Average Weekly Earnings of Production Employees: Mining, Logging, and Construction: Specialty Trade Contractors in New York City, NY (DISCONTINUED)

Observations

Dec 2015: 1,709.2

Updated: Jan 27, 2016 11:32 AM CST

Dec 2015:	1,709.2
Nov 2015:	1,647.0
Oct 2015:	1,598.9
Sep 2015:	1,617.4
Aug 2015:	1,615.0

Units:

Dollars per Week,

Seasonally Adjusted

Frequency:

Monthly

Notes

Title	Release Dates

Average Weekly Earnings of Production Employees: Mining, Logging, and Construction: Specialty Trade Contractors in New York City, NY	2014-01-28	2016-01-25
Average Weekly Earnings of Production Employees: Mining, Logging, and Construction: Specialty Trade Contractors in New York City, NY (DISCONTINUED)	2016-01-26	2016-01-26

Source

U.S. Bureau of Labor Statistics	2014-01-28	2016-01-25
Federal Reserve Bank of St. Louis	2014-01-28	2016-01-25
U.S. Bureau of Labor Statistics	2016-01-26	2016-01-26
Federal Reserve Bank of St. Louis	2016-01-26	2016-01-26

Release

State and Metro Area Employment, Hours, and Earnings	2014-01-28	2016-01-26

Units

Dollars per Week	2014-01-28	2016-01-26

Frequency

Monthly	2014-01-28	2016-01-26

Seasonal Adjustment

Seasonally Adjusted	2014-01-28	2016-01-26

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 https://www.census.gov/srd/www/x13as/.	2014-01-28	2016-01-25
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/SMU36935611523800030). 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/SMU36935611523800030) 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/SMU36935611523800030). 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.	2016-01-26	2016-01-26