Heavy Weight Truck Retail Sales - Seas Adj

Source:
U.S. Bureau of Economic Analysis

Release:
Retail Sales

Units:
Millions of Units, Seasonally Adjusted Annual Rate

Frequency:
Monthly

Available Through:
10/31/2021

Why Use:

Motor vehicle sales: Heavy Weight Trucks indicates the number of drivers, number of vehicles, and vehicle supply and demand.

Suggested Treatment:

The data shows autocorrection and a non-normal distribution. The data should be differenced. While the Yeo Johnson transformation, provides the best normality, the Log variable will also perform well.

Grain Transformation:

Data is able to be distributed by time but not by geography. The roll up method used is Sum.

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Heavy Weight Truck Retail Sales - Seas Adj

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 -0.31

Trend Analysis:

The Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test, KPSS Trend = 0.23 p-value = 0.01 indicates that the data is not stationary.

Distribution Analysis:

The Shapiro-Wilk test returned W = 0.96 with a p-value =0.01 indicating the data does not follow a normal distribution.

A skewness score of 0.43 indicates the data are fairly symmetrical.

Hartigan's dip test score of 0.04 with a p-value of 0.54 inidcates the data is unimodal

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

No transform
1.07
Box-cox
NA
Log_b(x-a)
0.99
sqrt(x+a)
1.09
exp(x)
1.11
arcsinh(x)
1.09
Yeo-Johnson
0.91
OrderNorm
1.04

Citation:

U.S. Bureau of Economic Analysis, Motor Vehicle Retail Sales: Heavy Weight Trucks [HTRUCKSSAAR], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/HTRUCKSSAAR, December 16, 2019.

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