See the EIA's report on Energy-Related Carbon Dioxide Emissions by State (http://www.eia.gov/environment/emissions/state/analysis/) for technical notes and documentation.

The Business Formation Statistics are now released on a monthly basis, and the quarterly series will no longer be updated. See BFBF8QTOTALNSANV (https://fred.stlouisfed.org/series/BFBF8QTOTALNSANV) for an alternative. The number of employer businesses that originate from Business Applications (BA) within eight quarters from the quarter of application, similar to https://fred.stlouisfed.org/series/BF4QNSANV. By definition, the end-point of this series is determined by the most recent quarter for which the administrative data is available on payroll.

The Business Formation Statistics are now released on a monthly basis, and the quarterly series will no longer be updated. See BABATOTALNSANV (https://fred.stlouisfed.org/series/BABATOTALNSANV) for an alternative. The core business applications series that correspond to a subset of all applications for an Employer Identification Number (EIN). Includes all applications for an EIN, except for applications for tax liens, estates, trusts, or certain financial filings, applications outside of 50 states and DC or with no state‐county geocodes, applications with a NAICS sector code of 11 (agriculture, forestry, fishing and hunting) or 92 (public administration), and applications in certain industries (e.g. private households, civic and social organizations).

The Business Formation Statistics are now released on a monthly basis, and the quarterly series will no longer be updated. See BFBF4QTOTALSANV (https://fred.stlouisfed.org/series/BFBF4QTOTALSANV) for an alternative. This series provides the number of employer businesses that originate from Business Applications (BA) within four quarters from the quarter of application. By definition, the end-point of this series is determined by the most recent quarter for which the administrative data is available on payroll.

The Business Formation Statistics are now released on a monthly basis, and the quarterly series will no longer be updated. See BAWBATOTALSANV (https://fred.stlouisfed.org/series/BAWBATOTALSANV) for an alternative. High-Propensity Business Applications (HBA) that indicate a first wages‐paid date on the IRS Form SS-4. The indication of a wages-paid date is associated with a high likelihood of transitioning into a business with payroll.

See the EIA's report on Energy-Related Carbon Dioxide Emissions by State (http://www.eia.gov/environment/emissions/state/analysis/) for technical notes and documentation.

See the EIA's report on Energy-Related Carbon Dioxide Emissions by State (http://www.eia.gov/environment/emissions/state/analysis/) for technical notes and documentation.

See the EIA's report on Energy-Related Carbon Dioxide Emissions by State (http://www.eia.gov/environment/emissions/state/analysis/) for technical notes and documentation.

See the EIA's report on Energy-Related Carbon Dioxide Emissions by State (http://www.eia.gov/environment/emissions/state/analysis/) for technical notes and documentation.

See the EIA's report on Energy-Related Carbon Dioxide Emissions by State (http://www.eia.gov/environment/emissions/state/analysis/) for technical notes and documentation.

See the EIA's report on Energy-Related Carbon Dioxide Emissions by State (http://www.eia.gov/environment/emissions/state/analysis/) for technical notes and documentation.

See the EIA's report on Energy-Related Carbon Dioxide Emissions by State (http://www.eia.gov/environment/emissions/state/analysis/) for technical notes and documentation.

The Business Formation Statistics are now released on a monthly basis, and the quarterly series will no longer be updated. See BFSBF4QTOTALSANV (https://fred.stlouisfed.org/series/BFSBF4QTOTALSANV) for an alternative. This series combines (splices) https://fred.stlouisfed.org/series/BF4QSANV and https://fred.stlouisfed.org/series/PBF4QSANV to provide the entire time series for the actual and projected business formations within 4 quarters.

The Business Formation Statistics are now released on a monthly basis, and the quarterly series will no longer be updated. See BFSBF8QTOTALSANV (https://fred.stlouisfed.org/series/BFSBF8QTOTALSANV) for an alternative. This series combines (splices) https://fred.stlouisfed.org/series/BF8QSANV and https://fred.stlouisfed.org/series/PBF8QSANV to provide the entire time series for the actual and projected business formations within 8 quarters.

See the EIA's report on Energy-Related Carbon Dioxide Emissions by State (http://www.eia.gov/environment/emissions/state/analysis/) for technical notes and documentation.

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/SMU32000005500000002). 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/SMU32000005500000002) 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/SMU32000005500000002). 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/SMU32000005500000003). 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/SMU32000005500000003) 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/SMU32000005500000003). 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/SMU32000005500000011). 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/SMU32000005500000011) 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/SMU32000005500000011). 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/SMU32000006000000002). 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/SMU32000006000000002) 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/SMU32000006000000002). 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/SMU32000006000000003). 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/SMU32000006000000003) 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/SMU32000006000000003). 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/SMU32000006000000011). 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/SMU32000006000000011) 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/SMU32000006000000011). 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/SMU32000007000000002). 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/SMU32000007000000002) 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/SMU32000007000000002). 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/SMU32000007000000003). 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/SMU32000007000000003) 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/SMU32000007000000003). 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 may have irregularities or important features that are not disclosed here. To see whether this is the case, please consult Part 1, Section 1, Table 8 in the original source at https://fraser.stlouisfed.org/scribd/?item_id=6408&filepath=%2Fdocs%2Fpublications%2Fbms%2F1914-1941%2FBMS14-41_complete.pdf&start_page=1 Relevant details can be found in the footnotes of each table as well as the introductory material for Section 1.

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 is constructed as a sum of Total Loan and Lease Finance Receivables, Nonaccrual call item RCFD1403 and Total Loan and Lease Finance Receivables, Past Due 90 Days or More and Still Accruing call item RCFD1407 to the Total Loans and Leases, Net of Unearned Income call item RCFD2122. Geographic location is determined by Abbreviated State Name call item RSSD9200 = 'NV' representing two character state abbreviation of Nevada. 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. Additional consolidated data is available on the FDIC's Bank Data and Statistics (https://www.fdic.gov/bank/statistical/). This series includes institutions with the Charter Type call item RSSD9048 = 200 and Entity Type call item RSSD9331 = 1. Charter Type call item RSSD9048 = 200 represents Commercial Bank (including depository trust companies, credit card companies with commercial bank charters, private banks, development banks, limited charter banks, and foreign banks) Entity Type call item RSSD9331 = 1 represents Commercial Bank. Geographic location is determined by Abbreviated State Name call item RSSD9200 = 'NV' representing two character state abbreviation of Nevada. 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/.

Please visit http://research.stlouisfed.org/fred2/personalincome for documentation on the derivation of personal income.

This series may have irregularities or important features that are not disclosed here. To see whether this is the case, please consult Part 1, Section 1, Table 8 in the original source at https://fraser.stlouisfed.org/scribd/?item_id=6408&filepath=%2Fdocs%2Fpublications%2Fbms%2F1914-1941%2FBMS14-41_complete.pdf&start_page=1 Relevant details can be found in the footnotes of each table as well as the introductory material for Section 1.

The Quarterly Summary of State and Local Government Tax Revenue provides quarterly estimates of state and local government tax revenue at a national level, as well as detailed tax revenue data for individual states. This quarterly survey has been conducted continuously since 1962. The information contained in this survey is the most current information available on a nationwide basis for government tax collections. For more information about the survey, visit the U.S. Census Bureau (https://www.census.gov/programs-surveys/qtax/about.html). A Special Note Concerning Revised Data: Revisions reflect tax collection amounts obtained from three general sources. State and local government respondents have submitted revisions to amounts as originally reported. In other cases, governments have reported data, which we used to replace data that were previously imputed or estimated. Finally, some of the revisions were compiled from government sources, both published and unpublished. For more information, see the survey's methodology (https://www.census.gov/programs-surveys/qtax/technical-documentation/methodology.html).

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 Charge-offs on Allowance for Loan and Lease Losses call item RIAD4635. Geographic location is determined by Abbreviated State Name call item RSSD9200 = 'NV' representing two character state abbreviation of Nevada. 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 represents Federal Funds Sold and Securities Purchased Under Agreements to Resell in Domestic Offices of the Bank and of Its Edge and Agreement Subsidiaries, and in International Banking Facilities (IBFs) call item RCFD1350. Geographic location is determined by Abbreviated State Name call item RSSD9200 = 'NV' representing two character state abbreviation of Nevada. 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 data series illustrates the movement of exports from the given state to the given country. A missing observation can mean two things. First, missing observations can appear because no exports were made to the listed country that year. Secondly, it could signify a low number of exporters thus giving away proprietary data away.

This data series illustrates the movement of exports from the given state to the given country. A missing observation can mean two things. First, missing observations can appear because no exports were made to the listed country that year. Secondly, it could signify a low number of exporters thus giving away proprietary data away.

This data series illustrates the movement of exports from the given state to the given country. A missing observation can mean two things. First, missing observations can appear because no exports were made to the listed country that year. Secondly, it could signify a low number of exporters thus giving away proprietary data away.

See the EIA's report on Energy-Related Carbon Dioxide Emissions by State (http://www.eia.gov/environment/emissions/state/analysis/) for technical notes and documentation.

See the EIA's report on Energy-Related Carbon Dioxide Emissions by State (http://www.eia.gov/environment/emissions/state/analysis/) for technical notes and documentation.

The U.S. Census Bureau provides annual estimates of income and poverty statistics for all school districts, counties, and states through the Small Area Income and Poverty Estimates (https://www.census.gov/programs-surveys/saipe/about.html) (SAIPE) program. The bureau's main objective with this program is to provide estimates of income and poverty for the administration of federal programs and the allocation of federal funds to local jurisdictions. In addition to these federal programs, state and local programs use the income and poverty estimates for distributing funds and managing programs. Poverty universe is one of the data sources used in producing SAIPE program estimates, it is made up of persons for whom the Census Bureau can determine poverty status (either "in poverty" or "not in poverty"). The definition of poverty universe for SAIPE estimates is the same for 2006 and beyond and conceptually matches the poverty universe of the American Community Survey (ACS). The poverty universe estimates are not the same as the population estimates from the Census Bureau's Population Estimates Program. Instead, they are derived estimates that differ from population estimates in the following ways: 1. The poverty universe does not include children under the age of 15 who are not related to a reference person within the household by way of birth, marriage or adoption (for example, foster children). The reason is that Census Bureau surveys typically ask income questions only of persons age 15 or older and those under 15 related to a reference person within the household. 2. Beginning with 2006, the poverty universe includes group quarters populations only for noninstitutionalized group quarters, not elsewhere classified. Residents of college dormitories, military housing, and all institutional group quarters populations are excluded. The 2005 poverty universe estimates excluded all group quarters' residents, matching the definition of the 2005 ACS. Prior to the estimates for 2005, the poverty universe data were derived from the Annual Social and Economic Supplement of the Current Population Survey. This marks a break in the data series due to a methodology change. See more details about SAIPE Model Input Data (https://www.census.gov/data/datasets/time-series/demo/saipe/model-tables.html).

The U.S. Census Bureau provides annual estimates of income and poverty statistics for all school districts, counties, and states through the Small Area Income and Poverty Estimates (https://www.census.gov/programs-surveys/saipe/about.html) (SAIPE) program. The bureau's main objective with this program is to provide estimates of income and poverty for the administration of federal programs and the allocation of federal funds to local jurisdictions. In addition to these federal programs, state and local programs use the income and poverty estimates for distributing funds and managing programs. Estimates of poverty by ages and families are not direct counts from enumerations or administrative records, nor direct estimates from sample surveys. Instead, for counties and states, the Census models income and poverty estimates by combining survey data with population estimates and administrative records. A confidence interval is a range of values, from the lower bound to the respective upper bound, that describes the uncertainty surrounding an estimate. A confidence interval is also itself an estimate. It is made using a model of how sampling, interviewing, measuring, and modeling contribute to uncertainty about the relation between the true value of the quantity we are estimating and our estimate of that value. The "90%" in the confidence interval listed above represents a level of certainty about our estimate. If we were to repeatedly make new estimates using exactly the same procedure (by drawing a new sample, conducting new interviews, calculating new estimates and new confidence intervals), the confidence intervals would contain the average of all the estimates 90% of the time. For more details about the confidence intervals and their interpretation, see this explanation (https://www.census.gov/programs-surveys/saipe/guidance/confidence-intervals.html).

For further information about this series go to https://www.census.gov/programs-surveys/saipe/about.html.

Information about this release can be found here (https://www.bea.gov/data/gdp/gdp-state). For information about BEA industries and other regional definitions, visit their Regional Economic Accounts: Regional Definitions website (https://www.bea.gov/data/gdp/gdp-state).

Information about this release can be found here (https://www.bea.gov/data/gdp/gdp-state). For information about BEA industries and other regional definitions, visit their Regional Economic Accounts: Regional Definitions website (https://apps.bea.gov/regional/definitions/).

Information about this release can be found here (https://www.bea.gov/data/gdp/gdp-state). For information about BEA industries and other regional definitions, visit their Regional Economic Accounts: Regional Definitions website (https://apps.bea.gov/regional/definitions/).

Information about this release can be found here (https://www.bea.gov/data/gdp/gdp-state). For information about BEA industries and other regional definitions, visit their Regional Economic Accounts: Regional Definitions website (https://apps.bea.gov/regional/definitions/).

Information about this release can be found here (https://www.bea.gov/data/gdp/gdp-state). For information about BEA industries and other regional definitions, visit their Regional Economic Accounts: Regional Definitions website (https://apps.bea.gov/regional/definitions/).

Information about this release can be found here (https://www.bea.gov/data/gdp/gdp-state). For information about BEA industries and other regional definitions, visit their Regional Economic Accounts: Regional Definitions website (https://apps.bea.gov/regional/definitions/).

This series may have irregularities or important features that are not disclosed here. To see whether this is the case, please consult Part 1, Section 1, Table 8 in the original source at https://fraser.stlouisfed.org/scribd/?item_id=6408&filepath=%2Fdocs%2Fpublications%2Fbms%2F1914-1941%2FBMS14-41_complete.pdf&start_page=1 Relevant details can be found in the footnotes of each table as well as the introductory material for Section 1.

Information about this release can be found here (https://www.bea.gov/data/gdp/gdp-state). For information about BEA industries and other regional definitions, visit their Regional Economic Accounts: Regional Definitions website (https://apps.bea.gov/regional/definitions/).

Information about this release can be found here (https://www.bea.gov/data/gdp/gdp-state). For information about BEA industries and other regional definitions, visit their Regional Economic Accounts: Regional Definitions website (https://apps.bea.gov/regional/definitions/).

A measure of spending on goods and services purchased by, and on behalf of, households based on households' state of residence in the fifty states and the District of Columbia. Spending on motor vehicle services and public transportation. Motor vehicle services consist of motor vehicle maintenance and repair and other motor vehicle services. Public transportation consists of ground transportation, air transportation, and water transportation.For more information about this release go to http://www.bea.gov/newsreleases/regional/pce/pce_newsrelease.htm.

A measure of spending on goods and services purchased by, and on behalf of, households based on households' state of residence in the fifty states and the District of Columbia. Spending on membership clubs, sports centers, parks, theaters, and museums, audio-video, photographic, and information processing equipment services, gambling, and other recreational services.For more information about this release go to http://www.bea.gov/newsreleases/regional/pce/pce_newsrelease.htm.

Personal consumption expenditures of a given area divided by the resident population of the area. Spending on motor vehicle services and public transportation. Motor vehicle services consist of motor vehicle maintenance and repair and other motor vehicle services. Public transportation consists of ground transportation, air transportation, and water transportation.For more information about this release go to http://www.bea.gov/newsreleases/regional/pce/pce_newsrelease.htm.

Personal consumption expenditures of a given area divided by the resident population of the area. Purchases of video, audio, photographic, and information processing equipment and media, sporting equipment supplies, guns, and ammunition, sports and recreational vehicles, recreational books, and musical instruments.For more information about this release go to http://www.bea.gov/newsreleases/regional/pce/pce_newsrelease.htm.

Personal consumption expenditures of a given area divided by the resident population of the area. Purchases of jewelry and watches, therapeutic appliances and equipment, educational books, luggage and similar personal items, and telephone and facsimile equipment.For more information about this release go to http://www.bea.gov/newsreleases/regional/pce/pce_newsrelease.htm.

Personal consumption expenditures of a given area divided by the resident population of the area. Spending on housing and household utilities. Housing consists of the monetary rents paid by tenants for tenant-occupied housing, an imputed rental value for owner-occupied dwellings (measured as the income the homeowner could have received if the house had been rented to a tenant), the rental value of farm dwellings, and spending on group housing. Household utilities consist of water supply and sanitation and electricity and gas.For more information about this release go to http://www.bea.gov/newsreleases/regional/pce/pce_newsrelease.htm.

Personal consumption expenditures of a given area divided by the resident population of the area. Purchases of motor vehicle fuels, lubricants, and fluids, and fuel oils and other fuels.For more information about this release go to http://www.bea.gov/newsreleases/regional/pce/pce_newsrelease.htm.

Personal consumption expenditures of a given area divided by the resident population of the area. Tangible products that can be stored or inventoried.For more information about this release go to http://www.bea.gov/newsreleases/regional/pce/pce_newsrelease.htm.

Personal consumption expenditures of a given area divided by the resident population of the area. Spending on food services and accommodations. Food services consist of purchased meals and beverages and food furnished to employees (including military).For more information about this release go to http://www.bea.gov/newsreleases/regional/pce/pce_newsrelease.htm.

Personal consumption expenditures of a given area divided by the resident population of the area. For more information about this release go to http://www.bea.gov/newsreleases/regional/pce/pce_newsrelease.htm.

A measure of spending on goods and services purchased by, and on behalf of, households based on households' state of residence in the fifty states and the District of Columbia. Spending on housing and household utilities. Housing consists of the monetary rents paid by tenants for tenant-occupied housing, an imputed rental value for owner-occupied dwellings (measured as the income the homeowner could have received if the house had been rented to a tenant), the rental value of farm dwellings, and spending on group housing. Household utilities consist of water supply and sanitation and electricity and gas.For more information about this release go to http://www.bea.gov/newsreleases/regional/pce/pce_newsrelease.htm.

A measure of spending on goods and services purchased by, and on behalf of, households based on households' state of residence in the fifty states and the District of Columbia. Consists of actual and imputed consumption expenditures for services by resident households.For more information about this release go to http://www.bea.gov/newsreleases/regional/pce/pce_newsrelease.htm.