PCE: Services: Net motor vehicle and other transportation insurance (chain-type price index)
Why Use This Data Source In Your Models?
The Personal Consumption Expenditures (PCE) for Services: Net Motor Vehicle and Other Transportation Insurance (chain-type price index) is a useful indicator for tracking inflation and cost trends in the transportation insurance sector. Professionals may use this metric to analyze the impact of rising insurance costs on household budgets, assess shifts in consumer spending on transportation-related services, or forecast broader economic trends tied to the automotive and insurance industries.
PCE: Services: Net motor vehicle and other transportation insurance (chain-type price index)
Instantly Download this Data Using Our Automated Feature Engineering Tool.
Automated Data Profiling
Suggested Treatment:
Grain Transformation:
Source:
U.S. Bureau of Labor Statistics
Release:
Expenditures
Units:
Index 2017=100, Not Seasonally Adjusted
Frequency:
Annual
Available Through:
12/31/2024
Suggested Treatment:
The data shows auto correlation and seasonality. The data should be differenced and seasonally adjusted.
Grain Transformation:
Data is unable to be distributed by time or geography. The roll up method used is Weighted Average.
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 = 0.08 p-value = 0.10 indicates that the data is stationary.
Distribution Analysis:
The Shapiro-Wilk test returned W = 0.94 with a p-value =0.48 indicating the data follows a normal distribution.
A skewness score of 0.08 indicates the data are fairly symmetrical.
Hartigan's dip test score of 0.09 with a p-value of 0.44 inidcates the data is unimodal
Statistics (Pearson P/ df, lower => more normal)
Auto Correlation Function
Auto Correlation Function After Differencing
Partial Auto Correlation Function
Citation:
U.S. Bureau of Economic Analysis, Personal consumption expenditures: Services: Net motor vehicle and other transportation insurance (chain-type price index) [DTINRG3A086NBEA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/DTINRG3A086NBEA, September 30, 2024.
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.
