The benchmark interest rate in the United States was last recorded at 4.50 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.

Graph and download economic data for Federal Funds Target Range - Upper Limit (DFEDTARU) from 2008-12-16 to 2025-07-12 about federal, interest rate, interest, rate, and USA.

Graph and download economic data for FOMC Summary of Economic Projections for the Fed Funds Rate, Median (FEDTARMD) from 2025 to 2027 about projection, federal, median, rate, and USA.

The benchmark interest rate in Japan was last recorded at 0.50 percent. This dataset provides - Japan Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

In May 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 early 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 May 2025. In contrast, Russia maintained a high inflation rate of 9.9 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.

The benchmark interest rate in Canada was last recorded at 2.75 percent. This dataset provides - Canada Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

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.

United States SCE: Interest Rate Expectation: Probability of Higher Average Interest Rate on Savings Accounts 1 Year from Now data was reported at 26.500 % in Apr 2025. This records an increase from the previous number of 26.133 % for Mar 2025. United States SCE: Interest Rate Expectation: Probability of Higher Average Interest Rate on Savings Accounts 1 Year from Now data is updated monthly, averaging 29.753 % from Jun 2013 (Median) to Apr 2025, with 143 observations. The data reached an all-time high of 41.800 % in Mar 2017 and a record low of 24.225 % in Mar 2024. United States SCE: Interest Rate Expectation: Probability of Higher Average Interest Rate on Savings Accounts 1 Year from Now data remains active status in CEIC and is reported by Federal Reserve Bank of New York. The data is categorized under Global Database’s United States – Table US.H085: Survey of Consumer Expectations: Financial.

The benchmark interest rate in the United Kingdom was last recorded at 4.25 percent. This dataset provides - United Kingdom Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

United States SCE: Stock Price: Probability That US Stock Prices will be Higher 1 Year from Now data was reported at 35.662 % in Apr 2025. This records an increase from the previous number of 33.832 % for Mar 2025. United States SCE: Stock Price: Probability That US Stock Prices will be Higher 1 Year from Now data is updated monthly, averaging 39.618 % from Jun 2013 (Median) to Apr 2025, with 143 observations. The data reached an all-time high of 51.840 % in Apr 2020 and a record low of 33.767 % in Jun 2022. United States SCE: Stock Price: Probability That US Stock Prices will be Higher 1 Year from Now data remains active status in CEIC and is reported by Federal Reserve Bank of New York. The data is categorized under Global Database’s United States – Table US.H085: Survey of Consumer Expectations: Financial.

United States SCE: Unemployment Expectation: Probability That the US Unemployment Rate will be Higher 1 Year from Now data was reported at 44.061 % in Apr 2025. This records an increase from the previous number of 44.045 % for Mar 2025. United States SCE: Unemployment Expectation: Probability That the US Unemployment Rate will be Higher 1 Year from Now data is updated monthly, averaging 37.023 % from Jun 2013 (Median) to Apr 2025, with 143 observations. The data reached an all-time high of 50.858 % in Mar 2020 and a record low of 30.680 % in Jun 2021. United States SCE: Unemployment Expectation: Probability That the US Unemployment Rate will be Higher 1 Year from Now data remains active status in CEIC and is reported by Federal Reserve Bank of New York. The data is categorized under Global Database’s United States – Table US.H082: Survey of Consumer Expectations: Job.

United States CSI: Personal: Real Income Gains Probability: Next 5 Yrs: Mean data was reported at 41.600 % in May 2018. This records an increase from the previous number of 39.900 % for Apr 2018. United States CSI: Personal: Real Income Gains Probability: Next 5 Yrs: Mean data is updated monthly, averaging 38.600 % from Dec 1997 (Median) to May 2018, with 246 observations. The data reached an all-time high of 46.000 % in Feb 2000 and a record low of 27.200 % in Sep 2011. United States CSI: Personal: Real Income Gains Probability: Next 5 Yrs: Mean data remains active status in CEIC and is reported by University of Michigan. The data is categorized under Global Database’s USA – Table US.H024: Consumer Sentiment Index: Personal Finance. The question was: What do you think the chances are that your (family) income will increase by more than the rate of inflation in the next five years or so?

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.

To prepare for an impending event of unknown temporal distribution, humans internally increase the perceived probability of event onset as time elapses. This effect is termed the hazard rate of events. We tested how the neural encoding of hazard rate changes by providing human participants with prior information on temporal event probability. We recorded behavioral and electroencephalographic (EEG) data while participants listened to continuously repeating five-tone sequences, composed of four standard tones followed by a non-target deviant tone, delivered at slow (1.6 Hz) or fast (4 Hz) rates. The task was to detect a rare target tone, which equiprobably appeared at either position two, three or four of the repeating sequence. In this design, potential target position acts as a proxy for elapsed time. For participants uninformed about the target’s distribution, elapsed time to uncertain target onset increased response speed, displaying a significant hazard rate effect at both slow and fast stimulus rates. However, only in fast sequences did prior information about the target’s temporal distribution interact with elapsed time, suppressing the hazard rate. Importantly, in the fast, uninformed condition pre-stimulus power synchronization in the beta band (Beta 1, 15–19 Hz) predicted the hazard rate of response times. Prior information suppressed pre-stimulus power synchronization in the same band, while still significantly predicting response times. We conclude that Beta 1 power does not simply encode the hazard rate, but—more generally—internal estimates of temporal event probability based upon contextual information.

Sea-level rise is an ongoing phenomenon that is expected to continue and is projected to have a wide range of effects on coastal environments and infrastructure during the 21st century and beyond. Consequently, there is a need to assemble relevant datasets and to develop modeling or other analytical approaches to evaluate the likelihood of particular sea-level rise impacts, such as coastal erosion, and to inform coastal management decisions with this information. This report builds on previous work that compiled oceanographic and geomorphic data as part of the U.S. Geological Survey's Coastal Vulnerability Index (CVI) for the U.S. Atlantic Coast, and developed a Bayesian Network to predict shoreline-change rates based on sea-level rise plus variables that describe the hydrodynamic and geologic setting. This report extends the previous analysis to include the Gulf and Pacific coasts of the continental United States and Alaska and Hawaii, which required using methods applied to the USGS CVI dataset to extract data for these regions. The Bayesian Network converts inputs that include observations of local rates of relative sea-level change, mean wave height, mean tide range, a geomorphic classification, coastal slope, and observed shoreline-change rates to calculate the probability of the shoreline-erosion rate exceeding a threshold level of 1 meter per year for the coasts of the United States. The calculated probabilities were compared to the historical observations of shoreline change to evaluate the hindcast success rate of the most likely probability of shoreline change.

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.

Sea-level rise is an ongoing phenomenon that is expected to continue and is projected to have a wide range of effects on coastal environments and infrastructure during the 21st century and beyond. Consequently, there is a need to assemble relevant datasets and to develop modeling or other analytical approaches to evaluate the likelihood of particular sea-level rise impacts, such as coastal erosion, and to inform coastal management decisions with this information. This report builds on previous work that compiled oceanographic and geomorphic data as part of the U.S. Geological Survey's Coastal Vulnerability Index (CVI) for the U.S. Atlantic Coast, and developed a Bayesian Network to predict shoreline-change rates based on sea-level rise plus variables that describe the hydrodynamic and geologic setting. This report extends the previous analysis to include the Gulf and Pacific coasts of the continental United States and Alaska and Hawaii, which required using methods applied to the USGS CVI dataset to extract data for these regions. The Bayesian Network converts inputs that include observations of local rates of relative sea-level change, mean wave height, mean tide range, a geomorphic classification, coastal slope, and observed shoreline-change rates to calculate the probability of the shoreline-erosion rate exceeding a threshold level of 1 meter per year for the coasts of the United States. The calculated probabilities were compared to the historical observations of shoreline change to evaluate the hindcast success rate of the most likely probability of shoreline change.

The time separating the first appearances of species from their divergences from related taxa affects assessments of macroevolutionary hypotheses about rates of anatomical or ecological change. Branch durations necessarily posit stratigraphic gaps in sampling within a clade over which we have failed to sample predecessors (ancestors) and over which there are no divergences leading to sampled relatives (sister taxa). The former reflects only sampling rates whereas the latter reflects sampling, origination and extinction rates. Because all three rates vary over time, the probability of a branch duration of any particular length will differ depending on when in the Phanerozoic that branch duration spans. Here, I present a birth death sampling model allowing interval to interval variation in diversification and sampling rates. Increasing either origination or sampling rates increases the probability of finding sister taxa that diverge both during and before intervals of high sampling/origination. Conversely, elevated extinction reduces the probability of divergences from sampled sister taxa before and during intervals of elevated extinction. In the case of total extinction, a Signor-Lipps will reduce expected sister-taxa leading up to the extinction, with the possible effect stretching back many millions of years when sampling is low. Simulations indicate that this approach provides reasonable estimates of branch duration probabilities under a variety of circumstances. Because our current probability models for describing morphological evolution are not as advanced as our methods for inferring diversification and sampling rates, branch duration priors allowing for time varying diversification and could be a potent tool for phylogenetic inference with fossil data.

We use the yield curve to predict future GDP growth and recession probabilities. The spread between short- and long-term rates typically correlates with economic growth. Predications are calculated using a model developed by the Federal Reserve Bank of Cleveland. Released monthly.

United States CSI: Personal: Real Income Gains Probability: Next 5 Yrs: 50% data was reported at 18.000 % in May 2018. This records an increase from the previous number of 16.000 % for Apr 2018. United States CSI: Personal: Real Income Gains Probability: Next 5 Yrs: 50% data is updated monthly, averaging 17.000 % from Dec 1997 (Median) to May 2018, with 246 observations. The data reached an all-time high of 26.000 % in Feb 1998 and a record low of 11.000 % in Jul 2014. United States CSI: Personal: Real Income Gains Probability: Next 5 Yrs: 50% data remains active status in CEIC and is reported by University of Michigan. The data is categorized under Global Database’s USA – Table US.H024: Consumer Sentiment Index: Personal Finance. The question was: What do you think the chances are that your (family) income will increase by more than the rate of inflation in the next five years or so?