List of US Counties (including FIPS State and FIPS County codes) and the respective Federal Reserve District they belong to.

This spreadsheet extends the Excel file "U.S. FIPS County Codes" by MDR Education to include 'Federal Reserve District Boundaries' based on the 1996 document published by the Federal Reserve Bank of St. Louis. It also includes the US territories that are under the Federal Reserve System. There may be some differences in county lists as minor changes to county names have occurred since 1996.

Insured domestically chartered commercial banks and savings associations that have one or more branch offices in a foreign country are required to report balance sheet information for each of their foreign branches on either the Federal Financial Institutions Examination Council (FFIEC) 030 or FFIEC 030S. The Foreign Branch Report of Condition (FFIEC 030) collects information on the structure and geographic distribution of foreign branch assets, liabilities, derivatives, and off-balance-sheet data. The Abbreviated Foreign Branch Report of Condition (FFIEC 030S) collects five financial data items for smaller, less complex branches. The FFIEC 030 is collected annually as of December 31 or quarterly for significant branches as of the last day of each calendar quarter; the FFIEC 030S is an abbreviated reporting form filed annually by smaller institutions. The Federal Reserve receives reports for all foreign branches of U.S. banks, regardless of charter type, on behalf of the U.S. banks' primary federal bank regulatory agency (Board, Federal Deposit Insurance Corporation (FDIC), or Office of the Comptroller of the Currency (OCC) (collectively, the agencies)). The agencies use the FFIEC 030 and FFIEC 030S reports to fulfill their statutory obligation to supervise foreign operations of domestic banks.

🏛️ Federal Reserve Document Scraper

1. Dataset description

This repository contains code for downloading and organizing Federal Reserve documents from the official Federal Reserve Board website.

These files were used as part of my NLP project. While collecting data, my data collection code is inspired by centralbank_analysis by yukit-k. However, that implementation had some limitations:

❌ Incomplete handling of newer HTML structures on the Fed website

❌ No support for Greenbook/Tealbook files

❌ File naming and folder structure not ideal for downstream processing

❌ No handling of failed downloads or noisy formatting

So I made som key Improvements:

✅ Supports both Greenbook and Minutes. You can choose which type to download

✅ Automatic directory organization. Files are saved using a consistent format as:

FOMC_[document type]_YYYY-MM-DD

✅ Duplicate check & resume support: Prevents redundant downloads and handles broken links gracefully

✅ Modular and extensible codebase Easy to extend for other Fed documents (e.g., SEP, transcripts)

2. Data detail

This repository contains modules for downloading and processing various official publications of the Federal Open Market Committee (FOMC). These documents, produced and released by the Federal Reserve, provide detailed insight into U.S. monetary policy formation, communication, and economic analysis over time.

Below is a reference guide to the major FOMC document types represented in this repository.

📅 FomcAgenda.py – Meeting Agendas

Agendas are created by the FOMC Secretariat in coordination with the Chair and outline the topics of discussion for each meeting, including standard items (e.g., open market operations, economic outlook) and special topics. Participants receive the agenda about one week in advance.

📄 FomcStatement.py – Policy Statements

FOMC statements are brief summaries of monetary policy decisions released immediately after each meeting. These statements have become a key communication tool since 1994 and are now issued after every scheduled meeting, even if policy remains unchanged.

📝 FomcMinutes.py – Meeting Minutes

Minutes provide a concise, narrative summary of policy discussions and rationales. Since 2004, they are released three weeks after each meeting. The minutes include details on voting outcomes and dissenting views, and are eventually included in the Fed’s Annual Report.

🧾 FomcPresConfScript.py – Press Conference Transcripts

Beginning in 2011, the Fed Chair has held press conferences following certain FOMC meetings. These transcripts document the Chair’s remarks and responses to journalists, offering additional context and forward guidance. Released shortly after the meeting.

🗣️ FomcMeetingScript.py – Meeting Transcripts

Verbatim transcripts of FOMC meetings, produced from audio recordings and lightly edited for readability. They are released with a 5-year delay. For meetings prior to 1994, transcripts were reconstructed from raw records and may contain transcription uncertainties.

📚 FomcGreenbook.py – Greenbook (1964–2010)

The Greenbook, officially titled Current Economic and Financial Conditions, was prepared by Board staff and delivered to FOMC members six days before each meeting. It provided forecasts, data analyses, and economic outlooks.

Part 1: Summary and forecast

Part 2: Detailed breakdowns

Supplement: Late-breaking updates

📘 FomcBlueBook.py – Bluebook (1965–2010)

The Bluebook, titled Monetary Policy Alternatives, outlined potential policy options and risks. It was distributed shortly after the Greenbook and informed FOMC decisions. The document evolved from earlier versions like Money Market and Reserve Relationships.

🧠 FomcTealbook.py – Tealbook (2010–Present)

The Tealbook replaced both the Greenbook and Bluebook in June 2010. It is split into two parts:

Tealbook A: Current Situation and Outlook — Forecasts and financial developments

Tealbook B: Strategies and Alternatives — Policy options and simulations

Both are released with a 5-year lag.

📙 FomcBeigeBook.py – Beige Book

The Beige Book, published eight times a year, summarizes anecdotal economic conditions across the 12 Federal Reserve Districts. Based on business surveys, interviews, and internal reports, it is released ~two weeks before each meeting.

🧾 FomcTestimony.py – Testimony before Congress

This includes the Chair’s Semiannual Monetary Policy Report to Congress and other testimonies. These communications explain the Fed’s outlook and policies directly to lawmakers and the public.

📚 References

Federal Reserve – FOMC Archive

Wikipedia – Federal Open Market Committee

Dataset Summary

For dataset summary, please refer to https://huggingface.co/datasets/gtfintechlab/federal_reserve_system

  Additional Information

This dataset is annotated across three different tasks: Stance Detection, Temporal Classification, and Uncertainty Estimation. The tasks have four, two, and two unique labels, respectively. This dataset contains 1,000 sentences taken from the meeting minutes of the Federal Reserve System.

  Label Interpretation… See the full description on the dataset page: https://huggingface.co/datasets/gtfintechlab/federal_reserve_system.

Graph and download economic data for All Employees: Leisure and Hospitality: Limited-Service Restaurants and Other Eating Places in California (SMU06000007072259001SA) from Jan 1990 to Aug 2025 about restaurant, leisure, hospitality, food, CA, services, employment, and USA.

The USGS Governmental Unit Boundaries dataset from The National Map (TNM) represents major civil areas for the Nation, including States or Territories, counties (or equivalents), Federal and Native American areas, congressional districts, minor civil divisions, incorporated places (such as cities and towns), and unincorporated places. Boundaries data are useful for understanding the extent of jurisdictional or administrative areas for a wide range of applications, including mapping or managing resources, and responding to natural disasters. Boundaries data also include extents of forest, grassland, park, wilderness, wildlife, and other reserve areas useful for recreational activities, such as hiking and backpacking. Boundaries data are acquired from a variety of government sources. The data represents the source data with minimal editing or review by USGS. Please refer to the feature-level metadata ...

This hosted feature layer has been published in RI State Plane Feet NAD 83.The RI Neighborhood Stabilization Program (NSP) Mapping analysis was performed to assist the Office of Housing and Community Development in identifying target areas with both a Foreclosure Rate (Block Group Level) >=6.5% and a Subprime Loan percentage rate >= 1.4% (Zip Code Level). Based on these criteria the following communities were identified as containing such target areas: Central Falls, Cranston, Cumberland, East Providence, Johnston, North Providence, Pawtucket, Providence, Warwick, West Warwick, and Woonsocket. Federal funding, under the Housing and Economic Recovery Act of 2008 (HERA), Neighborhood Stabilization Program (NSP), totaling $19.6 will be expended in these NSP Target Areas to assist in the rehabilitation and redevelopment of abandoned and foreclosed homes, stabilizing communities.The State of Rhode Island distributes funds allocated, giving priority emphasis and consideration to those areas with the greatest need, including those areas with - 1) Highest percentage of home foreclosures; 2) Highest percentage of homes financed by subprime mortgage loans; and 3) Anticipated increases in rate of foreclosure. The RI Office of Housing and Community Development, with the assistance of Rhode Island Housing, utilized the following sources to meet the above requirements. 1) U.S. Department of Housing & Urban Development (HUD) developed foreclosure data to assist grantees in identification of Target Areas. The State utilized HUD's predictive foreclosure rates to identify those areas which are likely to face a significant rise in the rate of home foreclosures. HUD's methodology factored in Home Mortgage Disclosure Act, income, unemployment, and other information in its calculation. The results were analyzed and revealed a high level of consistency with other needs data available. 2) The State obtained subprime mortgage loan information from the Federal Reserve Bank of Boston. Though the data does not include all mortgages, and was only available at the zip code level rather than Census Tract, findings were generally consistent with other need categories. This data was joined to the Foreclosure dataset in order to select areas with both a Foreclosure Rate >=6.5% and a Subprime Loan Rate >=1.4%. 3) The State also obtained, from the Warren Group, actual local foreclosure transaction records. The Warren Group is a source for real estate and banking news and transaction data throughout New England. This entity has analyzed local deed records in assembling information presented. The data set was normalized due to potential limitations. An analysis revealed a high level of consistency with HUD-predictive foreclosure rates.

The Surface Management Agency (SMA) Geographic Information System (GIS) dataset depicts Federal land for the United States and classifies this land by its active Federal surface managing agency. The SMA feature class covers the continental United States, Alaska, Hawaii, Puerto Rico, Guam, American Samoa and the Virgin Islands. A Federal SMA agency refers to a Federal agency with administrative jurisdiction over the surface of Federal lands. Jurisdiction over the land is defined when the land is either: Withdrawn by some administrative or legislative action, or Acquired or Exchanged by a Federal Agency. This layer is a dynamic assembly of spatial data layers maintained at various federal and local government offices. The GIS data contained in this dataset represents the polygon features that show the boundaries for Surface Management Agency and the surface extent of each Federal agency’s surface administrative jurisdiction. SMA data depicts current withdrawn areas for a particular agency and (when appropriate) includes land that was acquired or exchanged and is located outside of a withdrawal area for that agency. The SMA data do not illustrate land status ownership pattern boundaries or contain land ownership attribute details. The SMA Withdrawals feature class covers the continental United States, Alaska, Hawaii, Puerto Rico, Guam, American Samoa and the Virgin Islands. A Federal SMA Withdrawal is defined by formal actions that set aside, withhold, or reserve Federal land by statute or administrative order for public purposes. A withdrawal creates a title encumbrance on the land. Withdrawals must accomplish one or more of the following: A. Transfer total or partial jurisdiction of Federal land between Federal agencies. B. Close (segregate) Federal land to operation of all or some of the public land laws and/or mineral laws. C. Dedicate Federal land to a specific public purpose. There are four major categories of formal withdrawals: (1) Administrative, (2) Presidential Proclamations, (3) Congressional, and (4) Federal Power Act (FPA) or Federal Energy Regulatory Commission (FERC) Withdrawals. These SMA Withdrawals will include the present total extent of withdrawn areas rather than all of the individual withdrawal actions that created them over time. A Federal SMA agency refers to a Federal agency with administrative jurisdiction over the surface of Federal lands. Jurisdiction over the land is defined when the land is either: Withdrawn by some administrative or legislative action, or Acquired or Exchanged by a Federal Agency. This layer is a dynamic assembly of spatial data layers maintained at various federal and local government offices. The GIS data contained in this dataset represents the polygon features that show the boundaries for Surface Management Agency and the surface extent of each Federal agency’s surface administrative jurisdiction. SMA data depicts current withdrawn areas for a particular agency and (when appropriate) includes land that was acquired or exchanged and is located outside of a withdrawal area for that agency. The SMA data do not illustrate land status ownership pattern boundaries or contain land ownership attribute details.