93 datasets found
  1. T

    United States Wages and Salaries Growth

    • tradingeconomics.com
    • pl.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jun 14, 2025
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    TRADING ECONOMICS (2025). United States Wages and Salaries Growth [Dataset]. https://tradingeconomics.com/united-states/wage-growth
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    csv, json, xml, excelAvailable download formats
    Dataset updated
    Jun 14, 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, 1960 - Jun 30, 2025
    Area covered
    United States
    Description

    Wages in the United States increased 4.78 percent in June of 2025 over the same month in the previous year. This dataset provides the latest reported value for - United States Wages and Salaries Growth - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  2. Industrial production growth worldwide 2019-2024, by region

    • statista.com
    • ai-chatbox.pro
    Updated Sep 19, 2023
    + more versions
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    Jose Sanchez (2023). Industrial production growth worldwide 2019-2024, by region [Dataset]. https://www.statista.com/topics/6139/covid-19-impact-on-the-global-economy/
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    Dataset updated
    Sep 19, 2023
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Jose Sanchez
    Description

    In July 2024, global industrial production, excluding the United States, increased by 1.5 percent compared to the same time in the previous year, based on three month moving averages. This is compared to an increase of 0.2 percent in advanced economies (excluding the United States) for the same time period. The global industrial production collapsed after the outbreak of COVID-19, but increased steadily in the months after, peaking at 23 percent in June 2021. Industrial growth rate tracks the output production in the industrial sector.

  3. k

    US Economy to Slow in June as Fed Tightens Monetary Policy (Forecast)

    • kappasignal.com
    Updated May 27, 2023
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    KappaSignal (2023). US Economy to Slow in June as Fed Tightens Monetary Policy (Forecast) [Dataset]. https://www.kappasignal.com/2023/05/us-economy-to-slow-in-june-as-fed.html
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    Dataset updated
    May 27, 2023
    Dataset authored and provided by
    KappaSignal
    License

    https://www.kappasignal.com/p/legal-disclaimer.htmlhttps://www.kappasignal.com/p/legal-disclaimer.html

    Area covered
    United States
    Description

    This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

    US Economy to Slow in June as Fed Tightens Monetary Policy

    Financial data:

    • Historical daily stock prices (open, high, low, close, volume)

    • Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

    • Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

    Machine learning features:

    • Feature engineering based on financial data and technical indicators

    • Sentiment analysis data from social media and news articles

    • Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

    Potential Applications:

    • Stock price prediction

    • Portfolio optimization

    • Algorithmic trading

    • Market sentiment analysis

    • Risk management

    Use Cases:

    • Researchers investigating the effectiveness of machine learning in stock market prediction

    • Analysts developing quantitative trading Buy/Sell strategies

    • Individuals interested in building their own stock market prediction models

    • Students learning about machine learning and financial applications

    Additional Notes:

    • The dataset may include different levels of granularity (e.g., daily, hourly)

    • Data cleaning and preprocessing are essential before model training

    • Regular updates are recommended to maintain the accuracy and relevance of the data

  4. Monthly GDP growth of the UK 2022-2025

    • statista.com
    Updated Aug 14, 2025
    + more versions
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    Statista (2025). Monthly GDP growth of the UK 2022-2025 [Dataset]. https://www.statista.com/statistics/941233/monthly-gdp-growth-uk/
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    Dataset updated
    Aug 14, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jun 2023 - Jun 2025
    Area covered
    United Kingdom
    Description

    The UK economy grew by 0.4 percent in May 2025 after shrinking by 0.1 percent in May. Since a huge decline in GDP in April 2020, the UK economy has gradually recovered and is now around 4.4 percent larger than it was before the COVID-19 pandemic. After the initial recovery from the pandemic, however, the UK economy has effectively flatlined, fluctuating between low growth and small contractions since January 2022. Labour banking on growth to turn around fortunes in 2025 In February 2025, just over half a year after winning the last general election, the approval rating for the new Labour government fell to a low of -48 percent. Furthermore, the Prime Minister, Keir Starmer was not only less popular than the new Conservative leader, Kemi Badenoch, but also the leader of the Reform Party, Nigel Farage, whose party have surged in opinion polls recently. This remarkable decline in popularity for the new government is, in some part, due to a deliberate policy of making tough decisions early. Arguably, the most damaging of these policies was the withdrawal of the winter fuel allowance for some pensioners, although other factors such as a controversy about gifts and donations also hurt the government. While Labour aims to restore the UK's economic and political credibility in the long term, they will certainly hope for some good economic news sooner rather than later. Economy bounces back in 2024 after ending 2023 in recession Due to two consecutive quarters of negative economic growth, in late 2023 the UK economy ended the year in recession. After not growing at all in the second quarter of 2023, UK GDP fell by 0.1 percent in the third quarter, and then by 0.3 percent in the last quarter. For the whole of 2023, the economy grew by 0.4 percent compared to 2022, and for 2024 is forecast to have grown by 1.1 percent. During the first two quarters of 2024, UK GDP grew by 0.7 percent, and 0.4 percent, with this relatively strong growth followed by zero percent growth in the third quarter of the year. Although the economy had started to grow again by the time of the 2024 general election, this was not enough to save the Conservative government at the time. Despite usually seen as the best party for handling the economy, the Conservative's economic competency was behind that of Labour on the eve of the 2024 election.

  5. Quarterly gross domestic product (GDP) growth rate in China Q2 2022-Q2 2025

    • statista.com
    Updated Jul 15, 2025
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    Statista (2025). Quarterly gross domestic product (GDP) growth rate in China Q2 2022-Q2 2025 [Dataset]. https://www.statista.com/statistics/271769/quarterly-gross-domestic-product-gdp-growth-rate-in-china/
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    Dataset updated
    Jul 15, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    China
    Description

    In the second quarter of 2025, the growth of the real gross domestic product (GDP) in China ranged at *** percent compared to the same quarter of the previous year. GDP refers to the total market value of all goods and services that are produced within a country per year. It is an important indicator of the economic strength of a country. Real GDP is adjusted for price changes and is therefore regarded as a key indicator for economic growth. GDP growth in China In 2024, China ranged second among countries with the largest gross domestic product worldwide. Since the introduction of economic reforms in 1978, the country has experienced rapid social and economic development. In 2013, it became the world’s largest trading nation, overtaking the United States. However, per capita GDP in China was still much lower than that of industrialized countries. Until 2011, the annual growth rate of China’s GDP had constantly been above nine percent. However, economic growth has cooled down since and is projected to further slow down gradually in the future. Rising domestic wages and the competitive edge of other Asian and African countries are seen as main reasons for the stuttering in China’s economic engine. One strategy of the Chinese government to overcome this transition is a gradual shift of economic focus from industrial production to services. Challenges to GDP growth Another major challenge lies in the massive environmental pollution that China’s reckless economic growth has caused over the past decades. China’s development has been powered mostly by coal consumption, which resulted in high air pollution. To counteract industrial pollution, further investments in waste management and clean technologies are necessary. In 2017, about **** percent of GDP was spent on pollution control. Surging environmental costs aside, environmental issues could also be a key to industrial transition as China placed major investments in renewable energy and clean tech projects. The consumption of green energy skyrocketed from **** exajoules in 2005 to **** million in 2022.

  6. T

    United States ADP Employment Change

    • tradingeconomics.com
    • ar.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jul 30, 2025
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    TRADING ECONOMICS (2025). United States ADP Employment Change [Dataset]. https://tradingeconomics.com/united-states/adp-employment-change
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    csv, xml, json, excelAvailable download formats
    Dataset updated
    Jul 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
    Feb 28, 2010 - Jul 31, 2025
    Area covered
    United States
    Description

    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.

  7. A

    BLM REA YKL 2011 Long-Term Future (2060s) Decadal Mean July Temperature for...

    • data.amerigeoss.org
    Updated Jul 26, 2019
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    United States[old] (2019). BLM REA YKL 2011 Long-Term Future (2060s) Decadal Mean July Temperature for Alaska A2 [Dataset]. https://data.amerigeoss.org/dataset/blm-rea-ykl-2011-long-term-future-2060s-decadal-mean-july-temperature-for-alaska-a2
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    esri layer package (lpk), lpkAvailable download formats
    Dataset updated
    Jul 26, 2019
    Dataset provided by
    United States[old]
    Area covered
    Alaska
    Description

    This set of files includes downscaled projections of decadal means of July mean temperatures (in degrees Celsius, no unit conversion necessary) for each month of decades 2010-2019, 2020-2029, 2050-2059, and 2060-2069 at 771x771 meter spatial resolution. Each file represents a mean monthly mean in a given decade. Overview: This set of files is an average of five top performing Global Climate Models. These models are referred to by the acronyms: cccma_cgcm31, mpi_echam5, gfdl_cm21, ukmo_hadcm3, and miroc3_2_medres. For a description of the model selection process, please see Walsh et al. 2008. Global Climate Model Performance over Alaska and Greenland. Journal of Climate. v. 21 pp. 6156-6174 This set of files represents the A2 projected emission scenario. Emission scenarios in brief: The Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) created a range of scenarios to explore alternative development pathways, covering a wide range of demographic, economic and technological driving forces and resulting greenhouse gas emissions. The B1 scenario describes a convergent world, a global population that peaks in mid-century, with rapid changes in economic structures toward a service and information economy. The Scenario A1B assumes a world of very rapid economic growth, a global population that peaks in mid-century, rapid introduction of new and more efficient technologies, and a balance between fossil fuels and other energy sources. The A2 scenario describes a very heterogeneous world with high population growth, slow economic development and slow technological change. These files are bias corrected and downscaled via the delta method using PRISM (http://prism.oregonstate.edu/) 1971-2000 771m data as baseline climate. Absolute anomalies are utilized for temperature variables. Proportional anomalies are utilized for precipitation variables. Please see http://www.snap.uaf.edu/about for a description of the downscaling process.

  8. b

    BLM REA YKL 2011 Current (2010s) Decadal Mean July Temperature in Alaska A2

    • navigator.blm.gov
    + more versions
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    BLM REA YKL 2011 Current (2010s) Decadal Mean July Temperature in Alaska A2 [Dataset]. https://navigator.blm.gov/data/SQLUQJUW_2146/blm-rea-mbr-2010-swregap-173856-vertebrate-habitat-distribution-models
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    Area covered
    Alaska
    Description

    Some of the YKL rasters intentionally do not align or have the same extent. These rasters were not snapped to a common raster per the authors discretion. Please review selected rasters prior to use. These varying alignments are a result of the use of differing source data sets and all products derived from them. We recommend that users snap or align rasters as best suits their own projects. - This set of files includes downscaled projections of decadal means of July mean temperatures (in degrees Celsius, no unit conversion necessary) for each month of decades 2010-2019, 2020-2029, 2050-2059, and 2060-2069 at 771x771 meter spatial resolution. Each file represents a mean monthly mean in a given decade.

    Overview: This set of files is an average of five top performing Global Climate Models. These models are referred to by the acronyms: cccma_cgcm31, mpi_echam5, gfdl_cm21, ukmo_hadcm3, and miroc3_2_medres. For a description of the model selection process, please see Walsh et al. 2008. Global Climate Model Performance over Alaska and Greenland. Journal of Climate. v. 21 pp. 6156-6174

    This set of files represents the A2 projected emission scenario.

    Emission scenarios in brief:

    The Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) created a range of scenarios to explore alternative development pathways, covering a wide range of demographic, economic and technological driving forces and resulting greenhouse gas emissions. The B1 scenario describes a convergent world, a global population that peaks in mid-century, with rapid changes in economic structures toward a service and information economy. The Scenario A1B assumes a world of very rapid economic growth, a global population that peaks in mid-century, rapid introduction of new and more efficient technologies, and a balance between fossil fuels and other energy sources. The A2 scenario describes a very heterogeneous world with high population growth, slow economic development and slow technological change.

    These files are bias corrected and downscaled via the delta method using PRISM (http:prism.oregonstate.edu) 1971-2000 771m data as baseline climate. Absolute anomalies are utilized for temperature variables. Proportional anomalies are utilized for precipitation variables. Please see http:www.snap.uaf.eduabout for a description of the downscaling process.

  9. T

    United States Retail Sales YoY

    • tradingeconomics.com
    • pt.tradingeconomics.com
    • +13more
    csv, excel, json, xml
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    TRADING ECONOMICS, United States Retail Sales YoY [Dataset]. https://tradingeconomics.com/united-states/retail-sales-annual
    Explore at:
    json, xml, csv, excelAvailable download formats
    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, 1993 - Jul 31, 2025
    Area covered
    United States
    Description

    Retail Sales in the United States increased 3.90 percent in July of 2025 over the same month in the previous year. This dataset provides - United States Retail Sales YoY - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  10. Annual change in house prices in the UK 2015-2025, by month

    • statista.com
    Updated Jun 24, 2025
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    Statista (2025). Annual change in house prices in the UK 2015-2025, by month [Dataset]. https://www.statista.com/statistics/751619/house-price-change-uk/
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    Dataset updated
    Jun 24, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 2015 - Apr 2025
    Area covered
    United Kingdom
    Description

    House prices in the UK rose dramatically during the coronavirus pandemic, with growth slowing down in 2022 and turning negative in 2023. The year-on-year annual house price change peaked at 14 percent in July 2022. In April 2025, house prices increased by 3.5 percent. As of late 2024, the average house price was close to 290,000 British pounds. Correction in housing prices: a European phenomenon The trend of a growing residential real estate market was not exclusive to the UK during the pandemic. Likewise, many European countries experienced falling prices in 2023. When comparing residential property RHPI (price index in real terms, e.g. corrected for inflation), countries such as Germany, France, Italy, and Spain also saw prices decline. Sweden, one of the countries with the fastest growing residential markets, saw one of the largest declines in prices. How has demand for UK housing changed since the outbreak of the coronavirus? The easing of the lockdown was followed by a dramatic increase in home sales. In November 2020, the number of mortgage approvals reached an all-time high of over 107,000. One of the reasons for the housing boom were the low mortgage rates, allowing home buyers to take out a loan with an interest rate as low as 2.5 percent. That changed as the Bank of England started to raise the base lending rate, resulting in higher borrowing costs and a decline in homebuyer sentiment.

  11. w

    DCMS Economic Estimates: Monthly GVA (to September 2024)

    • gov.uk
    Updated Nov 27, 2024
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    Department for Culture, Media and Sport (2024). DCMS Economic Estimates: Monthly GVA (to September 2024) [Dataset]. https://www.gov.uk/government/statistics/dcms-economic-estimates-monthly-gva-to-september-2024
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    Dataset updated
    Nov 27, 2024
    Dataset provided by
    GOV.UK
    Authors
    Department for Culture, Media and Sport
    Description

    These estimates are the first to include scheduled revisions from the Office for National Statistics (ONS) National Accounts Blue Book 2024. National Accounts Gross Value Added (GVA) estimates incorporate scheduled revisions as more data becomes available. These revisions have affected monthly GVA data back to the start of our series (2019) for many industries in DCMS sectors.

    We expect revisions to GVA in the National Accounts Blue Book 2024 to affect our annual GVA estimates too. Annual GVA is more robust than this monthly data, but the annual data currently available does not incorporate these revisions. To address this, we are bringing forward a tables-only update to our Annual GVA publication to 19 December 2024. A more complete release will follow in January 2025.

    Alongside these quarterly releases, we often sum monthly GVA to produce or update estimates for each calendar year. All of the data required to calculate these estimates is available in the published tables. At the time of publication, Blue Book revisions have not yet been applied to our more robust, annual GVA measure. We have not presented summed monthly data here this quarter to reduce the risk of confusion.

    Headline findings

    All level estimates in this release are presented in 2022 prices.

    DCMS sectors (excluding tourism)

    In September 2024, these early estimates indicate that GVA by DCMS sectors fell by around 1.0% compared to August 2024, while GVA by the UK as a whole fell by 0.1%.

    Looking at the quarter as a whole, in the three months to September 2024, GVA by the included DCMS sectors is estimated to have grown slightly by 0.2% compared with the three months to June 2024, while the UK economy as a whole is estimated to have grown slightly by 0.1%.

    Since February 2020 (pre-pandemic), these early estimates indicate that included DCMS sector GVA has grown at a slightly slower rate than the UK as a whole at a 2% increase compared to 3% for the UK economy, though trends vary by sector.

    Released

    27 November 2024

    About this release

    The DCMS Sector total reported here includes civil society, creative industries, cultural sector, gambling and sport. Tourism is not included as the data is not yet available (see note in data table).

    Monthly estimates

    These Economic Estimates are Official Statistics, used to provide an estimate of the economic contribution of DCMS sectors, in terms of gross value added (GVA), for the period January 2019 to September 2024. This current release contains first estimates for July to September 2024.

    Estimates are in chained volume measures (i.e. have been adjusted for inflation), at 2022 prices, and are seasonally adjusted. These latest monthly estimates should only be used to illustrate general trends, not used as definitive figures.

    You can use these estimates to:

    • look at relative indicative changes in GVA over time for DCMS sectors and subsectors

    You should not use these estimates to:

    • quantify GVA for a specific month
    • measure absolute change in GVA over time
    • determine findings for sectors that are defined using more detailed industrial classes (due to the data sources only being available at broader industry levels)

    Data sources and technical information

    The estimates are calculated based on published ONS data sources including the Index of Services and Index of Production.

    These data sources provide an estimate of the monthly change in GVA for all UK industries. However, the data is only available for broader industry groups, whereas DCMS sectors are defined at a more detailed industrial level. For example, GVA for ‘cultural education’ (a sub-sector of the cultural sector within the DCMS sectors) is estimated based on the trend for all education. Sectors such as ‘cultural education’ may have been affected differently by COVID-19 compared to education in general. These estimates are also based on the composition of the economy in 2022. Overall, this means the accuracy of monthly GVA for DCMS sectors is likely to be lower for months in 2020 and 2021.

    The technical guidance contains further information about data sources, methodology, and the validation and accuracy of these estimates. The latest version of this guidance was published in November 2023.

    Content

    These statistics cover the contributions of the following sectors to the UK economy.

    DCMS Sectors:

    • civil society
    • creative industries
    • cultural sector
    • gambling
    • sport

    Users should note that there is ove

  12. Global merchandise exports index 2019-2024, by region

    • statista.com
    • ai-chatbox.pro
    Updated Sep 19, 2023
    + more versions
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    Jose Sanchez (2023). Global merchandise exports index 2019-2024, by region [Dataset]. https://www.statista.com/topics/6139/covid-19-impact-on-the-global-economy/
    Explore at:
    Dataset updated
    Sep 19, 2023
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Jose Sanchez
    Description

    In July 2024, the merchandise exports index worldwide, excluding the U.S., stood at 204.8. This is compared to an index value of 143 for the United States in the same month. The index was highest in emerging economies, reaching an index score of 353. Moreover, the merchandise imports index was also highest in emerging economies. The merchandise exports index is the U.S. dollar value of goods sold to the rest of the world, deflated by the U.S. Consumer Price Index (CPI).

  13. T

    China GDP Annual Growth Rate

    • tradingeconomics.com
    • ko.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jul 15, 2025
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    TRADING ECONOMICS (2025). China GDP Annual Growth Rate [Dataset]. https://tradingeconomics.com/china/gdp-growth-annual
    Explore at:
    xml, csv, json, excelAvailable download formats
    Dataset updated
    Jul 15, 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, 1989 - Jun 30, 2025
    Area covered
    China
    Description

    The Gross Domestic Product (GDP) in China expanded 5.20 percent in the second quarter of 2025 over the same quarter of the previous year. This dataset provides - China GDP Annual Growth Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  14. Waitrose sales growth year-on-year in Great Britain 2015-2025

    • statista.com
    + more versions
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    Statista, Waitrose sales growth year-on-year in Great Britain 2015-2025 [Dataset]. https://www.statista.com/statistics/603429/waitrose-sales-percentage-change-great-britain-uk/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United Kingdom
    Description

    Waitrose sales increased by 5.5 percent in Great Britain over a 12-week period ending July 13, 2025 compared to the same time period in 2024. Waitrose has experienced an unprecedented growth in sales throughout the 2020 when coronavirus induced lockdowns caused an increase in grocery shopping. Waitrose saw an all-time high in sales growth by 13.2 percent during the 12 weeks ending on 29 November 2020. Company profile Waitrose & Partners is the food retail division of John Lewis Partnership. It has been a subsidiary of John Lewis since 1937. The Bracknell based company was founded in West London in 1904 and operated 329 stores in the United Kingdom in 2024. The company also operates an online store which experienced growth of 13 percent during 2020. Market position The company generated a revenue of over 6.75 billion pounds in the 2022/23 financial year. Revenue growth has slowed down in recent years compared to the early 2010s. As of July 2025, the company ranked 8th in its market with a share of 4.4 percent. Its grocery market share has been stable at around five percent for a number of years now.

  15. Data from: Alpine and Arctic tundra shrub populations show similar...

    • data.niaid.nih.gov
    • search.dataone.org
    • +1more
    zip
    Updated Aug 9, 2024
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    Jiří Lehejček; František Trkal; Jiří Doležal; Vojtěch Čada (2024). Alpine and Arctic tundra shrub populations show similar ontogenetic growth trends but differing absolute growth rates and lifespan [Dataset]. http://doi.org/10.5061/dryad.w9ghx3frk
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    zipAvailable download formats
    Dataset updated
    Aug 9, 2024
    Dataset provided by
    Czech Academy of Sciences, Institute of Botany
    Czech University of Life Sciences Prague
    Tomas Bata University in Zlín
    Authors
    Jiří Lehejček; František Trkal; Jiří Doležal; Vojtěch Čada
    License

    https://spdx.org/licenses/CC0-1.0.htmlhttps://spdx.org/licenses/CC0-1.0.html

    Area covered
    Arctic
    Description

    The majority of terrestrial primary production is performed by plants, the ontogenetic growth trends of which greatly influence biomass and carbon dynamics. Here, we study ontogenetic trends of primary (apical) and secondary (stem thickening) growth in Arctic (Svalbard, Norway) and alpine (Krkonoše, Czechia) populations of black crowberry (Empetrum nigrum), the dominant plant species of certain tundra communities. The environmental conditions in alpine areas are more favourable for plant growth than those in the High Arctic, where temperatures are lower, there is less precipitation and soils are shallower, among other differences. These differences were reflected in significant differences in absolute growth rates and shrub age between the populations under study. However, we found almost no differences in ontogenetic growth trends between the populations. In both populations, primary growth and secondary (stem base) growth decrease throughout ontogeny whereas secondary (stem top) growth and basal area increment increase. No significant differences in the slope of the trends were found in either primary or secondary (stem base) growth. Trends in the ratio between basal area increment and primary growth revealed neither absolute nor relative differences between the populations. Ontogenetic trends in the shrubs analysed were surprisingly stable despite the prominently different environmental conditions. Empetrum plants have adapted to the different environments by altering their absolute growth rate only. This adaptation has probably also resulted in the different longevity of plants constituting the study populations, confirming the theory that slower-growing plants live longer. Primary growth and secondary (diameter) growth at the stem base seem to be more basic characteristics of plant growth compared to basal area increment and secondary (diameter) growth at the apex because the latter two seem to be dependent on the absolute growth rate. Methods Study sites and sampling Arctic and alpine populations of the black crowberry (Empetrum nigrum L.), be it the nominal subspecies or E. nigrum subsp. hermaphroditum (Hagerup) Böcher, is exposed to different climatic, soil, and vegetation conditions. We sampled forty individuals from an Arctic population at the end of August 2018 in the Colesdalen valley (78°6′ N; 15°5′ E), Svalbard, Norway. The average annual precipitation in the valley is 190 mm, mostly in the form of snow. From 1969 to 1990, the average annual temperature was −6.7°C, the coldest month was February, with an average temperature of −16.2°C, and the warmest month was July, with an average temperature of 5.9°C (Longyearbyen Airport station, 18 km north of the site; Norwegian Meteorological Institute, 2010). The onset of the growing season spans between days number 165 and 174 (12–23 June) in the Svalbard Islands. Samples were taken at elevations between 40 to 80 m a.s.l. on a south-facing slope with an inclination of 10–20%. Shallow and poor soils were present on the site. There were no other shrubs or herbs growing in the vicinity of the individuals sampled. The temperate alpine population was represented by 41 individuals collected in July and August 2019 in the Krkonoše Mountains, Czechia. Both co-occurring subspecies of E. nigrum (subsp. nigrum and subsp. hermaphroditum) were sampled because they are impossible to identify in the field. Individuals were sampled at three localities: Zadní Planina (50°42′49″ N; 15°40′35″ E), Pančavská louka (50°45′56″ N; 15°32′38″ E), and Labská louka (50°46′12″ N; 15° 32′20″ E). All samples were taken at elevations between 1,300 and 1,400 m a.s.l. The locality at Zadní Planina was on a 20% steep south-eastern slope and the other two localities were flat. At the elevation of 1,603 m a.s.l., the average annual temperature is 0.2°C, the warmest month being July (8.3°C) and the coldest January (−7.0°C). The average annual precipitation reaches 1,400 mm. The onset of cellular division (i.e. the growing season) in co-occurring Pinus mugo is between days 138 and 145 (18–25 May) in the Krkonoše Mts. Region is botanically relatively well described and Krkonoše Mts show high plant endemism from the central European perspective. Sampled shrubs occurred in closed vegetation with Calluna vulgaris, Vaccinium myrtillus, Vaccinium uliginosum, Pinus mugo, and several grass species (Poaceae). The sampling consisted of the extraction of complete individuals (in clonal alpine individuals only the relevant part), including lignified roots (to allow the laboratory assessment of radial growth and plant age from the root collar) and whole aboveground organs. Root samples were cleaned, placed in a marked plastic bag, and treated with 40% alcohol to prevent mold. Growth measurements The method of serial sectioning was used in order to determine the rate of primary growth. It consisted of tree-ring measurements of cross-sections at different heights and cross-dating the obtained series at the intra-individual level. The first cross-section was always made at the root collar or the bottom part of the stem and was followed by one to ten cross-sections evenly spaced across the shrub body so that the distances between the cross-sections were approximately 10 cm. All branches longer than 10 cm were included to account for the species’ greater growth complexity, as it branches heavily. The exact distances between all the cross-sections were measured for subsequent primary growth analysis. Slices no thicker than 20 µm were extracted from all cross-sections using a sledge microtome. The slices were stained using a 1:1 Safranin/Astra blue solution and embedded in Canada balsam. The entire area of each slice (i.e. whole cross-section) was photographed at 100× magnification in order to measure annual rings along multiple axes as well as to detect partially missing annual rings and other growth defects. Measurements were obtained from the images using NIS-Elements software for two radii per cross-section. The first measurement was always performed for the longest radius whereas the second measurement, aimed to reveal partially missing rings, was made at an angle of at least 90° to the first radius. Cross-dating was done mostly visually using PAST5 software, first at the cross-sectional level by comparing radii measurements and, secondly, at the level of the whole individual (including branches) by comparing mean cross-sectional series. In total, we were able to use a series from 30 individuals from Svalbard (92 missing and 232 partially missing annual rings detected) and 33 individuals from the Krkonoše Mts (23 missing and 126 partially missing annual rings detected). The remaining samples were not cross-dated successfully and were excluded from further analyses. We calculated the primary growth rate between cross-sections using the difference in the number of tree rings and stem length between two consecutive cross-sections for each considered branch. For the corresponding set of tree rings, we also calculated the rate of secondary growth at the shrub base (using measurements from the basal cross-section) and at the shrub top (using the measurements at the lower cross-section of each pair). We also calculated secondary growth expressed as basal area increment (measured in mm2) and the ratio between basal area increment and primary growth (measured in mm). Basal area increment, in contrast to simple ring width, includes the circumference of the stem on which the ring is produced and is, therefore, assumed to be more representative of stem conducting capacity and stem biomass produced. Statistics To test for relationships between the growth variables (primary growth, secondary growth at the base and top, basal area increment, and growth ratio), shrub age, and population age structure, we used multiple linear and polynomial regression models. These models were based on average growth rates within shrub sections. We also used a subset of the data for shrubs younger than ten years to avoid bias caused by large differences in shrub age between the two study regions. Similarly, to remove the age effect from the relationship, the residuals of growth vs age models were used to test for a relationship between primary and secondary growth. Finally, we calculated the age distribution of each sample population and tested for differences in these distributions between the populations. All the analyses were performed in R (R Core Team 2020).

  16. f

    DataSheet_1_Growth data of outlying plantations allows benchmarking the...

    • frontiersin.figshare.com
    docx
    Updated May 31, 2024
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    Jesús Julio Camarero; Antonio Gazol; Cristina Valeriano; Marta Vergarechea; Nicolás Cattaneo (2024). DataSheet_1_Growth data of outlying plantations allows benchmarking the tolerance to climate extremes and drought stress in the European larch.docx [Dataset]. http://doi.org/10.3389/fpls.2024.1404347.s001
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    Dataset updated
    May 31, 2024
    Dataset provided by
    Frontiers
    Authors
    Jesús Julio Camarero; Antonio Gazol; Cristina Valeriano; Marta Vergarechea; Nicolás Cattaneo
    License

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

    Description

    IntroductionPlantations located outside the species distribution area represent natural experiments to assess tree tolerance to climate variability. Climate change amplifies warming-related drought stress but also leads to more climate extremes. MethodsWe studied plantations of the European larch (Larix decidua), a conifer native to central and eastern Europe, in northern Spain. We used climate, drought and tree-ring data from four larch plantations including wet (Valgañón, site V; Santurde, site S), intermediate (Ribavellosa, site R) and dry (Santa Marina, site M) sites. We aimed to benchmark the larch tolerance to climate and drought stress by analysing the relationships between radial growth increment (hereafter growth), climate data (temperature, precipitation, radiation) and a drought index. ResultsBasal area increment (BAI) was the lowest in the driest site M (5.2 cm2 yr-1; period 1988–2022), followed by site R (7.5 cm2 yr-1), with the youngest and oldest and trees being planted in M (35 years) and R (150 years) sites. BAI peaked in the wettest sites (V; 10.4 cm2 yr-1; S, 10.8 cm2 yr-1). We detected a sharp BAI reduction (30% of the regional mean) in 2001 when springto-summer conditions were very dry. In the wettest V and S sites, larch growth positively responded to current March and June-July radiation, but negatively to March precipitation. In the R site, high April precipitation enhanced growth. In the driest M site, warm conditions in the late prior winter and current spring improved growth, but warm-sunny conditions in July and dry-sunny conditions in August reduced it. Larch growth positively responded to spring-summer wet conditions considering short (1-6 months) and long (9-24 months) time scales in dry (site M) and wet-intermediate (sites S and R) sites, respectively.DiscussionLarch growth is vulnerable to drought stress in dry slow-growing plantations, but also to extreme spring wet-cloudy events followed by dry-hot conditions in wet fast-growing plantations.

  17. T

    Vietnam Retail Sales YoY

    • tradingeconomics.com
    • id.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Aug 6, 2025
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    TRADING ECONOMICS (2025). Vietnam Retail Sales YoY [Dataset]. https://tradingeconomics.com/vietnam/retail-sales-yoy
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    csv, json, xml, excelAvailable download formats
    Dataset updated
    Aug 6, 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
    Mar 31, 2002 - Jul 31, 2025
    Area covered
    Vietnam
    Description

    Retail Sales in Vietnam increased 9.20 percent in July of 2025 over the same month in the previous year. This dataset provides - Vietnam Retail Sales YoY - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  18. Inflation rate and central bank interest rate 2025, by selected countries

    • statista.com
    Updated Aug 4, 2025
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    Statista (2025). Inflation rate and central bank interest rate 2025, by selected countries [Dataset]. https://www.statista.com/statistics/1317878/inflation-rate-interest-rate-by-country/
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    Dataset updated
    Aug 4, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jun 2025
    Area covered
    Worldwide
    Description

    In June 2025, global inflation rates and central bank interest rates showed significant variation across major economies. Most economies initiated interest rate cuts from mid-2024 due to declining inflationary pressures. The U.S., UK, and EU central banks followed a consistent pattern of regular rate reductions throughout late 2024. In the first half of 2025, Russia maintained the highest interest rate at 20 percent, while Japan retained the lowest at 0.5 percent. Varied inflation rates across major economies The inflation landscape varies considerably among major economies. China had the lowest inflation rate at 0.1 percent in June 2025. In contrast, Russia maintained a high inflation rate of 9.4 percent. These figures align with broader trends observed in early 2025, where China had the lowest inflation rate among major developed and emerging economies, while Russia's rate remained the highest. Central bank responses and economic indicators Central banks globally implemented aggressive rate hikes throughout 2022-23 to combat inflation. The European Central Bank exemplified this trend, raising rates from 0 percent in January 2022 to 4.5 percent by September 2023. A coordinated shift among major central banks began in mid-2024, with the ECB, Bank of England, and Federal Reserve initiating rate cuts, with forecasts suggesting further cuts through 2025 and 2026.

  19. T

    Poland Corporative Sector Wage Growth

    • tradingeconomics.com
    • de.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jun 14, 2025
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    TRADING ECONOMICS (2025). Poland Corporative Sector Wage Growth [Dataset]. https://tradingeconomics.com/poland/wage-growth
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    csv, xml, json, excelAvailable download formats
    Dataset updated
    Jun 14, 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, 2006 - Jun 30, 2025
    Area covered
    Poland
    Description

    Wages in Poland increased 9 percent in June of 2025 over the same month in the previous year. This dataset provides - Poland Wage Growth- actual values, historical data, forecast, chart, statistics, economic calendar and news.

  20. O

    Off-Road Vehicle Market Report

    • marketreportanalytics.com
    doc, pdf, ppt
    Updated Apr 21, 2025
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    Market Report Analytics (2025). Off-Road Vehicle Market Report [Dataset]. https://www.marketreportanalytics.com/reports/off-road-vehicle-market-105061
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    pdf, doc, pptAvailable download formats
    Dataset updated
    Apr 21, 2025
    Dataset authored and provided by
    Market Report Analytics
    License

    https://www.marketreportanalytics.com/privacy-policyhttps://www.marketreportanalytics.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The off-road vehicle (ORV) market, valued at $16.72 billion in 2025, is projected to experience robust growth, driven by a compound annual growth rate (CAGR) of 4.12% from 2025 to 2033. This expansion is fueled by several key factors. Increasing disposable incomes in developing economies are fostering greater participation in recreational activities like ATV and UTV riding, boosting demand. Furthermore, the growing popularity of adventure tourism and outdoor recreation contributes significantly to market expansion. Technological advancements leading to improved vehicle performance, enhanced safety features, and more environmentally friendly options also play a crucial role. The market is segmented by vehicle type (ATVs and UTVs) and application (sports, agriculture, and other applications). The sports application segment currently dominates, but the agricultural segment is expected to experience strong growth due to the increasing need for versatile and efficient vehicles in farming and ranching. While the market faces potential restraints from stringent emission regulations and safety concerns, the overall positive market outlook is underpinned by the continuous innovation in vehicle design and features, coupled with a rising global demand for recreational vehicles. The North American market currently holds a significant share, largely due to established recreational culture and a strong presence of major manufacturers. However, the Asia-Pacific region is anticipated to show the fastest growth during the forecast period, driven by burgeoning middle classes and a growing interest in off-road adventures. Europe and the Rest of the World regions are also expected to contribute to market growth, albeit at a slightly slower pace, influenced by factors such as evolving consumer preferences and government regulations. Key players like Polaris Inc., Bombardier Recreational Products Inc., and Yamaha Motor Corporation are strategically investing in product diversification and technological improvements to maintain their competitive edge in this dynamic and expanding market. The market's future trajectory hinges on the ongoing balance between consumer demand, technological innovation, and regulatory frameworks. Recent developments include: July 2022: American Landmaster launched the electric UTV in the United States. The electric UTV consists of a lithium-ion battery and has different battery options, the entry-level of which is good for 45 miles on a full charge., July 2022: Volcon launched the electric UTV in Texas. The electric UTV has a peak power of 107 kW (143 hp) with a peak torque of 265 lb-ft (360 Nm), a top speed of 130 Kmph, and a range of more than 160 km on a single charge.. Notable trends are: The All-Terrain Vehicle Segment is Likely to Witness Significant Growth.

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TRADING ECONOMICS (2025). United States Wages and Salaries Growth [Dataset]. https://tradingeconomics.com/united-states/wage-growth

United States Wages and Salaries Growth

United States Wages and Salaries Growth - Historical Dataset (1960-01-31/2025-06-30)

Explore at:
4 scholarly articles cite this dataset (View in Google Scholar)
csv, json, xml, excelAvailable download formats
Dataset updated
Jun 14, 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, 1960 - Jun 30, 2025
Area covered
United States
Description

Wages in the United States increased 4.78 percent in June of 2025 over the same month in the previous year. This dataset provides the latest reported value for - United States Wages and Salaries Growth - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

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