FRED® is a database of over 390,000 economic time series from 79 sources. With FRED®, you can download data in Microsoft Excel and text formats and view charts of data series. We plan to continually improve FRED® and encourage you to be a part of the development process by sending feedback through our contact form. Learn more
The FRED database is a useful tool for reporters, students and policy makers alike—anyone who has a need to analyze and disseminate economic data on the web or in print. The St. Louis Federal Reserve data desk has produced a series of informational web demos to help users get started with FRED and quickly progress to more advanced features. We currently have demos relating to: Intro to FRED and FRED graphand we have plans to produce more in the future. The demonstrations are meant to help answer basic questions users may encounter as they navigate the FRED site, and create their own custom data visualizations. As always, users with specific questions not addressed in the web demos are encouraged to contact the FRED Team at email@example.com or (314) 444-8444.
If you have questions about the data in the FRED® database, the Research staff prefers that you send an email to firstname.lastname@example.org. If your question necessitates a phone discussion, please call a Research staff member. Staff are available Monday through Friday, 8 a.m. to 4:00 p.m. CST. There are four numbers available for you to call:
Staff will respond to all email and telephone inquiries within two business day.
All dates are represented as daily dates for consistency and ease of use. We chose a single date format that is widely supported by various spreadsheet applications (Excel, Lotus, etc.) and statistical software packages (SAS, Eviews, Stata, RATS, etc.). Many annual, quarterly, and monthly data series represent different times during the period (beginning of period, middle of period, etc.) so we chose to convert these frequencies to the first day of the period for consistency. Dates for weekly and daily data series are natively daily dates and are not converted. Dates are formatted as YYYY-MM-DD. As an example, April 25, 2002 is represented as 2002-04-25.
Examples of how dates are converted to daily dates:
All FRED data series are freely available for personal use, and most are also freely available for use in publications and presentations if cited appropriately. But please note that some FRED data series are owned by third parties and subject to copyright restrictions. Please review the notes for any series you wish to publish or reprint.
For publicly available data: FRED now offers a suggested citation under the "Cite" tab. If you use FRED for research papers, publications, or presentations, please cite it using the information in that tab. FRED is also compatible with the Zotero citation tool and may be used with that tool.
For FRED data owned by third parties: Before using data owned by third parties for anything other than your own personal use, you must contact the data owner to obtain permission. The Federal Reserve Bank of St. Louis cannot give you such permission, and making the data series available through FRED does not constitute such permission. Copyrighted series include the word "copyright" and the copyright symbol in their title. Please see the "Note" tab for further information and contacts for permission. The list of copyrighted series can be found by either searching for the word "copyright" on the FRED website or through the fred/series/search api request.
Using ALFRED - ArchivaL Federal Reserve Economic Data - you can retrieve a data series as it existed on a specific date in history. Vintage data can be downloaded directly from the ALFRED website or by using 'My Data Lists.' Please see ALFRED Help for information about ALFRED and how to download data directly from the ALFRED website, and the How to Use 'My Data Lists' tutorial.
With a user account, you can store lists of economic data series. Data lists can be used to download series cross-tabulated by date or save links to series pages. See 'How to Use My Data Lists' for a step-by-step tutorial with screenshots.
Note that because FRED uses levels and rounded data as published by the source, calculations of percentage changes and/or growth rates in some series may not be identical to those in the original releases.
The following formulas are used:
x(t) - x(t-1)
Change from Year Ago
x(t) - x(t-n_obs_per_yr)
((x(t)/x(t-1)) - 1) * 100
Percent Change from Year Ago
((x(t)/x(t-n_obs_per_yr)) - 1) * 100
Compounded Annual Rate of Change
(((x(t)/x(t-1)) ** (n_obs_per_yr)) - 1) * 100
Continuously Compounded Rate of Change
(ln(x(t)) - ln(x(t-1))) * 100
Continuously Compounded Annual Rate of Change
((ln(x(t)) - ln(x(t-1))) * 100) * n_obs_per_yr
'x(t)' is the value of series x at time period t.
'n_obs_per_yr' is the number of observations per year. The number of observations per year differs by frequency:
Daily, 260 (no values on weekends)
'ln' represents the natural logarithm.
'**' represents to the power of.
The NBER recession data is available at http://www.nber.org/cycles/cyclesmain.html. The monthly dates for the peaks and troughs are represented as daily dates in the charts as:
The FRED frequency aggregation feature converts higher frequency data series into lower frequency data series (e.g. converts a monthly data series into an annual data series). In FRED, the highest frequency data is daily, and the lowest frequency data is annual. There are 3 aggregation methods available- average, sum, and end of period.
Higher frequency data may not be available for an entire lower frequency period. For example, a monthly data series may end in February. With only 2 of the 12 months of the year available, the converted annual value will be missing for the last year.
First and last observations for a converted lower frequency are missing if the number of higher frequency periods per lower frequency period is less than a minimum threshold. The minimum threshold depends on which frequencies are being converted. Below is a table of the thresholds.
Minimum number of higher frequency periods per lower frequency period for first and last observations:
|4||for Daily to Weekly|
|8||for Daily to Biweekly|
|17||for Daily to Monthly|
|52||for Daily to Quarterly|
|104||for Daily to Semiannual|
|208||for Daily to Annual|
|2||for Weekly to Biweekly|
|3||for Weekly to Monthly|
|10||for Weekly to Quarterly|
|20||for Weekly to Semiannual|
|39||for Weekly to Annual|
|2||for Biweekly to Monthly|
|7||for Biweekly to Quarterly|
|13||for Biweekly to Semiannual|
|26||for Biweekly to Annual|
|3||for Monthly to Quarterly|
|6||for Monthly to Semiannual|
|12||for Monthly to Annual|
|2||for Quarterly to Semiannual|
|4||for Quarterly to Annual|
|2||for Semiannual to Annual|
Daily and weekly series can have missing values due to holidays. Accordingly, the thresholds for converting daily or weekly data series to a lower frequency have been reduced. Otherwise, one missing value in a daily or weekly data series would cause the corresponding lower frequency period to also be missing.
The thresholds for converting monthly and quarterly data series to a lower frequency reflect that all higher frequency periods must be available. If any monthly or quarterly value is missing, the corresponding lower frequency period will also be missing.
The minimum thresholds above only apply to first and last observations. Observations in the middle of the data series are not set to missing if the number of higher frequency periods per lower frequency period is less than a minimum.
Missing values are ignored by the average, sum, and end of period aggregation methods for middle observations (not the first or last observations).
For example, consider a daily series from 2003-06-01 to 2003-07-31 with a missing value on Friday, 2000-07-04, the US Independence Day holiday. When converting from daily to weekly ending Friday values, the week containing 2000-07-04 will have values for 4 of the 5 days of the business week. Averaged and summed values will be calculated for that week using 4 values not 5. The end of period aggregation method will use the non-missing value for Thursday instead of the missing value on Friday, July 4th. If Thursday and Friday both had missing values, the end of period aggregation method would return the non-missing value from Wednesday.
It is possible for higher frequency periods to overlap lower frequency periods. For example, a week can start in one month and end in the next month. In these cases, FRED frequency aggregation only includes the higher frequency value in one of the lower frequency periods but not the other. The value is assigned to the lower frequency period containing the daily date for the higher frequency period. For example, a weekly ending Friday period with date 2010-09-03 is included in the aggregated value for September not August.
The average, sum, and end of period aggregation methods all return lower frequency values with the same number of decimal places as the higher frequency values that are being aggregated. For example, a monthly series with values 100.1, 100.4, and 100.9 for the first 3 months of year is averaged to a quarterly value of 100.5 (i.e. 100.467 rounded up to 100.5).
The values for a line in FRED Graph are calculated in the following order- first frequency aggregation is calculated (if any), second unit transformations are calculated (if any) (e.g. Percent Change), and third the formula to create your own transformation is applied (if changed from the default) (e.g. formula 'a - b' finds the difference between 2 data series).
The "Updated" date associated with each series is the most recent date that a series was updated in FRED®. This date does not necessarily correspond to the dates of observations.
For detailed definitions and methodology beyond that provided in the "Notes" with each series in FRED®, we recommend referring to the source of the data.
The inflation rate is typically calculated as the percent rate of change between two observations of the Consumer Price Index (typically from month to month or from the same month one year ago). Conventions used in our publications for calculating rates of change are available in the Tables of Contents of our Monetary Trends and our National Economic Trends publications.
Information on money stock measures, the monetary base and reserves, retail and deposit sweeps programs, and the monetary services index can be found in the Monetary Aggregates section of our website. Also included are historical data, references to further reading, and several datasets which are not included in the FRED® database.
FRASER® is a collection of historical documents. Some historical statistics that are not available in FRED® may be found in FRASER®.