Consumer price inflation statistics are important indicators of how the UK economy is performing. They are used in many ways by individuals, government, businesses and academics. Inflation statistics impact on everyone in some way as they affect interest rates, tax allowances, benefits, pensions, savings rates, maintenance contracts and many other payments. This article provides information about the users and uses of consumer price inflation statistics, and user experiences of these statistics, including the new CPIH and RPIJ measures. In addition, it also provides information on the characteristics of the different measures of consumer price inflation in relation to their potential use. Source agency: Office for National Statistics Designation: National Statistics Language: English Alternative title: consumer price inflation statistics

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When examining the intricate relationship between economic conditions and purchasing decisions, the utilization of practice datasets can offer invaluable insights. This particular artificial dataset comprises three main components: a dimension table of ten companies, a fact table documenting purchases from these companies, and a set of data points regarding economic conditions. These elements are meticulously designed to mimic real-world scenarios, enabling analysts to dissect and understand how fluctuations in the economy can influence the purchasing behavior of different types of companies.

The dimension table serves as the foundation, listing ten distinct companies, each potentially operating in varied sectors. This diversity allows for a comprehensive analysis across a spectrum of industries, highlighting sector-specific sensitivities to economic changes. The fact table of purchases acts as a historical record, offering detailed insights into the buying patterns of these companies over time. Analysts can observe trends, frequencies, and the magnitude of purchases, correlating them with the economic conditions presented in the third component of the dataset.

The economic conditions data is pivotal, as it encompasses a variety of indicators that can affect purchasing decisions. These may include inflation rates, interest rates, GDP growth, unemployment rates, and consumer confidence indices, among others. By examining the interplay between these economic indicators and the purchasing data, analysts can identify patterns and causations. For instance, an increase in interest rates might lead to a decrease in capital-intensive purchases by companies wary of higher borrowing costs.

Through this dataset, researchers can employ statistical models and data analysis techniques to uncover how economic fluctuations impact corporate purchasing decisions. The findings can offer valuable lessons for businesses in terms of budgeting, financial planning, and risk management. Companies can use these insights to make informed decisions, adjusting their purchasing strategies in anticipation of or in response to economic conditions. This proactive approach can help businesses maintain stability during economic downturns and capitalize on opportunities during favorable economic times.

Ultimately, this practice dataset not only aids in academic and educational pursuits but also serves as a practical tool for business analysts, economists, and corporate strategists seeking to better navigate the complex dynamics of the economy and its effects on corporate purchasing behaviors.

Techsalerator's News Events Data for Senegal: A Comprehensive Overview

Techsalerator's News Events Data for Senegal offers a valuable resource for businesses, researchers, and media organizations. This dataset compiles information on significant news events across Senegal, sourced from a wide array of media outlets, online publications, and social platforms. It provides insights for tracking trends, analyzing public sentiment, or monitoring developments within specific industries.

Key Data Fields - Event Date: Records the exact date of the news event. This is essential for analysts tracking trends over time or businesses responding to market shifts. - Event Title: A concise headline describing the event. This allows users to quickly categorize and assess news content based on their interests. - Source: Indicates the news outlet or platform where the event was reported. This helps users evaluate the credibility and reach of the event. - Location: Provides geographic information about where the event occurred within Senegal. This is particularly useful for regional analysis or targeted marketing efforts. - Event Description: A detailed summary of the event, outlining key developments, participants, and potential impact. This helps researchers and businesses understand the context and implications of the event.

Top 5 News Categories in Senegal - Politics: Coverage of government decisions, political movements, elections, and policy changes affecting the national landscape. - Economy: Focuses on Senegal’s economic indicators, inflation rates, international trade, and corporate activities impacting the business and finance sectors. - Social Issues: News on protests, public health, education, and other societal concerns driving public discourse. - Sports: Highlights events in football, athletics, and other popular sports, often drawing significant attention and engagement nationwide. - Technology and Innovation: Reports on tech developments, startups, and advancements in Senegal’s growing tech sector, featuring emerging companies and technological progress.

Top 5 News Sources in Senegal - Le Soleil: A major news outlet providing comprehensive coverage of national politics, economy, and social issues. - Seneweb: A popular online platform known for timely updates on breaking news, politics, and current affairs. - Walfadjri: A widely-read newspaper offering insights into local politics, economic developments, and societal trends. - RFI (Radio France Internationale): Provides in-depth reports on various topics, including politics, economy, and social issues in Senegal. - Sud Quotidien: Covers a broad spectrum of topics, including politics, economy, and social issues, with a focus on local developments.

Accessing Techsalerator’s News Events Data for Senegal To access Techsalerator’s News Events Data for Senegal, please contact info@techsalerator.com with your specific requirements. We will provide a customized quote based on the data fields and records you need, with delivery available within 24 hours. Ongoing access options can also be discussed.

Included Data Fields - Event Date - Event Title - Source - Location - Event Description - Event Category (Politics, Economy, Sports, etc.) - Participants (if applicable) - Event Impact (Social, Economic, etc.)

Techsalerator’s dataset is an essential tool for tracking significant events in Senegal. It supports informed decision-making, whether for business strategy, market analysis, or academic research, providing a comprehensive view of the country's news landscape.

Hereby I am sharing the data used in the paper: "The words have power: the impact of news on exchange rates". The dataset includes: Taylor Rule Fundamentals: - inflation, - industrial production index (as a high-frequency proxy of GDP), - money market rate from 2000 until 2018. Textual information: - Entropies of news items about the U.S. Dollar from Nexis-Uni database. This is how we get the textual data from Nexis-Uni database: We enter “U.S. Dollar” as a keyword in searching for the news, which gives over 15 Million non-duplicate news. Next, we clean data news and select the relevant news items as follows. We select news about U.S. Dollar with the following criteria: (i) the U.S. Dollar appears in the title of news items, (ii) U.S. Dollar is repeated several times in the news, (iii) the first paragraph of news contains the word “U.S. Dollar”, (iv) U.S. Dollar is the subject of news items which are automatically selected by Nexis-Uni database. - economic policy uncertainty index from https://www.policyuncertainty.com/index.html

Envestnet®| Yodlee®'s Online Purchase Data (Aggregate/Row) Panels consist of de-identified, near-real time (T+1) USA credit/debit/ACH transaction level data – offering a wide view of the consumer activity ecosystem. The underlying data is sourced from end users leveraging the aggregation portion of the Envestnet®| Yodlee®'s financial technology platform.

Envestnet | Yodlee Consumer Panels (Aggregate/Row) include data relating to millions of transactions, including ticket size and merchant location. The dataset includes de-identified credit/debit card and bank transactions (such as a payroll deposit, account transfer, or mortgage payment). Our coverage offers insights into areas such as consumer, TMT, energy, REITs, internet, utilities, ecommerce, MBS, CMBS, equities, credit, commodities, FX, and corporate activity. We apply rigorous data science practices to deliver key KPIs daily that are focused, relevant, and ready to put into production.

We offer free trials. Our team is available to provide support for loading, validation, sample scripts, or other services you may need to generate insights from our data.

Investors, corporate researchers, and corporates can use our data to answer some key business questions such as: - How much are consumers spending with specific merchants/brands and how is that changing over time? - Is the share of consumer spend at a specific merchant increasing or decreasing? - How are consumers reacting to new products or services launched by merchants? - For loyal customers, how is the share of spend changing over time? - What is the company’s market share in a region for similar customers? - Is the company’s loyal user base increasing or decreasing? - Is the lifetime customer value increasing or decreasing?

Additional Use Cases: - Use spending data to analyze sales/revenue broadly (sector-wide) or granular (company-specific). Historically, our tracked consumer spend has correlated above 85% with company-reported data from thousands of firms. Users can sort and filter by many metrics and KPIs, such as sales and transaction growth rates and online or offline transactions, as well as view customer behavior within a geographic market at a state or city level. - Reveal cohort consumer behavior to decipher long-term behavioral consumer spending shifts. Measure market share, wallet share, loyalty, consumer lifetime value, retention, demographics, and more.) - Study the effects of inflation rates via such metrics as increased total spend, ticket size, and number of transactions. - Seek out alpha-generating signals or manage your business strategically with essential, aggregated transaction and spending data analytics.

Use Cases Categories (Our data provides an innumerable amount of use cases, and we look forward to working with new ones): 1. Market Research: Company Analysis, Company Valuation, Competitive Intelligence, Competitor Analysis, Competitor Analytics, Competitor Insights, Customer Data Enrichment, Customer Data Insights, Customer Data Intelligence, Demand Forecasting, Ecommerce Intelligence, Employee Pay Strategy, Employment Analytics, Job Income Analysis, Job Market Pricing, Marketing, Marketing Data Enrichment, Marketing Intelligence, Marketing Strategy, Payment History Analytics, Price Analysis, Pricing Analytics, Retail, Retail Analytics, Retail Intelligence, Retail POS Data Analysis, and Salary Benchmarking

1. Investment Research: Financial Services, Hedge Funds, Investing, Mergers & Acquisitions (M&A), Stock Picking, Venture Capital (VC)

2. Consumer Analysis: Consumer Data Enrichment, Consumer Intelligence

3. Market Data: AnalyticsB2C Data Enrichment, Bank Data Enrichment, Behavioral Analytics, Benchmarking, Customer Insights, Customer Intelligence, Data Enhancement, Data Enrichment, Data Intelligence, Data Modeling, Ecommerce Analysis, Ecommerce Data Enrichment, Economic Analysis, Financial Data Enrichment, Financial Intelligence, Local Economic Forecasting, Location-based Analytics, Market Analysis, Market Analytics, Market Intelligence, Market Potential Analysis, Market Research, Market Share Analysis, Sales, Sales Data Enrichment, Sales Enablement, Sales Insights, Sales Intelligence, Spending Analytics, Stock Market Predictions, and Trend Analysis

ntroducing our retail tariff database, a comprehensive and user-friendly platform designed to provide in-depth information on retail energy tariffs in the GB market. Updated regularly and meticulously maintained, our database offers invaluable insights for a range of stakeholders, including energy retailers, economic analysts, and electric vehicle (EV) operators.

Our retail tariff database covers all types of tariffs available in the GB market and provides an extensive set of data fields, such as tariff types, rates, contract lengths, and more. The platform is designed for easy navigation and customization, allowing users to quickly access the information they need to make informed decisions.

Energy Retailers: For energy retailers, our retail tariff database is an essential tool for staying competitive in the constantly evolving energy market. By providing real-time access to the latest tariffs from competitors, our platform enables retailers to adjust their own pricing strategies and remain competitive in the market. Furthermore, the database offers valuable information on emerging trends and consumer preferences, helping retailers identify new opportunities and challenges in the sector.

Predicting Inflation: For economic analysts and professionals interested in predicting inflation, our retail tariff database serves as a rich source of data for examining the energy market's impact on consumer prices. As energy costs are a significant factor in overall inflation, our platform provides timely and granular information on energy tariffs, allowing users to better understand the relationship between energy prices and inflation. By incorporating this data into their analysis, professionals can develop more accurate predictions and provide valuable insights to policymakers and businesses.

EV Operators: For electric vehicle operators, our retail tariff database offers insights into the evolving landscape of energy pricing, which has a direct impact on the cost and attractiveness of EV charging infrastructure. By staying informed about the latest energy tariffs, EV operators can make strategic decisions regarding the location, pricing, and expansion of their charging networks. Additionally, the database can help operators identify potential synergies between energy tariffs and EV charging demand, enabling them to develop innovative business models that cater to the needs of EV users.

Economic Risk, Resources and Environment (ERRE) is a system dynamics model whose purpose is to analyse the financial pressures emerging from global economic growth while coping with natural limits in both energy and agricultural systems. A major feature of the model is to integrate in the same framework both the dynamic evolution of long term phenomena (e.g. energy transition, climate effects) and the short to medium term structures that are more relevant to decision making in the real world (e.g. extreme weather effects, irrational behaviours of markets). Building on the World3-03 Limits to Growth model, ERRE links the financial system with the energy, agriculture and climate systems through the real economy, by means of feedback loops, time lags and non-linear rationally bounded decision making. Prices and their interaction with growth, inflation and interest rates are assumed to be the main driver of economic failure while reaching planetary limits. Developed within the the CUSP System Dynamics theme, the model allows for the stress-testing of fat tail extreme risk scenarios, such as climate shocks, energy transition, monetary policies and carbon taxes. Risks are addressed via scenario analyses, compared to real available data, and assessed in terms of the economic theory that lies behind.We propose to establish a multi-disciplinary Centre for the Understanding of Sustainable Prosperity (CUSP). Led by the University of Surrey, CUSP will work with a range of academic and non-academic partners to establish a rich international network of collaborative research. The aim of this research will be to explore the economic, ecological, social and governance dimensions of sustainable prosperity and to make concrete recommendations to government, business and civil society in pursuit of it. Our guiding vision for sustainable prosperity is one in which people everywhere have the capability to flourish as human beings - within the ecological and resource constraints of a finite planet. Our work will explore not just the economic aspects of this challenge, but also its social, political and philosophical dimensions. We will address the implications of sustainable prosperity at the level of households and firms; and we will explore sector-level and macro-economic implications of different pathways to prosperity. We will pay particular attention to the pragmatic steps that need to be taken by enterprise, government and civil society in order to achieve a sustainable prosperity. The CUSP work programme is split into five themes (our MAPSS framework). Theme M explores the moral framing and contested meanings of prosperity itself. Taking a broadly philosophical approach we examine how people, enterprise and government negotiate the tensions between sustainability and prosperity. Theme A explores the role of the arts and of culture in our society. We will look not only at the role of the arts in communicating sustainability but at culture as a vital element in prosperity itself. Theme P addresses the politics of sustainable prosperity and explores the institutional shifts that will be needed to achieve it. We will work closely with both corporate and social enterprise to test new models of sustainability for business. Theme S1 explores the social and psychological dimensions of prosperity. We will work with households and individuals in order to understand how people negotiate their aspirations for the good life. As part of this theme we will engage with UNEP in a major study of young people's lifestyles across the world. Theme S2 examines the complex dynamics of social and economic systems on which sustainable prosperity depends. We will address in particular the challenge of achieving financial stability and high employment under conditions of constrained resource consumption. Alongside our MAPSS work programme, we will initiate a major international Sustainable Prosperity Dialogue (chaired by Dr Rowan Williams - former Archbishop of Canterbury and Master of Magdalene College Cambridge). We will also establish an international network of CUSP Fellows from both academic and non-academic institutions. Model development (software). A book, Resources, Financial Risk and Dynamics of Growth: Systems and Global Society by Roberto Pasqualino and Aled Jones, was published in 2020 by Routledge and describes the background to this model development. Here you will find the appendix to that book (Appendix_ERRE.pdf) which contains the detail equations and model structure alongside the Vensim ERRE model (ERRE_Model_10012020.vpm), a short guide (ERRE Vensim Reader Guide.pdf) and scenario runs and data (*.vdf files).

This dataset presents information about own unincorporated business income. The data covers the financial years 2011-12 to 2017-18, and is based on Statistical Area Level 3 (SA3) according to the 2016 edition of the Australian Statistical Geography Standard (ASGS).

Own unincorporated business income (OMUE income) is the profit or loss that accrues to owners of, or partners in, their own unincorporated businesses. Profit or loss is the value of the gross output of the enterprise after the deduction of operating expenses, including reportable superannuation contributions, depreciation and operating costs, but before income tax is taken out. Losses occur when operating expenses are greater than receipts and are treated as negative income.

Own unincorporated business income includes the following data items on the Individual Tax Returns (ITR):

• Net income or loss from business primary production

• Net income or loss from business non primary production

• Distribution from trusts primary production

• Net Personal Services Income

• Distribution from partnerships less foreign income non primary production

• Distribution from partnerships primary production

  These data exclude distributions from trusts for non-primary production activities as this may include aspects of investment income. It also excludes the income of working directors/owners of incorporated businesses who are classified as employees; consequently their income is included under Wage and salary income.

"Net personal services income" does not include income a person received as an employee, making it different from "Attributed personal services income".

All monetary values are presented as gross pre-tax dollars, as far as possible. This means they reflect income before deductions and loses, and before any taxation or levies (e.g. the Medicare levy or the temporary budget repair levy) are applied. The amounts shown are nominal, they have not been adjusted for inflation. The income presented in this release has been categorised into income types, these categories have been devised by the Australian Bureau of Statistics (ABS) to closely align to ABS definitions of income.

The statistics in this release are compiled from the Linked Employer Employee Dataset (LEED), a cross-sectional database based on administrative data from the Australian taxation system. The LEED includes more than 120 million tax records over seven consecutive years between 2011-12 and 2017-18.

Please note:

• All personal income tax statistics included in LEED were provided in de-identified form with no home address or date of birth. Addresses were coded to the ASGS and date of birth was converted to an age at 30 June of the reference year prior to data provision.

• To minimise the risk of identifying individuals in aggregate statistics, perturbation has been applied to the statistics in this release. Perturbation involves small random adjustment of the statistics and is considered the most satisfactory technique for avoiding the release of identifiable statistics, while maximising the range of information that can be released. These adjustments have a negligible impact on the underlying pattern of the statistics. Some cells have also been suppressed due to low counts.

• Totals may not align with the sum of their components due to missing or unpublished information in the underlying data and perturbation.

For further information please visit the Australian Bureau of Statistics.

AURIN has made the following changes to the original data:

• Spatially enabled the original data.

• Set 'np' (not published to protect the confidentiality of individuals or businesses) values to Null.

Attitudes of elites and persons influencing opinion on questions of economic policy. Topics: most important tasks of large concerns; expected development of the Dollar exchange rate to the end 1993 and the growth rate of the gross national product in 1993; inflation expectation for 1993; expected unemployment figures; preferred measures to combat unemployment; judgement on the importance of European cooperation in selected areas; most able politicians in selected subject areas; print media usage; judgement on German products in international competition (scale); effects of the EC domestic market on selected areas of business in the FRG; prediction for the Federal Parliament election; effect of a red-green coalition on the economy; party preference; preferred measures for a flexible arrangement of working hours; area of business affiliation and personal interest in areas of business; importance of various characteristics for companies. Also encoded was position and area of responsibility of respondent. Einstellungen von Eliten und meinungsbildenden Personen zu wirtschaftspolitischen Fragen. Themen: Wichtigste Aufgaben von Großunternehmen; vermutete Entwicklung des Dollarkurses bis Ende 1993 und der Wachstumsrate des Bruttosozialprodukts im Jahr 1993; Inflationserwartung für das Jahr 1993; erwartete Arbeitslosenzahl; präferierte Maßnahmen zur Bekämpfung der Arbeitslosigkeit; Beurteilung der Wichtigkeit einer europäischen Kooperation in ausgewählten Bereichen; kompetenteste Politiker in ausgewählten Sachgebieten; Print-Mediennutzung; Beurteilung von deutschen Produkten im internationalen Wettbewerb (Skala); Auswirkungen des EG-Binnenmarktes auf ausgewählte Branchen in der BRD; Prognose für die Bundestagswahl; Auswirkung einer rot-grünen Koalition auf die Wirtschaft; Parteipräferenz; präferierte Maßnahmen für eine flexiblere Regelung der Arbeitszeit; Branchenzugehörigkeit und persönliches Interesse an Branchen; Wichtigkeit verschiedener Eigenschaften für Unternehmen. Demographie: Alter; Geschlecht; Bundesland; Zusätzlich verkodet wurde die Position und das Aufgabengebiet des Befragten. Stratified random sample Geschichtete Zufallsauswahl

Corporate Profits in the United States increased to 3266.20 USD Billion in the second quarter of 2025 from 3203.60 USD Billion in the first quarter of 2025. This dataset provides the latest reported value for - United States Corporate Profits - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

This dataset presents information about own unincorporated business income. The data covers the financial years 2011-12 to 2017-18, and is based on Greater Capital City Statistical Areas (GCCSA) according to the 2016 edition of the Australian Statistical Geography Standard (ASGS).

Own unincorporated business income (OMUE income) is the profit or loss that accrues to owners of, or partners in, their own unincorporated businesses. Profit or loss is the value of the gross output of the enterprise after the deduction of operating expenses, including reportable superannuation contributions, depreciation and operating costs, but before income tax is taken out. Losses occur when operating expenses are greater than receipts and are treated as negative income.

Own unincorporated business income includes the following data items on the Individual Tax Returns (ITR):

• Net income or loss from business primary production

• Net income or loss from business non primary production

• Distribution from trusts primary production

• Net Personal Services Income

• Distribution from partnerships less foreign income non primary production

• Distribution from partnerships primary production

  These data exclude distributions from trusts for non-primary production activities as this may include aspects of investment income. It also excludes the income of working directors/owners of incorporated businesses who are classified as employees; consequently their income is included under Wage and salary income.

"Net personal services income" does not include income a person received as an employee, making it different from "Attributed personal services income".

All monetary values are presented as gross pre-tax dollars, as far as possible. This means they reflect income before deductions and loses, and before any taxation or levies (e.g. the Medicare levy or the temporary budget repair levy) are applied. The amounts shown are nominal, they have not been adjusted for inflation. The income presented in this release has been categorised into income types, these categories have been devised by the Australian Bureau of Statistics (ABS) to closely align to ABS definitions of income.

The statistics in this release are compiled from the Linked Employer Employee Dataset (LEED), a cross-sectional database based on administrative data from the Australian taxation system. The LEED includes more than 120 million tax records over seven consecutive years between 2011-12 and 2017-18.

Please note:

• All personal income tax statistics included in LEED were provided in de-identified form with no home address or date of birth. Addresses were coded to the ASGS and date of birth was converted to an age at 30 June of the reference year prior to data provision.

• To minimise the risk of identifying individuals in aggregate statistics, perturbation has been applied to the statistics in this release. Perturbation involves small random adjustment of the statistics and is considered the most satisfactory technique for avoiding the release of identifiable statistics, while maximising the range of information that can be released. These adjustments have a negligible impact on the underlying pattern of the statistics. Some cells have also been suppressed due to low counts.

• Totals may not align with the sum of their components due to missing or unpublished information in the underlying data and perturbation.

For further information please visit the Australian Bureau of Statistics.

AURIN has made the following changes to the original data:

• Spatially enabled the original data.

• Set 'np' (not published to protect the confidentiality of individuals or businesses) values to Null.

Inflation Expectations in New Zealand decreased to 2.28 percent in the third quarter of 2025 from 2.29 percent in the second quarter of 2025. This dataset provides - New Zealand Business Inflation Expectations- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Consumer Confidence in the United States decreased to 58.20 points in August from 61.70 points in July of 2025. This dataset provides the latest reported value for - United States Consumer Sentiment - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.