8 datasets found
  1. T

    Sweden Interest Rate

    • tradingeconomics.com
    • fa.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated May 8, 2025
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    TRADING ECONOMICS (2025). Sweden Interest Rate [Dataset]. https://tradingeconomics.com/sweden/interest-rate
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    csv, excel, xml, jsonAvailable download formats
    Dataset updated
    May 8, 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
    May 26, 1994 - Jul 31, 2025
    Area covered
    Sweden
    Description

    The benchmark interest rate in Sweden was last recorded at 2 percent. This dataset provides the latest reported value for - Sweden Interest Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  2. T

    Australia Interest Rate

    • tradingeconomics.com
    • it.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jul 8, 2025
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    TRADING ECONOMICS (2025). Australia Interest Rate [Dataset]. https://tradingeconomics.com/australia/interest-rate
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    excel, csv, xml, jsonAvailable download formats
    Dataset updated
    Jul 8, 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 22, 1990 - Jul 8, 2025
    Area covered
    Australia
    Description

    The benchmark interest rate in Australia was last recorded at 3.85 percent. This dataset provides - Australia Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  3. e

    Macro time series and monetary policy decisions for Norway (1990-2018) -...

    • b2find.eudat.eu
    Updated Aug 9, 2024
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    (2024). Macro time series and monetary policy decisions for Norway (1990-2018) - Dataset - B2FIND [Dataset]. https://b2find.eudat.eu/dataset/96980487-38bc-5ea3-a8c0-3f7d7d040890
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    Dataset updated
    Aug 9, 2024
    Area covered
    Norway
    Description

    Monetary policy is generally regarded as a central element in the attempts of policy makers to attenuate business-cycle fluctuations. According to the New Keynesian paradigm, central banks are able to stimulate or depress aggregate demand in the short run by adjusting their nominal interest rate targets. The effects of interest rate changes on aggregate consumption, the largest component of aggregate demand, are well understood in the context of this paradigm, on which the canonical "workhorse'' model used in monetary policy analysis is grounded. A key feature of the model is that aggregate consumption is fully described by the amount of goods consumed by a representative household. A decline in the policy rate for instance implies that the real interest rate declines, the representative household saves less and hence increase its demand for consumption. At the same time, general equilibrium effects let labour income grow causing consumption to increase further. However, the mechanism outlined above ignores a considerable amount of empirically-observed heterogeneity among households. For example, households with a higher earnings elasticity to interest rate changes benefit more from a rate cut than those with a lower elasticity; households with large debt positions are at a relative advantage over households with large bond holdings; and households with low exposure to inflation are relatively better off than those holding a sizeable amount of nominal assets. As a result, the contribution to the aggregate consumption response differs substantially across households, implying that monetary expansions and tightenings produce relative "winners'' and relative "losers''. The aim of the project laid out in this proposal is to give a disaggregated account of the heterogeneous effects of monetary-policy induced interest rate changes on household consumption and a detailed analysis of the channels underlying them. Additionally, it seeks to draw conclusions about the determinants of the strength of the transmission mechanism of monetary policy. To do so, it relies on a large panel comprising detailed data from the universe of all households residing in Norway between 1993 and 2015 supplemented with additional micro-data provided by the European Commission. I will be assisted by two project partners, Pascal Paul who is a member of the Research Department of the Federal Reserve Bank of San Francisco and Martin Holm who is affiliated with the Research Unit of Statistics Norway and the University of Oslo. In addition, I would like to collaborate with and help train a doctoral student based at the University of Lausanne on this project. Existing empirical studies of the consumption response to monetary policy at the micro level rely on survey data. Therefore, they are subject to a number of severe data limitations. The surveys employed typically have either no or only a short panel dimension, suffer from attrition, include only limited information on income and wealth, are top-coded, and contain a significant amount of measurement error. The administrative data set provided to us by Statistics Norway suffers from none of these issues, implying that we are in a unique position to evaluate the household-level effects of policy rate changes. In a first step, we use forecasts published by the Norwegian central bank to derive monetary policy shocks that are robust to the simultaneity problem inherent in the identification of the effects of monetary policy following Romer and Romer (2004). We then confront the micro-data with the estimated shocks to study the consumption response along different segments of the income and wealth distribution and to test the importance of heterogeneity in labour earnings, financial income, liquid assets, inflation exposure and interest rate exposure among others. The findings will be of high relevance as they will not only allow us to evaluate channels hypothesised in the analytical literature, improve our understanding of the monetary policy transmission mechanism and its distributional consequences but also serve as a benchmark for structural models built both by theorists and practitioners.

  4. T

    Turkey Interest Rate

    • tradingeconomics.com
    • de.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jul 24, 2025
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    TRADING ECONOMICS (2025). Turkey Interest Rate [Dataset]. https://tradingeconomics.com/turkey/interest-rate
    Explore at:
    json, excel, csv, xmlAvailable download formats
    Dataset updated
    Jul 24, 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 2, 1990 - Jul 24, 2025
    Area covered
    Türkiye
    Description

    The benchmark interest rate in Turkey was last recorded at 43 percent. This dataset provides the latest reported value for - Turkey Interest Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  5. Financial market statistics, as at Wednesday, Bank of Canada

    • www150.statcan.gc.ca
    • datasets.ai
    • +1more
    Updated Aug 8, 2025
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    Government of Canada, Statistics Canada (2025). Financial market statistics, as at Wednesday, Bank of Canada [Dataset]. http://doi.org/10.25318/1010014501-eng
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    Dataset updated
    Aug 8, 2025
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Government of Canadahttp://www.gg.ca/
    Area covered
    Canada
    Description

    This table contains 38 series, with data starting from 1957 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada), Rates (38 items: Bank rate; Chartered bank administered interest rates - prime business; Chartered bank - consumer loan rate; Forward premium or discount (-), United States dollars in Canada: 1 month; ...).

  6. T

    Nigeria Interest Rate

    • tradingeconomics.com
    • jp.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated May 20, 2025
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    TRADING ECONOMICS (2025). Nigeria Interest Rate [Dataset]. https://tradingeconomics.com/nigeria/interest-rate
    Explore at:
    json, excel, csv, xmlAvailable download formats
    Dataset updated
    May 20, 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, 2007 - Jul 22, 2025
    Area covered
    Nigeria
    Description

    The benchmark interest rate in Nigeria was last recorded at 27.50 percent. This dataset provides - Nigeria Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  7. Bank of Canada, money market and other interest rates

    • www150.statcan.gc.ca
    • open.canada.ca
    • +1more
    Updated Aug 11, 2025
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    Government of Canada, Statistics Canada (2025). Bank of Canada, money market and other interest rates [Dataset]. http://doi.org/10.25318/1010013901-eng
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    Dataset updated
    Aug 11, 2025
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Government of Canadahttp://www.gg.ca/
    Area covered
    Canada
    Description

    This table contains 39 series, with data for starting from 1991 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada); Financial market statistics (39 items: Government of Canada Treasury Bills, 1-month (composite rates); Government of Canada Treasury Bills, 2-month (composite rates); Government of Canada Treasury Bills, 3-month (composite rates);Government of Canada Treasury Bills, 6-month (composite rates); ...).

  8. f

    Data from: S1 Dataset -

    • plos.figshare.com
    xlsx
    Updated Sep 6, 2024
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    Verónica M. Merino; René Aguilar; Luis F. Piña; Miguel Garriga; Enrique Ostria-Gallardo; M. Dolores López; Felipe Noriega; Jorge Campos; Soledad Navarrete; M. Jordana Rivero (2024). S1 Dataset - [Dataset]. http://doi.org/10.1371/journal.pone.0310009.s001
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    xlsxAvailable download formats
    Dataset updated
    Sep 6, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Verónica M. Merino; René Aguilar; Luis F. Piña; Miguel Garriga; Enrique Ostria-Gallardo; M. Dolores López; Felipe Noriega; Jorge Campos; Soledad Navarrete; M. Jordana Rivero
    License

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

    Description

    Traditional pastures in temperate regions face limitations such as reduced growth and nutritional quality during the summer season. Plantain (P. lanceolata L.) offers advantages like increased yield and decreased nitrogen losses from grazing ruminants. Effective grazing management is essential for pasture health, and defoliation frequency and intensity play a pivotal role. This study aimed to evaluate plantain’s regrowth, yield, and morpho-physiological and chemical responses under different defoliation frequencies and intensities, with the goal of enhancing its management in pastures. The study was conducted in pots within a controlled-environment growth chamber, examining the impact of three defoliation frequencies (based on extended leaf length: 15, 25 and 35 cm) and two defoliation intensities (5 and 8 cm of residual heights) with four replicates (24 pots as experimental units). The variables of interest were morphological characteristics, dry matter (DM) accumulation, herbage chemical composition, growth rate traits, and photosynthetic parameters. Defoliation frequency affected plantain’s growth and nutritional composition. More frequent cuts (15 cm) resulted in lower DM yield per cut and lower stem content, while less frequent cuts (35 cm) produced higher values. Defoliation intensity influenced the proportion of leaves and stems in the total DM, with 5 cm cuts favoring leaves. Nutrient content was also affected by defoliation frequency, with less frequent cuts (35 cm) showing lower crude protein concentration and metabolizable energy content but higher neutral detergent fiber and water-soluble carbohydrate concentration. Plantain’s growth rate variables were mainly influenced by defoliation frequency, with less frequent cuts promoting faster leaf appearance and growth of new leaves. The basal fluorescence variables and chlorophyll content were affected by cutting frequency, being highest when cut less frequently (35 cm), while no differences were found in the actual quantum efficiency among different defoliation frequencies and intensities. The fraction of light dedicated to non-photochemical quenching was highest when cut less frequently and more intensively. Overall, defoliation at 25 cm of extended leaf length balanced plantain forage quality and regrowth capacity.

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TRADING ECONOMICS (2025). Sweden Interest Rate [Dataset]. https://tradingeconomics.com/sweden/interest-rate

Sweden Interest Rate

Sweden Interest Rate - Historical Dataset (1994-05-26/2025-07-31)

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11 scholarly articles cite this dataset (View in Google Scholar)
csv, excel, xml, jsonAvailable download formats
Dataset updated
May 8, 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
May 26, 1994 - Jul 31, 2025
Area covered
Sweden
Description

The benchmark interest rate in Sweden was last recorded at 2 percent. This dataset provides the latest reported value for - Sweden Interest Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

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