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Agent-Based Modeling for exploring

Pakistan’s Urban Dynamics

Ammar A. Malik Hilton L. Root

Andrew T. Crooks Melanie Swartz

SWARMFEST 2013

Orlando, FL

Presentation Outline

• Acknowledgement: IFPRI, Pakistan Planning Commission

• The Urban Century

• Role of Creativity in Urban Development

• The Creative City Model

• Experiments: Karachi

• The Next Steps

Percentage of Urban Population by Size, 1960

Source: UN Stats

Source: UN Stats

Percentage of Urban Population by Size, 2011

Source: UN Stats

Percentage of Urban Population by Size, 2025

The Expansion of Cities

• World Urbanization: 50% in 2006, 75% by 2050.

• Every week, more than 1 million people are being added to cities, likely to continue till 2050.

• Problems: global warming, pollution/disease, energy.

• Solutions: crucibles of civilization, avenues for unleashing entrepreneurial energy.

0

50

100

150

200

250

300

1951 1961 1972 1981 1990 2001 2010 2020 2030

Mil

lio

ns

Urban Rural

Pakistan’s Population: Urban vs. Rural

Source: UN-Habitat (2008)

Developing Country Megacities

Population Growth Comparison

0

2

4

6

8

10

12

14

16

18

1970 1980 1990 2000 2010

Mil

lio

ns

Cairo

Beijing

Jakarta

Delhi

Karachi

Source: United Nations

Why Karachi?

• The journey from being the ‘Beirut of South Asia’ to ‘the most violent city on earth’

• “The world’s fastest growing megacity, has grown 80% between 2000 and 2010 to 21m people” (Forbes 2013)

• A microcosm of Pakistan, representation of all ethnicities.

• Produces 20% of national GDP, 25% of national revenues, handles 95% of foreign trade, retains 45% of employment in large-scale manufacturing (ADB 2005)

• Pakistan’s financial and banking hub: hosts 40% of all financial activity and 50% of bank deposits (KSDP 2007)

Creativity & Urban Development

Insights from Literature

• Individual or Social?

• Creative ideas have “novelty, usefulness and surprise” (Simonton 2012)

• Richard Florida’s (2002) “Theory of the Creative Class” o Creative workers, who “draw on complex bodies of knowledge

to solve specific problems” associated with prosperity

o The 3Ts: Technology, Tolerance & Talent

• Human Capital driving long-term economic growth (Barro 2001; Cohen and Soto 2007) o Creative Clusters in cities are formed by free flow of ideas

(Andersson 1985)

New Urbanism

• Density fosters human interactions, “the loci for development” (Glaeser 2011) o Environmental Efficiency

o Education as the “most reliable predictor of urban growth”

o Successful cities attract the poor; they thrive on diversity

• Vibrant Urban Culture & Public Spaces (Landry 2000) o Cultural and physical amenities attract creative individuals

• Jacobs (1961) “Cities happen to be problems in organized complexity, like the life sciences.” o “…the whole is more than the sum of the parts.” (Simon 1962)

o Understanding the macro-level from individual-level interaction

Model Purpose

• An Urban Laboratory for asking what if questions and testing policy ideas.

• To Explain: o The relationship between land-use regulation and creative economy.

o When, where and how creative clusters emerge in cities?

• To Test Policy Scenarios: o What if land-use zones are altered in favor of mixed land-use?

o What if urban mobility or transportation costs change?

o What if income inequality across households improves?

The Creative City Model

The Creative City Model

• Conceptual model built using Netlogo

• Scope of model area representation is a city or urban area

• System behaviors: o Impact attributes of and number of agents in model over time o Restrict or enable where agents can interact with the environment

• Agent behaviors:

o Agents are dynamic and change over time o Interact with other agents o Interact with the environment

• Environment behaviors: o Change over time o Impacted by agents

Individual Agents Income

Tolerance Education

Neighborhood

Environment

Landuse

Neighborhood

Rent

City Level Factors Population growth rates

Brain Drain

Observer Controls Mobility restriction

Development restrictions Segregation / Tolerance

Model Features and Attributes

Model Features and Attributes

Individual Agents

Assigned at the start. When an agent is “inspired” by partnering with a high creative agent in a creative space, the agent can raise a level.

Creativity Level

High Med

Low

Creative Space and Value

Based on frequency of visits by medium and high creative agents. Or, based on creative-density.

Environment

The Creative City Model Flow

el Set up environment (landuse, neighborhoods,

creative space, rent)

Set up agents with attributes (income, education, tolerance,

creativity)

Pop Growth and Brain Drain

Partner/Inspire Creativity

via Interaction

Update Environment Values (Rent,

Creative Space)

Update displays and check interface values

Content and

Satisfied?

Check Satisfaction

Move

yes

no

stay

Update creative value from

frequency visit by med and high creative

Adjust rents

If max creative value, convert neighbor cells

to creative space

Creative space?

Find partner

Get inspired?

Un couple

Is partner medium or

high creative? Is place high

creative value?

Raise Creativity

Environment (affordability,

occupancy, landuse,

neighborhood)

Check tolerance level of nearby

Start Sim

End Sim?

Behavioral Rules Summary

Role Behavioral Rule

Agent Movement Stop when satisfied (based on environment) and

content (based on nearby agents)

Agent Interaction Partnering may lead to increased creativity level

Environment Values

(Density, Rent, Occupancy,

Creative Value)

Based on density/frequency of agent visit

User controls Impact range of movement of agents

User interaction Modify values, change display of environment and

agents based on attributes, query agents

Basic Model Interface

http://malik.gmu.edu/Creativity

Inputs Environment Outputs

Model Outputs

• Allowing development typically increases amount of creative space

• Restricting movement does not have as big an impact as anticipated

• Ability to afford rent in a desired neighborhood and tolerance of the neighbors also have a large impact

Parameter Sweep Findings

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0 10 20 30 40 50 60 70 80 90 100

Cre

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Tolerance Level

Tolerance Level

12.6

12.65

12.7

12.75

12.8

12.85

12.9

12.95

13

13.05

13.1

0 25 50 75 100 200

Cre

ativ

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pac

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Rent Percentage of Income

Rent Percentage of Income

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-10 -5 0 5 10 15

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pac

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Brain Drain

Brain Drain

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10

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18

-10 -5 0 5 10

Cre

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pac

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Population Growth Rate

Population Growth Rate

Parameter Sweep Findings

• Brain drain and population growth have a large impact on ability to support creative spaces, more so than just size of population.

Typical Model Run

http://malik.gmu.edu/Creativity

Application on Karachi

Karachi Experiments

Input Parameters Karachi Values*

Starting Population 1,800

Population Growth Rate 3

Education 50

Brain Drain 5

Percent Highly Creative 15

Tolerance 30

Income(average) / top10 30,000 / 100,000

Average Rent 12,000

Rent Percentage of Income 40

* Karachi values interpolated based on recent Pew Research Study

Experiments*

Movement ON/OFF

Development ON/OFF

Segregation ON/OFF

* Run model for period of 10 years for each combination

Business as usual…

Key Outputs

Today

3 Years

5 Years

10 Years

20 Years

Percent

Highly Creative 10 7 6 3 1

Gini Coefficient 0.67 0.66 0.69 0.72 0.75

Percent

Creative Space 1.8 3.7 6 4.5 4.8

Percent

University Edu. 50 38 32 21 15

Average

Income (Rs.) 37,000 41,165 45,200 55,013 60,394

Percent

Affording Rent 46 45 44 43 45

Karachi Experiments Results

Segregation ON

Rest. Movement OFF Development OFF

(Base)

Rest. Movement OFF Development ON

Rest. Movement ON Development OFF

Rest. Movement ON Development ON

Percent

Creative Space <1 <1 <1 <1

Percent Afford Rent 35 38 38 38

Percent

Creative Population 11.8 12 12 12

Segregation OFF

Percent

Creative Space 2 1 3 1

Percent Afford Rent 46 93 45 92

Percent

Creative Population 12.5 12 13.2 12

Karachi Findings

• Few creative clusters emerge, creative space is very low, as expected.

• Key issues for Karachi: high brain drain and low tolerance.

• Development, or mixed land-use, alone won’t work.

• Smart development strengthening neighborhoods and increasing access to creative places fosters creativity.

• More experimentation, calibration & interpretation!

The Next Steps

• Apply verified theoretical model to Karachi.

• GIS Integration, using R for spatial economic data analysis.

• Empirically grounded behavioral rules, Karachi fieldwork.

• Applying Creative City Model to several real-world cities!

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Agent-Based Modeling for exploring

Pakistan’s Urban Dynamics

amalik8@gmu.edu