READY SIGNAL CONTROL DATA

PPI: Wood Pulp - Not Seas Adj, Index 2006 = 100

Why Use This Data Source In Your Models?

The producer price index for wood pulp represents the average movement in selling prices from domestic production over time. This indicates supply and demand for wood pulp and its inputs.

PPI: Wood Pulp - Not Seas Adj, Index 2006 = 100

Instantly Download this Data Using Our Automated Feature Engineering Tool.

Automated Data Profiling

Ready Signal automatically profiles each data set and offers up suggested industry standard data science treatments to utilize with these data in your models.

Suggested Treatment:

The data shows seasonality. The data should be adjusted. 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.

Source:
U.S. Bureau of Labor Statistics

Release:
Producer Price Index

Units:
Index 2006=100, Not Seasonally Adjusted

Frequency:
Monthly

Available Through:
10/31/2024

Suggested Treatment:

The data shows seasonality. The data should be adjusted. 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.

Auto Correlation Analysis:

Data does not show strong auto correlation indicating no need for differencing

The ACF indicates 0 order differencing is appropriate.

Further differencing is reccommended

Trend Analysis:

The Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test, KPSS Trend = 0.14 p-value = 0.06 indicates that the data is 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 0.33 indicates the data are fairly symmetrical.

Hartigan's dip test score of 0.04 with a p-value of 0.08 inidcates the data is unimodal

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

No transform
7.40
Box-cox
6.59
Log_b(x-a)
7.13
sqrt(x+a)
6.96
exp(x)
146.88
arcsinh(x)
7.13
Yeo-Johnson
6.59
OrderNorm
0.05

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, Producer Price Index by Commodity for Pulp, Paper, and Allied Products: Wood Pulp [WPU0911], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/WPU0911, November 8, 2019.

Designed For Data Scientists and Analysts

400+ Data Sources

Use our platform to aggregate, normalize, and profile open source and premium control data. Spend less time finding and wrangling data, and more time building efficient and feature-rich machine learning data pipelines.

Data Science Treatments

Instantly apply industry-standard data science treatments and transformations, including (but not limited to) Differencing, Lead/Lag, Box Cox. Easily manipulate data across different time and geographic grains.

Auto Discovery

Our Patent Pending iterative testing engine allows you to upload your target variable, and the platform will test for possible statistical relationships across all available data sources. Saving you time and removing analyst bias.

Data Ingestion

Easily integrate your Ready Signal data to the data science platform of your choice. Connect directly to Ready Signal through our API or using one of our pre-built data connectors or download directly in Excel or CSV format.

Scroll to Top