Central East Housing and Homelessness Area Network 2010

Modelling Social Housing Need

An Overview of Actors & Factors

Dr. Delwar AkbarSustainable Regional Development Program

Centre for Environmental Management (CEM)

Modelling Social Housing Need - An overview of Actors & Factors

Structure of the Presentation

CQ Region – An Overview SRDP (CEM)’s Expertise in Housing Study Our Engagement in the CQ Region

Example: Bowen Basin Regional Housing Model(s)

Social Housing Need – Provision and Actors Social Housing Need – Factors Proposed Model for Social Housing Need Analysis Questions

The CQ region – An Overview

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The CQ Region – An Overview

Resource Boom and the CQ Housing

Pressure, State, Impact & Response

HOUSING(Quick, Short & Long)

[Social Housing]

Population Dynamics

Social Cohesion & Services Location

Environmental Consideration

Spatial Interaction(Push, Pull & Trade-off)

Behavioural Functions

Economic force (Direct & Indirect &

Flow on)

CQU’s Housing Research

Key areas

Housing Economics Housing Policy and Planning

Market analysis Housing demand forecasting

Non-linear valuation Housing supply analysis

Affordable and Social Housing

Housing policy and planning

Our Engagement in the CQ Region

2010: Non-linear and neural housing demand modelling for the Surat Basin Towns 2010: Housing demand modelling and accommodation impact study for the

Grosvenor Mine Project in “Economic Impact Study of Grosvenor Mine Project”. 2010: Housing demand forecasting and supply analysis for the Coppabella

Underground Mine Project in “Social and Economic Impact Study of Coppabella Underground Mine Project”.

2009: Housing demand forecasting and supply analysis for the Codrilla Mine Project in “Social and Economic Impact Study of Codrilla Mine Project”.

2009: 2009: Housing demand forecasting and supply analysis for the Boulder Steel Project in “Economic Impact Assessment of the Boulder Steel Project”.

2009: Housing demand forecasting and supply analysis for Eagle Downs Mine Project in “Economic Impact Study of Eagle Downs Mine Project”.

2008-09: Assessing Housing and Labour Market Impacts of Mining Developments in Bowen Basin Communities (ACARP Funded Research Project)

Bowen Basin Regional Housing (BBRH) Model

Aim

To forecast housing demand for a long period in the Bowen Basin region

Method

Stage 1: Linear extrapolation of demographic variables and housing

types

Stage 2: Incorporating local variable(s) into the model: changing labour

market and expenditure pattern

Stage 3: Testing the model

Assumptions

Every household has propensity to own/rent a dwelling unit Government initiatives to construct public housing in a certain area or

any emergency situation would not reflect in this model Changing housing preferences due to changes in tastes over time has

not been considered

Example: Bowen Basin Regional Housing (BBRH) Model

The Model

Input: Population by age and sex, family type by age, housing type by family type; cumulative population impacts within the town’s threshold

Process: Linear extrapolation based on 1996, 2001 and 2006 census data; count household size and occupancy rate by family type and % of changes over time; % of change in labour in-migration within the town’s threshold

Output: Household types and dwelling types over a 20-30 year period.

Bowen Basin Regional Housing (BBRH) Model

Application of the model on Moranbah– based on ABS data

10

Housing demand by dwelling type

2006 2011 2016 2021 2026 2031 2036 Change

Separate house 2,031 2,221 1,792 1,842 1,948 1,942 1,938 -93

Semi-detached /townhouse 43 97 121 123 129 128 128 85

Flat/ unit 85 190 229 234 244 243 243 158

Other 208 211 171 155 150 141 135 -73

Total private dwellings 2,366 2,719 2,313 2,354 2,470 2,454 2,443 76

Separate house as % of total 86% 82% 77% 78% 79% 79% 79%

Bowen Basin Regional Housing (BBRH) Model

Application of the model on Moranbah – Incorporating cumulating impacts

Housing demand by dwelling type

2006 2011 2016 2021 2026 2031 2036 Change %

Separate house 2,087 3,185 4,096 4,287 4,391 4,389 4,387 2,300 110

Semi-detached /townhouse 62 194 393 412 422 422 422 360 582

Flat / unit 81 253 563 568 568 558 550 469 575

Other 90 136 194 200 203 202 201 111 124

Total private dwellings 2,320 3,768 5,245 5,467 5,584 5,570 5,560 3,240 140

NPD (including SPQ) 995 2,129 4,237 4,441 4,553 4,553 4,553 3,557 357

Separate house as % of total 90% 85% 78% 78% 79% 79% 79%

Social Housing Provision in the CQ Region

Social housing stock• 508/10,000hh in CQ (except Woorabinda)• Public housing• ATSI housing• Long-term community housing• Local government and affordable housing providers

Social housing clients• Low income (especially in the resource towns)• Centrelink clients (26% in the CQ region compared to 35% in QLD - HS)• Homelessness people (70/10,000p in CQ while 38/10,000p in QLD)

Social housing providers and actors• Churches and Community Organisations (e.g., Anglicare, Roseberry Community

Services)• Co-operatives and Large NGOs (e.g., Emu Park Housing Collective Ltd)• Local Government (e.g., RRC)• QLD Government• Commonwealth Government

Social Housing Need in the CQ Region: Factors

Mining booms and labour market impacts on the regional and rural and resource (3R) towns:

• Higher housing and rental prices• Higher real housing costs for lower income households,• Accommodation costs of split families• Housing affordability to the non-mining labours

Population growth and changing demographic structure Unemployment, Income and wealth gap Seniors and disable persons Family violence, separation and divorce Mobility Aspiration

Social Housing Need: Proposed Model

CQ Social Housing Demand Forecasting Model 1 – Linear

Stage 1: Baseline information structuring (family type by income

and dwelling type by family type)

Stage 2: Identifying and adding cumulative impacts

Stage 3: linear extrapolation of the demographic and housing

variables

Stage 4: Predicting number of social housing need over a thirty

years period

Social Housing Need: Proposed Model

CQ Social Housing Demand Forecasting Model 2 – Non-

linear

Stage 1: Establish relationship among income, occupation

household type and dwelling type (Logit model)

Stage 2: Identifying households for social housing - trend

Stage 3: Applying Monte-Carlo Simulation

Stage 4: Predicting number of social housing need over a

thirty years period

Social Housing Need: Proposed Model

CQ Social Housing Supply Analysis

Existing housing stocks Land availability Approval processes Building costs Availability of builders Institutional arrangements Social benefit-cost analysis

Social Housing – A Key for Regional Sustainability

Plan now – Act immediately

!

Thank You

Questions?

Modelling Social Housing Need - An overview of Actors & Factors