Mapping Social Indicators for South East Coastal Adaptation project Yogi Vidyattama, Binod Nepal and...
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Transcript of Mapping Social Indicators for South East Coastal Adaptation project Yogi Vidyattama, Binod Nepal and...
Mapping Social Indicators for South East Coastal Adaptation project
Yogi Vidyattama, Binod Nepal and Itismita MohantyThe National Centre for Social and Economic Modelling (NATSEM)
SECA Researchers’ May 2012 Workshop University of Canberra
2
Background
● NCCARF Grant on Coastal urban climate futures in SE Australia. ● need for some economic, social and demographic profiling of
coastal communities from Wollongong to Lakes Entrance● to be considered for further analysis using fieldwork
● The ten communities currently identified● NSW: Wollongong, Batemans Bay, Narooma, Eden, Tuross
head, Bermagui, North Durras, Tathra● Victoria: Lakes entrance, Mallacoota
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Data Sources● ABS Population and Housing Census (2006)
● Age, Gender, Family, Housing Tenure, Employment, Education, Income, Volunteering by Various geographical unit
● ABS National Regional Profile (2009/2010)● Various variable including income (ATO) by SLA
● DEEWR Small Area Labour Market (SALM) data● Unemployment and Labour force participation by SLA (2011)
● Treasury Intergerational Report● Changes in Labour force status by age (2007 and projection)
● DOHA, NSW and Victoria Department of Planning● Population projection by age groups by SLA (5 yearly to 2031)
● PHIDU Interactive Social Health Atlas ● Various Health Indicators (2006,2007/2008) by SLA
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Requested data● Median Income (2011 and 2021)
● Change in Income
● Age/Sex Profile (2011 and 2021)● Change in Age/Sex Profile
● Family Types (2011)
● Unemployment and Youth Unemployment Rate (2011)
● Poverty Rates (2011 and 2021)
● Income Inequality (2011 and 2021)
● Self Assessed Health (2007-08) PHIDU
● Voluntary Work (2006) Census
● Other SpatialMSM Projection
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Spatial Microsimulation
● Definition:● The use of individual characteristic in survey data to do
estimation at Specific Geographical Location● Reweight unit record file from survey data based on the
constraints from Census small area level data– Variables have to be available in both data set
● SpatialMSM● Households record data of 2005-06 and 2007-08 ABS Surveys
of Income and Housing ● Constrained or Benchmark to 2006 Census● Reweighting the households unit record data using GREGWT
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Spatial Methodology : Reweighting Method
turning the national household weights in the SIH 02-03 and 03-04 file into …
… household weightsof small-areas
Unit record
Household ID
Weekly income
Weekly rent
Other variables
Household weight
1 1 7 3 . 10292 2 11 4 . 1573 2 11 4 . 1574 2 11 4 . 1575 3 11 0 . 10036 3 11 0 . 10037 4 10 4 . 708 4 12 4 . 709 6 12 0 . 703
10 6 12 0 . 703. . . . . .. . . . . .
53220 15374 . . . .
15,374,000Num of households in Aust
NSW SLA1
NSW SLA2
NSW SLA3
Other SLAs
0 0 0 .0 0 0 .0 0 0 .0 0 0 .
2.45 13.54 16.38 .2.45 13.54 16.38 .
0 0 0 .0 0 0 .
3.27 0 0 .3.27 0 0 .
. . . .
. . . .
. . . .
12465 25853 27940 .
Num of households in small areas
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Surveys reweighted to following 2006 Census benchmark tables
Number Benchmark Table Level
1 Age by sex by labour force status Person
2 Total number of households by dwelling type (Occupied private dwelling/Non private dwelling) Household
3 Tenure by weekly household rent Household
4 Tenure by household type Household
5 Dwelling structure by household family composition Household
6 Number of adults usually resident in household Household
7 Number of children usually resident in household Household
8 Monthly household mortgage by weekly household income Household
9 Persons in non-private dwelling Person
10 Tenure type by weekly household income Household
11 Weekly household rent by weekly household income Household
Note: SpatialMSM/08C. Most Benchmark Tables contain the total number of persons or households in occupied private dwellings (OPD) except for Table 2 and Table 9. These tables include people in non-private dwellings. People in non-private dwellings include people in prisons, hospitals, aged care facilities, etc
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Projecting SpatialMSM● Projecting age by sex by labour force status benchmark table
● combine SLA-level population projections (to 2027) from the ABS (or State Government Projection) with (national) projections of labour force status from the Treasury’s 2007 Inter Generational Report (IGR) and DEEWR small area Labour force market data
● Projecting the other 10 benchmark tables● obtain the coefficients used to project other benchmark tables
● the population growth in each benchmark table can be projected as
● Increasing income using Tax income from NRP
265
110
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2006
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Issue● Although SpatialMSM could produce data at Urban
Centre or Locality (UCL) unit ● It will largely reflect the projection of the SLA● We use SLA instead
UCL code UCL name SLA code SLA nameUCL139100Wollongong 115058454 Wollongong (C) BalUCL184800Wollongong 115058451 Wollongong (C) - InnerUCL105400Batemans Bay 145152750 Eurobodalla (A)UCL128280Durras (L) 145152750 Eurobodalla (A)UCL176800Tuross Heads 145152750 Eurobodalla (A)UCL159000Narooma 145152750 Eurobodalla (A)UCL107400Bermagui 145150550 Bega Valley (A)UCL172800Tathra 145150550 Bega Valley (A)UCL226400Lakes Entrance 250052111 E. Gippsland (S) - BairnsdaleUCL230600Mallacoota (L) 250052113 E. Gippsland (S) - Orbost
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Result Include all SLAs in NSW and Victoria as comparison
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Result
● We put the result in the interactive map● http://web.natsem.canberra.edu.au/maps/NCCARF/atlas.html● Locally at ACR MAPS\Atlas\atlas.html● may be updated by the end of the month
● Laminated big map● Sample● Based on request
www.natsem.canberra.edu.au