PCE: Excl Food & Energy - SA

Source:
U.S. Bureau of Economic Analysis

Release:
Personal Income and Outlays

Units:
Index 2012 = 100, Seasonally Adjusted

Frequency:
Monthly

Available Through:
10/31/2021

Why Use:

Personal consumption expenditures measures consumer spending on goods and services. Data scientists use it as a measure for economic growth.

Suggested Treatment:

The data shows autocorrection and a non-normal distribution. The data should be differenced. While the Order Norm 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.

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PCE: Excl Food & Energy - SA

Auto Correction Function

Auto Correlation Function After Differencing

Partial Auto Correlation Function

Seasonal Impact

Seasonal and Trend Decompostion

Autocorrectation Analysis:

Data shows autocorrectation 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 0.00

Trend Analysis:

The Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test, KPSS Trend = 0.57 p-value = 0.01 indicates that the data is not stationary.

Distribution Analysis:

The Shapiro-Wilk test returned W = 0.95 with a p-value =0.00 indicating the data does not follow a normal distribution.

A skewness score of 0.16 indicates the data are fairly symmetrical.

Hartigan's dip test score of 0.02 with a p-value of 1.00 inidcates the data is unimodal

Statistics (Pearson P/ df, lower => more normal)

No transform
1.35
Box-cox
1.32
Log_b(x-a)
1.38
sqrt(x+a)
1.39
exp(x)
8.16
arcsinh(x)
1.38
Yeo-Johnson
1.33
OrderNorm
1.17

Citation:

U.S. Bureau of Economic Analysis, Personal Consumption Expenditures Excluding Food and Energy (Chain-Type Price Index) [PCEPILFE], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/PCEPILFE, December 16, 2019.

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