The benchmark interest rate in the United States was last recorded at 4.25 percent. This dataset provides the latest reported value for - United States Fed Funds Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The benchmark interest rate in Indonesia was last recorded at 4.75 percent. This dataset provides - Indonesia Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The benchmark interest rate in Australia was last recorded at 3.60 percent. This dataset provides - Australia Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

View data of the Effective Federal Funds Rate, or the interest rate depository institutions charge each other for overnight loans of funds.

The benchmark interest rate in Canada was last recorded at 2.50 percent. This dataset provides - Canada Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Graph and download economic data for Interest Rates, Discount Rate for United States (INTDSRUSM193N) from Jan 1950 to Aug 2021 about discount, interest rate, interest, rate, and USA.

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.

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; ...).

A dataset of mentions, growth rate, and total volume of the keyphrase 'China Rate Cuts' over time.

This dataset contains the predicted prices of Rate Cuts for the upcoming years based on user-defined projections.

The benchmark interest rate in China was last recorded at 3 percent. This dataset provides the latest reported value for - China Interest Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The data and programs replicate tables and figures from "Piece-rate cuts and ratchet effects", by Shearer. Please see the ReadMe file for additional details.

This data is from the California Department of Managed Health Care (DMHC). It contains all information on health plan proposed premium rates filed with the DMHC since January 1, 2011. The DMHC is committed to providing the public with information in order to expand consumer understanding about premium rate increases. The DMHC does not have the authority to approve or deny rate increases; however, the DMHC's review of proposed premium rates improves accountability in health plan rate setting and often results in a reduction in the proposed rate.

Graph and download economic data for Personal Saving Rate (PSAVERT) from Jan 1959 to Jul 2025 about savings, personal, rate, and USA.

This dataset tracks annual graduation rate from 2013 to 2023 for Cut Bank High School District vs. Montana

The benchmark interest rate In the Euro Area was last recorded at 2.15 percent. This dataset provides - Euro Area Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The Reduced Rate Certificate (RRC) report lists the name and addresses of all facilities that are covered by a Climate Change Agreement and the period for which they are covered by an agreement. We are required to publish the list of facilities as soon as reasonably practicable after the first day of each certification period. The certification periods are as follows: • Certification period 1 (01 April 2013 – 30 June 2015) • Certification period 2 (01 July 2015 – 30 June 2017) • Certification period 3 (01 July 2017 – 30 June 2019) • Certification period 4 (01 July 2019 – 30 June 2021) • Certification period 5 (01 July 2021 – 30 June 2023) • Certification period 6 (01 July 2023 – 30 June 2025) • Certification period 7 (01 July 2025 – 30 June 2027) (Current) We are also required to update the list on the last working day of each month if there have been any changes since the date of the last publication. The requirements to publish the list and updates stem from Regulations 9(1) and (2) of the Climate Change Agreements (Administration) Regulations 2012. Facility addresses for the six sectors listed below are not released for reasons of National Security/Site Security: • NFU1 (Pigs) • NFU5 (Eggs & Poultry Meat) • BMPA (Meat) • BPC1 (Poultry Meat) • BPC2 (Poultry) • DATC (Data Centres). The operators of facilities included in this list are entitled to claim a discount on the Climate Change Levy. Attribution statement: © Environment Agency copyright and/or database right 2016. All rights reserved.

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.

This data set provides energetic (MeV) ion count rates and events measured by the Heavy Ion Counter (HIC) instrument on the Galileo spacecraft. These data are derived from high time resolution raw data that were recorded to tape and then played back later in the orbit. There are two basic types of data files associated with the full-rate reduced data: Detector Count Rates and Events (Pulse Heights).

New Zonage “A/B/C” applicable from 01/10/2014 (Ministerial Decree of 01 August 2014).

The “A/B/C” zoning, created in 2003 at the time when Robien’s rental investment scheme was introduced, characterises the tension of the local real estate market, i.e. the adequacy of the demand for and the supply of available housing on a territory. It consists of five modalities ranging from the most tense (Abis) to the most relaxed (C).Franche-Comté is only affected by zones B2 and C. Several financial schemes use this zoning to determine the eligibility of territories for aid or to adjust their parameters (level of aid, ceiling of rents, etc.). These include the Intermediate Rental Investment Facility for Individuals (see Duflot Zoning), the Old Borloo, the Intermediate Rental Loan (PLI), the Zero Rate Loan (PTZ), the Social Accession Rental Loan (PSLA) and the Social Access Loan (PAS) to property, and the reduced rate VAT in the ANRU area.Some ANAH aid to social lenders is also linked to a ceiling on rent and the amount of resources of the tenant, which varies according to the zoning A/B/C. Following a consultation conducted by the Regional Prefect with the local authorities in the 4th quarter of 2013, the new zoning A/B/C was adopted by the Minister in charge of Housing on 1 August 2014. For Franche-Comté, 19 new municipalities were reclassified from C to B2, while no decommissioning was recorded. Its entry into force varies between 1 October 2014 and 1 February 2015 depending on the arrangements attached to it:

as of 1 October 2014 for: — the zero-rate loan; — the guarantee scheme of the FGAS; — the reduced rate VAT scheme for intermediate rental accommodation (279-0a A of the CGI); — the aid scheme for intermediate rental investment for private individuals (199 novitiies of the General Tax Code (CGI); — promises of sales of public land, pursuant to Article R. 3211-15 of the General Code of Ownership of Public Persons;

on 1 January 2015 for: — the benefit of aid from the National Housing Agency, the ‘old Borloo’ tax scheme; — the intermediate rental loan; — reduced VAT in ANRU area; — devices related to HLM promotion; — the assessment of resources for new intermediate dwellings held by HLML bodies in the context of their service of general economic interest;

as of 1 February 2015 for: — approvals of social loans for leasing-accession.

Data sources: order of the Minister of Housing dated 01 August 2014