GINI Index, Total US
Why Use This Data Source In Your Models?
The GINI Index measures economic equality in the US. This is useful for descibing how GDP, income, and wealth may vary across the population.
GINI Index, Total US
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Suggested Treatment:
Grain Transformation:
Source:
World Bank
Release:
World Development Indicators
Units:
Index, Not Seasonally Adjusted
Frequency:
Annual
Available Through:
12/31/2022
Suggested Treatment:
The data shows seasonality. The data should be adjusted. While the Arcsin transformation, provides the best normality, the Boxcox 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 does not show strong auto correlation indicating no need for differencing
The ACF indicates 0 order differencing is appropriate.
Following first order differencing, no further differencing is required based on the differenced ACF at lag one of -0.52
Trend Analysis:
The Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test, KPSS Trend = 0.15 p-value = 0.04 indicates that the data is not stationary.
Distribution Analysis:
The Shapiro-Wilk test returned W = 0.93 with a p-value =0.49 indicating the data follows a normal distribution.
A skewness score of -0.46 indicates the data are fairly symmetrical.
Hartigan's dip test score of 0.13 with a p-value of 0.21 inidcates the data is unimodal
Statistics (Pearson P/ df, lower => more normal)
Auto Correlation Function
Auto Correlation Function After Differencing
Partial Auto Correlation Function
Data Notes:
2020 data is not currently available.
Citation:
World Bank, GINI Index for the United States [SIPOVGINIUSA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/SIPOVGINIUSA, December 19, 2019.
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