The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'x12' package from R with default parameter settings. The package uses the U.S. Bureau of the Census X-12-ARIMA Seasonal Adjustment Program. More information on the 'x12' package can be found at http://cran.r-project.org/web/packages/x12/x12.pdf. More information on X-12-ARIMA can be found at https://www.census.gov/srd/www/x13as/.

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'x12' package from R with default parameter settings. The package uses the U.S. Bureau of the Census X-12-ARIMA Seasonal Adjustment Program. More information on the 'x12' package can be found at http://cran.r-project.org/web/packages/x12/x12.pdf. More information on X-12-ARIMA can be found at https://www.census.gov/srd/www/x13as/.

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'x12' package from R with default parameter settings. The package uses the U.S. Bureau of the Census X-12-ARIMA Seasonal Adjustment Program. More information on the 'x12' package can be found at http://cran.r-project.org/web/packages/x12/x12.pdf. More information on X-12-ARIMA can be found at https://www.census.gov/srd/www/x13as/.

This series is discontinued and will no longer be updated. The Federal Reserve Bank of St. Louis previously calculated this seasonally adjusted (SA) series based on the not seasonally adjusted (NSA) version available here (https://fred.stlouisfed.org/series/SMU25716540500000011). However, most of the earnings-related series do not have a significant seasonal component, so the values for both the SA and the NSA series are very similar. See the NSA series (https://fred.stlouisfed.org/series/SMU25716540500000011) for updated values. The Federal Reserve Bank of St. Louis previously used to seasonally adjust this series by using the 'statsmodels' library from Python with default parameter settings. The package uses the U.S. Bureau of the Census X-13ARIMA-SEATS Seasonal Adjustment Program. More information on the 'statsmodels' X-13ARIMA-SEATS package can be found here (https://www.statsmodels.org/dev/generated/statsmodels.tsa.x13.x13_arima_analysis.html). More information on X-13ARIMA-SEATS can be found here (https://www.census.gov/data/software/x13as.html). Many series include both seasonally adjusted (SA) and not seasonally adjusted (NSA) data. Occasionally, updates to the data will not include sufficient seasonal factors to trigger a seasonal adjustment. In these cases, the NSA series will be updated normally; but the SA series will also be updated with the NSA data. The NSA series can be located here here (https://fred.stlouisfed.org/series/SMU25716540500000011). Some seasonally adjusted series may exhibit negative values because they are created from a seasonal adjustment process regardless of the actual meaning or interpretation of the given indicator.

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'x12' package from R with default parameter settings. The package uses the U.S. Bureau of the Census X-12-ARIMA Seasonal Adjustment Program. More information on the 'x12' package can be found at http://cran.r-project.org/web/packages/x12/x12.pdf. More information on X-12-ARIMA can be found at https://www.census.gov/srd/www/x13as/.

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'x12' package from R with default parameter settings. The package uses the U.S. Bureau of the Census X-12-ARIMA Seasonal Adjustment Program. More information on the 'x12' package can be found at http://cran.r-project.org/web/packages/x12/x12.pdf. More information on X-12-ARIMA can be found at https://www.census.gov/srd/www/x13as/.

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'x12' package from R with default parameter settings. The package uses the U.S. Bureau of the Census X-12-ARIMA Seasonal Adjustment Program. More information on the 'x12' package can be found at http://cran.r-project.org/web/packages/x12/x12.pdf. More information on X-12-ARIMA can be found at https://www.census.gov/srd/www/x13as/.

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'x12' package from R with default parameter settings. The package uses the U.S. Bureau of the Census X-12-ARIMA Seasonal Adjustment Program. More information on the 'x12' package can be found at http://cran.r-project.org/web/packages/x12/x12.pdf. More information on X-12-ARIMA can be found at https://www.census.gov/srd/www/x13as/.

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'x12' package from R with default parameter settings. The package uses the U.S. Bureau of the Census X-12-ARIMA Seasonal Adjustment Program. More information on the 'x12' package can be found at http://cran.r-project.org/web/packages/x12/x12.pdf. More information on X-12-ARIMA can be found at https://www.census.gov/srd/www/x13as/.

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'x12' package from R with default parameter settings. The package uses the U.S. Bureau of the Census X-12-ARIMA Seasonal Adjustment Program. More information on the 'x12' package can be found at http://cran.r-project.org/web/packages/x12/x12.pdf. More information on X-12-ARIMA can be found at https://www.census.gov/srd/www/x13as/.

This series is discontinued and will no longer be updated. Additional consolidated data is available on the FDIC's Bank Data and Statistics (https://www.fdic.gov/bank/statistical/). This series represents Allowance for Loan and Lease Losses call item RCFD3123. The asset class is determined by using Total Assets call item RCFD2170 less than or equal to $5B. Geographic location is determined by Abbreviated State Name call item RSSD9200 and County Code call item RSSD9150, which is mapped to the proper Core Based Statistical Area (CBSA) defined by the Office of Management and Budget (OMB). Users are advised to use the Federal Reserve Board of Governors' data dictionary (https://www.federalreserve.gov/apps/mdrm/data-dictionary) to retrieve detailed information for specific call items. This series is calculated by the Federal Reserve Bank of St. Louis using raw data that are collected by the FFIEC. Raw data can be found at https://cdr.ffiec.gov/public/.

The Implicit Regional Price Deflator (IRPD) is the ratio of the current-dollar value of a series, such as regional personal income, to its corresponding chained-dollar value, multiplied by 100. For more information about this release go to http://www.bea.gov/newsreleases/regional/rpp/rpp_newsrelease.htm or http://www.bea.gov/regional/methods.cfm.

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'x12' package from R with default parameter settings. The package uses the U.S. Bureau of the Census X-12-ARIMA Seasonal Adjustment Program. More information on the 'x12' package can be found at http://cran.r-project.org/web/packages/x12/x12.pdf. More information on X-12-ARIMA can be found at https://www.census.gov/srd/www/x13as/.

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'x12' package from R with default parameter settings. The package uses the U.S. Bureau of the Census X-12-ARIMA Seasonal Adjustment Program. More information on the 'x12' package can be found at http://cran.r-project.org/web/packages/x12/x12.pdf. More information on X-12-ARIMA can be found at https://www.census.gov/srd/www/x13as/.

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'x12' package from R with default parameter settings. The package uses the U.S. Bureau of the Census X-12-ARIMA Seasonal Adjustment Program. More information on the 'x12' package can be found at http://cran.r-project.org/web/packages/x12/x12.pdf. More information on X-12-ARIMA can be found at https://www.census.gov/srd/www/x13as/.

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'x12' package from R with default parameter settings. The package uses the U.S. Bureau of the Census X-12-ARIMA Seasonal Adjustment Program. More information on the 'x12' package can be found at http://cran.r-project.org/web/packages/x12/x12.pdf. More information on X-12-ARIMA can be found at https://www.census.gov/srd/www/x13as/.

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'x12' package from R with default parameter settings. The package uses the U.S. Bureau of the Census X-12-ARIMA Seasonal Adjustment Program. More information on the 'x12' package can be found at http://cran.r-project.org/web/packages/x12/x12.pdf. More information on X-12-ARIMA can be found at https://www.census.gov/srd/www/x13as/.

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'x12' package from R with default parameter settings. The package uses the U.S. Bureau of the Census X-12-ARIMA Seasonal Adjustment Program. More information on the 'x12' package can be found at http://cran.r-project.org/web/packages/x12/x12.pdf. More information on X-12-ARIMA can be found at https://www.census.gov/srd/www/x13as/.

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'x12' package from R with default parameter settings. The package uses the U.S. Bureau of the Census X-12-ARIMA Seasonal Adjustment Program. More information on the 'x12' package can be found at http://cran.r-project.org/web/packages/x12/x12.pdf. More information on X-12-ARIMA can be found at https://www.census.gov/srd/www/x13as/.

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'x12' package from R with default parameter settings. The package uses the U.S. Bureau of the Census X-12-ARIMA Seasonal Adjustment Program. More information on the 'x12' package can be found at http://cran.r-project.org/web/packages/x12/x12.pdf. More information on X-12-ARIMA can be found at https://www.census.gov/srd/www/x13as/.

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'x12' package from R with default parameter settings. The package uses the U.S. Bureau of the Census X-12-ARIMA Seasonal Adjustment Program. More information on the 'x12' package can be found at http://cran.r-project.org/web/packages/x12/x12.pdf. More information on X-12-ARIMA can be found at https://www.census.gov/srd/www/x13as/.

Series Is Presented Here As Two Variables--(1)-- Original Data, 1890-1919 (2)--Original Data, 1913-1944. 1913-1919 Copied From Bls Handwritten Files. Taken From The Bls. Beginning In 1913, Prices Are Quoted Weekly, On Saturday. Called Spruce Eastern, Random Cargoes, 2 By 3 And 4 (See Bulletin 473, 1926-1928. Bulletin 473 Gives 1926 Overlap And Annual Review Figures Showing That Series Is Consistent From Beginning Of 1920). From 1929-June, 1940, Series Labelled Spruce Eastern, Boston. For July-December, 1940, Specification States "No Quantity Specified;" Beginning 1941, Called"Eastern, Random No. 1, 2 Inches By 3 Inches And 4 Inches, Per Thousand Board Feet, Carlot, Delivered By Rail, On Boston Rate Of Freight." Series Remains The Same As That Called"Eastern, Boston." Source: Bureau Of Labor Statistics Bulletins, Monthly "Wholesale Prices", Bls Files. This NBER data series m04090b appears on the NBER website in Chapter 4 at http://www.nber.org/databases/macrohistory/contents/chapter04.html. NBER Indicator: m04090b

This series is discontinued and will no longer be updated. Additional consolidated data is available on the FDIC's Bank Data and Statistics (https://www.fdic.gov/bank/statistical/). This series represents Net Interest Income call item RIAD4074. The asset class is determined by using Total Assets call item RCFD2170 less than or equal to $5B. Geographic location is determined by Abbreviated State Name call item RSSD9200 and County Code call item RSSD9150, which is mapped to the proper Core Based Statistical Area (CBSA) defined by the Office of Management and Budget (OMB). Users are advised to use the Federal Reserve Board of Governors' data dictionary (https://www.federalreserve.gov/apps/mdrm/data-dictionary) to retrieve detailed information for specific call items. This series is calculated by the Federal Reserve Bank of St. Louis using raw data that are collected by the FFIEC. Raw data can be found at https://cdr.ffiec.gov/public/.

Average consumer prices are calculated for household fuel, motor fuel, and food items from prices collected for the Consumer Price Index (CPI). Average prices are best used to measure the price level in a particular month, not to measure price change over time. It is more appropriate to use CPI index values for the particular item categories to measure price change. Prices, except for electricity, are collected monthly by BLS representatives in the 75 urban areas priced for the CPI. Electricity prices are collected for the BLS for the same 75 areas on a monthly basis by the Department of Energy using mail questionnaires. All fuel prices include applicable Federal, State, and local taxes; prices for natural gas and electricity also include fuel and purchased gas adjustments. For more information, please visit the Bureau of Labor Statistics (https://www.bls.gov/cpi/factsheets/average-prices.htm).

This series is discontinued and will no longer be updated. The Federal Reserve Bank of St. Louis previously calculated this seasonally adjusted (SA) series based on the not seasonally adjusted (NSA) version available here (https://fred.stlouisfed.org/series/SMU25716503100000008). However, most of the earnings-related series do not have a significant seasonal component, so the values for both the SA and the NSA series are very similar. See the NSA series (https://fred.stlouisfed.org/series/SMU25716503100000008) for updated values. The Federal Reserve Bank of St. Louis used to seasonally adjust this series by using the 'statsmodels' library from Python with default parameter settings. The package uses the U.S. Bureau of the Census X-13ARIMA-SEATS Seasonal Adjustment Program. More information on the 'statsmodels' X-13ARIMA-SEATS package can be found here (https://www.statsmodels.org/dev/generated/statsmodels.tsa.x13.x13_arima_analysis.html). More information on X-13ARIMA-SEATS can be found here (https://www.census.gov/data/software/x13as.html). Many series include both seasonally adjusted (SA) and not seasonally adjusted (NSA) data. Occasionally, updates to the data will not include sufficient seasonal factors to trigger a seasonal adjustment. In these cases, the NSA series will be updated normally; but the SA series will also be updated with the NSA data. The NSA series can be located here here (https://fred.stlouisfed.org/series/SMU25716503100000008). Some seasonally adjusted series may exhibit negative values because they are created from a seasonal adjustment process regardless of the actual meaning or interpretation of the given indicator.

This series is discontinued and will no longer be updated. The Federal Reserve Bank of St. Louis previously calculated this seasonally adjusted (SA) series based on the not seasonally adjusted (NSA) version available here (https://fred.stlouisfed.org/series/SMU25716503100000030). However, most of the earnings-related series do not have a significant seasonal component, so the values for both the SA and the NSA series are very similar. See the NSA series (https://fred.stlouisfed.org/series/SMU25716503100000030) for updated values. The Federal Reserve Bank of St. Louis used to seasonally adjust this series by using the 'statsmodels' library from Python with default parameter settings. The package uses the U.S. Bureau of the Census X-13ARIMA-SEATS Seasonal Adjustment Program. More information on the 'statsmodels' X-13ARIMA-SEATS package can be found here (https://www.statsmodels.org/dev/generated/statsmodels.tsa.x13.x13_arima_analysis.html). More information on X-13ARIMA-SEATS can be found here (https://www.census.gov/data/software/x13as.html). Many series include both seasonally adjusted (SA) and not seasonally adjusted (NSA) data. Occasionally, updates to the data will not include sufficient seasonal factors to trigger a seasonal adjustment. In these cases, the NSA series will be updated normally; but the SA series will also be updated with the NSA data. The NSA series can be located here here (https://fred.stlouisfed.org/series/SMU25716503100000030). Some seasonally adjusted series may exhibit negative values because they are created from a seasonal adjustment process regardless of the actual meaning or interpretation of the given indicator.

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'x12' package from R with default parameter settings. The package uses the U.S. Bureau of the Census X-12-ARIMA Seasonal Adjustment Program. More information on the 'x12' package can be found at http://cran.r-project.org/web/packages/x12/x12.pdf. More information on X-12-ARIMA can be found at https://www.census.gov/srd/www/x13as/.

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'x12' package from R with default parameter settings. The package uses the U.S. Bureau of the Census X-12-ARIMA Seasonal Adjustment Program. More information on the 'x12' package can be found at http://cran.r-project.org/web/packages/x12/x12.pdf. More information on X-12-ARIMA can be found at https://www.census.gov/srd/www/x13as/.

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'x12' package from R with default parameter settings. The package uses the U.S. Bureau of the Census X-12-ARIMA Seasonal Adjustment Program. More information on the 'x12' package can be found at http://cran.r-project.org/web/packages/x12/x12.pdf. More information on X-12-ARIMA can be found at https://www.census.gov/srd/www/x13as/.

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'x12' package from R with default parameter settings. The package uses the U.S. Bureau of the Census X-12-ARIMA Seasonal Adjustment Program. More information on the 'x12' package can be found at http://cran.r-project.org/web/packages/x12/x12.pdf. More information on X-12-ARIMA can be found at https://www.census.gov/srd/www/x13as/.

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'x12' package from R with default parameter settings. The package uses the U.S. Bureau of the Census X-12-ARIMA Seasonal Adjustment Program. More information on the 'x12' package can be found at http://cran.r-project.org/web/packages/x12/x12.pdf. More information on X-12-ARIMA can be found at https://www.census.gov/srd/www/x13as/.

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'x12' package from R with default parameter settings. The package uses the U.S. Bureau of the Census X-12-ARIMA Seasonal Adjustment Program. More information on the 'x12' package can be found at http://cran.r-project.org/web/packages/x12/x12.pdf. More information on X-12-ARIMA can be found at https://www.census.gov/srd/www/x13as/.

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'x12' package from R with default parameter settings. The package uses the U.S. Bureau of the Census X-12-ARIMA Seasonal Adjustment Program. More information on the 'x12' package can be found at http://cran.r-project.org/web/packages/x12/x12.pdf. More information on X-12-ARIMA can be found at https://www.census.gov/srd/www/x13as/.

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'statsmodels' library from Python with default parameter settings. The package uses the U.S. Bureau of the Census X-13ARIMA-SEATS Seasonal Adjustment Program. More information on the 'statsmodels' X-13ARIMA-SEATS package can be found here (https://www.statsmodels.org/dev/generated/statsmodels.tsa.x13.x13_arima_analysis.html). More information on X-13ARIMA-SEATS can be found here (https://www.census.gov/data/software/x13as.html). Many series include both seasonally adjusted (SA) and not seasonally adjusted (NSA) data. Occasionally, updates to the data will not include sufficient seasonal factors to trigger a seasonal adjustment. In these cases, the NSA series will be updated normally; but the SA series will also be updated with the NSA data. The NSA series can be located here here (https://fred.stlouisfed.org/series/SMU25716544245100001). Some seasonally adjusted series may exhibit negative values because they are created from a seasonal adjustment process regardless of the actual meaning or interpretation of the given indicator.

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'statsmodels' library from Python with default parameter settings. The package uses the U.S. Bureau of the Census X-13ARIMA-SEATS Seasonal Adjustment Program. More information on the 'statsmodels' X-13ARIMA-SEATS package can be found here (https://www.statsmodels.org/dev/generated/statsmodels.tsa.x13.x13_arima_analysis.html). More information on X-13ARIMA-SEATS can be found here (https://www.census.gov/data/software/x13as.html). Many series include both seasonally adjusted (SA) and not seasonally adjusted (NSA) data. Occasionally, updates to the data will not include sufficient seasonal factors to trigger a seasonal adjustment. In these cases, the NSA series will be updated normally; but the SA series will also be updated with the NSA data. The NSA series can be located here here (https://fred.stlouisfed.org/series/SMU25716544244600001). Some seasonally adjusted series may exhibit negative values because they are created from a seasonal adjustment process regardless of the actual meaning or interpretation of the given indicator.

This series is discontinued and will no longer be updated. Additional consolidated data is available on the FDIC's Bank Data and Statistics (https://www.fdic.gov/bank/statistical/). This series represents Quarterly Average of Total Loans, Net of Unearned Income call item RCFD3360. The asset class is determined by using Total Assets call item RCFD2170 less than or equal to $5B. Geographic location is determined by Abbreviated State Name call item RSSD9200 and County Code call item RSSD9150, which is mapped to the proper Core Based Statistical Area (CBSA) defined by the Office of Management and Budget (OMB). Users are advised to use the Federal Reserve Board of Governors' data dictionary (https://www.federalreserve.gov/apps/mdrm/data-dictionary) to retrieve detailed information for specific call items. This series is calculated by the Federal Reserve Bank of St. Louis using raw data that are collected by the FFIEC. Raw data can be found at https://cdr.ffiec.gov/public/.

This series is discontinued and will no longer be updated. The Federal Reserve Bank of St. Louis previously calculated this seasonally adjusted (SA) series based on the not seasonally adjusted (NSA) version available here (https://fred.stlouisfed.org/series/SMU25716503000000007). However, most of the earnings-related series do not have a significant seasonal component, so the values for both the SA and the NSA series are very similar. See the NSA series (https://fred.stlouisfed.org/series/SMU25716503000000007) for updated values. The Federal Reserve Bank of St. Louis used to seasonally adjust this series by using the 'statsmodels' library from Python with default parameter settings. The package uses the U.S. Bureau of the Census X-13ARIMA-SEATS Seasonal Adjustment Program. More information on the 'statsmodels' X-13ARIMA-SEATS package can be found here (https://www.statsmodels.org/dev/generated/statsmodels.tsa.x13.x13_arima_analysis.html). More information on X-13ARIMA-SEATS can be found here (https://www.census.gov/data/software/x13as.html). Many series include both seasonally adjusted (SA) and not seasonally adjusted (NSA) data. Occasionally, updates to the data will not include sufficient seasonal factors to trigger a seasonal adjustment. In these cases, the NSA series will be updated normally; but the SA series will also be updated with the NSA data. The NSA series can be located here here (https://fred.stlouisfed.org/series/SMU25716503000000007). Some seasonally adjusted series may exhibit negative values because they are created from a seasonal adjustment process regardless of the actual meaning or interpretation of the given indicator.

This series is discontinued and will no longer be updated. The Federal Reserve Bank of St. Louis previously calculated this seasonally adjusted (SA) series based on the not seasonally adjusted (NSA) version available here (https://fred.stlouisfed.org/series/SMU25716503000000008). However, most of the earnings-related series do not have a significant seasonal component, so the values for both the SA and the NSA series are very similar. See the NSA series (https://fred.stlouisfed.org/series/SMU25716503000000008) for updated values. The Federal Reserve Bank of St. Louis used to seasonally adjust this series by using the 'statsmodels' library from Python with default parameter settings. The package uses the U.S. Bureau of the Census X-13ARIMA-SEATS Seasonal Adjustment Program. More information on the 'statsmodels' X-13ARIMA-SEATS package can be found here (https://www.statsmodels.org/dev/generated/statsmodels.tsa.x13.x13_arima_analysis.html). More information on X-13ARIMA-SEATS can be found here (https://www.census.gov/data/software/x13as.html). Many series include both seasonally adjusted (SA) and not seasonally adjusted (NSA) data. Occasionally, updates to the data will not include sufficient seasonal factors to trigger a seasonal adjustment. In these cases, the NSA series will be updated normally; but the SA series will also be updated with the NSA data. The NSA series can be located here here (https://fred.stlouisfed.org/series/SMU25716503000000008). Some seasonally adjusted series may exhibit negative values because they are created from a seasonal adjustment process regardless of the actual meaning or interpretation of the given indicator.

This series is discontinued and will no longer be updated. The Federal Reserve Bank of St. Louis previously calculated this seasonally adjusted (SA) series based on the not seasonally adjusted (NSA) version available here (https://fred.stlouisfed.org/series/SMU25716503000000030). However, most of the earnings-related series do not have a significant seasonal component, so the values for both the SA and the NSA series are very similar. See the NSA series (https://fred.stlouisfed.org/series/SMU25716503000000030) for updated values. The Federal Reserve Bank of St. Louis used to seasonally adjust this series by using the 'statsmodels' library from Python with default parameter settings. The package uses the U.S. Bureau of the Census X-13ARIMA-SEATS Seasonal Adjustment Program. More information on the 'statsmodels' X-13ARIMA-SEATS package can be found here (https://www.statsmodels.org/dev/generated/statsmodels.tsa.x13.x13_arima_analysis.html). More information on X-13ARIMA-SEATS can be found here (https://www.census.gov/data/software/x13as.html). Many series include both seasonally adjusted (SA) and not seasonally adjusted (NSA) data. Occasionally, updates to the data will not include sufficient seasonal factors to trigger a seasonal adjustment. In these cases, the NSA series will be updated normally; but the SA series will also be updated with the NSA data. The NSA series can be located here here (https://fred.stlouisfed.org/series/SMU25716503000000030). Some seasonally adjusted series may exhibit negative values because they are created from a seasonal adjustment process regardless of the actual meaning or interpretation of the given indicator.

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'x12' package from R with default parameter settings. The package uses the U.S. Bureau of the Census X-12-ARIMA Seasonal Adjustment Program. More information on the 'x12' package can be found at http://cran.r-project.org/web/packages/x12/x12.pdf. More information on X-12-ARIMA can be found at https://www.census.gov/srd/www/x13as/.

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'x12' package from R with default parameter settings. The package uses the U.S. Bureau of the Census X-12-ARIMA Seasonal Adjustment Program. More information on the 'x12' package can be found at http://cran.r-project.org/web/packages/x12/x12.pdf. More information on X-12-ARIMA can be found at https://www.census.gov/srd/www/x13as/.

This series is discontinued and will no longer be updated. The Federal Reserve Bank of St. Louis previously calculated this seasonally adjusted (SA) series based on the not seasonally adjusted (NSA) version available here (https://fred.stlouisfed.org/series/SMU25716503100000007). However, most of the earnings-related series do not have a significant seasonal component, so the values for both the SA and the NSA series are very similar. See the NSA series (https://fred.stlouisfed.org/series/SMU25716503100000007) for updated values. The Federal Reserve Bank of St. Louis used to seasonally adjust this series by using the 'statsmodels' library from Python with default parameter settings. The package uses the U.S. Bureau of the Census X-13ARIMA-SEATS Seasonal Adjustment Program. More information on the 'statsmodels' X-13ARIMA-SEATS package can be found here (https://www.statsmodels.org/dev/generated/statsmodels.tsa.x13.x13_arima_analysis.html). More information on X-13ARIMA-SEATS can be found here (https://www.census.gov/data/software/x13as.html). Many series include both seasonally adjusted (SA) and not seasonally adjusted (NSA) data. Occasionally, updates to the data will not include sufficient seasonal factors to trigger a seasonal adjustment. In these cases, the NSA series will be updated normally; but the SA series will also be updated with the NSA data. The NSA series can be located here here (https://fred.stlouisfed.org/series/SMU25716503100000007). Some seasonally adjusted series may exhibit negative values because they are created from a seasonal adjustment process regardless of the actual meaning or interpretation of the given indicator.

Overview of the Index The Index is a quarterly comprehensive picture of the average American household’s financial condition. Built by assessing the key elements of financial health and distress, it converts a complex set of factors into a single, easy to understand number. Scope and History The index measures the U.S., all 50 states and more than 70 MSAs. The national and state versions date back to 1980 and the MSA versions date back to 1990. Public Data and Proprietary Methodology We use more than 65 data points from government, public and private data and a proprietary methodology for compiling, combining and evaluating data. With nearly 50 years of experience and insight into helping consumers in financial distress, we know the biggest causes of distress, how people react to financial challenges and proven strategies for regaining control. (Note: Our client data is not a data source for the Index) Measured on a 100 Point Scale Financial distress is measured on a 100 point scale and a score under 70 indicates financial distress. The lower the score equals more distress, a weaker financial position, more urgency to act, takes longer and is harder to resolve, and increases the probability of needing a third party help to resolve. The Index score is tied to one of 5 general rating categories, which reflect the strength and stability of the consumer’s position. Less than 60 Emergency / Crisis 60 – 69 Distressed / Unstable 70 – 79 Weakening / At-Risk 80 – 89 Good / Stable 90 and Above Excellent / Secure What Does the Index Measure? We measure the 5 categories of personal finance that reflect or lead to a secure, stable financial life—Employment, Housing, Credit, Household Budget and Net Worth. All are equally important, so have given each category equal weighting. Employment. Stable income is the foundation of any family’s finances. This category measures the impact of unemployment and underemployment on financial health. Key Measures: Unemployment, Underemployment Sample Data Source: Department of Labor, Bureau of Labor Statistics Housing. Safe, affordable housing is a priority for all families. This category measures how consumers are paying their mortgage/rent and the impact of housing costs on their finances. Key Measures: Mortgage and Rental Delinquencies, Housing as Percent of Budget Sample Data Source: National Delinquency Survey Credit. Responsible use of credit creates more borrowing options and lower costs. This category assesses the strength of credit scores and how well families manage their credit. Key Measures: Credit Scores, Trade Line Utilization, Credit Delinquencies, Per Capita Bankruptcies Sample Data Source: National Credit Bureau Household Budget. Spending less than you make is the daily choice that leads to long-term success. This category measures families’ spending patterns and saving for emergencies. Key Measures: Disposable Income, Savings, Consumer Confidence Sample Data Source: Department of Commerce, Bureau of Economic Analysis Net Worth. Strong, positive net worth creates options and independence. This category measures how well consumers are strengthening their personal balance sheets. Key Measures: Household Net Worth, Net Worth versus Funds Required for Long-Term Needs (e.g. retirement) Sample Data Source: Federal Reserve Flow of Funds, Survey of Consumer Finances

Average consumer prices are calculated for household fuel, motor fuel, and food items from prices collected for the Consumer Price Index (CPI). Average prices are best used to measure the price level in a particular month, not to measure price change over time. It is more appropriate to use CPI index values for the particular item categories to measure price change. Prices, except for electricity, are collected monthly by BLS representatives in the 75 urban areas priced for the CPI. Electricity prices are collected for the BLS for the same 75 areas on a monthly basis by the Department of Energy using mail questionnaires. All fuel prices include applicable Federal, State, and local taxes; prices for natural gas and electricity also include fuel and purchased gas adjustments. For more information, please visit the Bureau of Labor Statistics (https://www.bls.gov/cpi/factsheets/average-prices.htm).