At Overcoming Bias, Doug argued that the rich tend to be rural despite the image of urban “SWPLs”. That didn’t sound quite right to me, so I decided to check the GSS.

Frequency Distribution
Cells contain:
-Column percent
-Weighted N
SRCBELT
1
12 LRGST SMSA’S
2
SMSA’S 13-100
3
SUBURB, 12 LRGST
4
SUBURB, 13-100
5
OTHER URBAN
6
OTHER RURAL
ROW
TOTAL
W
E
A
L
T
H
1: Less than $5,000 12.8
12.3
17.5
28.8
8.3
17.0
10.5
26.6
12.1
73.1
13.0
21.5
12.0
179.3
2: $5,000 to $20,000 12.5
12.0
14.5
23.9
11.1
22.6
10.2
25.8
12.6
76.4
15.1
24.9
12.5
185.6
3: $20,000 to $40,000 9.8
9.4
14.1
23.2
2.6
5.3
6.6
16.8
9.7
59.0
8.3
13.6
8.6
127.3
4: $40,000 to $75,000 11.7
11.3
11.1
18.4
10.3
21.0
7.2
18.1
8.1
49.1
8.3
13.7
8.8
131.7
5: $75,000 to $100,000 6.5
6.2
7.2
11.9
10.3
21.1
5.6
14.2
6.1
37.2
7.3
12.0
6.9
102.7
6: $100,000 to $150,000 12.6
12.1
4.7
7.7
4.7
9.6
6.9
17.4
8.5
51.3
9.2
15.2
7.6
113.4
7: $150,000 to $250,000 13.4
12.9
9.6
15.9
8.0
16.2
15.1
38.2
13.4
81.4
11.0
18.1
12.3
182.7
8: $250,000 to $500,000 9.7
9.3
15.7
25.9
21.9
44.7
18.9
47.7
16.5
100.2
14.2
23.5
16.9
251.2
9: $500,000 to $1 million 8.4
8.1
4.9
8.0
14.8
30.1
14.7
37.2
9.7
58.6
9.3
15.3
10.6
157.3
10: $1 million to $2 million 1.9
1.9
.5
.9
4.2
8.5
3.5
8.9
2.6
15.7
4.0
6.6
2.9
42.5
11: $2 million to $3 million .0
.0
.3
.4
.9
1.9
.2
.4
.4
2.2
.0
.0
.3
5.0
12: $3 million to $4 million .0
.0
.0
.0
2.3
4.8
.0
.0
.0
.0
.3
.4
.4
5.2
14: $5 million to $10 million .0
.0
.0
.0
.6
1.3
.0
.0
.1
.9
.0
.0
.1
2.1
15: Above $10 million .9
.9
.0
.0
.0
.0
.5
1.3
.1
.9
.0
.0
.2
3.0
COL TOTAL 100.0
96.4
100.0
165.1
100.0
204.2
100.0
252.7
100.0
605.9
100.0
164.8
100.0
1,489.1
Means 5.01 4.42 6.12 5.83 5.28 5.11 5.36
Std Devs 2.83 2.71 3.01 2.91 2.86 2.89 2.91
Unweighted N 95 171 180 229 601 188 1,464
Color coding: <-2.0 <-1.0 <0.0 >0.0 >1.0 >2.0 Z
N in each cell: Smaller than expected Larger than expected
Summary Statistics
Eta* = .17 Gamma = .00 Rao-Scott-P: F(65,2600) = 1.61 (p= 0.00)
R = .02 Tau-b = .00 Rao-Scott-LR: F(65,2600) = 1.54 (p= 0.00)
Somers’ d* = .00 Tau-c = .00 Chisq-P(65) = 114.53
Chisq-LR(65) = 109.10
*Row variable treated as the dependent variable.
Text for ‘WEALTH’

1092. Please estimate your total wealth. IF ASKED: Wealth means 
the value of your house plus the value of your vehicles, stocks 
and mutual funds, cash, checking accounts, retirement accounts 
including 401(k) and pension assets, and any other assets minus 
what you owe for your mortgage and your debts.

I was actually surprised at the rarity of the wealthy in the biggest metropoli.

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