Federal Surplus or Deficit
Why Use This Data Source In Your Models?
The federal surplus or deficit measures the overall difference between government revenues and spending. This is indicative of ??
Federal Surplus or Deficit
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Automated Data Profiling
Suggested Treatment:
Grain Transformation:
Source:
U.S. Dept. of the Treasury, Fiscal Service
Release:
Monthly Treasury Statement
Units:
Millions of Dollars, Not Seasonally Adjusted
Frequency:
Monthly
Available Through:
03/31/2025
Suggested Treatment:
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 Untransformed 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 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 -0.50
Trend Analysis:
The Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test, KPSS Trend = 0.15 p-value = 0.05 indicates that the data is not stationary.
Distribution Analysis:
The Shapiro-Wilk test returned W = 0.89 with a p-value =0.00 indicating the data does not follow a normal distribution.
A skewness score of -1.43 indicates the data are substantially skewed.
Hartigan's dip test score of 0.04 with a p-value of 0.27 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 Impact
Seasonal and Trend Decompostion
Citation:
U.S. Department of the Treasury. Fiscal Service, Federal Surplus or Deficit [-] [MTSDS133FMS], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/MTSDS133FMS, December 19, 2019.
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