Federal Reserve Economic Data

What is FRED?

FRED, which is short for Federal Reserve Economic Data, is an online repository of a vast array of economic data time series from numerous national, international, public, and private sources. NestQuant collects this kind of data from Federal Reserve Bank of St. Louis. For more information, please check this explanation and introduction about FRED.

Data catalog

FRED has multiple release and revision times, at each time a number can be different. For instance, the US GDP for Q4 2013 was first released to be 17102.5 on 2014-01-30, and then revised to 17080.7 on 2014-02-28, and then revised to 17089.6 on 2014-03-27. In our provided data we keep only the first release version and omit all modified data because in a financial market position most of us are interested in first release data to make a decision.

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Note for the 'Seasonal adjustment' column: A seasonally adjusted time series is a monthly or quarterly time series that has been modified to eliminate the effect of seasonal and calendar influences.

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Seasonal adjustment

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The Consumer Price Index for All Urban Consumers: All Items (CPIAUCSL) is a price index of a basket of goods and services paid by urban consumers. Percent changes in the price index measure the inflation rate between any two time periods. The most common inflation metric is the percent change from one year ago. It can also represent the buying habits of urban consumers. This particular index includes roughly 88 percent of the total population, accounting for wage earners, clerical workers, technical workers, self-employed, short-term workers, unemployed, retirees, and those not in the labor force. The CPIs are based on prices for food, clothing, shelter, and fuels; transportation fares; service fees (e.g., water and sewer service); and sales taxes. Prices are collected monthly from about 4,000 housing units and approximately 26,000 retail establishments across 87 urban areas. To calculate the index, price changes are averaged with weights representing their importance in the spending of the particular group. The index measures price changes (as a percent change) from a predetermined reference date. In addition to the original unadjusted index distributed, the Bureau of Labor Statistics also releases a seasonally adjusted index. The unadjusted series reflects all factors that may influence a change in prices. However, it can be very useful to look at the seasonally adjusted CPI, which removes the effects of seasonal changes, such as weather, school year, production cycles, and holidays. The CPI can be used to recognize periods of inflation and deflation. Significant increases in the CPI within a short time frame might indicate a period of inflation, and significant decreases in CPI within a short time frame might indicate a period of deflation. However, because the CPI includes volatile food and oil prices, it might not be a reliable measure of inflationary and deflationary periods. For a more accurate detection, the core CPI (CPILFESL (https://fred.stlouisfed.org/series/CPILFESL)) is often used. When using the CPI, please note that it is not applicable to all consumers and should not be used to determine relative living costs. Additionally, the CPI is a statistical measure vulnerable to sampling error since it is based on a sample of prices and not the complete average. For more information on the consumer price indexes, see: Bureau of Economic Analysis. "CPI Detailed Report." (https://www.bls.gov/cpi/) 2013. Handbook of Methods (https://www.bls.gov/opub/hom/pdf/cpihom.pdf) Understanding the CPI: Frequently Asked Questions (https://www.bls.gov/cpi/questions-and-answers.htm)

Calculated as the ratio of quarterly nominal GDP (https://fred.stlouisfed.org/series/GDP) to the quarterly average of M2 money stock (https://fred.stlouisfed.org/series/M2SL). The velocity of money is the frequency at which one unit of currency is used to purchase domestically- produced goods and services within a given time period. In other words, it is the number of times one dollar is spent to buy goods and services per unit of time. If the velocity of money is increasing, then more transactions are occurring between individuals in an economy. The frequency of currency exchange can be used to determine the velocity of a given component of the money supply, providing some insight into whether consumers and businesses are saving or spending their money. There are several components of the money supply,: M1, M2, and MZM (M3 is no longer tracked by the Federal Reserve); these components are arranged on a spectrum of narrowest to broadest. Consider M1, the narrowest component. M1 is the money supply of currency in circulation (notes and coins, traveler's checks [non-bank issuers], demand deposits, and checkable deposits). A decreasing velocity of M1 might indicate fewer short- term consumption transactions are taking place. We can think of shorter- term transactions as consumption we might make on an everyday basis. Beginning May 2020, M2 consists of M1 plus (1) small-denomination time deposits (time deposits in amounts of less than $100,000) less IRA and Keogh balances at depository institutions; and (2) balances in retail MMFs less IRA and Keogh balances at MMFs. Seasonally adjusted M2 is constructed by summing savings deposits (before May 2020), small-denomination time deposits, and retail MMFs, each seasonally adjusted separately, and adding this result to seasonally adjusted M1. For more information on the H.6 release changes and the regulatory amendment that led to the creation of the other liquid deposits component and its inclusion in the M1 monetary aggregate, see the H.6 announcements (https://www.federalreserve.gov/feeds/h6.html) and Technical Q&As (https://www.federalreserve.gov/releases/h6/h6_technical_qa.htm) posted on December 17, 2020. MZM (money with zero maturity) is the broadest component and consists of the supply of financial assets redeemable at par on demand: notes and coins in circulation, traveler's checks (non-bank issuers), demand deposits, other checkable deposits, savings deposits, and all money market funds. The velocity of MZM helps determine how often financial assets are switching hands within the economy.

Household data are collected as of March. As stated in the Census's Source and Accuracy of Estimates for Income, Poverty, and Health Insurance Coverage in the United States: 2011 (http://www.census.gov/hhes/www/p60_243sa.pdf). Estimation of Median Incomes. The Census Bureau has changed the methodology for computing median income over time. The Census Bureau has computed medians using either Pareto interpolation or linear interpolation. Currently, we are using linear interpolation to estimate all medians. Pareto interpolation assumes a decreasing density of population within an income interval, whereas linear interpolation assumes a constant density of population within an income interval. The Census Bureau calculated estimates of median income and associated standard errors for 1979 through 1987 using Pareto interpolation if the estimate was larger than $20,000 for people or $40,000 for families and households. This is because the width of the income interval containing the estimate is greater than $2,500. We calculated estimates of median income and associated standard errors for 1976, 1977, and 1978 using Pareto interpolation if the estimate was larger than $12,000 for people or $18,000 for families and households. This is because the width of the income interval containing the estimate is greater than $1,000. All other estimates of median income and associated standard errors for 1976 through 2011 (2012 ASEC) and almost all of the estimates of median income and associated standard errors for 1975 and earlier were calculated using linear interpolation. Thus, use caution when comparing median incomes above $12,000 for people or $18,000 for families and households for different years. Median incomes below those levels are more comparable from year to year since they have always been calculated using linear interpolation. For an indication of the comparability of medians calculated using Pareto interpolation with medians calculated using linear interpolation, see Series P-60, Number 114, (https://www2.census.gov/prod2/popscan/p60-114.pdf) Money Income in 1976 of Families and Persons in the United States.

Calculated as the ratio of quarterly nominal GDP (GDP (https://fred.stlouisfed.org/series/GDP)) to the quarterly average of M1 money stock (M1SL (https://fred.stlouisfed.org/series/M1SL)) The velocity of money is the frequency at which one unit of currency is used to purchase domestically- produced goods and services within a given time period. In other words, it is the number of times one dollar is spent to buy goods and services per unit of time. If the velocity of money is increasing, then more transactions are occurring between individuals in an economy. The frequency of currency exchange can be used to determine the velocity of a given component of the money supply, providing some insight into whether consumers and businesses are saving or spending their money. There are several components of the money supply,: M1, M2, and MZM (M3 is no longer tracked by the Federal Reserve); these components are arranged on a spectrum of narrowest to broadest. Consider M1, the narrowest component. M1 is the money supply of currency in circulation (notes and coins, demand deposits, and other liquid deposits). A decreasing velocity of M1 might indicate fewer short- term consumption transactions are taking place. We can think of shorter- term transactions as consumption we might make on an everyday basis. Beginning May 2020, M1 consists of (1) currency outside the U.S. Treasury, Federal Reserve Banks, and the vaults of depository institutions; (2) demand deposits at commercial banks (excluding those amounts held by depository institutions, the U.S. government, and foreign banks and official institutions) less cash items in the process of collection and Federal Reserve float; and (3) other liquid deposits, consisting of OCDs and savings deposits (including money market deposit accounts). Seasonally adjusted M1 is constructed by summing currency, demand deposits, and OCDs (before May 2020) or other liquid deposits (beginning May 2020), each seasonally adjusted separately. For more information on the H.6 release changes and the regulatory amendment that led to the creation of the other liquid deposits component and its inclusion in the M1 monetary aggregate, see the H.6 announcements (https://www.federalreserve.gov/feeds/h6.html) and Technical Q&As (https://www.federalreserve.gov/releases/h6/h6_technical_qa.htm) posted on December 17, 2020. The broader M2 component includes M1 in addition to saving deposits, certificates of deposit (less than $100,000), and money market deposits for individuals. Comparing the velocities of M1 and M2 provides some insight into how quickly the economy is spending and how quickly it is saving. MZM (money with zero maturity) is the broadest component and consists of the supply of financial assets redeemable at par on demand: notes and coins in circulation, traveler’s checks (non-bank issuers), demand deposits, other checkable deposits, savings deposits, and all money market funds. The velocity of MZM helps determine how often financial assets are switching hands within the economy.

This time series is an interpretation of US Business Cycle Expansions and Contractions data provided by The National Bureau of Economic Research (http://www.nber.org/cycles/cyclesmain.html) (NBER). Our time series is composed of dummy variables that represent periods of expansion and recession. The NBER identifies months and quarters of turning points without designating a date within the period that turning points occurred. The dummy variable adopts an arbitrary convention that the turning point occurred at a specific date within the period. The arbitrary convention does not reflect any judgment on this issue by the NBER's Business Cycle Dating Committee. A value of 1 is a recessionary period, while a value of 0 is an expansionary period. For this time series, the recession begins the first day of the period following a peak and ends on the last day of the period of the trough. For more options on recession shading, see the notes and links below. The recession shading data that we provide initially comes from the source as a list of dates that are either an economic peak or trough. We interpret dates into recession shading data using one of three arbitrary methods. All of our recession shading data is available using all three interpretations. The period between a peak and trough is always shaded as a recession. The peak and trough are collectively extrema. Depending on the application, the extrema, both individually and collectively, may be included in the recession period in whole or in part. In situations where a portion of a period is included in the recession, the whole period is deemed to be included in the recession period. The first interpretation, known as the midpoint method, is to show a recession from the midpoint of the peak through the midpoint of the trough for monthly and quarterly data. For daily data, the recession begins on the 15th of the month of the peak and ends on the 15th of the month of the trough. Daily data is a disaggregation of monthly data. For monthly and quarterly data, the entire peak and trough periods are included in the recession shading. This method shows the maximum number of periods as a recession for monthly and quarterly data. The Federal Reserve Bank of St. Louis uses this method in its own publications. One version of this time series is represented using the midpoint method (https://fred.stlouisfed.org/series/USRECM) The second interpretation, known as the trough method, is to show a recession from the period following the peak through the trough (i.e. the peak is not included in the recession shading, but the trough is). For daily data, the recession begins on the first day of the first month following the peak and ends on the last day of the month of the trough. Daily data is a disaggregation of monthly data. The trough method is used when displaying data on FRED graphs. The trough method is used for this series. The third interpretation, known as the peak method, is to show a recession from the period of the peak to the trough (i.e. the peak is included in the recession shading, but the trough is not). For daily data, the recession begins on the first day of the month of the peak and ends on the last day of the month preceding the trough. Daily data is a disaggregation of monthly data. Here is an example of this time series represented using the peak method (https://fred.stlouisfed.org/series/USRECP).