Smoothed U.S. Recession Probabilities
Why Use This Data Source In Your Models?
Smoothed US recession probabilities measures the liklihood that the US is in or will enter an economic recession. This is useful for describing the overall economic situation in the US.
Smoothed U.S. Recession Probabilities
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Automated Data Profiling
Suggested Treatment:
Grain Transformation:
Source:
Hamilton, James
Release:
U.S. Recessions
Units:
Percent, Not Seasonally Adjusted
Frequency:
Monthly
Available Through:
03/31/2025
Suggested Treatment:
The data shows seasonality. The data should be adjusted. While the Order Norm transformation, provides the best normality, the Log 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.
Following first order differencing, no further differencing is required based on the differenced ACF at lag one of 0.00
Trend Analysis:
The Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test, KPSS Trend = 0.05 p-value = 0.10 indicates that the data is stationary.
Distribution Analysis:
The Shapiro-Wilk test returned W = 0.12 with a p-value =0.00 indicating the data does not follow a normal distribution.
A skewness score of 7.83 indicates the data are substantially skewed.
Hartigan's dip test score of 0.05 with a p-value of 0.04 inidcates the data is multimodal
Statistics (Pearson P/ df, lower => more normal)
Auto Correlation Function
Auto Correlation Function After Differencing
Partial Auto Correlation Function
Seasonal Impact
Seasonal and Trend Decompostion
Citation:
Piger, Jeremy Max and Chauvet, Marcelle, Smoothed U.S. Recession Probabilities [RECPROUSM156N], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/RECPROUSM156N, December 19, 2019.
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