Table 1 Two-sided Spearman correlations of socio-economic variables for US metropolitan areas with CCT quantities and other segregation measures

From: Quantifying ethnic segregation in cities through random walks

	Diffusion				Moran I		Sp. Gini		Distance decay		Spatial dissimilarity
Soc.-Econ. variables	Δμ	Δϱ	Δσ	${\tilde{\sigma }}_{\langle \Gamma \rangle }$	MI_e[Γ]	MI_〈Γ〉	SG_e[Γ]	SG_〈Γ〉	DDE_〈Γ〉	DDI_〈Γ〉	SD_〈Γ〉	PSD_〈Γ〉	BSD_〈Γ〉
Employment
Employed	0.02	0.71***	0.00	0.33*	0.35*	0.40**	0.09	0.11	0.01	0.35*	0.16	0.16	0.16
Unemployed	0.01	0.44**	0.05	0.27	0.30*	0.73***	0.07	0.05	0.01	0.23	0.06	0.06	0.06
Commuting
Car/truck/van (alone)	0.02	0.71***	0.01	0.35*	0.33*	0.28	0.09	0.10	0.03	0.35*	0.15	0.15	0.15
Public transportation	0.00	0.42**	0.00	0.21	0.29	0.42**	0.16	0.08	0.00	0.16	0.10	0.10	0.10
Walked	0.04	0.73***	0.09	0.45**	0.37*	0.59***	0.16	0.16	0.03	0.52**	0.17	0.17	0.17
Other means	0.00	0.32*	0.02	0.05	0.33*	0.40**	0.01	0.01	0.09	0.33*	0.00	0.00	0.00
Worked at home	0.02	0.25	0.01	0.06	0.42**	0.52**	0.00	0.01	0.00	0.29	0.00	0.00	0.00
Occupation
Management/science/arts	0.00	0.61***	0.00	0.37*	0.39*	0.45**	0.14	0.06	0.00	0.39*	0.09	0.09	0.09
Service	0.01	0.69***	0.01	0.42**	0.32*	0.45**	0.13	0.14	0.02	0.36*	0.16	0.16	0.16
Sales and office	0.04	0.73***	0.00	0.33*	0.32*	0.36*	0.13	0.10	0.00	0.25	0.17	0.17	0.17
Prod./transp./material	0.12	0.44**	0.25	0.28	0.00	0.13	0.02	0.35*	0.00	0.04	0.28	0.28	0.28
Occupation Industry
Retail trade	0.03	0.73***	0.03	0.33*	0.39*	0.56**	0.14	0.10	0.00	0.30*	0.16	0.16	0.16
Finan./real estate/leasing	0.07	0.79***	0.03	0.36*	0.33*	0.45**	0.16	0.13	0.00	0.27	0.22	0.22	0.22
Profe./scient./manag./adm.	0.00	0.40**	0.00	0.19	0.39*	0.42**	0.01	0.00	0.00	0.39*	0.01	0.01	0.01
Edu./health/social care	0.05	0.82***	0.06	0.61***	0.30*	0.56**	0.24	0.21	0.00	0.45**	0.25	0.25	0.25
Arts/entert./accom./food	0.00	0.54**	0.00	0.24	0.33*	0.44**	0.05	0.04	0.00	0.25	0.07	0.07	0.07
Income (USD)
< $10,000	0.10	0.77***	0.12	0.69***	0.08	0.32*	0.37*	0.39*	0.03	0.15	0.42**	0.42**	0.42**
$10,000-$14,999	0.02	0.50**	0.19	0.50**	0.03	0.59***	0.08	0.35*	0.00	0.11	0.29	0.29	0.29
$15,000-$24,999	0.14	0.59***	0.20	0.45**	0.01	0.33*	0.07	0.45**	0.00	0.07	0.40**	0.40**	0.40**
$25,000-$34,999	0.20	0.67***	0.10	0.50**	0.00	0.14	0.10	0.50**	0.01	0.06	0.47**	0.47**	0.47**
$50,000-$74,999	0.05	0.77***	0.01	0.45**	0.24	0.32*	0.20	0.16	0.01	0.23	0.24	0.24	0.24
$75,000-$99,999	0.00	0.65***	0.01	0.39*	0.35*	0.50**	0.16	0.10	0.00	0.30*	0.14	0.14	0.14
$100,000-$149,999	0.01	0.65***	0.00	0.40**	0.36*	0.40**	0.11	0.09	0.01	0.45**	0.11	0.11	0.11
> $200,000	0.01	0.42**	0.00	0.28	0.33*	0.42**	0.02	0.02	0.03	0.47**	0.02	0.02	0.02
Supplementary Security
Social Security	0.01	0.71***	0.06	0.65***	0.19	0.59***	0.28	0.24	0.00	0.24	0.28	0.28	0.28
Cash public assist.	0.00	0.47**	0.04	0.73***	0.06	0.59***	0.17	0.23	0.00	0.19	0.20	0.20	0.20
Food Stamp/SNAP 12m	0.12	0.75***	0.13	0.67***	0.04	0.30*	0.32*	0.42**	0.04	0.10	0.45**	0.45**	0.45**

The spatial heterogeneity, spatial variance, and spatial diversity of a city show a remarkably consistent association with several socio-economic indicators, especially those related to occupation, employment, income, and security. As a result, those indicators, and in particular Δϱ, are good candidates to work as a proxy of socio-economic segregation and of the quality of life of an urban area.
*ρ < 0.1; **ρ < 0.05; ***ρ < 0.01. Actual p-values are reported in Supplementary Table 3.

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Table 1 Two-sided Spearman correlations of socio-economic variables for US metropolitan areas with CCT quantities and other segregation measures

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