13 datasets found
  1. U.S. monthly projected recession probability 2021-2026

    • statista.com
    Updated Jun 24, 2025
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    Statista (2025). U.S. monthly projected recession probability 2021-2026 [Dataset]. https://www.statista.com/statistics/1239080/us-monthly-projected-recession-probability/
    Explore at:
    Dataset updated
    Jun 24, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Apr 2021 - Apr 2026
    Area covered
    United States
    Description

    By April 2026, it is projected that there is a probability of ***** percent that the United States will fall into another economic recession. This reflects a significant decrease from the projection of the preceding month.

  2. F

    Dates of U.S. recessions as inferred by GDP-based recession indicator

    • fred.stlouisfed.org
    json
    Updated Jul 30, 2025
    + more versions
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    (2025). Dates of U.S. recessions as inferred by GDP-based recession indicator [Dataset]. https://fred.stlouisfed.org/series/JHDUSRGDPBR
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    jsonAvailable download formats
    Dataset updated
    Jul 30, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    Graph and download economic data for Dates of U.S. recessions as inferred by GDP-based recession indicator (JHDUSRGDPBR) from Q4 1967 to Q1 2025 about recession indicators, GDP, and USA.

  3. a

    COVID-19 and the potential impacts on employment data tables

    • hub.arcgis.com
    • opendata-nzta.opendata.arcgis.com
    Updated Aug 26, 2020
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    Waka Kotahi (2020). COVID-19 and the potential impacts on employment data tables [Dataset]. https://hub.arcgis.com/datasets/9703b6055b7a404582884f33efc4cf69
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    Dataset updated
    Aug 26, 2020
    Dataset authored and provided by
    Waka Kotahi
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    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.

  4. S

    A global streamflow indices time series dataset for large-sample...

    • scidb.cn
    Updated Feb 7, 2023
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    Xinyu Chen; Liguang Jiang; Yuning Luo; Junguo Liu (2023). A global streamflow indices time series dataset for large-sample hydrological analyses on streamflow regime [Dataset]. http://doi.org/10.57760/sciencedb.07227
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 7, 2023
    Dataset provided by
    Science Data Bank
    Authors
    Xinyu Chen; Liguang Jiang; Yuning Luo; Junguo Liu
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    With the booming big data techniques, large-sample hydrological analysis on streamflow regime is becoming feasible, which could derive robust conclusions on hydrological processes from a big-picture perspective. However, there is a lack of a comprehensive global large-sample dataset for components of the streamflow regime yet. This paper presents a new time series dataset on global streamflow indices calculated from daily streamflow records after data quality control. The dataset contains 79 indices over seven major components of streamflow regime (i.e., magnitude, frequency, duration, changing rate, timing, variability, and recession) of 41263 river reaches globally on yearly and multiyear scales. Streamflow indices values until 2022 are covered in the dataset. Time span of the time series dataset is from 1806 to 2022 with an average length of 36 years. Compared to existing global datasets, this global dataset covers more stations and more indices, especially those characterizing the frequency, duration, changing rate, and recession of streamflow regime. With the dataset, research on streamflow regime will become easier without spending time handling raw streamflow records. This comprehensive dataset will be a valuable resource to the hydrology community to facilitate a wide range of studies, such as studies of hydrological behavior of a catchment, streamflow regime prediction in data-scarce regions, as well as variations in streamflow regime from a global perspective.

  5. f

    Real wage growth 2007–2021.

    • figshare.com
    xls
    Updated Nov 27, 2024
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    David G. Blanchflower; Alex Bryson (2024). Real wage growth 2007–2021. [Dataset]. http://doi.org/10.1371/journal.pone.0305347.t021
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    xlsAvailable download formats
    Dataset updated
    Nov 27, 2024
    Dataset provided by
    PLOS ONE
    Authors
    David G. Blanchflower; Alex Bryson
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Using micro-data on six surveys–the Gallup World Poll 2005–2023, the U.S. Behavioral Risk Factor Surveillance System, 1993–2022, Eurobarometer 1991–2022, the UK Covid Social Survey Panel, 2020–2022, the European Social Survey 2002–2020 and the IPSOS Happiness Survey 2018–2023 –we show individuals’ reports of subjective wellbeing in Europe declined in the Great Recession of 2008/9 and during the Covid pandemic of 2020–2021 on most measures. They also declined in four countries bordering Ukraine after the Russian invasion in 2022. However, the movements are not large and are not apparent everywhere. We also used data from the European Commission’s Business and Consumer Surveys on people’s expectations of life in general, their financial situation and the economic and employment situation in the country. All of these dropped markedly in the Great Recession and during Covid, but bounced back quickly, as did firms’ expectations of the economy and the labor market. Neither the annual data from the United Nation’s Human Development Index (HDI) nor data used in the World Happiness Report from the Gallup World Poll shifted much in response to negative shocks. The HDI has been rising in the last decade reflecting overall improvements in economic and social wellbeing, captured in part by real earnings growth, although it fell slightly after 2020 as life expectancy dipped. This secular improvement is mirrored in life satisfaction which has been rising in the last decade. However, so too have negative affect in Europe and despair in the United States.

  6. T

    United States Michigan Consumer Sentiment

    • tradingeconomics.com
    • es.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Aug 2, 2025
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    TRADING ECONOMICS (2025). United States Michigan Consumer Sentiment [Dataset]. https://tradingeconomics.com/united-states/consumer-confidence
    Explore at:
    csv, xml, json, excelAvailable download formats
    Dataset updated
    Aug 2, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Nov 30, 1952 - Jul 31, 2025
    Area covered
    United States
    Description

    Consumer Confidence in the United States increased to 61.70 points in July from 60.70 points in June 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.

  7. F

    S&P 500

    • fred.stlouisfed.org
    json
    Updated Jul 30, 2025
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    (2025). S&P 500 [Dataset]. https://fred.stlouisfed.org/series/SP500
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jul 30, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-pre-approvalhttps://fred.stlouisfed.org/legal/#copyright-pre-approval

    Description

    View data of the S&P 500, an index of the stocks of 500 leading companies in the US economy, which provides a gauge of the U.S. equity market.

  8. T

    Japan GDP Growth Rate

    • tradingeconomics.com
    • de.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jun 9, 2025
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    TRADING ECONOMICS (2025). Japan GDP Growth Rate [Dataset]. https://tradingeconomics.com/japan/gdp-growth
    Explore at:
    json, csv, xml, excelAvailable download formats
    Dataset updated
    Jun 9, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jun 30, 1980 - Mar 31, 2025
    Area covered
    Japan
    Description

    The Gross Domestic Product (GDP) in Japan stagnated 0 percent in the first quarter of 2025 over the previous quarter. This dataset provides - Japan GDP Growth Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  9. T

    India GDP Annual Growth Rate

    • tradingeconomics.com
    • pl.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated May 30, 2025
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    TRADING ECONOMICS (2025). India GDP Annual Growth Rate [Dataset]. https://tradingeconomics.com/india/gdp-growth-annual
    Explore at:
    xml, excel, json, csvAvailable download formats
    Dataset updated
    May 30, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 31, 1951 - Mar 31, 2025
    Area covered
    India
    Description

    The Gross Domestic Product (GDP) in India expanded 7.40 percent in the first quarter of 2025 over the same quarter of the previous year. This dataset provides - India GDP Annual Growth Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  10. T

    Australia GDP Growth Rate

    • tradingeconomics.com
    • ru.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Mar 5, 2025
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    TRADING ECONOMICS (2025). Australia GDP Growth Rate [Dataset]. https://tradingeconomics.com/australia/gdp-growth
    Explore at:
    csv, json, xml, excelAvailable download formats
    Dataset updated
    Mar 5, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 31, 1959 - Mar 31, 2025
    Area covered
    Australia
    Description

    The Gross Domestic Product (GDP) in Australia expanded 0.20 percent in the first quarter of 2025 over the previous quarter. This dataset provides - Australia GDP Growth Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  11. T

    Canada GDP Growth Rate

    • tradingeconomics.com
    • pt.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated May 30, 2025
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    TRADING ECONOMICS (2025). Canada GDP Growth Rate [Dataset]. https://tradingeconomics.com/canada/gdp-growth
    Explore at:
    xml, json, csv, excelAvailable download formats
    Dataset updated
    May 30, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jun 30, 1961 - Mar 31, 2025
    Area covered
    Canada
    Description

    The Gross Domestic Product (GDP) in Canada expanded 0.50 percent in the first quarter of 2025 over the previous quarter. This dataset provides - Canada GDP Growth Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  12. T

    Denmark Net Unemployment Rate

    • tradingeconomics.com
    • tr.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated May 28, 2025
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    TRADING ECONOMICS (2025). Denmark Net Unemployment Rate [Dataset]. https://tradingeconomics.com/denmark/unemployment-rate
    Explore at:
    csv, xml, json, excelAvailable download formats
    Dataset updated
    May 28, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 31, 1980 - Jun 30, 2025
    Area covered
    Denmark
    Description

    Unemployment Rate in Denmark remained unchanged at 2.50 percent in June. This dataset provides - Denmark Unemployment Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  13. T

    Japan Gross National Income

    • tradingeconomics.com
    • ar.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Aug 25, 2015
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    TRADING ECONOMICS (2015). Japan Gross National Income [Dataset]. https://tradingeconomics.com/japan/gross-national-product
    Explore at:
    xml, json, csv, excelAvailable download formats
    Dataset updated
    Aug 25, 2015
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Mar 31, 1980 - Mar 31, 2025
    Area covered
    Japan
    Description

    Gross National Product in Japan increased to 591411.90 JPY Billion in the first quarter of 2025 from 590296.60 JPY Billion in the fourth quarter of 2024. This dataset provides - Japan Gross National Income - actual values, historical data, forecast, chart, statistics, economic calendar and news.

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    Learn how you can add new datasets to our index.

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Statista (2025). U.S. monthly projected recession probability 2021-2026 [Dataset]. https://www.statista.com/statistics/1239080/us-monthly-projected-recession-probability/
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U.S. monthly projected recession probability 2021-2026

Explore at:
Dataset updated
Jun 24, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
Apr 2021 - Apr 2026
Area covered
United States
Description

By April 2026, it is projected that there is a probability of ***** percent that the United States will fall into another economic recession. This reflects a significant decrease from the projection of the preceding month.

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