Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/305501 
Erscheinungsjahr: 
2024
Schriftenreihe/Nr.: 
Working Paper No. WP 2024-22
Verlag: 
Federal Reserve Bank of Chicago, Chicago, IL
Zusammenfassung: 
We characterize the dynamics of neighborhood racial composition by using the k-medians machine learning technique to group neighborhoods into five different patterns according to the evolution of the Black population share of census tracts from 1950 through 1990. The procedure classifies tracts into groups that: always have a high Black population share, always have a low Black population share, have a steep increase in the Black population share from 1950-1960, or 1960-1970, and those that have a gradual increase in the Black population share from 1950-1990. We calculate the growth in median rents and home values in each to the five groups and find that those with steep increases in the Black population share show the smallest increases in home values and rent implying that Black households that bought homes in these neighborhoods in 1950 or 1960 were likely to have lost money or barely broken even by 1990.
Schlagwörter: 
Blockbusting
neighborhood dynamics
cluster analysis
housing prices
wealth gap
JEL: 
C38
N22
N92
G21
R23
Persistent Identifier der Erstveröffentlichung: 
Dokumentart: 
Working Paper

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