The Survey of Consumer Finances (SCF) is normally a triennial cross-sectional survey of U.S. families. The survey data include information on families' balance sheets, pensions, income, and demographic characteristics.

Since 2013, the Federal Reserve Board has conducted the Survey of Household Economics and Decision-making (SHED), which measures the economic well-being of U.S. households and identifies potential risks to their finances. The survey includes modules on a range of topics of current relevance to financial well-being including credit access and behaviors, savings, retirement, economic fragility, and education and student loans.

The Enhanced Financial Accounts (EFA) initiative is a long-term effort to augment the Financial Accounts of the United States with a richer and more detailed picture of financial intermediation and interconnections. As part of this initiative, we are providing supplementary information that offers finer detail, additional types of activities, higher-frequency data, and more-disaggregated data, even if such data are not available for all sectors or easily incorporated into the existing structure of the Financial Accounts. Many of the EFA projects are accompanied by FEDS Notes that provide additional information or context. Like all Financial Accounts data, EFA data are updated regularly and subject to revision.

Content

Source ID: FL313066220.Q

For more information about the Flow of Funds tables, see: https://www.federalreserve.gov/apps/fof/Default.aspx

For a detailed description, including how this series is constructed, see: https://www.federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL313066220&t=

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: 1945-10-01

• Observation End : 2019-04-01

Acknowledgements

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

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

The Compensation and Salary Surveys (FR 29) is comprised of the (1) Compensation and Salary Survey (FR 29a) and (2) Ad Hoc Surveys (FR 29b). The FR 29a is collected annually and the FR 29b is collected on an as needed basis but not more frequently than five times per year. These surveys collect information on salaries, employee compensation policies, and other employee programs from employers that are considered competitors of the Board. The data from the surveys primarily are used to determine the appropriate salary structure and salary adjustments for Board employees.

Context

The Federal Reserve sets interest rates to promote conditions that achieve the mandate set by the Congress — high employment, low and stable inflation, sustainable economic growth, and moderate long-term interest rates. Interest rates set by the Fed directly influence the cost of borrowing money. Lower interest rates encourage more people to obtain a mortgage for a new home or to borrow money for an automobile or for home improvement. Lower rates encourage businesses to borrow funds to invest in expansion such as purchasing new equipment, updating plants, or hiring more workers. Higher interest rates restrain such borrowing by consumers and businesses.

Content

This dataset includes data on the economic conditions in the United States on a monthly basis since 1954. The federal funds rate is the interest rate at which depository institutions trade federal funds (balances held at Federal Reserve Banks) with each other overnight. The rate that the borrowing institution pays to the lending institution is determined between the two banks; the weighted average rate for all of these types of negotiations is called the effective federal funds rate. The effective federal funds rate is determined by the market but is influenced by the Federal Reserve through open market operations to reach the federal funds rate target. The Federal Open Market Committee (FOMC) meets eight times a year to determine the federal funds target rate; the target rate transitioned to a target range with an upper and lower limit in December 2008. The real gross domestic product is calculated as the seasonally adjusted quarterly rate of change in the gross domestic product based on chained 2009 dollars. The unemployment rate represents the number of unemployed as a seasonally adjusted percentage of the labor force. The inflation rate reflects the monthly change in the Consumer Price Index of products excluding food and energy.

Acknowledgements

The interest rate data was published by the Federal Reserve Bank of St. Louis' economic data portal. The gross domestic product data was provided by the US Bureau of Economic Analysis; the unemployment and consumer price index data was provided by the US Bureau of Labor Statistics.

Inspiration

How does economic growth, unemployment, and inflation impact the Federal Reserve's interest rates decisions? How has the interest rate policy changed over time? Can you predict the Federal Reserve's next decision? Will the target range set in March 2017 be increased, decreased, or remain the same?

The interest rate set by the Federal Reserve is a crucial tool for promoting economic conditions that meet the mandate established by the United States Congress, which includes high employment, low and stable inflation, sustainable economic growth, and the moderation of long-term interest rates. The interest rates determined by the Fed directly influence the cost of credit, making financing either more accessible or more restrictive. When interest rates are low, there is a greater incentive for consumers to purchase homes through mortgages, finance automobiles, or undertake home renovations. Additionally, businesses are encouraged to invest in expanding their operations, whether by purchasing new equipment, modernizing facilities, or hiring more workers. Conversely, higher interest rates tend to curb such activity, discouraging borrowing and slowing economic expansion.

The dataset analyzed contains information on the economic conditions in the United States on a monthly basis since 1954, including the federal funds rate, which represents the percentage at which financial institutions trade reserves held at the Federal Reserve with each other in the interbank market overnight. This rate is determined by the market but is directly influenced by the Federal Reserve through open market operations to reach the established target. The Federal Open Market Committee (FOMC) meets eight times a year to determine the federal funds rate target, which has been defined within a range with upper and lower limits since December 2008.

Furthermore, real Gross Domestic Product (GDP) is calculated based on the seasonally adjusted quarterly rate of change in the economy, using chained 2009 dollars as a reference. The unemployment rate represents the seasonally adjusted percentage of the labor force that is unemployed. Meanwhile, the inflation rate is determined by the monthly change in the Consumer Price Index, excluding food and energy prices for a more stable analysis of core inflation.

The interest rate data was sourced from the Federal Reserve Bank of St. Louis' economic data portal, while GDP information was provided by the U.S. Bureau of Economic Analysis, and unemployment and inflation data were made available by the U.S. Bureau of Labor Statistics.

The analysis of this data helps to understand how economic growth, the unemployment rate, and inflation influence the Federal Reserve’s monetary policy decisions. Additionally, it allows for a study of the evolution of interest rate policies over time and raises the question of how predictable the Fed’s future decisions may be. Based on observed trends, it is possible to speculate whether the target range set in March 2017 will be maintained, lowered, or increased, considering the prevailing economic context and the challenges faced in conducting U.S. monetary policy.

Under the Bank Holding Company Act, submission of this application is required for any company organized under the laws of a foreign country seeking to acquire a U.S. subsidiary bank or bank holding company. Applicants must provide financial and managerial information, discuss the competitive effects of the proposed transaction, and discuss how the proposed transaction would enhance the convenience and needs of the community to be served. The Federal Reserve uses the information, in part, to fulfill its supervisory responsibilities with respect to foreign banking organizations in the United States.

Content

Weighted average of the rates received on the interest-bearing assets included in M2. The interest-bearing assets include size of the other checkable deposits, thrift saving deposits, money market mutual fund holdings, and small time deposits that are weighted using their corresponding rates.

The construction of this series was discontinued as of July 12, 2019. The underlying data can be accessed through the following sources: size of the assets can be obtained from the H.6 release (https://www.federalreserve.gov/releases/h6/current/default.htm) published by the Board of Governors, rate on the money market mutual funds from iMoneyNet (https://financialintelligence.informa.com/products-and-services/data-analysis-and-tools/imoneynet), and the remaining rates from the Weekly National Rates and Rate Caps (https://www.fdic.gov/regulations/resources/rates/index.html) from the FDIC website. Listing of the sources is provided for informational purposes only: the Federal Reserve Bank of St. Louis is not associated with any listed private entities and cannot guarantee that the listed data sources will provide the data in the future.

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: 1959-02-01

• Observation End : 2019-06-01

Acknowledgements

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

Cover photo by Leon Skibitzki on Unsplash
Unsplash Images are distributed under a unique Unsplash License.

🏛️ 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

This dataset represents a snapshot of the FRED catalog, captured on 2025-03-24.

What is FRED? As per the FRED website,

Short for Federal Reserve Economic Data, FRED is an online database consisting of hundreds of thousands of economic data time series from scores of national, international, public, and private sources. FRED, created and maintained by the Research Department at the Federal Reserve Bank of St. Louis, goes far beyond simply providing data: It combines data with a powerful mix of tools that help the user understand, interact with, display, and disseminate the data. In essence, FRED helps users tell their data stories. The purpose of this article is to guide the potential (or current) FRED user through the various aspects and tools of the database.

The FRED database is an abolute gold mine of economic data time series. Thousands of such series are published on the FRED website, organized by category and avialable for viewing and downloading. In fact, a number of these economic datasets have been uploaded to kaggle. With in the current notebook, however, we are not interested in the individual time series; rather, we are focused on catalog itself.

The FRED API has been used for gaining access to the catalog. The catalog consists of two files

• categories.csv - the heirarchy of categories used for organizing the time series
• series.csv - the list of avialable time series themselves

A given category is identified by a category_id. And, in a similar fashion, a given series is identified by a series_id. In a given category, one may find both a group of series and a set of sub-categories. As such every series record contains a category_id to identify the immediate category under which it is found category record contains a parent_id to indicate where in the category heirarchy it resides

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.

Content

Reverse repurchase agreements are transactions in which securities are sold to a set of counterparties under an agreement to buy them back from the same party on a specified date at the same price plus interest. Reverse repurchase agreements may be conducted with foreign official and international accounts as a service to the holders of these accounts. All other reverse repurchase agreements, including transactions with primary dealers and a set of eligible money market funds, are open market operations intended to manage the supply of reserve balances; reverse repurchase agreements absorb reserve balances from the banking system for the length of the agreement. As with repurchase agreements, the naming convention used here reflects the transaction from the counterparties' perspective; the Federal Reserve receives cash in a reverse repurchase agreement and provides collateral to the counterparties.

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 : 2019-12-18

Acknowledgements

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

Cover photo by Andrew Pons on Unsplash
Unsplash Images are distributed under a unique Unsplash License.

US wages for college majors

It includes data on specific college majors and their median earnings early in their career along with mid level in their career. The data also includes unemployment and underemployment rates for each college major.

Unemployment and Underemployment rates

This data also contains the unemployment and underemployment rates over the last few years in the United States for recent college graduates along with college graduates overall.

Wages

Median annual wages for those holding a high school diploma, along with the 25th median and 75th percentile annual wages for those holding a bachelor's degree.

This data set was collected from the Federal Reserve Bank of New York. https://www.newyorkfed.org/