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.

The purpose of the data is to investigate whether and how financial markets have responded to the change in the Federal Open Market Commission (FOMC) disclosure policy, specifically, whether the policy of immediate disclosure has created an announcement effect and whether the policy of immediate disclosure has increased or reduced financial market uncertainty.

For many years prior to the global financial crisis, the Federal Open Market Committee set a target for the federal funds rate and achieved that target through small purchases and sales of securities in the open market. In the aftermath of the financial crisis, with a superabundant level of reserve balances in the banking system having been created as a result of the Federal Reserve's large-scale asset purchase programs, this approach to implementing monetary policy will no longer work. This paper provides a primer on the Fed's implementation of monetary policy. We use the standard textbook model to illustrate why the approach used by the Federal Reserve before the financial crisis to keep the federal funds rate near the Federal Open Market Committee's target will not work in current circumstances, and explain the approach that the Committee intends to use instead when it decides to begin raising short-term interest rates.

Among the ** Federal Reserve Banks of the Federal Reserve System in the United States, the Federal Reserve Bank of New York held by far the highest value of assets in 2023. With approximately *** trillion U.S. dollars on its balance sheet, the Federal Reserve Bank of New York held over ** percent of the Fed's total assets. It was followed by the Federal Reserve Bank of San Francisco.

Graph and download economic data for Longer Run FOMC Summary of Economic Projections for the Civilian Unemployment Rate, Central Tendency, Midpoint (UNRATECTMLR) from 2009-02-18 to 2025-06-18 about projection, civilian, unemployment, rate, and USA.

Abstract (en): The Federal Reserve implements its monetary policy by using open market operations in United States government securities to target the federal funds rate. A substantial decline in the stock of United States Treasury debt could interfere with the conduct of monetary policy, possibly forcing the Fed to rely more heavily on discount window lending or to conduct open market transactions in other types of securities. Either choice would cause the implementation of monetary policy to resemble the methods used by the Fed before World War II. This paper describes two things: (1) how the Fed implemented monetary policy before the war and (2) the conflicts that arose within the Fed over the allocation of private-sector credit when discount window loans and Fed purchases of private securities were a substantial component of Federal Reserve credit. Those conflicts help explain the Fed's failure to respond vigorously to the Great Depression. The experience suggests that a renewed reliance on the discount window or on open market operations in securities other than those issued by the United States Treasury could hamper the conduct of monetary policy if it leads to increased pressure on the Fed to affect the allocation of credit. The file submitted is 0205dwd.txt. These data are part of ICPSR's Publication-Related Archive and are distributed exactly as they arrived from the data depositor. ICPSR has not checked or processed this material. Users should consult the investigator if further information is desired.

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

Graph and download economic data for Future Employment; Percent Reporting Increases for Federal Reserve District 3: Philadelphia (NEFISA156MSFRBPHI) from May 1968 to Jun 2025 about FRB PHI District, percent, employment, and USA.

This paper investigates the nature of nonlinearities in the monetary policy rule of the US Federal Reserve (Fed) using the flexible approach to nonlinear inference. We find that while there is significant evidence of nonlinearity for the period to 1979, there is little such evidence for the subsequent period. Possible asymmetries in the Fed's reactions to inflation deviations from target and the output gap in the 1960s and 1970s may tell part of the story, but do not capture the entire nature of the nonlinearity. The inclusion of the interaction between inflation deviations and the output gap, as recently proposed, appears to characterize the nonlinear policy rule more adequately.

Kansas Fed Composite Index in the United States increased to -2 points in June from -3 points in May of 2025. This dataset includes a chart with historical data for the United States Kansas Fed Composite Index.

The STLFSI4 measures the degree of financial stress in the markets and is constructed from 18 weekly data series: seven interest rate series, six yield spreads and five other indicators. Each of these variables captures some aspect of financial stress. Accordingly, as the level of financial stress in the economy changes, the data series are likely to move together.

How to Interpret the Index: The average value of the index, which begins in late 1993, is designed to be zero. Thus, zero is viewed as representing normal financial market conditions. Values below zero suggest below-average financial market stress, while values above zero suggest above-average financial market stress.

More information: The STLFSI4 is the third revision (i.e., STLFSI3 (https://fred.stlouisfed.org/series/STLFSI3) and STLFSI2 (https://fred.stlouisfed.org/series/STLFSI2) of the original STLFSI (https://fred.stlouisfed.org/series/STLFSI). Whereas the STLFSI3 used the past 90-day average backward-looking secured overnight financing rate (SOFR) (https://fred.stlouisfed.org/series/SOFR90DAYAVG) in two of their yield spreads, the STLFSI4 uses the 90-day forward-looking SOFR (https://www.cmegroup.com/market-data/cme-group-benchmark-administration/term-sofr.html) in its place. For more information, see "The St. Louis Fed’s Financial Stress Index, Version 4.0" (https://fredblog.stlouisfed.org/2022/11/the-st-louis-feds-financial-stress-index-version-4/). For information on earlier STLFSIs, see "Measuring Financial Market Stress" (https://files.stlouisfed.org/files/htdocs/publications/es/10/ES1002.pdf), "The St. Louis Fed’s Financial Stress Index, Version 2.0." (https://fredblog.stlouisfed.org/2020/03/the-st-louis-feds-financial-stress-index-version-2-0/), and "The St. Louis Fed’s Financial Stress Index, Version 3.0" (https://fredblog.stlouisfed.org/2022/01/the-st-louis-feds-financial-stress-index-version-3-0/).

Graph and download economic data for Overnight Reverse Repurchase Agreements Award Rate: Treasury Securities Sold by the Federal Reserve in the Temporary Open Market Operations (RRPONTSYAWARD) from 2013-09-23 to 2025-07-11 about reverse repos, overnight, securities, Treasury, sales, rate, and USA.

Content

Kim and Wright (2005) produced this data by fitting a simple three-factor arbitrage-free term structure model to U.S. Treasury yields since 1990, in order to evaluate the behavior of long-term yields, distant-horizon forward rates, and term premiums. For the full paper, please go to http://www.federalreserve.gov/pubs/feds/2005/200533/200533abs.html

Context

This is a dataset from the Federal Reserve hosted by the Federal Reserve Economic Database (FRED). FRED has a data platform found here and they update their information according to the frequency that the data updates. Explore the Federal Reserve using Kaggle and all of the data sources available through the Federal Reserve organization page!

• Update Frequency: This dataset is updated daily.

• Observation Start: 1990-01-02

• Observation End : 2019-09-30

Acknowledgements

This dataset is maintained using FRED's API and Kaggle's API.

Cover photo by Ian Schneider on Unsplash
Unsplash Images are distributed under a unique Unsplash License.

United States Diffusion Index: sa: New York Fed: General Business Condition: Highe data was reported at 39.600 NA in Jul 2018. This records an increase from the previous number of 37.700 NA for Jun 2018. United States Diffusion Index: sa: New York Fed: General Business Condition: Highe data is updated monthly, averaging 30.700 NA from Jul 2001 (Median) to Jul 2018, with 205 observations. The data reached an all-time high of 50.600 NA in Apr 2004 and a record low of 9.900 NA in Mar 2009. United States Diffusion Index: sa: New York Fed: General Business Condition: Highe data remains active status in CEIC and is reported by Federal Reserve Bank of New York. The data is categorized under Global Database’s USA – Table US.S009: Empire State Manufacturing Survey.

Philly Fed CAPEX Index in the United States decreased to 14.50 points in June from 27 points in May of 2025. This dataset includes a chart with historical data for the United States Philly Fed CAPEX Index.

Summary:The Fire Event Data Suite, or FEDS, algorithm uses high resolution VIIRS observations to map fire perimeters, identify the active portion of fire fronts, and track the progression and attributes of individual fires every 12 hours. For individual fire events, FEDS contains information on the latest active fire detections, as well as the total fire event history in 12 hour increments. The vector output from the FEDS algorithm is produced within approximately 4 hours following the availability of VIIRS 375 m active fire data in FIRMS. The FEDS algorithm was originally developed and tested for large fires in California (Chen et al., (2022)). The EIS Fire team has scaled the production of the fire event tracking approach to cover CONUS and Canada, with data available via OGC API. Data for additional regions, including Alaska and Hawaii, will be released through FIRMS when available.Information on this data and FIRMS can be found here.Suggested Usage:Perimeter data are helpful for understanding the time series progression of a fire event, as observed via the VIIRS sensor. Given the source data, the same considerations that must be taken for FIRMS active fire data are applicable here. All data are experimental and should always be verified with supplementary sources of information when available.The VIIRS Modeled Fire Perimeter Data product provides situational awareness for large fire events in CONUS and Canada every 12 hours, based on the FEDS algorithm and available 375 m VIIRS active fire detection data from Suomi-NPP and NOAA-20. The modeled perimeter is an estimate of the fire-affected area, active portion of the fire perimeter, and metrics of fire behavior. The VIIRS Modeled Fire Perimeter data also provides a history of modeled large fire growth every 12 hours for all fire events detected by VIIRS in CONUS and Canada. By contrast, the USA Fire Perimeter layer is the most recent official incident perimeter data. Official incident data provide a more precise estimate of the perimeter of large fire events in the US than the VIIRS Modeled Fire Perimeter data. The USA Fire Perimeter layer is updated periodically with new official incident perimeter data.Date of Next Image:Updates available at approximate 12-hour intervals.Satellite/Sensor:Suomi NPP and NOAA-20 satellites carrying the VIIRS sensor. The FEDS algorithm uses the locations and sizes of each pixel to derive perimeter information and track individual fire events.Resolution:375m at nadirCredits:NASA Earth Information System (EIS)Doug Morton, Melanie Follette-Cook, Elijah Orland, Tempest McCabe (all GSFC), Yang Chen (UC Irvine)Scientific PaperEsri REST Endpoint:See URL section on right side of page

Enforcement actions against entities and individuals for violations of laws, rules, or regulations

Content

This series has been discontinued and will no longer be updated. It was a duplicate of the following series, which will continue to be updated: https://fred.stlouisfed.org/series/WSHOMCB

The current face value of mortgage-backed obligations held by Federal Reserve Banks. These securities are guaranteed by Fannie Mae, Freddie Mac, or Ginnie Mae.

Context

This is a dataset from the Federal Reserve hosted by the Federal Reserve Economic Database (FRED). FRED has a data platform found here and they update their information according to the frequency that the data updates. Explore the Federal Reserve using Kaggle and all of the data sources available through the Federal Reserve organization page!

• Update Frequency: This dataset is updated daily.

• Observation Start: 2002-12-18

• Observation End : 2018-06-13

Acknowledgements

This dataset is maintained using FRED's API and Kaggle's API.

Cover photo by Rob Sarmiento on Unsplash
Unsplash Images are distributed under a unique Unsplash License.

Content

More details about each file are in the individual file descriptions.

Context

This is a dataset from the Federal Reserve hosted by the Federal Reserve Economic Database (FRED). FRED has a data platform found here and they update their information according to the frequency that the data updates. Explore the Federal Reserve using Kaggle and all of the data sources available through the Federal Reserve organization page!

• Update Frequency: This dataset is updated daily.

Acknowledgements

This dataset is maintained using FRED's API and Kaggle's API.

This dataset tracks annual two or more races student percentage from 2022 to 2023 for Feds Creek Elementary School vs. Kentucky and Pike County School District