This dataset provides a comprehensive collection of key U.S. macroeconomic indicators spanning the past 25 years (approximately 1998–2023). It includes monthly data on:

M2 Money Supply (M2SL): A broad measure of money in circulation, including cash, checking deposits, and easily convertible near money. Federal Funds Effective Rate (FEDFUNDS): The interest rate at which depository institutions trade federal funds with each other overnight. Interest Rates: Various benchmark interest rates relevant to economic analysis. 10-Year Treasury Constant Maturity Rate (GS10): Reflects market expectations for long-term interest rates and economic growth. All data are sourced from the Federal Reserve Economic Data (FRED) database and are seasonally adjusted where applicable.

This dataset is ideal for economic research, financial modeling, market forecasting, and machine learning applications where macroeconomic variables are relevant. The data is cleaned, merged, and formatted for immediate use, with date-stamped entries aligned on a monthly frequency.

Source: Federal Reserve Economic Data (FRED) — https://fred.stlouisfed.org/

License: CC0: Public Domain

Permutable AI’s Global Macro Sentiment API provides aggregated sentiment data for global macroeconomic topics, including inflation, GDP, monetary policy, fiscal policy, geopolitics, and natural disasters. With support for Python, R, and Java client libraries, plus webhook integration, the API allows developers and analysts to retrieve structured insights from news sources within custom date ranges. Parameters include start and end dates (30-day lookback), filtering by sources, and strict real-time extraction options. Data outputs include sentiment scores, topic classifications, and aggregated publication timestamps—ideal for market insights, trading strategies, and research applications. Full API reference documentation is available at copilot-api.permutable.ai/redoc .

AMECO is the annual macro-economic database of the European Commission's Directorate General for Economic and Financial Affairs (DG ECFIN). The database is regularly cited in DG ECFIN's publications and is indispensable for DG ECFIN's analyses and reports. To ensure that DG ECFIN's analyses are verifiable and transparent to the public, AMECO data is made available free of charge. AMECO contains data for EU-27, the euro area, EU Member States, candidate countries and other OECD countries (United States, Japan, Canada, Switzerland, Norway, Iceland, Mexico, Korea, Australia and New Zealand).

Here, we present a comprehensive traits database for the butterflies and macro-moths of Great Britain and Ireland. The database covers 968 species in 21 families. Ecological traits fall into four main categories: life cycle ecology and phenology, host plant specificity and characteristics, breeding habitat, and morphological characteristics. The database also contains data regarding species distribution, conservation status, and temporal trends for abundance and occupancy. This database can be used for a wide array of purposes including further fundamental research on species and community responses to environmental change, conservation and management studies, and evolutionary biology. A more recent version of the dataset is available at https://doi.org/10.5285/dbc7cc17-cbbd-49dd-bab4-8e8855768d66 entitled 'Traits data for the butterflies and macro-moths of Great Britain and Ireland, 2024'.

The Economic Indicator Service (EIS) aims to deliver economic content to financial institutions on both buy and sell-side and service providers. This new service currently covers 34,351 recurring macro-economic indicators from 135 countries ( as of December 16, 2019 ) such as GDP data, unemployment releases, PMI numbers etc.

Economic Indicator Service gathers the major economic events from a variety of regions and countries around the globe and provides an Economic Events Data feed and Economic Calendar service to our clients. This service includes all previous historic data on economic indicators that are currently available on the database.

Depending on availability, information regarding economic indicators, including the details of the issuing agency as well as historical data series can be made accessible for the client. Key information about EIS: • Cloud-based service for Live Calendar – delivered via HTML/JavaScript application formats, which can then be embedded onto any website using iFrames • Alternatives methods available – such as API and JSON feed for the economic calendar that can be integrated into the company’s system • Live data – updated 24/5, immediately after the data has been released • Historical data – includes a feed of all previous economic indicators available We are currently adding additional indicators/countries from Africa as well as expanding our coverage of Indicators in G20. The calendar includes the following. • Recurring & Non-recurring indicators covering 136 countries across 21 regions. • Indicators showing high, medium, and low impact data. • Indicators showing actual, previous, and forecast data. • Indicators can be filtered across 16 subtypes. • News generation for selected high-impact data. • Indicator description and historical data up to the latest eight historical points with a chart.

AMECO is the annual macro-economic database of DG ECFIN, the European Commission's Directorate General for Economic and Financial Affairs.

The database is regularly cited in DG ECFIN's publications and is indispensable for DG ECFIN's analyses and reports. AMECO contains data, mainly from the national accounts domain, for EU-27, the euro area, EU Member States, candidate countries and other OECD countries (United Kingdom, United States, Japan, Canada, Switzerland, Norway, Iceland, Mexico, Korea, Australia and New Zealand).

The Latin Macro Watch (LMW) is a comprehensive macroeconomic and financial dataset developed by the Inter-American Development Bank (IDB). It provides economic indicators and historical data on growth, employment, fiscal accounts, external balances, financial markets, and forecasts for Latin America and the Caribbean.

The dataset includes monthly, quarterly, and annual data beginning in 1990, covering the 26 borrowing member countries of the IDB. Users can explore variables such as GDP, consumption, trade, inflation, and debt to analyze macroeconomic trends and regional development patterns.

The Latin Macro Watch Dataset is currently undergoing a revision and enhancement process to improve data quality, coverage, and accessibility. Updated data will continue to be made available through the IDB Open Data Portal, enabling policymakers, researchers, and economists to make data-driven decisions.

Dataset

This dataset was created by KRKirov

Released under Database: Open Database, Contents: Database Contents

Contents

This data is used for article of macroeconomic of some Asian countries in long period which explained about four Asian countries, such as Indonesia, Malaysia, Singapore, and South Korea. This data has taken from World Bank Development Indicators (WDI) database and is formed by Vector Auto Regression (VAR) model, then empirical result is executed by Granger causality model on E-views 11 program to gauge the relationship between gross domestic product, exchange rate, inflation rate, foreign direct investment, net export, government expenditures, unemployment rate, and savings. The results showed that most of gross domestic product of sample and other macro-economy variables have not causality relationship.

In April and May 2019, we compiled the “BenBio” part of the “BenBioDen database” following the “Preferred Reporting Items for Systematic reviews and Meta-Analyses” (PRISMA) Statement for systematic reviews and meta-analyses. In the first PRISMA step, the “Identification” step, we identified 1,373 articles in the Web of Science using the key words “marine meiofauna biomass”, “marine macrofauna biomass”, “marine megafauna biomass”, “marine meiobenth* biomass”, “marine macrobenth* biomass”, “marine megabenth* biomass”, “nematode biomass”, and “benthic ‘standing stock’”. We located an additional 201 publications based on expert knowledge. A search of the PANGAEA® Data Publisher (https://www.pangaea.de/) identified 1,488 datasets representing 148 publications using the key words “meiofauna biomass”, “macrofauna biomass” and “megafauna biomass”. Further 30 datasets were found in the EOL data archive (http://data.eol.ucar.edu/), through citations in review papers, and based on expert knowledge...

Classification of the territory as urbanised, urbanizable or rural according to the provisions of art. 28 of Regional Law 20/2000. The urbanized territory "includes all the areas actually built or under construction and the enclosed lots", the rural territory is made up of all the non-urbanized territory and is characterized by the need to integrate and make coherent policies aimed at safeguarding the natural, environmental and landscape of the territory with policies aimed at guaranteeing the development of sustainable agricultural activities"; the urbanizable territory is "rural territory susceptible to urbanization". Each type of territory is characterized by the maximum settlement quantification envisaged by the urban plan for new housing and for new settlements productive or specialized.

1613 Global export shipment records of Macro Camera with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

China Macro-economic Climate Index: Coincident Index data was reported at 98.800 2019=100 in Nov 2024. This records a decrease from the previous number of 98.900 2019=100 for Oct 2024. China Macro-economic Climate Index: Coincident Index data is updated monthly, averaging 98.600 2019=100 from Dec 2022 (Median) to Nov 2024, with 24 observations. The data reached an all-time high of 100.100 2019=100 in Nov 2023 and a record low of 95.305 2019=100 in Dec 2022. China Macro-economic Climate Index: Coincident Index data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Business and Economic Survey – Table CN.OF: Economic Climate Indicator.

These macro-invertebrate data incorporate the results from the national river water quality network (NRWQN) from 66 sites throughout New Zealand for the purpose of monitoring long-term trends. Data included: 1990 to 2008. The NRWQN was funded by the Foundation for Research, Science, & Technology through NIWA's Nationally Significant Database: Water Resources & Climate programme. Current funding (from July 2011) comes from the NIWA Environmental Information/Monitoring programme core funding. The data are collected annually in summer, and data collection was initiated in January 1989.

The database MOVE-SUF presents a macro-data-compilation of the MOVE project (macro-analysis in work-package 2) which has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No. 649263. The consortium of MOVE comprises nine partners in six countries: Luxembourg, Germany, Hungary, Norway, Romania, and Spain. The main objective of MOVE is to provide evidence-based knowledge on mobility of young people in Europe as a prerequisite to improve mobility conditions, and to identify fostering and hindering factors of mobility. The objective was followed by using a multilevel interdisciplinary research design, combining macro- and micro analysis with three empricial approaches. The MOVE-SUF was compiled within the macro-analysis approach: “Sampling and secondary analyses of macro data of youth mobility in Europe and the partner countries” by the German Youth Institute. The MOVE-SUF served as basis for the secondary data-analyses within the MOVE project and is now published as open-access available dataset. The MOVE-SUF is set up with data from all EU-28 and 3 EFTA countries (CH, IS, NO), with a total of 31 country-cases. The MOVE-SUF covers a core period of 10 years (2004-2013). For some indicators data for 2014 can be provided additionally. For single variables data was not available for all years of the core period (the covered period for each variable can be seen in each variable name). If only yearly data for single countries was missing, the cells were left empty. The MOVE-SUF is compiled only with comparable macro data derived from the following institutions: EUROSTAT, OECD, UN and World Bank. The Users Manual includes links to the data sources which provide additional information. AggregationKompilation AggregationCompilation Macro indicators of the 31 countries, youth mobility indicators for people from 15 up to 29 years

Dataset

This dataset was created by FML

Contents

Argentina Banco Macro SA: Assets: Miscellaneous Receivables data was reported at 349,677,507.000 ARS th in Jan 2025. This records an increase from the previous number of 333,020,984.000 ARS th for Dec 2024. Argentina Banco Macro SA: Assets: Miscellaneous Receivables data is updated monthly, averaging 496,241.000 ARS th from May 2001 (Median) to Jan 2025, with 285 observations. The data reached an all-time high of 349,677,507.000 ARS th in Jan 2025 and a record low of 10.800 ARS th in Oct 2001. Argentina Banco Macro SA: Assets: Miscellaneous Receivables data remains active status in CEIC and is reported by Central Bank of Argentina. The data is categorized under Global Database’s Argentina – Table AR.KB033: Balance Sheet: Banco Macro S.A..

Argentina Banco Macro SA: Liabilities: Deposits: NFPS & Residents: Others data was reported at 92,211,369.000 ARS th in Jan 2025. This records a decrease from the previous number of 103,321,086.000 ARS th for Dec 2024. Argentina Banco Macro SA: Liabilities: Deposits: NFPS & Residents: Others data is updated monthly, averaging 695,067.000 ARS th from May 2001 (Median) to Jan 2025, with 285 observations. The data reached an all-time high of 103,321,086.000 ARS th in Dec 2024 and a record low of 15.800 ARS th in Nov 2001. Argentina Banco Macro SA: Liabilities: Deposits: NFPS & Residents: Others data remains active status in CEIC and is reported by Central Bank of Argentina. The data is categorized under Global Database’s Argentina – Table AR.KB033: Balance Sheet: Banco Macro S.A..

Permutable AI’s G7 macroeconomic sentiment datasets deliver structured quantitative analytics by transforming unstructured global news into actionable insights. Powered by proprietary large language models, our platform captures sentiment around monetary policy from the Federal Reserve, ECB, Bank of England, and Bank of Japan, refreshing every five minutes. Additional feeds quantify reactions to key economic indicators such as employment, GDP, and inflation, while geopolitical intelligence tracks trade tensions, elections, and G7 summit communications. Real-time natural disaster tracking scores supply chain risks, with ten years of historical datasets available for backtesting systematic trading strategies. Accessible through the Co-Pilot API, the platform offers millisecond-latency sentiment scores, event classifications, and risk metrics for institutional-grade market analysis.

This page provides the data of the manuscript: Martínez, C. G. B., Niediek, J., Mormann, F. & Andrzejak,R. G. Seizure onset zone lateralization using a nonlinear analysis of micro versus macro electroencephalographic recordings during seizure-free stages of the sleep-wake cycle from epilepsy patients. Frontiers in Neurology 11, 1057, 2020. If you use any of this data, please make sure that you cite this reference. For more detailed information, please refer to https://www.upf.edu/web/ntsa/downloads