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Residential Location
David Levinson
Push and Pull
• Pull - advantages of locating near specific things
• Push - disadvantages of locating near specific things (advantage of locating far from specific things)
Hedonism I
• We seek “pleasure” in deciding where to locate
• Pleasure comprises attributes of structure (house) and location.
• We consider especially location
Accessibility
• A measure that relates the transportation network to the pattern of activities that comprise land use.
• It measures the ease of reaching valued destinations.
• Accessibility “is perhaps the most important concept in defining and explaining regional form and function.” (Wachs and Kumagai 1973)
The Power of Networks
• Top picture: two “markets”: A-B and B-A.
• Middle Picture: six markets: B-C, C-B, C-A, A-C
• Bottom Picture: twelve markets: D-C, C-D, D-B, B-D, D-A, A-D
A B
A B
A B DC
C
Mathematical Expression
S = N ( N-1)S = Size of the
Network:N = Number of
Nodes (places)
• To illustrateWith 2 nodes: S = 2*1
= 2With 3 nodes: S = 3*2
= 6With 4 nodes: S = 4*3
=12. And so on.
Relative vs. Absolute Change
• Do people value the absolute increase (each person I am connected to adds the same value)?
• Or do people value the relative change (I will pay twice as much for a network that is twice the size)?
Law of the Network: Increasing or Decreasing Returns
0
2000
4000
6000
8000
10000
12000
0 20 40 60 80 100 120
N - Number of Nodes
S - Size of the Network
0%
50%
100%
150%
200%
250%
% Increase in S
S % Increase in S
Measuring Point Accessibility
€
Ai = E j f Cij( )j
∑
Where:• Ej = some measure
of activity at point j (for example jobs)
• Cij = the cost to travel between i and j (for example travel time by auto).
Measuring Metropolitan Accessibility
€
A = Wi Ej f Cij( )( )j
∑ ⎛
⎝ ⎜
⎞
⎠ ⎟
i
∑
where: • A = Accessibility
• Wi = Workers at origin i
• Ej = Employment at destination j
• f(Cij) = function of the travel cost (time and money) between i and j.
Network Size vs. Accessibility
Network Size: • All nodes valued
equally• Independent of
type of node• Independent of
spatial separation of nodes
Accessibilty:• Places are not
equal• Places (i, j) are
weighted according to size
• Considers spatial separation of places.
Absolute vs. Relative Accessibility
• A transportation improvement reduces the travel time between two places. What happens?
• The absolute accessibility of the entire region increases. The pie increases
• The relative accessibility of the two places increases at a greater rate than the rest of the region. The slice of the pie going to those two places increases even more.
• Why does this matter?
Network ExternalitiesNetwork Externalities
0
1
2
3
4
5
6
0 1 2 3 4 5 6
Number of Network Members (Quantity Demanded)
Price, Cost
Demand:n=1
Demand:n=2
Demand:n=3
Demand:n=4
Demand:n=*
Revealed Demand
Multi-Modal & Multi-Purpose Accessibility
Mode Jobs Workers Shops OtherAutoTransitWalkBike
Access By Mode & Distance, DC Data
0
10000
20000
30000
40000
50000
60000
70000
80000
90000
0 5 10 15 20 25 30 35
Distance from the center (miles)
Accessibility Index
Access to Jobs by Auto Access to Housing by Auto Access to Jobs by Transit Access to Housing by Transit
Accessibility and Housing Value
Urban Economics suggests trade-off time & money
- finding supported for auto accessibility
- not for transit accessibility
Is Race (Still) an Issue in Transport & Land Use?
• Why?• Why Not?
American Apartheid (Massey & Denton)
• Sources of Racism• Theories:
– Culture of Poverty– Insitutional Racism– Welfare Disincentives– Structural Economic Change (leading to
spatial mismatch)– Spatial Segregation
Segregation
• Self-Segregation– Why would a group self-segregate?
• Assimiliation vs. Melting Pot vs. Salad Bowl
• Segregation when integration is preferred
• Segregation of blacks vs. other minorities.
Segregation & Poverty
• Interaction of segregation and high poverty levels exacerbates problem
• If poverty rates are higher in the segregated group than average, all in the segregated group live a disproportionately poor area.
Dimensions of (Hyper)Segregation
• Unevenness - blacks overrepresented in some areas, underrepresented in others (Dissimilarity)
• Isolation - blacks don’t share neighborhoods with whites (=100 when all blacks live in black only neighborhoods)
• Clustering - black neighborhoods may be clustered (so that they adjoin) (or they may be checkerboard)( = 100 when all black neighborhoods contiguous)
• Centralization- around the urban core, or out in the suburbs. (=100 if all black neighborhoods in urban core)
• Concentration - in a small area, or over a large area. (relative amount of physical space occupied by group = 100 when blacks occupy smallest possible area)
• Measures largely reflect the same phenomenon, but are defined somewhat differently.
Dissimilarity Index
• Where: – Gi = population of group g
in area i – Hi = population of group h
in area i – G = total population of
group g in all areas– H = total population of
group h in all areas
• The higher the more dissimilar (100 = max dissimilarity)
€
D = 0.5GiG
−H i
Hi
∑
The South is Less Segregated
Measure Northern Areas
Southern Areas
Unevenness 80.1 68.3
Isolation 66.1 63.5
Clustering 52.2 30.9
Centralization
88.4 75.3
Concentration
83.3 60.8
Racial Profile of areas in Columbia, MD
Elementary School YearOpen
Capacity Enrollment White(%)
Black(%)
Asian(%)
Hispanic(%)
Other(%)
Atholton 1961 365 496 74.4 15.4 9.0 0.8 0.4Bryant Woods 1968 311 300 41.1 50.9 6.0 1.3 0.7Clemens Crossing 1979 478 609 78.3 11.6 9.1 1.1 0.0Dasher Green 1976 415 411 45.7 46.8 4.6 2.2 0.7Guilford 1954 390 451 52.8 38.6 6.3 2.5 0.0Jeffers Hill 1974 421 459 47.9 36.4 10.3 5.4 0.0Longfellow 1970 396 352 54.2 34.9 6.3 4.2 0.4Phelp's Luck 1972 496 558 33.8 49.2 6.8 10.0 0.2Pointer Run 1991 750 893 69.3 6.6 23.0 0.8 0.3Running Brook 1970 261 252 28.2 48.2 7.2 16.4 0.0Steven's Forest 1972 333 291 58.2 29.1 6.6 5.7 0.4Swansfield 1972 484 551 38.4 44.1 8.5 6.8 2.2Talbott Springs 1973 421 428 29.3 53.1 7.9 9.3 0.4Thunder Hill 1970 346 371 73.1 16.6 9.3 0.8 0.2Waterloo 1964 522 543 64.5 21.8 10.1 3.4 0.2
Total 6389 6965 54.9 30.9 9.8 4.2 0.2
Dissimilarity Index From Columbia, MD (/100)
Dissimilarity Index Elementary SchoolWhite/Black 0.37White/Asian 0.19Black/Asian 0.40White/Hispanic 0.48Black/Hispanic 0.22Asian/Hispanic 0.46Total/White 0.13Total/Black 0.24Total/Asian 0.18Total/Hispanic 0.37
Neighborhood Preference
• How similar should the neighbors be?• E.g. A survey of Detroit found that a
majority of blacks preferred living in a neighborhood that was 50% black,
• Whites on the other hand would prefer a neighborhood more than 50% white.