akbar & greer social housing
DESCRIPTION
Presentation for Internation educators on social housing issues in Central QueenslandTRANSCRIPT
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