Transcript Shade T. Shutters Global Security Initiative Arizona State University

A network approach to understanding
and guiding urban economies
Shade T. Shutters
Global Security Initiative
Arizona State University
Motivation
Kannapolis
- About 38,000 residents
- Predominantly textile factories
- Home of the Earnhardt’s of U.S. auto racing
U.S. State of
North Carolina
Motivation
BIO-TECHNOLOGY!
-
250 acre campus
Research/business “incubator”
$600M from David Murdock
$35M from the city
$400M over 20 years from UNC
To Date:
- No spinoff companies
- 50-60 PhD’s hired – from out of town
- One unsubstantiated patent
- Most firms are part of Castle & Cooke holdings
- Research almost exclusively on “nutraceuticals”
An economic network “map” for cities
First quantify the interdependence between every two occupations
• If interdependence > 0, cities tend to specialize in both or neither
– these occupations complement
j
i
• If interdependence < 0, cities tend to specialize in one or the other
– these occupations conflict
i
j
For the math see Muneepeerakul et al (2013) PLoS ONE 8(9):e73676
Use interdependence values to build a network
•
Nodes are occupations
•
The network is complete,
weighted and undirected
•
Links removed for clarity
•
Proximity is a function of
interdependence
For the math see Muneepeerakul et al (2013) PLoS ONE 8(9):e73676
“Locate” individual cities within that network
Toronto
Halifax
Charlottetown
Locate any labor signature in our network map
Bay City, Michigan, USA
Creative Occupations
Measuring network differences
Bay City
Creative Jobs
Overlap
For detailed math please see Shutters et al (2015) Urban Studies, Online first
Quantified proximity to creative economy
The 10 highest and 10 lowest values of Creative Jobs index C among 364 US metropolitan statistical areas in 2013.
Rank
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
355.
356.
357.
358.
359.
360.
361.
362.
363.
364.
Metropolitan Statistical Area (MSA)
Boston-Cambridge-Newton, MA-NH
Washington-Arlington-Alexandria, DC-VA-MD-WV
San Francisco-Oakland-Hayward, CA
Seattle-Tacoma-Bellevue, WA
Portland-Vancouver-Hillsboro, OR-WA
Los Angeles-Long Beach-Anaheim, CA
Minneapolis-St. Paul-Bloomington, MN-WI
San Diego-Carlsbad, CA
Denver-Aurora-Lakewood, CO
Baltimore-Columbia-Towson, MD
C
0.723
0.715
0.674
0.636
0.630
0.630
0.604
0.602
0.599
0.594
Rome, GA
Madera, CA
Bay City, MI
San Angelo, TX
Goldsboro, NC
Burlington, NC
Punta Gorda, FL
Hinesville, GA
Hanford-Corcoran, CA
Gadsden, AL
0.076
0.073
0.071
0.071
0.065
0.063
0.062
0.058
0.058
0.049
For detailed math please see Shutters et al (2015) Urban Studies, Online first
Quantified proximity to creative economy
Creative
Jobs Index
0.489
0.436
0.410
0.265
0.245
National
Ranking
19
33
41
103
119
Fort Wayne, IN
Evansville, IN-KY
Bloomington, IN
Terre Haute, IN
Lafayette-West Lafayette, IN
0.213
0.197
0.178
0.164
0.137
145
159
189
204
250
Muncie, IN
Kokomo, IN
Elkhart-Goshen, IN
Anderson, IN
Columbus, IN
Michigan City-La Porte, IN
0.117
0.113
0.110
0.098
0.087
0.085
286
289
297
323
341
346
Metro Area
Chicago-Naperville-Elgin, IL-IN-WI
Cincinnati, OH-KY-IN
Indianapolis-Carmel-Anderson, IN
Louisville/Jefferson County, KY-IN
South Bend-Mishawaka, IN-MI
For detailed math please see Shutters et al (2015) Urban Studies, Online first
Using networks to quantify resilience
“Highly integrated systems are inherently
stable [and] show high degrees of resilience”
Dhaka: “lacks the connectedness….needed for
resilience”
resilience ∝ connectedness
Using networks to quantify resilience
“[when] resilience is high….
connectedness is low”
1
resilience ∝
connectedness
Visualize differences in connectedness
Washington, DC
Brunswick, GA
For the math see Shutters, Muneepeerakul, Lobo (2015) Palgrave Communications 1(201510):1-7
100
A
400
B
C
80
60
40
20
10-6
80
Home Purchase Index
Real per capita GDP ($000)
Nominal per capital personal income ($000)
More connected = better when no shocks
60
40
10-4
Tightness T
10-3
100
R = 0.51
10-2
200
20
R = 0.44
10-5
300
0
10-6
10-5
10-4
Tightness T
10-3
10-2
10-9
R = 0.18
10-8
10-7
Tightness T
10-6
10-5
100
A
400
B
40
60
40
10-6
10-5
10-4
10-3
10-5
10-4
A
0
10
0
-10
10-5
10-4
Tightness T
R = 0.18
10-9
10-2
10-8
10-3
10-2
-2
-4
-6
-8
-10
R = -0.21
-12
10-6
10
-5
10
-4
Tightness T
10-7
10-6
10-5
Tightness T
B
R = -0.35
-20
10-6
10-3
Tightness T
Change in employment rate
20
200
100
R = 0.51
0
10-6
10-2
300
20
R = 0.44
Change in Home Purchase Index (%)
20
Home Purchase Index
60
80
Tightness T
Change in per capital personal income (%)
C
80
Real per capita GDP ($000)
Nominal per capital personal income ($000)
More connected = worse following a shock
10
-3
10
-2
20
C
0
-20
-40
-60
R = -0.20
10
-9
10
-8
10
-7
Tightness T
10-6
10-5
More connected = longer recovery time
0.0014
0.0012
Mean Tightness
0.0010
0.0008
0.0006
0.0004
0.0002
0.0000
0
1
2
3
not regained
Years after recession until per capita income = 2006 level
From occupations to industries
Cross-talk between occupations and industries
Locate any labor signature in our network map
Bay City, Michigan, USA
Creative Occupations
Locate any labor signature in our network map
Bay City, Michigan, USA
Industry X
Quantified proximity to advanced industries
Suitability
Bloomington
Evansville
Indianapolis
Terre Haute
Lafayette
Rank
Advanced Industry (NAICS code)
0.96
76
Medical and Diagnostic Laboratories (6215)
0.59
100
Resin, Synthetic Rubber, and Artificial Synthetic Fibers and Filaments Manufacturing (3252)
0.51
103
Basic Chemical Manufacturing (3251)
0.42
105
Pharmaceutical and Medicine Manufacturing (3254)
0.26
109
Research and Development in the Social Sciences and Humanities (54172)
1.25
50
Iron and Steel Mills and Ferroalloy Manufacturing (3311)
1.15
51
Ship and Boat Building (3366)
1.11
54
Clay Product and Refractory Manufacturing (3271)
1.05
59
Foundries (3315)
1.07
60
Other Nonmetallic Mineral Product Manufacturing (3279)
2.40
6
Other Transportation Equipment Manufacturing (3369)
2.17
7
Other Nonmetallic Mineral Product Manufacturing (3279)
2.13
8
Jewelry and Silverware Manufacturing (33991)
1.86
11
Petroleum and Coal Products Manufacturing (324)
2.31
12
Pharmaceutical and Medicine Manufacturing (3254)
0.79
82
Pesticide, Fertilizer, and Other Agricultural Chemical Manufacturing (3253)
0.43
117
Other Chemical Product and Preparation Manufacturing (3259)
0.41
123
Clay Product and Refractory Manufacturing (3271)
0.24
125
Basic Chemical Manufacturing (3251)
0.20
131
Iron and Steel Mills and Ferroalloy Manufacturing (3311)
0.87
72
Motor Vehicle Manufacturing (3361)
0.54
95
Motor Vehicle Parts Manufacturing (3363)
0.58
96
Household Appliance Manufacturing (3352)
0.54
101
Alumina and Aluminum Production and Processing (3313)
0.44
102
Foundries (3315)
Cities as multiplex networks of networks
Exponential effect on
system resilience
See for example, “Catastrophic cascade of failures in interdependent networks”, Nature 464:1025-1028