro-Einführung im Land; Gefühl, gut über den Euro informiert zu sein; gewünschte Zeit für Informationen über die Einführung des Euro; Vertrauen in ausgewählte Institutionen oder Gruppen in Bezug auf ihre Informationen zur Umstellung auf den Euro; wesentliche Fragen für die Informationskampagne; wesentliche Maßnahmen der Informationskampagne; positive oder negative Folgen für die Länder, die den Euro bereits verwenden; erwartete positive oder negativen Folgen der Einführung des Euro für das Land und für den Befragten persönlich; Einstellung zur Einführung des Euro; gewünschte Zeit für die Einführung des Euro als neue Währung; erwartete Auswirkungen der Einführung des Euro auf die Preise im Land; positiven Aspekte der Euro-Einführung (einfacherer Preisvergleich, einfacherer Einkauf in anderen Euro-Ländern, Einsparungen durch Wegfall von Wechselgebühren, praktisch für Reisen, Schutz des Landes vor den Auswirkungen der internationale Krisen); positive Aspekte der Einführung des Euro für das Land (Sicherstellen niedrigerer Zinsen, weniger Schuldengebühren, gesündere öffentliche Finanzen, Verbesserung von Wachstum und der Beschäftigung, sorgen für geringe Inflationsraten, verstärken den Platz Europas in der Welt, stärken eine europäische Identität); Ersetzen der nationalen Währung durch den Euro wird Unannehmlichkeiten verursachen; Besorgnis über missbräuchliche Preisauszeichnungen während der Umstellung; Einführung des Euro führt zum Kontrollverlust über die Wirtschaftspolitik des Landes; die Einführung des Euro bedeutet teilweisen Identitätsverlust für das Land. Demographie: Alter; Geschlecht; Alter bei Ende der Schulbildung; Beruf und berufliche Stellung; Region; Urbanisierungsgrad; Besitz von Mobiltelefon und Festnetz-Telefon; Anzahl der Personen im Haushalt im Alter von 15 Jahren und älter (Haushaltsgröße).

Inflation Rate in Vietnam increased to 3.24 percent in August from 3.19 percent in July of 2025. This dataset provides the latest reported value for - Vietnam Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.