Leading Index by US State
Why Use This Data Source In Your Models?
The Conference Board Leading Economic Index is an American economic leading indicator derived from ten key variables. Data scientists use this to forecast future economic activity.
Leading Index by US State
Instantly Download this Data Using Our Automated Feature Engineering Tool.
Automated Data Profiling
Federal Reserve Bank of Philadelphia
Percent, Seasonally Adjusted
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 Square Root variable will also perform well.
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.
Following first order differencing, no further differencing is required based on the differenced ACF at lag one of -0.11
The Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test, KPSS Trend = 0.13 p-value = 0.09 indicates that the data is stationary.
The Shapiro-Wilk test returned W = 0.98 with a p-value =0.23 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 0.03 with a p-value of 0.75 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 and Trend Decompostion
The following states do not report for this feature: District of Columbia, Puerto Rico.
Federal Reserve Bank of Philadelphia, Leading Index, retrieved from FRED, Federal Reserve Bank of St. Louis; January 27, 2020.
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.
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.
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.