Natural Unemployment Rate: Long-term, Total US
Why Use This Data Source In Your Models?
The long-term natural rate of unemployment measures the rate of unemployment arising from all sources except fluctuations in aggregate demand. This indicates GDP levels and long-term economic health.
Natural Unemployment Rate: Long-term, Total US
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Automated Data Profiling
Suggested Treatment:
Grain Transformation:
Source:
U.S. Bureau of Labor Statistics
Release:
Employment Situation
Units:
Percent, Not Seasonally Adjusted
Frequency:
Quarterly
Available Through:
12/31/2035
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 Exponential 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 2 order differencing is appropriate.
Further differencing is reccommended
Trend Analysis:
The Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test, KPSS Trend = 0.49 p-value = 0.01 indicates that the data is not stationary.
Distribution Analysis:
The Shapiro-Wilk test returned W = 0.94 with a p-value =0.00 indicating the data does not follow a normal distribution.
A skewness score of 0.36 indicates the data are fairly symmetrical.
Hartigan's dip test score of 0.02 with a p-value of 0.99 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, Unemployment Rate: 20 years and over, Black or African American Men [LNS14000031], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/LNS14000031, December 19, 2019.
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