SNAP Benefits Recipient by State
Why Use This Data Source In Your Models?
SNAP benefits recipients measures the number of individuals receiving government assistance as a part of the SNAP program. This indicates income & wages, as well as class composition of each US state.
SNAP Benefits Recipient by State
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Automated Data Profiling
Suggested Treatment:
Grain Transformation:
Source:
Small Area Income and Poverty Estimates
Release:
Small Area Income and Poverty Estimates
Units:
Persons, Not Seasonally Adjusted
Frequency:
Monthly
Available Through:
06/30/2023
Suggested Treatment:
The data shows auto correlation and a non-normal distribution. The data should be differenced. While the Order Norm transformation, provides the best normality, the Yeo Johnson variable will also perform well.
Grain Transformation:
Data is able to be distributed by geography but not by time. The roll up method used is Sum.
Auto Correlation Analysis:
Data shows auto correlation indicating a need for differencing
The ACF indicates 1 order differencing is appropriate.
Further differencing is reccommended
Trend Analysis:
The Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test, KPSS Trend = 0.32 p-value = 0.01 indicates that the data is not stationary.
Distribution Analysis:
The Shapiro-Wilk test returned W = 0.93 with a p-value =0.00 indicating the data does not follow a normal distribution.
A skewness score of -0.51 indicates the data are moderately skewed.
Hartigan's dip test score of 0.03 with a p-value of 0.65 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
Data Notes:
The following states do not report for this feature: District of Columbia, Puerto Rico. Additionally, 2020 data is not currently available.
Citation:
U.S. Census Bureau, SNAP Benefits Recipients, retrieved from FRED, Federal Reserve Bank of St. Louis; January 27, 2020.
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