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LEARNING BY SIMULATION LEARNING BY SIMULATION An Urban Laboratory Exercise An Urban Laboratory Exercise in Developing Policy for Low Income in Developing Policy for Low Income Housing Housing in Metropolitan Regions of Developing in Metropolitan Regions of Developing Countries Countries Terrence McGee Terrence McGee UFABC UFABC São Paulo, Brazil São Paulo, Brazil 11-15 April 2008 11-15 April 2008

LEARNING BY SIMULATION An Urban Laboratory Exercise in Developing Policy for Low Income Housing in Metropolitan Regions of Developing Countries Terrence

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LEARNING BY SIMULATIONLEARNING BY SIMULATION

An Urban Laboratory ExerciseAn Urban Laboratory Exercisein Developing Policy for Low Income Housingin Developing Policy for Low Income Housing

in Metropolitan Regions of Developing Countriesin Metropolitan Regions of Developing Countries

Terrence McGeeTerrence McGee

UFABCUFABCSão Paulo, BrazilSão Paulo, Brazil11-15 April 200811-15 April 2008

Background to the Course

► Offered as part of UBC – Brazil Project on Public Consortia and Metropolitan Governance

► Course offers participants an opportunity to learn:

• about low-income housing policy

• to take part in role-playing exercise in developing policy

Course Outline

PART 1: The Urban Transition and the Growth of Metropolitan Regions

PART 2: Housing Metropolitan Populations

PART 3: “Learning by Simulation” – an urban laboratory exercise in developing low income housing solutions

The Inevitability of Metropolitan Growth

PART1

Megacities with 5, 8 and 10 million inhabitants in the year 2000 (Source: UN 2002; Cartography: SPOHNER)

Megacities with 5, 8 and 10 million inhabitants in the year 2015 (Source: UN 2002; Cartography: SPOHNER)

The Policy Context: Challenges of Mega-Urban Regions

► Sustainability

► Livability

► Governance

The Policy Context: Soft & Hard Planning for Mega-Urban Regions

HARDHARD SOFTSOFT

ChallengeChallenge StraightforwardStraightforward Messy (Problematic)Messy (Problematic)

PurposePurpose Problem SolvingProblem Solving Problem StructuringProblem Structuring

OrganizationOrganization HierarchicalHierarchical To be negotiatedTo be negotiated

MethodologyMethodology Logical (Math)Logical (Math) Conceptual ModelsConceptual Models

ResultResult ProductProduct Learning ProcessLearning Process

Poverty in the Urban Context: Changing Conceptual Approaches

► From understanding poverty as “culture” (Lewis) to “deprivation of capabilities” (Sen).

► Breaking down the “space of dualisms”. The Brazilian contribution (Santos).

► Poverty as one dimension of a multi-dimensional approach to targeting low-income populations for the purposes of “adequate housing provision”.

What should a Metropolitan Region be?

► Environmentally sustainable

► Livable

► Inclusive socially and politically

► Economically productive and competitive providing employment

► Cultural identity

What are the types of governance that exist in metropolitan regions?

Relationships between different levels of government: national, state, municipal

► Centralised / Hierarchical e.g. Singapore (city state), China

► Politically decentralized at sub-metropolitan level but formation of sectorial collaboration for example in transportation or service provision, e.g. water

► Metropolitan Regional Authority based on collaborative buy–in of sub-regional political units (e.g. cities) to some form of coordinating charged with Metropolitan Regional Planning. Preparation of Master Plan; Strategic Planning etc. e.g. Vancouver Regional Authority (Metro)

The Challenges of Metropolitan Governance?

► Jurisdictional - intergovernmental cooperation

► Sectorial

► Fiscal

► Including stakeholders

► Implementation mechanisms e.g. consortia

Housing Metropolitan Populations

PART2

The Housing Situation in Metropolitan Regions of

Developing Countries

► Global rhetoric: - Davis, “A Planet of Slums”. - UN Habitat - the ‘right’ to housing

► Shortfalls in ‘adequate’ housing stock. World = 1 billion units (2006)

Defining ‘adequate’ housing

a) Physical:- homeless- sub-standard housing- lack of basic infrastructure

b) The issue of illegality and property rights

c) Household income and housing: poverty and low-income

d) The issue of eligibility and targeting

Land and Housing Markets

a) The Housing Industry: supplier, sellers, developers, buyers

b) Two Housing Markets: formal & informal

c) Ecology of Metropolitan Housing:- Core city: slums, upper class housing, old

established squatter area- Peri-urban: slums, squatters, worker housing,

illegal housing, middle income housing, enclave upper income housing

- Periphery: squatters, illegal housing developments, gated high income housing

Spatial configuration of Asian mega-urban region (circa 2000)

Policies to provide ‘adequate’ housing to low income

populations

► Urban Reform

► Policies- Forced relocation- Subsidized rental public housing- Upgrading- Fiscal policies – ‘enabling’

Learning by Simulation:An Urban Laboratory Exercise

PART3

Signing of Protocol of Intentions, Belo Horizonte, October 2007

Aims

► To develop collaborative action

► To actively engage participants in the process of decision-making

► To develop the capacity of participants to use this ‘learning’ in policy making for urban areas

The Simulation Exercise

► Relies on databases

► Often developed using computer programmes

► But needs ‘interpersonal’ role-playing

Assumptions

► Broad commitment of stakeholders

► Institutional support for low income housing in place - finance

► Involves collaboration between municipalities

► Limited course time means that a simplified outline proposal is needed

► Exercise will focus on relocation of 3 squatter areas

Project Request

► Federal and state government request

► Produce a strategic agenda in developing metro-wide response for provision of low-income housing

► Assume some form of ‘public consortia’

► Produce framework for implementing 3 squatter projects

Issues in Municipal Collaboration

► Disparities in resources of three municipalities

► Different goals of municipalities

► Need to understand spatial and structural features of the metropolitan housing and land market

► Issue of funding

► Multi-dimensional housing policy

The Housing Context of the Case Study

► Three municipalities:(1) Core(2) Peri-urban(3) Periphery

► Three squatter areas:(1) Core(2) Peri-urban(3) Periphery

Metroville: Locations of Squatter Settlements

Context

► Municipality B has land available for housing development

► Municipality A wants to upgrade squatter areas. Needs to relocate 20% squatter HH

► Municipality B wants to relocate squatters from existing site to new housing development

► Municipality C wants to relocate squatters because of environmental and health problems

Squatter Areas

► No. of households offered relocation = 10,000

► No. of households < poverty line = 4400

► No. of households of low & lower middle income = 5600

See Appendices 1 & 2

Aim of Project

1. To offer voluntary relocation to 10,000 squatter households in housing development in municipality B

2. To create ‘incentives’ for all stakeholders that will implement this project

3. To use ‘public consortia’ law to facilitate the project

Organization

1. Organize participants into three municipal-led teams:- A (Core)- B (Peri-urban)- C (Periphery)

2. Each team has representatives from:- Municipal government- Civil society- Private sector

TimetableUrban Laboratory Two (Saturday 12 April)

1. Work in Teams to prepare a ‘position paper’ for each municipality outlining each municipalities’ bargaining position.

2. This will be used as a basis for ‘negotiating’ and agreement between the three municipal teams in the ‘roundtable’ meeting of the three municipalities.

3. If time is available, the ‘roundtable’ will also prepare an ‘outline agenda’ for implementation of the project.

Timetable

Urban Laboratory Three (Monday 14 April)

1. This laboratory will take the form of a roundtable

2. The task will be to produce an outline statement of a Memorandum of Understanding to proceed with the project and draft an Agenda for Implementation

3. Roundtable to be chaired by ‘Mayors’ of each municipality