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.
Attribution-NonCommercial 3.0 (CC BY-NC 3.0)https://creativecommons.org/licenses/by-nc/3.0/
License information was derived automatically
Description: This dataset contains historical economic data spanning from 1871 to 2024, used in Jaouad Karfali’s research on Economic Cycle Analysis with Numerical Time Cycles. The study aims to improve economic forecasting accuracy through the 9-year cycle model, which demonstrates superior predictive capabilities compared to traditional economic indicators.
Dataset Contents: The dataset includes a comprehensive range of economic indicators used in the research, such as:
USGDP_1871-2024.csv – U.S. Gross Domestic Product (GDP) data. USCPI_cleaned.csv – U.S. Consumer Price Index (CPI), cleaned and processed. USWAGE_1871-2024.csv – U.S. average wages data. EXCHANGEGLOBAL_cleaned.csv – Global exchange rates for the U.S. dollar. EXCHANGEPOUND_cleaned.csv – U.S. dollar to British pound exchange rates. INTERESTRATE_1871-2024.csv – U.S. interest rate data. UNRATE.csv – U.S. unemployment rate statistics. POPTOTUSA647NWDB.csv – U.S. total population data. Significance of the Data: This dataset serves as a foundation for a robust economic analysis of the U.S. economy over multiple decades. It was instrumental in testing the 9-year economic cycle model, which demonstrated an 85% accuracy rate in economic forecasting when compared to traditional models such as ARIMA and VAR.
Applications:
Economic Forecasting: Predicts a 1.5% decline in GDP in 2025, followed by a gradual recovery between 2026-2034. Economic Stability Analysis: Used for comparing forecasts with estimates from institutions like the IMF and World Bank. Academic and Institutional Research: Supports studies in economic cycles and long-term forecasting. Source & Further Information: For more details on the methodology and research findings, refer to the full paper published on SSRN:
https://ssrn.com/author=7429208 https://orcid.org/0009-0002-9626-7289
Water provides society with economic benefits that increasingly involve tradeoffs, making accounting for water quality, quantity, and their corresponding economic productivity more relevant in our interconnected world. In the past, physical and economic data about water have been fragmented, but integration is becoming more widely adopted internationally through application of the System of Environmental-Economic Accounts for Water (SEEA-Water), which enables the tracking of linkages between water and the economy over time and across scales. In this paper, we present the first national and subnational SEEA-Water accounts for the United States. We compile accounts for: (1) physical supply and use of water, (2) water productivity, (3) water quality, and (4) water emissions. These cover state and national levels for roughly the years 2000 to 2015. The results illustrate broad aggregate trends as well as subnational or industry-level phenomena. Specifically, the accounts show that total U.S. water use declined by 22% from 2000 to 2015, continuing a national trend seen since 1980. Total water use fell in 44 states, though groundwater use increased in 21 states. Nationally, a larger percent of water use comes from groundwater than at any time since 1950. Reductions in water use, combined with economic growth, lead to increases in water productivity for the entire national economy (65%), mining (99%), and agriculture (68%), though substantial variation occurred among states. Surface-water quality trends for the years 2002 to 2012 were most evident at regional levels, and differ by water-quality constituent and region. Chloride, nitrate, and total dissolved solids levels in groundwater had more consistent and widespread water-quality declines nationally. This work provides a baseline of recent historical water resource trends and their value in the U.S., as well as roadmap for the completion of future accounts for water, a critical ecosystem service. Our work also aids in the interpretation of ecosystem accounts in the context of long-term trends in U.S. water resources.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Private businesses in the United States hired 104 thousand workers in July of 2025 compared to -23 thousand in June of 2025. This dataset provides the latest reported value for - United States ADP Employment Change - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Economic Optimism Index in South Korea increased to 92.90 points in July from 92.80 points in June of 2025. This dataset provides - South Korea Economic Optimism Index- actual values, historical data, forecast, chart, statistics, economic calendar and news.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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
<p>RBA Governor Lowe’s Testimony High inflation is damaging and corrosive </p>
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.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The Gross Domestic Product (GDP) in Ghana was worth 82.83 billion US dollars in 2024, according to official data from the World Bank. The GDP value of Ghana represents 0.08 percent of the world economy. This dataset provides the latest reported value for - Ghana GDP - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Russia RU: Women Business and the Law Index Score: scale 1-100 data was reported at 73.125 NA in 2023. This stayed constant from the previous number of 73.125 NA for 2022. Russia RU: Women Business and the Law Index Score: scale 1-100 data is updated yearly, averaging 66.875 NA from Dec 1970 (Median) to 2023, with 54 observations. The data reached an all-time high of 73.125 NA in 2023 and a record low of 52.500 NA in 1971. Russia RU: Women Business and the Law Index Score: scale 1-100 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Russian Federation – Table RU.World Bank.WDI: Governance: Policy and Institutions. The index measures how laws and regulations affect women’s economic opportunity. Overall scores are calculated by taking the average score of each index (Mobility, Workplace, Pay, Marriage, Parenthood, Entrepreneurship, Assets and Pension), with 100 representing the highest possible score.;World Bank: Women, Business and the Law. https://wbl.worldbank.org/;;1. For the reference period, WDI and Gender Databases take the data coverage years instead of reporting years used in WBL (https://wbl.worldbank.org/). For example, the data for YR2020 in WBL (report year) corresponds to data for YR2019 in WDI and Gender Databases. 2. The 2024 Women, Business and the Law (WBL) report has introduced two distinct datasets, labeled as 1.0 and 2.0. The WBL data in the Gender database is based on the dataset 1.0. This dataset maintains consistency with the indicators used in previous WBL reports from 2020 to 2023. In contrast, the WBL 2.0 dataset includes new areas of childcare and safety. For those interested in exploring the WBL 2.0 dataset, it is available on the WBL website at https://wbl.worldbank.org.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Chile CL: Women Business and the Law Index Score: scale 1-100 data was reported at 80.000 NA in 2023. This stayed constant from the previous number of 80.000 NA for 2022. Chile CL: Women Business and the Law Index Score: scale 1-100 data is updated yearly, averaging 60.625 NA from Dec 1970 (Median) to 2023, with 54 observations. The data reached an all-time high of 80.000 NA in 2023 and a record low of 33.750 NA in 1972. Chile CL: Women Business and the Law Index Score: scale 1-100 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Chile – Table CL.World Bank.WDI: Governance: Policy and Institutions. The index measures how laws and regulations affect women’s economic opportunity. Overall scores are calculated by taking the average score of each index (Mobility, Workplace, Pay, Marriage, Parenthood, Entrepreneurship, Assets and Pension), with 100 representing the highest possible score.;World Bank: Women, Business and the Law. https://wbl.worldbank.org/;;1. For the reference period, WDI and Gender Databases take the data coverage years instead of reporting years used in WBL (https://wbl.worldbank.org/). For example, the data for YR2020 in WBL (report year) corresponds to data for YR2019 in WDI and Gender Databases. 2. The 2024 Women, Business and the Law (WBL) report has introduced two distinct datasets, labeled as 1.0 and 2.0. The WBL data in the Gender database is based on the dataset 1.0. This dataset maintains consistency with the indicators used in previous WBL reports from 2020 to 2023. In contrast, the WBL 2.0 dataset includes new areas of childcare and safety. For those interested in exploring the WBL 2.0 dataset, it is available on the WBL website at https://wbl.worldbank.org.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the Economy population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Economy across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.
Key observations
In 2023, the population of Economy was 8,962, a 0.18% decrease year-by-year from 2022. Previously, in 2022, Economy population was 8,978, a decline of 0.74% compared to a population of 9,045 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Economy decreased by 452. In this period, the peak population was 9,414 in the year 2000. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).
When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).
Data Coverage:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Economy Population by Year. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Norway NO: Women Business and the Law Index Score: scale 1-100 data was reported at 96.875 NA in 2023. This stayed constant from the previous number of 96.875 NA for 2022. Norway NO: Women Business and the Law Index Score: scale 1-100 data is updated yearly, averaging 88.125 NA from Dec 1970 (Median) to 2023, with 54 observations. The data reached an all-time high of 96.875 NA in 2023 and a record low of 63.750 NA in 1977. Norway NO: Women Business and the Law Index Score: scale 1-100 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Norway – Table NO.World Bank.WDI: Governance: Policy and Institutions. The index measures how laws and regulations affect women’s economic opportunity. Overall scores are calculated by taking the average score of each index (Mobility, Workplace, Pay, Marriage, Parenthood, Entrepreneurship, Assets and Pension), with 100 representing the highest possible score.;World Bank: Women, Business and the Law. https://wbl.worldbank.org/;;1. For the reference period, WDI and Gender Databases take the data coverage years instead of reporting years used in WBL (https://wbl.worldbank.org/). For example, the data for YR2020 in WBL (report year) corresponds to data for YR2019 in WDI and Gender Databases. 2. The 2024 Women, Business and the Law (WBL) report has introduced two distinct datasets, labeled as 1.0 and 2.0. The WBL data in the Gender database is based on the dataset 1.0. This dataset maintains consistency with the indicators used in previous WBL reports from 2020 to 2023. In contrast, the WBL 2.0 dataset includes new areas of childcare and safety. For those interested in exploring the WBL 2.0 dataset, it is available on the WBL website at https://wbl.worldbank.org.
ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
License information was derived automatically
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.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Ecuador recorded a Current Account surplus of 2529.44 USD Million in the first quarter of 2025. This dataset provides - Ecuador Current Account - actual values, historical data, forecast, chart, statistics, economic calendar and news.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset tabulates the population of Economy by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Economy. The dataset can be utilized to understand the population distribution of Economy by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Economy. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Economy.
Key observations
Largest age group (population): Male # 65-69 years (412) | Female # 60-64 years (490). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Age groups:
Scope of gender :
Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Economy Population by Gender. You can refer the same here
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
This release includes annual estimates of low carbon and renewable energy economy activity in the UK and constituent countries: turnover, employment, exports, imports, acquisitions, disposals and number of businesses.
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
Movements in the volume of production for the UK production industries: manufacturing, mining and quarrying, energy supply, and water and waste management. Figures are seasonally adjusted.
Attribution-NonCommercial-ShareAlike 4.0 (CC BY-NC-SA 4.0)https://creativecommons.org/licenses/by-nc-sa/4.0/
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The exclusive economic zone of Tonga comprises those areas of the sea, seabed, and subsoil that are beyond and adjacent to the territorial sea of Tonga, having as their outer limits a line measured seaward from the baseline described in Sections 5 and 6 of this Act, every point of which line is distant 200 nautical miles from the nearest point of the baseline. (2) Notwithstanding subsection (1) of this section, where/- (a) Any part of the median line between Tonga and any other country is less than 200 nautical miles from the nearest part of the baseline of the territorial sea of Tonga; and (b) No other outer limit of the exclusive economic zone is for the time being determined by agreement with a neighboring country or by an Order-in-Council made under subsection (3) of this section - that part of the median line shall be an outer limit of the zone. (3) For the purposes of implementing any international agreement, or the arbitral award of any international body, or the judgement of any international Court, or for any other purpose in accordance with international law, the King may from time to time, by Order-in Council, declare that the exclusive economic zone shall not extend to any specified area of the sea, seabed, or subsoil, that would otherwise be included within the exclusive economic zone by virtue of this section
https://www.un.org/depts/los/LEGISLATIONANDTREATIES/PDFFILES/TON_1989_Act.pdf
The Exclusive Economic Zone for Tonga was extracted from the Global Marine Regions platform. Tonga has not formally deposited with UNDOALOS their 200M.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Sudan SD: Women Business and the Law Index Score: scale 1-100 data was reported at 32.500 NA in 2023. This stayed constant from the previous number of 32.500 NA for 2022. Sudan SD: Women Business and the Law Index Score: scale 1-100 data is updated yearly, averaging 25.000 NA from Dec 1970 (Median) to 2023, with 54 observations. The data reached an all-time high of 32.500 NA in 2023 and a record low of 17.500 NA in 1990. Sudan SD: Women Business and the Law Index Score: scale 1-100 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Sudan – Table SD.World Bank.WDI: Governance: Policy and Institutions. The index measures how laws and regulations affect women’s economic opportunity. Overall scores are calculated by taking the average score of each index (Mobility, Workplace, Pay, Marriage, Parenthood, Entrepreneurship, Assets and Pension), with 100 representing the highest possible score.;World Bank: Women, Business and the Law. https://wbl.worldbank.org/;;1. For the reference period, WDI and Gender Databases take the data coverage years instead of reporting years used in WBL (https://wbl.worldbank.org/). For example, the data for YR2020 in WBL (report year) corresponds to data for YR2019 in WDI and Gender Databases. 2. The 2024 Women, Business and the Law (WBL) report has introduced two distinct datasets, labeled as 1.0 and 2.0. The WBL data in the Gender database is based on the dataset 1.0. This dataset maintains consistency with the indicators used in previous WBL reports from 2020 to 2023. In contrast, the WBL 2.0 dataset includes new areas of childcare and safety. For those interested in exploring the WBL 2.0 dataset, it is available on the WBL website at https://wbl.worldbank.org.
The Atlas of Economic Complexity maintains trade data in multiple international classification systems. This data set contains trade flows classified via Harmonized System (HS) 1992. HS data offers a contemporary and detailed classification of goods, but covers a relatively short time period: Categorizes approximately 5,000 goods Covers years from 1995–2021 Categories break down to 1-, 2-, 4-, or 6-digit detail levels (though country reporting can be less reliable at the 6-digit level) Raw data on trade in goods is provided by United Nations Statistical Division (COMTRADE). The data is then cleaned by Growth Lab researchers using the Bustos-Yildirim Method which uses bilateral trade flows to account for inconsistent reporting and provides more reliable accounting. In addition to trade in goods, the data additionally contains unilateral data on services trade provided by the International Monetary Fund (IMF) and acquired through the World Development Indicators (WDI) of The World Bank. For further information, see the data information page on the Atlas website.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
South Korea Women Business and the Law Index Score: scale 1-100 data was reported at 88.125 NA in 2023. This stayed constant from the previous number of 88.125 NA for 2022. South Korea Women Business and the Law Index Score: scale 1-100 data is updated yearly, averaging 59.063 NA from Dec 1970 (Median) to 2023, with 54 observations. The data reached an all-time high of 88.125 NA in 2023 and a record low of 38.125 NA in 1973. South Korea Women Business and the Law Index Score: scale 1-100 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s South Korea – Table KR.World Bank.WDI: Governance: Policy and Institutions. The index measures how laws and regulations affect women’s economic opportunity. Overall scores are calculated by taking the average score of each index (Mobility, Workplace, Pay, Marriage, Parenthood, Entrepreneurship, Assets and Pension), with 100 representing the highest possible score.;World Bank: Women, Business and the Law. https://wbl.worldbank.org/;;1. For the reference period, WDI and Gender Databases take the data coverage years instead of reporting years used in WBL (https://wbl.worldbank.org/). For example, the data for YR2020 in WBL (report year) corresponds to data for YR2019 in WDI and Gender Databases. 2. The 2024 Women, Business and the Law (WBL) report has introduced two distinct datasets, labeled as 1.0 and 2.0. The WBL data in the Gender database is based on the dataset 1.0. This dataset maintains consistency with the indicators used in previous WBL reports from 2020 to 2023. In contrast, the WBL 2.0 dataset includes new areas of childcare and safety. For those interested in exploring the WBL 2.0 dataset, it is available on the WBL website at https://wbl.worldbank.org.
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.