Federal Reserve Bank of Philadelphia
Percent, Seasonally Adjusted
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.
The data shows autocorrection and a non-normal distribution. The data should be differenced. While the Untransformed transformation, provides the best normality, the Yeo Johnson variable will also perform well.
Data is unable to be distributed by time or geography. The roll up method used is Weighted Average.
Leading Index by US State
Auto Correction Function
Auto Correlation Function After Differencing
Partial Auto Correlation Function
Seasonal and Trend Decompostion
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 -0.10
The Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test, KPSS Trend = 0.26 p-value = 0.01 indicates that the data is not stationary.
The Shapiro-Wilk test returned W = 0.99 with a p-value =0.73 indicating the data follows a normal distribution.
A skewness score of 0.02 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)
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.