Median Weekly Earnings - Full-Time Workers Age 16+
Why Use This Data Source In Your Models?
Mean weekly real earnings for full time employees represents the average dollar amount paid to employees each week in the United States. This is indicative of hourly wage rates, economic health, cost of living, and rural vs urban demographics.
Median Weekly Earnings - Full-Time Workers Age 16+
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Automated Data Profiling
Suggested Treatment:
Grain Transformation:
Source:
U.S. Bureau of Labor Statistics
Release:
Wages & Salaries
Units:
1982-84 CPI Adjusted Dollars, Not Seasonally Adjusted
Frequency:
Quarterly
Available Through:
03/31/2025
Suggested Treatment:
The data shows auto correlation and a non-normal distribution. The data should be differenced. While the Arcsin transformation, provides the best normality, the Log variable will also perform well.
Grain Transformation:
Data is unable to be distributed by time or geography. The roll up method used is Weighted Average.
Auto Correlation Analysis:
Data shows auto correlation indicating a need for differencing
The ACF indicates 1 order differencing is appropriate.
Following first order differencing, no further differencing is required based on the differenced ACF at lag one of -0.06
Trend Analysis:
The Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test, KPSS Trend = 0.08 p-value = 0.10 indicates that the data is stationary.
Distribution Analysis:
The Shapiro-Wilk test returned W = 0.96 with a p-value =0.13 indicating the data follows a normal distribution.
A skewness score of 0.55 indicates the data are moderately skewed.
Hartigan's dip test score of 0.05 with a p-value of 0.51 inidcates the data is unimodal
Statistics (Pearson P/ df, lower => more normal)
Auto Correlation Function
Auto Correlation Function After Differencing
Partial Auto Correlation Function
Seasonal Impact
Seasonal and Trend Decompostion
Citation:
U.S. Bureau of Labor Statistics, Employed full time: Median usual weekly real earnings: Wage and salary workers: 16 years and over [LEU0252881600Q], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/LEU0252881600Q, December 18, 2019.
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