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Average Weekly Wages for Employees in Private Establishments in Laredo, TX (MSA) (ENUC297040510SA)

Q3 2024: 788
Updated: Mar 5, 2025 11:23 AM CST
Q3 2024:  788  
Q2 2024:  775  
Q1 2024:  785  
Q4 2023:  809  
Q3 2023:  756  

Units:

Dollars per Week,
Seasonally Adjusted

Frequency:

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Date:
Bar 1 - Average Weekly Wages for Employees in Private Establishments in Laredo, TX (MSA) Vintage: 2024-12-05
Bar 1
(a) Average Weekly Wages for Employees in Private Establishments in Laredo, TX (MSA), Dollars per Week, Seasonally Adjusted (ENUC297040510SA)
Average weekly wages are the wages paid by unemployment insurance covered employers during the calendar quarter, regardless of when the services were performed. Included in wages are pay for vacation and other paid leave, bonuses, stock options, tips, the cash value of meals and lodging, and in some States, contributions to deferred compensation plans (such as 401(k) plans). 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. 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/ENUC297040510) 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. The data were retrieved from the BLS API on the "Updated" date referenced above the graph. BLS.gov cannot vouch for the data or analyses derived from these data after the data have been retrieved from BLS.gov. "

Select a date that will equal 100 for your custom index:
  Enter date as YYYY-MM-DD
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Write a custom formula to transform one or more series or combine two or more series.

You can begin by adding a series to combine with your existing series.

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    Now create a custom formula to combine or transform the series.

    For example, invert an exchange rate by using formula 1/a, where “a” refers to the first FRED data series added to this line. Or calculate the spread between 2 interest rates, a and b, by using the formula a - b.

    Use the assigned data series variables (a, b, c, etc.) together with operators (+, -, *, /, ^, etc.), parentheses and constants (1, 1.5, 2, etc.) to create your own formula (e.g., 1/a, a-b, (a+b)/2, (a/(a+b+c))*100). As noted above, you may add other data series to this line before entering a formula.

    Finally, you can change the units of your new series.

    Select a date that will equal 100 for your custom index:
        Enter date as YYYY-MM-DD

    Bar 1 - Average Weekly Wages for Employees in Private Establishments in Laredo, TX (MSA) Vintage: 2024-12-05
    Bar 2
    (a) Average Weekly Wages for Employees in Private Establishments in Laredo, TX (MSA), Dollars per Week, Seasonally Adjusted (ENUC297040510SA)
    Average weekly wages are the wages paid by unemployment insurance covered employers during the calendar quarter, regardless of when the services were performed. Included in wages are pay for vacation and other paid leave, bonuses, stock options, tips, the cash value of meals and lodging, and in some States, contributions to deferred compensation plans (such as 401(k) plans). 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. 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/ENUC297040510) 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. The data were retrieved from the BLS API on the "Updated" date referenced above the graph. BLS.gov cannot vouch for the data or analyses derived from these data after the data have been retrieved from BLS.gov. "

    Select a date that will equal 100 for your custom index:
      Enter date as YYYY-MM-DD
    to

    Write a custom formula to transform one or more series or combine two or more series.

    You can begin by adding a series to combine with your existing series.

    Type keywords to search for data

      Now create a custom formula to combine or transform the series.

      For example, invert an exchange rate by using formula 1/a, where “a” refers to the first FRED data series added to this line. Or calculate the spread between 2 interest rates, a and b, by using the formula a - b.

      Use the assigned data series variables (a, b, c, etc.) together with operators (+, -, *, /, ^, etc.), parentheses and constants (1, 1.5, 2, etc.) to create your own formula (e.g., 1/a, a-b, (a+b)/2, (a/(a+b+c))*100). As noted above, you may add other data series to this line before entering a formula.

      Finally, you can change the units of your new series.

      Select a date that will equal 100 for your custom index:
          Enter date as YYYY-MM-DD

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      Bar 1
      Average Weekly Wages for Employees in Private Establishments in Laredo, TX (MSA) Vintage: 2024-12-05
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      Bar 2
      Average Weekly Wages for Employees in Private Establishments in Laredo, TX (MSA) Vintage: 2025-03-05
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      Notes

      Title Release Dates

      2016-09-07 2025-03-05
       
      Source    

      2016-09-07 2019-03-05
      2016-09-07 2019-03-05
      2019-03-06 2019-08-26
      2019-03-06 2019-08-26
      2019-08-27 2025-03-05
      2019-08-27 2025-03-05
       
      Release    

      2016-09-07 2025-03-05
       
      Units    

      2016-09-07 2025-03-05
       
      Frequency    

      2016-09-07 2025-03-05
       
      Seasonal Adjustment    

      2016-09-07 2025-03-05
       
      Notes    

      2016-09-07 2019-03-05
      2019-03-06 2019-08-26
      2019-08-27 2025-03-05

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