READY SIGNAL CONTROL DATA

Homeownership Rate, Total US (NSA)

Why Use This Data Source In Your Models?

The homeownership rate provides an indication of the percentage of the population that owns as opposed to rents. This gives an indication of the stability of real estate markets as well as economic stability.

Homeownership Rate, Total US (NSA)

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Automated Data Profiling

Ready Signal automatically profiles each data set and offers up suggested industry standard data science treatments to utilize with these data in your models.

Suggested Treatment:

The data shows auto correlation and a non-normal distribution. The data should be differenced. While the Yeo Johnson transformation, provides the best normality, the Order Norm 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.

Source:
U.S. Census Bureau

Release:
Housing Vacancies and Homeownership

Units:
Percent, Not Seasonally Adjusted

Frequency:
Quarterly

Available Through:
12/31/2023

Suggested Treatment:

The data shows auto correlation and a non-normal distribution. The data should be differenced. While the Yeo Johnson transformation, provides the best normality, the Order Norm 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.

Further differencing is reccommended

Trend Analysis:

The Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test, KPSS Trend = 0.23 p-value = 0.01 indicates that the data is not stationary.

Distribution Analysis:

The Shapiro-Wilk test returned W = 0.94 with a p-value =0.02 indicating the data does not follow a normal distribution.

A skewness score of 0.74 indicates the data are moderately skewed.

Hartigan's dip test score of 0.05 with a p-value of 0.48 inidcates the data is unimodal

Statistics (Pearson P/ df, lower => more normal)

No transform
2.33
Box-cox
1.90
Log_b(x-a)
1.90
sqrt(x+a)
1.90
exp(x)
3.08
arcsinh(x)
1.90
Yeo-Johnson
1.68
OrderNorm
1.70

Auto Correlation Function

Auto Correlation Function After Differencing

Partial Auto Correlation Function

Seasonal Impact

Seasonal and Trend Decompostion


Citation:

U.S. Census Bureau, Homeownership Rate for the United States [RHORUSQ156N], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/RHORUSQ156N, December 13, 2019.

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