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All Employees: Total Private in Portland-South Portland, ME (NECTA) (SMU23767500500000001SA)

Observation:

Nov 2024: 195.32655 (+ more)  Updated: Dec 21, 2024 5:40 AM CST
Nov 2024:  195.32655  
Oct 2024:  196.95356  
Sep 2024:  196.25527  
Aug 2024:  194.99104  
Jul 2024:  194.75818  

Units:

Thousands of Persons,
Seasonally Adjusted

Frequency:

Monthly

NOTES

Title Release Dates
All Employees: Total Private in Portland-South Portland-Biddeford, ME (NECTA) 2014-01-28 2015-03-26
All Employees: Total Private in Portland-South Portland, ME (NECTA) 2015-03-27 2024-12-20
 
Source    
U.S. Bureau of Labor Statistics 2014-01-28 2015-03-26
Federal Reserve Bank of St. Louis 2014-01-28 2015-03-26
U.S. Bureau of Labor Statistics 2015-03-27 2018-11-15
Federal Reserve Bank of St. Louis 2015-03-27 2018-11-15
U.S. Bureau of Labor Statistics 2018-11-16 2019-04-18
Federal Reserve Bank of St. Louis 2018-11-16 2019-04-18
U.S. Bureau of Labor Statistics 2019-04-19 2019-08-26
Federal Reserve Bank of St. Louis 2019-04-19 2019-08-26
U.S. Bureau of Labor Statistics 2019-08-27 2019-12-19
Federal Reserve Bank of St. Louis 2019-08-27 2019-12-19
U.S. Bureau of Labor Statistics 2019-12-20 2024-12-20
Federal Reserve Bank of St. Louis 2019-12-20 2024-12-20
 
Release    
State and Metro Area Employment, Hours, and Earnings 2014-01-28 2024-12-20
 
Units    
Thousands of Persons 2014-01-28 2024-12-20
 
Frequency    
Monthly 2014-01-28 2024-12-20
 
Seasonal Adjustment    
Seasonally Adjusted 2014-01-28 2024-12-20
 
Notes    
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 http://www.census.gov/srd/www/x12a/.

2014-01-28 2018-11-15
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 X13-ARIMA-SEATS Seasonal Adjustment Program. More information on the 'x12' package can be found at https://cran.r-project.org/web/packages/x12/index.html. More information on X13-ARIMA-SEATS can be found at https://www.census.gov/srd/www/x13as/.

2018-11-16 2019-04-18
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 at https://www.statsmodels.org/dev/generated/statsmodels.tsa.x13.x13_arima_analysis.html. More information on X-13ARIMA-SEATS can be found at https://www.census.gov/srd/www/x13as/.

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.

2019-04-19 2019-08-26
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 (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/srd/www/x13as/).

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 (https://fred.stlouisfed.org/series/SMU23767500500000001) 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.

2019-08-27 2019-12-19
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/SMU23767500500000001).

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.

2019-12-20 2024-12-20

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New England City and Town Areas Portland Maine State and Metro Area Employment, Hours, and Earnings Private St. Louis Fed Employment Seasonally Adjusted Bureau of Labor Statistics Monthly Public Domain: Citation Requested United States of America