Graph and download economic data for Government current expenditures: Economic affairs: Space (G160241A027NBEA) from 1959 to 2023 about outer space, economic affairs, expenditures, government, GDP, and USA.

Techsalerator’s News Event Data in Latin America offers a detailed and extensive dataset designed to provide businesses, analysts, journalists, and researchers with an in-depth view of significant news events across the Latin American region. This dataset captures and categorizes key events reported from a wide array of news sources, including press releases, industry news sites, blogs, and PR platforms, offering valuable insights into regional developments, economic changes, political shifts, and cultural events.

Key Features of the Dataset: Comprehensive Coverage:

The dataset aggregates news events from numerous sources such as company press releases, industry news outlets, blogs, PR sites, and traditional news media. This broad coverage ensures a wide range of information from multiple reporting channels. Categorization of Events:

News events are categorized into various types including business and economic updates, political developments, technological advancements, legal and regulatory changes, and cultural events. This categorization helps users quickly locate and analyze information relevant to their interests or sectors. Real-Time Updates:

The dataset is updated regularly to include the most recent events, ensuring users have access to the latest news and can stay informed about current developments. Geographic Segmentation:

Events are tagged with their respective countries and regions within Latin America. This geographic segmentation allows users to filter and analyze news events based on specific locations, facilitating targeted research and analysis. Event Details:

Each event entry includes comprehensive details such as the date of occurrence, source of the news, a description of the event, and relevant keywords. This thorough detailing helps in understanding the context and significance of each event. Historical Data:

The dataset includes historical news event data, enabling users to track trends and perform comparative analysis over time. This feature supports longitudinal studies and provides insights into how news events evolve. Advanced Search and Filter Options:

Users can search and filter news events based on criteria such as date range, event type, location, and keywords. This functionality allows for precise and efficient retrieval of relevant information. Latin American Countries Covered: South America: Argentina Bolivia Brazil Chile Colombia Ecuador Guyana Paraguay Peru Suriname Uruguay Venezuela Central America: Belize Costa Rica El Salvador Guatemala Honduras Nicaragua Panama Caribbean: Cuba Dominican Republic Haiti (Note: Primarily French-speaking but included due to geographic and cultural ties) Jamaica Trinidad and Tobago Benefits of the Dataset: Strategic Insights: Businesses and analysts can use the dataset to gain insights into significant regional developments, economic conditions, and political changes, aiding in strategic decision-making and market analysis. Market and Industry Trends: The dataset provides valuable information on industry-specific trends and events, helping users understand market dynamics and emerging opportunities. Media and PR Monitoring: Journalists and PR professionals can track relevant news across Latin America, enabling them to monitor media coverage, identify emerging stories, and manage public relations efforts effectively. Academic and Research Use: Researchers can utilize the dataset for longitudinal studies, trend analysis, and academic research on various topics related to Latin American news and events. Techsalerator’s News Event Data in Latin America is a crucial resource for accessing and analyzing significant news events across the region. By providing detailed, categorized, and up-to-date information, it supports effective decision-making, research, and media monitoring across diverse sectors.

Techsalerator’s News Event Data in Asia offers a detailed and expansive dataset designed to provide businesses, analysts, journalists, and researchers with comprehensive insights into significant news events across the Asian continent. This dataset captures and categorizes major events reported from a diverse range of news sources, including press releases, industry news sites, blogs, and PR platforms, offering valuable perspectives on regional developments, economic shifts, political changes, and cultural occurrences.

Key Features of the Dataset: Extensive Coverage:

The dataset aggregates news events from a wide range of sources such as company press releases, industry-specific news outlets, blogs, PR sites, and traditional media. This broad coverage ensures a diverse array of information from multiple reporting channels. Categorization of Events:

News events are categorized into various types including business and economic updates, political developments, technological advancements, legal and regulatory changes, and cultural events. This categorization helps users quickly find and analyze information relevant to their interests or sectors. Real-Time Updates:

The dataset is updated regularly to include the most current events, ensuring users have access to the latest news and can stay informed about recent developments as they happen. Geographic Segmentation:

Events are tagged with their respective countries and regions within Asia. This geographic segmentation allows users to filter and analyze news events based on specific locations, facilitating targeted research and analysis. Event Details:

Each event entry includes comprehensive details such as the date of occurrence, source of the news, a description of the event, and relevant keywords. This thorough detailing helps users understand the context and significance of each event. Historical Data:

The dataset includes historical news event data, enabling users to track trends and perform comparative analysis over time. This feature supports longitudinal studies and provides insights into the evolution of news events. Advanced Search and Filter Options:

Users can search and filter news events based on criteria such as date range, event type, location, and keywords. This functionality allows for precise and efficient retrieval of relevant information. Asian Countries and Territories Covered: Central Asia: Kazakhstan Kyrgyzstan Tajikistan Turkmenistan Uzbekistan East Asia: China Hong Kong (Special Administrative Region of China) Japan Mongolia North Korea South Korea Taiwan South Asia: Afghanistan Bangladesh Bhutan India Maldives Nepal Pakistan Sri Lanka Southeast Asia: Brunei Cambodia East Timor (Timor-Leste) Indonesia Laos Malaysia Myanmar (Burma) Philippines Singapore Thailand Vietnam Western Asia (Middle East): Armenia Azerbaijan Bahrain Cyprus Georgia Iraq Israel Jordan Kuwait Lebanon Oman Palestine Qatar Saudi Arabia Syria Turkey (partly in Europe, but often included in Asia contextually) United Arab Emirates Yemen Benefits of the Dataset: Strategic Insights: Businesses and analysts can use the dataset to gain insights into significant regional developments, economic conditions, and political changes, aiding in strategic decision-making and market analysis. Market and Industry Trends: The dataset provides valuable information on industry-specific trends and events, helping users understand market dynamics and identify emerging opportunities. Media and PR Monitoring: Journalists and PR professionals can track relevant news across Asia, enabling them to monitor media coverage, identify emerging stories, and manage public relations efforts effectively. Academic and Research Use: Researchers can utilize the dataset for longitudinal studies, trend analysis, and academic research on various topics related to Asian news and events. Techsalerator’s News Event Data in Asia is a crucial resource for accessing and analyzing significant news events across the continent. By offering detailed, categorized, and up-to-date information, it supports effective decision-making, research, and media monitoring across diverse sectors.

This 6MB download is a zip file containing 5 pdf documents and 2 xlsx spreadsheets. Presentation on COVID-19 and the potential impacts on employment

May 2020Waka Kotahi wants to better understand the potential implications of the COVID-19 downturn on the land transport system, particularly the potential impacts on regional economies and communities.

To do this, in May 2020 Waka Kotahi commissioned Martin Jenkins and Infometrics to consider the potential impacts of COVID-19 on New Zealand’s economy and demographics, as these are two key drivers of transport demand. In addition to providing a scan of national and international COVID-19 trends, the research involved modelling the economic impacts of three of the Treasury’s COVID-19 scenarios, to a regional scale, to help us understand where the impacts might be greatest.

Waka Kotahi studied this modelling by comparing the percentage difference in employment forecasts from the Treasury’s three COVID-19 scenarios compared to the business as usual scenario.

The source tables from the modelling (Tables 1-40), and the percentage difference in employment forecasts (Tables 41-43), are available as spreadsheets.

Arataki - potential impacts of COVID-19 Final Report

Employment modelling - interactive dashboard

The modelling produced employment forecasts for each region and district over three time periods – 2021, 2025 and 2031. In May 2020, the forecasts for 2021 carried greater certainty as they reflected the impacts of current events, such as border restrictions, reduction in international visitors and students etc. The 2025 and 2031 forecasts were less certain because of the potential for significant shifts in the socio-economic situation over the intervening years. While these later forecasts were useful in helping to understand the relative scale and duration of potential COVID-19 related impacts around the country, they needed to be treated with care recognising the higher levels of uncertainty.

The May 2020 research suggested that the ‘slow recovery scenario’ (Treasury’s scenario 5) was the most likely due to continuing high levels of uncertainty regarding global efforts to manage the pandemic (and the duration and scale of the resulting economic downturn).

The updates to Arataki V2 were framed around the ‘Slower Recovery Scenario’, as that scenario remained the most closely aligned with the unfolding impacts of COVID-19 in New Zealand and globally at that time.

Find out more about Arataki, our 10-year plan for the land transport system

May 2021The May 2021 update to employment modelling used to inform Arataki Version 2 is now available. Employment modelling dashboard - updated 2021Arataki used the May 2020 information to compare how various regions and industries might be impacted by COVID-19. Almost a year later, it is clear that New Zealand fared better than forecast in May 2020.Waka Kotahi therefore commissioned an update to the projections through a high-level review of:the original projections for 2020/21 against performancethe implications of the most recent global (eg International monetary fund world economic Outlook) and national economic forecasts (eg Treasury half year economic and fiscal update)The treasury updated its scenarios in its December half year fiscal and economic update (HYEFU) and these new scenarios have been used for the revised projections.Considerable uncertainty remains about the potential scale and duration of the COVID-19 downturn, for example with regards to the duration of border restrictions, update of immunisation programmes. The updated analysis provides us with additional information regarding which sectors and parts of the country are likely to be most impacted. We continue to monitor the situation and keep up to date with other cross-Government scenario development and COVID-19 related work. The updated modelling has produced employment forecasts for each region and district over three time periods - 2022, 2025, 2031.The 2022 forecasts carry greater certainty as they reflect the impacts of current events. The 2025 and 2031 forecasts are less certain because of the potential for significant shifts over that time.

Data reuse caveats: as per license.

Additionally, please read / use this data in conjunction with the Infometrics and Martin Jenkins reports, to understand the uncertainties and assumptions involved in modelling the potential impacts of COVID-19.

COVID-19’s effect on industry and regional economic outcomes for NZ Transport Agency [PDF 620 KB]

Data quality statement: while the modelling undertaken is high quality, it represents two point-in-time analyses undertaken during a period of considerable uncertainty. This uncertainty comes from several factors relating to the COVID-19 pandemic, including:

a lack of clarity about the size of the global downturn and how quickly the international economy might recover differing views about the ability of the New Zealand economy to bounce back from the significant job losses that are occurring and how much of a structural change in the economy is required the possibility of a further wave of COVID-19 cases within New Zealand that might require a return to Alert Levels 3 or 4.

While high levels of uncertainty remain around the scale of impacts from the pandemic, particularly in coming years, the modelling is useful in indicating the direction of travel and the relative scale of impacts in different parts of the country.

Data quality caveats: as noted above, there is considerable uncertainty about the potential scale and duration of the COVID-19 downturn. Please treat the specific results of the modelling carefully, particularly in the forecasts to later years (2025, 2031), given the potential for significant shifts in New Zealand's socio-economic situation before then.

As such, please use the modelling results as a guide to the potential scale of the impacts of the downturn in different locations, rather than as a precise assessment of impacts over the coming decade.

This statistic shows the share of respondents stating 'the economy' as one of the most important issues facing Great Britain as of **********, by voting intention. The Liberal Democrat party had the greatest share of supporters who think the economy is one of the most important issues facing Great Britain.

Techsalerator’s News Event Data in Europe is a comprehensive and meticulously curated dataset designed to provide businesses, analysts, journalists, and researchers with an extensive view of significant news events across Europe. This dataset captures and categorizes key events reported from a variety of news sources, offering valuable insights into industry developments, economic changes, political shifts, and other noteworthy occurrences throughout the continent.

Key Features of the Dataset: Extensive Coverage:

The dataset aggregates news events from a wide range of sources including press releases, industry news sites, blogs, PR platforms, and traditional news outlets. This broad coverage ensures that users receive a diverse array of information from multiple reporting channels. Categorization of Events:

News events are meticulously categorized into various types such as business and financial updates, political developments, technological advancements, legal and regulatory changes, and cultural events. This categorization helps users quickly locate and analyze information relevant to specific interests or sectors. Real-Time Updates:

Data is updated regularly to include the most current events. This ensures that users have access to the latest information and can stay informed about recent developments as they unfold. Geographic Segmentation:

Events are tagged with their respective countries and regions within Europe. This geographic segmentation allows users to filter and analyze news events based on specific locations, facilitating targeted research and analysis. Event Details:

Each event entry includes detailed information such as the date of occurrence, source of the news, event description, and relevant keywords. This comprehensive detail aids in understanding the context and significance of each event. Historical Data:

The dataset includes historical news event data, enabling users to track trends and analyze changes over time. This feature supports longitudinal studies and comparative analysis of historical and recent events. Advanced Search and Filter Options:

Users can search and filter news events based on various criteria such as date range, event type, location, and keywords. This functionality allows for precise and efficient retrieval of relevant information. European Countries Covered: Austria Belgium Bulgaria Croatia Cyprus Czech Republic Denmark Estonia Finland France Germany Greece Hungary Ireland Italy Latvia Lithuania Luxembourg Malta Netherlands Poland Portugal Romania Slovakia Slovenia Spain Sweden Benefits of the Dataset: Informed Decision-Making: Businesses and analysts can leverage the dataset to stay updated on key developments that may impact their operations, market conditions, or strategic decisions. Market and Industry Analysis: The dataset provides valuable insights into industry trends, economic changes, and political events, helping users analyze market dynamics and make informed decisions. Media and PR Monitoring: Journalists and PR professionals can track relevant news and events across Europe, allowing them to monitor media coverage, identify emerging stories, and manage public relations efforts effectively. Academic and Research Purposes: Researchers can use the dataset for longitudinal studies, trend analysis, and academic research on various topics related to European news and events. Techsalerator’s News Event Data in Europe is a vital resource for accessing and analyzing significant news events across the continent. By offering detailed, categorized, and up-to-date information, it supports effective decision-making, research, and media monitoring across diverse sectors.

The database used includes annual frequency data for 43 countries, defined by the IMF as 24 advanced countries and 19 emerging countries, for the years 1992-2018.The database contains the fiscal stress variable and a set of variables that can be classified as follows: macroeconomic and global economy (interest rates in the US, OECD; real GDP in the US, y-o-y, OECD; real GDP in China, y-o-y, World Bank; oil price, y-o-y, BP p.l.c.; VIX, CBOE; real GDP, y-o-y, World Bank, OECD, IMF WEO; GDP per capita in PPS, World Bank); financial (nominal USD exchange rate, y-o-y, IMF IFS; private credit to GDP, change in p.p., IMF IFS, World Bank and OECD); fiscal (general government balance, % GDP, IMF WEO; general government debt, % GDP, IMF WEO, effective interest rate on the g.g. debt, IMF WEO); competitiveness and domestic demand (currency overvaluation, IMF WEO; current account balance, % GDP, IMF WEO; share in global exports, y-o-y, World Bank, OECD; gross fixed capital formation, y-o-y, World Bank, OECD; CPI, IMF IFS, IMF WEO; real consumption, y-o-y, World Bank, OECD); labor market (unemployment rate, change in p.p., IMF WEO; labor productivity, y-o-y, ILO).In line with the convention adopted in the literature, the fiscal stress variable is a binary variable equal to 1 in the case of a fiscal stress event and 0 otherwise. In more recent literature in this field, the dependent variable tends to be defined broadly, reflecting not only outright default or debt restructuring, but also less extreme events. Therefore, following Baldacci et al. (2011), the definition used in the present database is broad, and the focus is on signalling fiscal stress events, in contrast to the narrower event of a fiscal crisis related to outright default or debt restructuring. Fiscal problems can take many forms; in particular, some of the outright defaults can be avoided through timely, targeted responses, like support programs of international institutions. The fiscal stress variable is shifted with regard to the other variables: crisis_next_year – binary variable shifted by 1 year, all years of a fiscal stress coded as 1; crisis_next_period – binary variable shifted by 2 years, all years of a fiscal stress coded as 1; crisis_first_year1 – binary variable shifted by 1 year, only the first year of a fiscal stress coded as 1; crisis_first_year2 - binary variable shifted by 2 years, only the first year of a fiscal stress coded as 1.

Techsalerator’s News Event Data in North America offers a comprehensive and detailed dataset designed to provide businesses, analysts, journalists, and researchers with a thorough view of significant news events across North America. This dataset captures and categorizes major events reported from a diverse range of news sources, including press releases, industry news sites, blogs, and PR platforms, providing valuable insights into regional developments, economic shifts, political changes, and cultural events.

Key Features of the Dataset: Extensive Coverage:

The dataset aggregates news events from a wide array of sources, including company press releases, industry-specific news outlets, blogs, PR sites, and traditional media. This broad coverage ensures a diverse range of information from multiple reporting channels. Categorization of Events:

News events are categorized into various types such as business and economic updates, political developments, technological advancements, legal and regulatory changes, and cultural events. This categorization helps users quickly find and analyze information relevant to their interests or sectors. Real-Time Updates:

The dataset is updated regularly to include the most current events, ensuring that users have access to up-to-date news and can stay informed about recent developments as they happen. Geographic Segmentation:

Events are tagged with their respective countries and territories within North America. This geographic segmentation allows users to filter and analyze news events based on specific locations, facilitating targeted research and analysis. Event Details:

Each event entry includes comprehensive details such as the date of occurrence, source of the news, a description of the event, and relevant keywords. This thorough detailing helps users understand the context and significance of each event. Historical Data:

The dataset includes historical news event data, enabling users to track trends and conduct comparative analysis over time. This feature supports longitudinal studies and provides insights into how news events evolve. Advanced Search and Filter Options:

Users can search and filter news events based on criteria such as date range, event type, location, and keywords. This functionality allows for precise and efficient retrieval of relevant information. North American Countries and Territories Covered: Countries: Canada Mexico United States Territories: American Samoa (U.S. territory) French Polynesia (French overseas collectivity; included for regional relevance) Guam (U.S. territory) New Caledonia (French special collectivity; included for regional relevance) Northern Mariana Islands (U.S. territory) Puerto Rico (U.S. territory) Saint Pierre and Miquelon (French overseas territory; geographically close to North America and included for regional comprehensiveness) Wallis and Futuna (French overseas collectivity; included for regional relevance) Benefits of the Dataset: Strategic Insights: Businesses and analysts can use the dataset to gain insights into significant regional developments, economic conditions, and political changes, aiding in strategic decision-making and market analysis. Market and Industry Trends: The dataset provides valuable information on industry-specific trends and events, helping users understand market dynamics and identify emerging opportunities. Media and PR Monitoring: Journalists and PR professionals can track relevant news across North America, enabling them to monitor media coverage, identify emerging stories, and manage public relations efforts effectively. Academic and Research Use: Researchers can utilize the dataset for longitudinal studies, trend analysis, and academic research on various topics related to North American news and events. Techsalerator’s News Event Data in North America is a crucial resource for accessing and analyzing significant news events across the continent. By providing detailed, categorized, and up-to-date information, it supports effective decision-making, research, and media monitoring across diverse sectors.

A. SUMMARY San Francisco offers numerous events and activities tailored for children, youth, and families. However, finding and navigating the disparate sources of information can be a major challenge. Our415.org seeks to simplify this by consolidating all relevant details, ensuring that families can easily find what they need, when they need it. It also encourages discovery of new interests and things to do. This dataset compiles current and upcoming events and activities in San Francisco for children, youth, and their families.

B. HOW THE DATASET IS CREATED This dataset is a consolidation of multiple datasets from contributing City agencies and departments as well as Community Based Organizations. Currently, the information in the dataset is sourced from Rec Park’s activities catalog, SF Public Library’s events calendar, Department of Early Childhood’s family events calendar, and Support for Families' family events calendar. Rec Park activities include any “Open” activities appropriate for ages 0-24, and SF Public Library, Department of Early Childhood, and Support for Families events include events going into the next month.

C. UPDATE PROCESS The dataset will be updated on a daily basis, reflecting changes to the source data.

D. HOW TO USE THIS DATASET Taxonomy related fields and eligibility fields are either AI-determined or assigned through a DCYF-created crosswalk. These values are determined for the purposes of categorization and search functionality on Our415.org. Use with caution - errors may exist.

The Long Depression was, by a large margin, the longest-lasting recession in U.S. history. It began in the U.S. with the Panic of 1873, and lasted for over five years. This depression was the largest in a series of recessions at the turn of the 20th century, which proved to be a period of overall stagnation as the U.S. financial markets failed to keep pace with industrialization and changes in monetary policy. Great Depression The Great Depression, however, is widely considered to have been the most severe recession in U.S. history. Following the Wall Street Crash in 1929, the country's economy collapsed, wages fell and a quarter of the workforce was unemployed. It would take almost four years for recovery to begin. Additionally, U.S. expansion and integration in international markets allowed the depression to become a global event, which became a major catalyst in the build up to the Second World War. Decreasing severity When comparing recessions before and after the Great Depression, they have generally become shorter and less frequent over time. Only three recessions in the latter period have lasted more than one year. Additionally, while there were 12 recessions between 1880 and 1920, there were only six recessions between 1980 and 2020. The most severe recession in recent years was the financial crisis of 2007 (known as the Great Recession), where irresponsible lending policies and lack of government regulation allowed for a property bubble to develop and become detached from the economy over time, this eventually became untenable and the bubble burst. Although the causes of both the Great Depression and Great Recession were similar in many aspects, economists have been able to use historical evidence to try and predict, prevent, or limit the impact of future recessions.

Series Name: Direct economic loss to cultural heritage damaged or destroyed attributed to disasters (millions of current United States dollars)Series Code: VC_DSR_CHLNRelease Version: 2021.Q2.G.03 This dataset is part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 1.5.2: Direct economic loss attributed to disasters in relation to global gross domestic product (GDP)Target 1.5: By 2030, build the resilience of the poor and those in vulnerable situations and reduce their exposure and vulnerability to climate-related extreme events and other economic, social and environmental shocks and disastersGoal 1: End poverty in all its forms everywhereFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

Introducing our comprehensive economic calendar, your ultimate resource for tracking major global economic events and their impact on currency and stock market prices. With a vast array of fields including event name, country, previous and current values, and more, our calendar provides you with essential data to make informed financial decisions. Stay ahead of the curve with our real-time updates, ensuring you have access to the latest information every 15 minutes. With this powerful tool at your fingertips, you can confidently navigate the dynamic world of economic events and seize opportunities for success. Don't miss out on this essential resource for staying informed and making calculated moves in the market.

Techsalerator’s News Event Data in Oceania provides a thorough and detailed dataset designed to offer businesses, analysts, journalists, and researchers with comprehensive insights into significant news events across the Oceania region. This dataset captures and categorizes major events reported from a variety of news sources, including press releases, industry news sites, blogs, and PR platforms, offering valuable perspectives on regional developments, economic shifts, political changes, and cultural occurrences.

Key Features of the Dataset: Extensive Coverage:

The dataset aggregates news events from a wide range of sources such as company press releases, industry-specific news outlets, blogs, PR sites, and traditional media. This broad coverage ensures a diverse array of information from multiple reporting channels. Categorization of Events:

News events are categorized into various types including business and economic updates, political developments, technological advancements, legal and regulatory changes, and cultural events. This categorization helps users quickly find and analyze information relevant to their interests or sectors. Real-Time Updates:

The dataset is updated regularly to include the latest events, ensuring users have access to the most current news and can stay informed about recent developments as they occur. Geographic Segmentation:

Events are tagged with their respective countries and territories within Oceania. This geographic segmentation allows users to filter and analyze news events based on specific locations, facilitating targeted research and analysis. Event Details:

Each event entry includes comprehensive details such as the date of occurrence, source of the news, a description of the event, and relevant keywords. This thorough detailing helps users understand the context and significance of each event. Historical Data:

The dataset includes historical news event data, enabling users to track trends and perform comparative analysis over time. This feature supports longitudinal studies and provides insights into the evolution of news events. Advanced Search and Filter Options:

Users can search and filter news events based on various criteria such as date range, event type, location, and keywords. This functionality allows for precise and efficient retrieval of relevant information. Oceania Countries and Territories Covered: Australia and New Zealand: Australia New Zealand Pacific Island Countries and Territories: Fiji Kiribati Marshall Islands Micronesia (Federated States of) Nauru Palau Papua New Guinea Samoa Solomon Islands Tonga Tuvalu Vanuatu French Overseas Territories: New Caledonia (French special collectivity) French Polynesia (French overseas collectivity) Wallis and Futuna (French overseas collectivity) U.S. Territories: American Samoa (U.S. territory) Guam (U.S. territory) Northern Mariana Islands (U.S. territory) Benefits of the Dataset: Strategic Insights: Businesses and analysts can utilize the dataset to gain insights into significant regional developments, economic conditions, and political changes, aiding in strategic decision-making and market analysis. Market and Industry Trends: The dataset provides valuable information on industry-specific trends and events, helping users understand market dynamics and identify emerging opportunities. Media and PR Monitoring: Journalists and PR professionals can track relevant news across Oceania, enabling them to monitor media coverage, identify emerging stories, and manage public relations efforts effectively. Academic and Research Use: Researchers can leverage the dataset for longitudinal studies, trend analysis, and academic research on various topics related to Oceania’s news and events. Techsalerator’s News Event Data in Oceania is an essential resource for accessing and analyzing significant news events across the region. By offering detailed, categorized, and up-to-date information, it supports effective decision-making, research, and media monitoring across diverse sectors.

This dataset features 25,000 annotated sentences extracted from official central bank documents worldwide. Its primary purpose is to facilitate the analysis and deciphering of global central bank communications. Each sentence is categorised across three distinct tasks: Stance Detection, Temporal Classification, and Uncertainty Estimation, making it a valuable resource for understanding monetary policy sentiment and future outlook.

Columns

• sentence: The text extracted directly from official central bank documents.
• stance_label: Indicates the monetary policy stance, labelled as:
  • hawkish: Supporting a contractionary monetary policy.
  • dovish: Supporting an expansionary monetary policy.
  • neutral: Containing neither hawkish nor dovish sentiment, or a mix of both.
  • irrelevant: Not pertaining to monetary policy discussions.
• time_label: Specifies the temporal nature of the sentence:
  • forward-looking: Discusses future economic events or policy decisions.
  • not forward-looking: Discusses past or current economic events or decisions.
• certainty_label: Assesses the level of certainty conveyed:
  • certain: Information presented definitively.
  • uncertain: Information presented with speculation, possibility, or doubt.
• year: The publication year of the original document from which the sentence was taken.
• central_bank: The central bank that issued the document, drawn from a total of 25 different banks.

Distribution

The dataset is provided as a CSV file and contains 25,000 unique annotated sentences. The distribution of key labels is as follows: * Stance Labels: neutral (35%), dovish (33%), and other categories (32%). * Temporal Labels: not forward-looking (56%) and forward-looking (44%). * Uncertainty Labels: certain (77%) and uncertain (23%).

Usage

This dataset is ideally suited for applications in: * Natural Language Processing (NLP), including sentiment analysis and text classification. * Machine Learning (ML) model training for financial text understanding. * Data Science and Analytics projects focused on economic forecasting and policy impact. * Academic research into central banking and monetary policy communication.

Coverage

The dataset spans documents published from 1996 to 2024. It includes sentences originating from 25 different central banks, providing a global perspective on monetary policy communications.

License

CC-BY-NC-SA

Who Can Use It

• Data Scientists and Machine Learning Engineers for developing and testing NLP models.
• Economists and Financial Analysts seeking to analyse central bank statements and monetary policy trends.
• Academic Researchers in fields such as economics, finance, and computer science.
• Policymakers interested in understanding the communication strategies of global central banks.

Dataset Name Suggestions

• Global Central Bank Communication Data
• Monetary Policy Stance and Outlook Dataset
• Annotated Central Bank Statements
• Central Bank Text Analysis Corpus
• WCB Annotated Sentences

Attributes

Original Data Source: WCB Dataset (Annotated)

This Gallup poll explores the opinions of Canadians on various political issues, current events, and asks their predictions for the future. It also tackles such topics as unemployment and gender issues. All respondents were asked questions so that they could be classified according to demographic, geographic and social variables. Topics of interest include: car ownership; China; city problems; communism; economic depression; Eisenhower; elections; gender issues; housing; ideal job for women; international trade; life expectancy; marriage quarrels; price trends; Prime Minister; political parties; changes in postage price; Russia; sleeping patterns; unemployment rates; union membership; voting behaviour; work in an asylum; and the world tour taken by the Prime Minister. Basic demographics variables are also included.

Series Name: Direct economic loss in the housing sector attributed to disasters (current United States dollars)Series Code: VC_DSR_HOLHRelease Version: 2021.Q2.G.03 This dataset is part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 1.5.2: Direct economic loss attributed to disasters in relation to global gross domestic product (GDP)Target 1.5: By 2030, build the resilience of the poor and those in vulnerable situations and reduce their exposure and vulnerability to climate-related extreme events and other economic, social and environmental shocks and disastersGoal 1: End poverty in all its forms everywhereFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

Series Name: Direct agriculture loss attributed to disasters (current United States dollars)Series Code: VC_DSR_AGLHRelease Version: 2021.Q2.G.03 This dataset is part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 1.5.2: Direct economic loss attributed to disasters in relation to global gross domestic product (GDP)Target 1.5: By 2030, build the resilience of the poor and those in vulnerable situations and reduce their exposure and vulnerability to climate-related extreme events and other economic, social and environmental shocks and disastersGoal 1: End poverty in all its forms everywhereFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

This national survey focuses on attitudes toward economic conditions, causes of inflation, and wage-price controls.Questions include personal financial status, equity of various price increases, overall performance and effectiveness of Pay Board and Price Commission, prices of food and other goods, wage increases, wage- price freeze. There are also some current events questions that focus on the upcoming presidential election and include rating of Richard Nixon, Spiro Agnew, and George McGovern.

This dataset includes the replication code and supporting data files for the accepted piece by Foreign Policy Analysis (Manuscript ID FPA-22-Jul-0118.R1), including the data, R script file, R script file in Word document format, R script file in PDF format, and a code book.

Series Name: Direct economic loss resulting from damaged or destroyed critical infrastructure attributed to disasters (current United States dollars)Series Code: VC_DSR_CILNRelease Version: 2021.Q2.G.03 This dataset is part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 1.5.2: Direct economic loss attributed to disasters in relation to global gross domestic product (GDP)Target 1.5: By 2030, build the resilience of the poor and those in vulnerable situations and reduce their exposure and vulnerability to climate-related extreme events and other economic, social and environmental shocks and disastersGoal 1: End poverty in all its forms everywhereFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/