Supply of Houses in the US - Not Seas Adj
Why Use This Data Source In Your Models?
The months' supply is the ratio of houses for sale to houses sold in the US, indicating how long the current for-sale inventory would last given the current sales rate if no additional new houses were built. This is indicative of supply and demand of houses in the US, as well as the overall economic situation.
Supply of Houses in the US - Not Seas Adj
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Automated Data Profiling
Suggested Treatment:
Grain Transformation:
Source:
U.S. Census Bureau
Release:
Housing & Urban Development
Units:
Months' Supply, Not Seasonally Adjusted
Frequency:
Monthly
Available Through:
11/30/2024
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 Boxcox variable will also perform well.
Grain Transformation:
Data is able to be distributed by geography but not by time. The roll up method used is Sum.
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 = 0.09 p-value = 0.10 indicates that the data is stationary.
Distribution Analysis:
The Shapiro-Wilk test returned W = 0.92 with a p-value =0.00 indicating the data does not follow a normal distribution.
A skewness score of 1.21 indicates the data are substantially skewed.
Hartigan's dip test score of 0.04 with a p-value of 0.23 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. Census Bureau and U.S. Department of Housing and Urban Development, Monthly Supply of Houses in the United States [MSACSRNSA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/MSACSRNSA, December 15, 2019.
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