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FRED Graph

1Y | 5Y | 10Y | Max

NOTES

Source: U.S. Census Bureau  

Release: Housing Units Authorized By Building Permits  

Units:  Units, Seasonally Adjusted

Frequency:  Monthly

Notes:

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'statsmodel' 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 'statsmodel' X-13ARIMA-SEATS package can be found here. More information on X-13ARIMA-SEATS can be found here.

Many series include both seasonally adjusted (SA) and not seasonally adjusted (NSA) data. In some cases, the NSA data will be updated but the SA data will not be updated. The reason is usually that the data series has not accumulated enough new seasonal factors to trigger an adjustment.The NSA series can be located here The FRED team is currently working on a new procedure to replace SA data that has not yet be updated with NSA data that has been updated.

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.

Suggested Citation:

U.S. Census Bureau, New Private Housing Units Authorized by Building Permits for Utah [UTBPPRIVSA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/UTBPPRIVSA, December 6, 2019.

Source: U.S. Bureau of Labor Statistics  

Release: State Employment and Unemployment  

Units:  Thousands of Persons, Seasonally Adjusted

Frequency:  Monthly

Suggested Citation:

U.S. Bureau of Labor Statistics, All Employees: Total Nonfarm in Utah [UTNA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/UTNA, December 6, 2019.

Source: U.S. Census Bureau  

Release: Housing Units Authorized By Building Permits  

Units:  Units, Seasonally Adjusted

Frequency:  Monthly

Notes:

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'statsmodel' 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 'statsmodel' X-13ARIMA-SEATS package can be found here. More information on X-13ARIMA-SEATS can be found here.

Many series include both seasonally adjusted (SA) and not seasonally adjusted (NSA) data. In some cases, the NSA data will be updated but the SA data will not be updated. The reason is usually that the data series has not accumulated enough new seasonal factors to trigger an adjustment.The NSA series can be located here The FRED team is currently working on a new procedure to replace SA data that has not yet be updated with NSA data that has been updated.

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.

Suggested Citation:

U.S. Census Bureau, New Private Housing Units Authorized by Building Permits for California [CABPPRIVSA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/CABPPRIVSA, December 6, 2019.

Source: U.S. Bureau of Labor Statistics  

Release: State Employment and Unemployment  

Units:  Thousands of Persons, Seasonally Adjusted

Frequency:  Monthly

Suggested Citation:

U.S. Bureau of Labor Statistics, All Employees: Total Nonfarm in California [CANA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/CANA, December 6, 2019.

Source: U.S. Census Bureau  

Release: Housing Units Authorized By Building Permits  

Units:  Units, Seasonally Adjusted

Frequency:  Monthly

Notes:

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'statsmodel' 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 'statsmodel' X-13ARIMA-SEATS package can be found here. More information on X-13ARIMA-SEATS can be found here.

Many series include both seasonally adjusted (SA) and not seasonally adjusted (NSA) data. In some cases, the NSA data will be updated but the SA data will not be updated. The reason is usually that the data series has not accumulated enough new seasonal factors to trigger an adjustment.The NSA series can be located here The FRED team is currently working on a new procedure to replace SA data that has not yet be updated with NSA data that has been updated.

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.

Suggested Citation:

U.S. Census Bureau, New Private Housing Units Authorized by Building Permits for Vermont [VTBPPRIVSA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/VTBPPRIVSA, December 6, 2019.

Source: U.S. Bureau of Labor Statistics  

Release: State Employment and Unemployment  

Units:  Thousands of Persons, Seasonally Adjusted

Frequency:  Monthly

Suggested Citation:

U.S. Bureau of Labor Statistics, All Employees: Total Nonfarm in Vermont [VTNA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/VTNA, December 6, 2019.

Source: U.S. Census Bureau  

Release: Housing Units Authorized By Building Permits  

Units:  Units, Seasonally Adjusted

Frequency:  Monthly

Notes:

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'statsmodel' 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 'statsmodel' X-13ARIMA-SEATS package can be found here. More information on X-13ARIMA-SEATS can be found here.

Many series include both seasonally adjusted (SA) and not seasonally adjusted (NSA) data. In some cases, the NSA data will be updated but the SA data will not be updated. The reason is usually that the data series has not accumulated enough new seasonal factors to trigger an adjustment.The NSA series can be located here The FRED team is currently working on a new procedure to replace SA data that has not yet be updated with NSA data that has been updated.

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.

Suggested Citation:

U.S. Census Bureau, New Private Housing Units Authorized by Building Permits for Texas [TXBPPRIVSA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/TXBPPRIVSA, December 6, 2019.

Source: U.S. Bureau of Labor Statistics  

Release: State Employment and Unemployment  

Units:  Thousands of Persons, Seasonally Adjusted

Frequency:  Monthly

Suggested Citation:

U.S. Bureau of Labor Statistics, All Employees: Total Nonfarm in Texas [TXNA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/TXNA, December 6, 2019.

Source: U.S. Bureau of Labor Statistics  

Release: State Employment and Unemployment  

Units:  Thousands of Persons, Seasonally Adjusted

Frequency:  Monthly

Suggested Citation:

U.S. Bureau of Labor Statistics, All Employees: Total Nonfarm in Mississippi [MSNA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/MSNA, December 6, 2019.

Source: U.S. Census Bureau  

Release: Housing Units Authorized By Building Permits  

Units:  Units, Seasonally Adjusted

Frequency:  Monthly

Notes:

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'statsmodel' 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 'statsmodel' X-13ARIMA-SEATS package can be found here. More information on X-13ARIMA-SEATS can be found here.

Many series include both seasonally adjusted (SA) and not seasonally adjusted (NSA) data. In some cases, the NSA data will be updated but the SA data will not be updated. The reason is usually that the data series has not accumulated enough new seasonal factors to trigger an adjustment.The NSA series can be located here The FRED team is currently working on a new procedure to replace SA data that has not yet be updated with NSA data that has been updated.

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.

Suggested Citation:

U.S. Census Bureau, New Private Housing Units Authorized by Building Permits for Mississippi [MSBPPRIVSA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/MSBPPRIVSA, December 6, 2019.

Source: U.S. Census Bureau  

Release: Housing Units Authorized By Building Permits  

Units:  Units, Seasonally Adjusted

Frequency:  Monthly

Notes:

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'statsmodel' 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 'statsmodel' X-13ARIMA-SEATS package can be found here. More information on X-13ARIMA-SEATS can be found here.

Many series include both seasonally adjusted (SA) and not seasonally adjusted (NSA) data. In some cases, the NSA data will be updated but the SA data will not be updated. The reason is usually that the data series has not accumulated enough new seasonal factors to trigger an adjustment.The NSA series can be located here The FRED team is currently working on a new procedure to replace SA data that has not yet be updated with NSA data that has been updated.

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.

Suggested Citation:

U.S. Census Bureau, New Private Housing Units Authorized by Building Permits for Colorado [COBPPRIVSA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/COBPPRIVSA, December 6, 2019.

Source: U.S. Bureau of Labor Statistics  

Release: State Employment and Unemployment  

Units:  Thousands of Persons, Seasonally Adjusted

Frequency:  Monthly

Suggested Citation:

U.S. Bureau of Labor Statistics, All Employees: Total Nonfarm in Colorado [CONA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/CONA, December 6, 2019.

Source: U.S. Census Bureau  

Release: Housing Units Authorized By Building Permits  

Units:  Units, Seasonally Adjusted

Frequency:  Monthly

Notes:

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'statsmodel' 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 'statsmodel' X-13ARIMA-SEATS package can be found here. More information on X-13ARIMA-SEATS can be found here.

Many series include both seasonally adjusted (SA) and not seasonally adjusted (NSA) data. In some cases, the NSA data will be updated but the SA data will not be updated. The reason is usually that the data series has not accumulated enough new seasonal factors to trigger an adjustment.The NSA series can be located here The FRED team is currently working on a new procedure to replace SA data that has not yet be updated with NSA data that has been updated.

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.

Suggested Citation:

U.S. Census Bureau, New Private Housing Units Authorized by Building Permits for Massachusetts [MABPPRIVSA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/MABPPRIVSA, December 6, 2019.

Source: U.S. Bureau of Labor Statistics  

Release: State Employment and Unemployment  

Units:  Thousands of Persons, Seasonally Adjusted

Frequency:  Monthly

Suggested Citation:

U.S. Bureau of Labor Statistics, All Employees: Total Nonfarm in Massachusetts [MANA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/MANA, December 6, 2019.

Source: U.S. Census Bureau  

Release: Housing Units Authorized By Building Permits  

Units:  Units, Seasonally Adjusted

Frequency:  Monthly

Notes:

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'statsmodel' 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 'statsmodel' X-13ARIMA-SEATS package can be found here. More information on X-13ARIMA-SEATS can be found here.

Many series include both seasonally adjusted (SA) and not seasonally adjusted (NSA) data. In some cases, the NSA data will be updated but the SA data will not be updated. The reason is usually that the data series has not accumulated enough new seasonal factors to trigger an adjustment.The NSA series can be located here The FRED team is currently working on a new procedure to replace SA data that has not yet be updated with NSA data that has been updated.

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.

Suggested Citation:

U.S. Census Bureau, New Private Housing Units Authorized by Building Permits for Nevada [NVBPPRIVSA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/NVBPPRIVSA, December 6, 2019.

Source: U.S. Bureau of Labor Statistics  

Release: State Employment and Unemployment  

Units:  Thousands of Persons, Seasonally Adjusted

Frequency:  Monthly

Suggested Citation:

U.S. Bureau of Labor Statistics, All Employees: Total Nonfarm in Nevada [NVNA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/NVNA, December 6, 2019.

Source: U.S. Census Bureau  

Release: Housing Units Authorized By Building Permits  

Units:  Units, Seasonally Adjusted

Frequency:  Monthly

Notes:

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'statsmodel' 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 'statsmodel' X-13ARIMA-SEATS package can be found here. More information on X-13ARIMA-SEATS can be found here.

Many series include both seasonally adjusted (SA) and not seasonally adjusted (NSA) data. In some cases, the NSA data will be updated but the SA data will not be updated. The reason is usually that the data series has not accumulated enough new seasonal factors to trigger an adjustment.The NSA series can be located here The FRED team is currently working on a new procedure to replace SA data that has not yet be updated with NSA data that has been updated.

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.

Suggested Citation:

U.S. Census Bureau, New Private Housing Units Authorized by Building Permits for Florida [FLBPPRIVSA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/FLBPPRIVSA, December 6, 2019.

Source: U.S. Bureau of Labor Statistics  

Release: State Employment and Unemployment  

Units:  Thousands of Persons, Seasonally Adjusted

Frequency:  Monthly

Suggested Citation:

U.S. Bureau of Labor Statistics, All Employees: Total Nonfarm in Florida [FLNA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/FLNA, December 6, 2019.

Source: U.S. Census Bureau  

Release: Housing Units Authorized By Building Permits  

Units:  Units, Seasonally Adjusted

Frequency:  Monthly

Notes:

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'statsmodel' 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 'statsmodel' X-13ARIMA-SEATS package can be found here. More information on X-13ARIMA-SEATS can be found here.

Many series include both seasonally adjusted (SA) and not seasonally adjusted (NSA) data. In some cases, the NSA data will be updated but the SA data will not be updated. The reason is usually that the data series has not accumulated enough new seasonal factors to trigger an adjustment.The NSA series can be located here The FRED team is currently working on a new procedure to replace SA data that has not yet be updated with NSA data that has been updated.

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.

Suggested Citation:

U.S. Census Bureau, New Private Housing Units Authorized by Building Permits for Arizona [AZBPPRIVSA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/AZBPPRIVSA, December 6, 2019.

Source: U.S. Bureau of Labor Statistics  

Release: State Employment and Unemployment  

Units:  Thousands of Persons, Seasonally Adjusted

Frequency:  Monthly

Suggested Citation:

U.S. Bureau of Labor Statistics, All Employees: Total Nonfarm in Arizona [AZNA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/AZNA, December 6, 2019.

Source: U.S. Census Bureau  

Release: Housing Units Authorized By Building Permits  

Units:  Units, Seasonally Adjusted

Frequency:  Monthly

Notes:

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'statsmodel' 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 'statsmodel' X-13ARIMA-SEATS package can be found here. More information on X-13ARIMA-SEATS can be found here.

Many series include both seasonally adjusted (SA) and not seasonally adjusted (NSA) data. In some cases, the NSA data will be updated but the SA data will not be updated. The reason is usually that the data series has not accumulated enough new seasonal factors to trigger an adjustment.The NSA series can be located here The FRED team is currently working on a new procedure to replace SA data that has not yet be updated with NSA data that has been updated.

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.

Suggested Citation:

U.S. Census Bureau, New Private Housing Units Authorized by Building Permits for Indiana [INBPPRIVSA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/INBPPRIVSA, December 6, 2019.

Source: U.S. Bureau of Labor Statistics  

Release: State Employment and Unemployment  

Units:  Thousands of Persons, Seasonally Adjusted

Frequency:  Monthly

Suggested Citation:

U.S. Bureau of Labor Statistics, All Employees: Total Nonfarm in Indiana [INNA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/INNA, December 6, 2019.

Source: U.S. Census Bureau  

Release: Housing Units Authorized By Building Permits  

Units:  Units, Seasonally Adjusted

Frequency:  Monthly

Notes:

The Federal Reserve Bank of St. Louis seasonally adjusts this series by using the 'statsmodel' 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 'statsmodel' X-13ARIMA-SEATS package can be found here. More information on X-13ARIMA-SEATS can be found here.

Many series include both seasonally adjusted (SA) and not seasonally adjusted (NSA) data. In some cases, the NSA data will be updated but the SA data will not be updated. The reason is usually that the data series has not accumulated enough new seasonal factors to trigger an adjustment.The NSA series can be located here The FRED team is currently working on a new procedure to replace SA data that has not yet be updated with NSA data that has been updated.

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.

Suggested Citation:

U.S. Census Bureau, New Private Housing Units Authorized by Building Permits for Delaware [DEBPPRIVSA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/DEBPPRIVSA, December 6, 2019.

Source: U.S. Bureau of Labor Statistics  

Release: State Employment and Unemployment  

Units:  Thousands of Persons, Seasonally Adjusted

Frequency:  Monthly

Suggested Citation:

U.S. Bureau of Labor Statistics, All Employees: Total Nonfarm in Delaware [DENA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/DENA, December 6, 2019.

RELEASE TABLES
RELATED CONTENT

Related Resources

Other Formats

New Private Housing Units Authorized by Building Permits for Utah

Monthly, Not Seasonally Adjusted

All Employees: Total Nonfarm in Utah

3-month Average Change, Thousands of Persons, Monthly, Seasonally Adjusted Annual, Not Seasonally Adjusted Monthly, Not Seasonally Adjusted

New Private Housing Units Authorized by Building Permits for California

Monthly, Not Seasonally Adjusted

All Employees: Total Nonfarm in California

3-month Average Change, Thousands of Persons, Monthly, Seasonally Adjusted Annual, Not Seasonally Adjusted Monthly, Not Seasonally Adjusted

New Private Housing Units Authorized by Building Permits for Vermont

Monthly, Not Seasonally Adjusted

All Employees: Total Nonfarm in Vermont

3-month Average Change, Thousands of Persons, Monthly, Seasonally Adjusted Annual, Not Seasonally Adjusted Monthly, Not Seasonally Adjusted

New Private Housing Units Authorized by Building Permits for Texas

Monthly, Not Seasonally Adjusted

All Employees: Total Nonfarm in Texas

3-month Average Change, Thousands of Persons, Monthly, Seasonally Adjusted Annual, Not Seasonally Adjusted Monthly, Not Seasonally Adjusted

All Employees: Total Nonfarm in Mississippi

3-month Average Change, Thousands of Persons, Monthly, Seasonally Adjusted Annual, Not Seasonally Adjusted Monthly, Not Seasonally Adjusted

New Private Housing Units Authorized by Building Permits for Mississippi

Monthly, Not Seasonally Adjusted

New Private Housing Units Authorized by Building Permits for Colorado

Monthly, Not Seasonally Adjusted

All Employees: Total Nonfarm in Colorado

3-month Average Change, Thousands of Persons, Monthly, Seasonally Adjusted Annual, Not Seasonally Adjusted Monthly, Not Seasonally Adjusted

New Private Housing Units Authorized by Building Permits for Massachusetts

Monthly, Not Seasonally Adjusted

All Employees: Total Nonfarm in Massachusetts

3-month Average Change, Thousands of Persons, Monthly, Seasonally Adjusted Annual, Not Seasonally Adjusted Monthly, Not Seasonally Adjusted

New Private Housing Units Authorized by Building Permits for Nevada

Monthly, Not Seasonally Adjusted

All Employees: Total Nonfarm in Nevada

3-month Average Change, Thousands of Persons, Monthly, Seasonally Adjusted Annual, Not Seasonally Adjusted Monthly, Not Seasonally Adjusted

New Private Housing Units Authorized by Building Permits for Florida

Monthly, Not Seasonally Adjusted

All Employees: Total Nonfarm in Florida

3-month Average Change, Thousands of Persons, Monthly, Seasonally Adjusted Annual, Not Seasonally Adjusted Monthly, Not Seasonally Adjusted

New Private Housing Units Authorized by Building Permits for Arizona

Monthly, Not Seasonally Adjusted

All Employees: Total Nonfarm in Arizona

3-month Average Change, Thousands of Persons, Monthly, Seasonally Adjusted Annual, Not Seasonally Adjusted Monthly, Not Seasonally Adjusted

New Private Housing Units Authorized by Building Permits for Indiana

Monthly, Not Seasonally Adjusted

All Employees: Total Nonfarm in Indiana

3-month Average Change, Thousands of Persons, Monthly, Seasonally Adjusted Annual, Not Seasonally Adjusted Monthly, Not Seasonally Adjusted

New Private Housing Units Authorized by Building Permits for Delaware

Monthly, Not Seasonally Adjusted

All Employees: Total Nonfarm in Delaware

3-month Average Change, Thousands of Persons, Monthly, Seasonally Adjusted Annual, Not Seasonally Adjusted Monthly, Not Seasonally Adjusted

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