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Rowville Rail Project Economic Impact Study
FINAL REPORT
Strategic and Economic Development Division
Knox City Council
May 2012
This report has been prepared for:
Strategic and Economic Development Division Knox City Council
This report has been prepared by:
SGS Economics and Planning Pty Ltd
ACN 007 437 729
Level 5 171 Latrobe Street
MELBOURNE VIC 3000
P: + 61 3 8616 0331
F: + 61 3 8616 0332
W: www.sgsep.com.au
Offices in Brisbane, Canberra, Hobart, Melbourne, Sydney
Table of Contents
Page i of 175
GLOSSARY OF TERMS .................................................................... i
EXECUTIVE SUMMARY .................................................................. i i
Objectives of Study .............................................................................................................. ii
Assessed Economic & Employment Impacts ............................................................................. ii
Estimated Accessibility & Land Use Impacts ................................................................... iii
Estimated Construction and Operation Phase Impacts (Indirect Impacts) .......................... iv
Estimated Wider Economic Benefits .............................................................................. vi
Estimated Environmental Savings ................................................................................. vi
Results Summary ...................................................................................................... vii
Upshot of Findings .............................................................................................................. vii
1 INTRODUCTION .................................................................... 1
1.1 Project in Context ........................................................................................................ 1
1.2 Project Objectives ........................................................................................................ 1
1.3 SGS Response ............................................................................................................. 2
1.4 Assumptions and Limitations ......................................................................................... 3
1.5 Report Structure ......................................................................................................... 5
2 PROPOSED ROWVILLE RAIL .................................................... 7
2.1 Project History and Background ..................................................................................... 7
2.2 Council’s Advocacy Efforts for Improved Transport........................................................... 8
2.2.1 2004 Pre Feasibility Study of the Rowville Rail ................................................... 8
2.2.2 Who’s on Board? Campaign ............................................................................. 9
2.3 2012 SKM Draft Feasibility Study ................................................................................... 9
2.3.1 Proposed Route .............................................................................................. 9
2.3.2 Community/ Stakeholder Consultation ............................................................ 11
2.3.3 Traffic Modelling Method................................................................................ 11
2.3.4 Traffic Modelling Results ................................................................................ 12
2.3.5 Construction and Operations .......................................................................... 13
2.3.6 SKM Study Recommendations ........................................................................ 14
3 BASELINE SOCIO ECONOMIC PROFILE ................................... 15
3.1 Geographical Scope ................................................................................................... 15
3.2 Resident Profile ......................................................................................................... 16
3.2.1 Population, Dwellings and Growth ................................................................... 16
3.2.2 Skills Profile ................................................................................................. 18
3.2.3 Occupation Profile ........................................................................................ 20
3.3 Employment Profile .................................................................................................... 21
3.3.1 Industry Profile ............................................................................................ 21
3.3.2 Employment Growth ..................................................................................... 25
3.3.3 Occupation Profile ........................................................................................ 26
Table of Contents
3.4 Journey to Work Patterns ........................................................................................... 27
3.4.1 Origin and Destination of Workers .................................................................. 27
3.4.2 Travel Mode ................................................................................................. 29
3.4.3 Travel Time ................................................................................................. 31
3.4.4 Accessibility ................................................................................................. 33
3.5 Section Summary ...................................................................................................... 34
4 BASELINE FORECASTS ......................................................... 36
4.1 Population Forecasts .................................................................................................. 36
4.2 Employment Forecasts ............................................................................................... 37
4.3 Section Summary ...................................................................................................... 44
5 STRATEGIC POLICY CONTEXT ............................................... 45
5.1 Metropolitan Policy Context ......................................................................................... 45
5.2 South East Region Planning Context ............................................................................ 45
5.2.1 Melbourne South East Regional Economic Strategy 2009-2030 ........................... 45
5.3 Knox City Council Planning Context .............................................................................. 46
5.3.1 Strengths and Challenges for Knox ................................................................. 46
5.3.2 Opportunities and Actions for Sustainable Growth ............................................ 47
5.3.3 Vision for City of Knox .................................................................................. 49
5.4 Section Summary ...................................................................................................... 50
6 CASE STUDY INVESTIGATIONS ............................................. 51
6.1 Introduction .............................................................................................................. 51
6.2 Short Term Construction Phase Impacts ....................................................................... 51
6.2.1 Australian Experience ................................................................................... 52
6.2.2 International Experience ............................................................................... 52
6.3 Long Term Operational Phase Impacts ......................................................................... 53
6.3.1 Australian Experience ................................................................................... 54
6.3.2 International Experience ............................................................................... 57
6.4 Section Summary ...................................................................................................... 58
7 CONSULTATION FINDINGS ................................................... 59
7.1 Respondent Profile ..................................................................................................... 59
7.2 Consultation Outcomes .............................................................................................. 62
7.3 Section Summary ...................................................................................................... 66
8 ACCESSIBILITY CHANGE ANALYSIS ....................................... 67
8.1 Land Use and Accessibility .......................................................................................... 67
8.2 Accessibility Shifts Model ............................................................................................ 69
8.2.1 Historical Relationship Analysis ...................................................................... 70
8.2.2 Accessibility Induced Land Use Shifts .............................................................. 80
8.3 Anticipated Induced Impacts ....................................................................................... 84
Table of Contents
8.3.1 Households .................................................................................................. 84
8.3.2 Employment ................................................................................................ 88
8.4 Section Summary ...................................................................................................... 93
9 ESTIMATED IMPACTS OF PROJECT ........................................ 94
9.1 Estimation Methodology ............................................................................................. 94
9.1.1 Assumptions and Limitations.......................................................................... 95
9.2 Estimated Impacts of Construction Phase ..................................................................... 96
9.3 Estimated Impacts During Operations Phase ................................................................. 98
9.3.1 Scope and Assumptions ................................................................................ 99
9.3.2 Impacts of Induced Dwellings ........................................................................ 99
9.3.3 Impacts of Induced Employment .................................................................. 104
9.3.4 Total Estimated Impacts of Project Operations ............................................... 108
9.4 Section Summary .................................................................................................... 110
10 WIDER ECONOMIC BENEFITS OF PROJECT............................ 111
10.1 Estimated Environmental Savings .............................................................................. 111
10.2 Estimated Agglomeration Effects ............................................................................... 112
10.2.1 What is Agglomeration ................................................................................ 112
10.2.2 Estimated Productivity Enhancements ........................................................... 113
11 CONCLUDING REMARKS ..................................................... 115
APPENDIX A: SGS POPULATION AND EMPLOYMENT FORECAST
METHODOLOGY ................................................................. 118
11.1 Projection Methodology ............................................................................................ 118
11.1.1 Employment .............................................................................................. 118
11.1.2 Module Description ..................................................................................... 120
11.1.3 Dwellings and Population ............................................................................. 124
11.1.4 Module Description ..................................................................................... 126
APPENDIX B: SURVEY QUESTIONNAIRE FOR SGS CONSULTATION . 131
APPENDIX C: EFFECTIVE JOB DENSITY CALCULATIONS ............... 135
APPENDIX D: SGS METHODOLOGY TO MEASURE AGGLOMERATION 137
11.2 Review of the Evidence on the Nature and Sources of Agglomeration Economies ............. 137
11.3 The Scope of Increasing Returns ............................................................................... 138
11.3.1 Industrial Scope ......................................................................................... 140
11.3.2 Geographic Scope ...................................................................................... 141
11.3.3 Temporal Scope ......................................................................................... 142
11.4 ‘Culture’ and the Transmission of Agglomeration Economies ......................................... 143
11.5 Sources of Agglomeration Economies ......................................................................... 143
Table of Contents
11.5.1 Input Sharing ............................................................................................ 144
11.5.2 Knowledge / Technological Spillovers ............................................................ 145
11.5.3 Labour Market Pooling ................................................................................ 145
11.5.4 Home Market Effect .................................................................................... 146
11.5.5 Consumption ............................................................................................. 147
APPENDIX E: DETAILED INDUSTRY WIDE BREAKDOWN OF INDUCED
IMPACTS .......................................................................... 149
REFERENCES ........................................................................... 152
Table of Contents
List of Tables
Table 1 Estimated Rail Construction Cost of Rowville Line .................................................... 13
Table 2 Growth in Population, 1996-2011 .......................................................................... 17
Table 3 Growth in Dwellings, 1996-2011 ........................................................................... 17
Table 4 Employment by Industry (Workers), 2011 .............................................................. 22
Table 5 Knox (C) Gross Regional Product by Industry, 2011 ................................................ 26
Table 6 Jobs Accessibility by Car and Public Transport, 2011 ............................................... 33
Table 7 Estimated Population Projections, 2011-46 ............................................................. 36
Table 8 Estimated Dwelling Projections, 2011-46 ............................................................... 37
Table 9 Estimated Employment Projections by 1-digit ANZSIC Industry, Knox (C) .................. 40
Table 10 Relative EJD Index, Selected SLAs, 1996-2011 ....................................................... 75
Table 11 Induced Household Changes................................................................................. 85
Table 12 Induced Employment Changes .............................................................................. 89
Table 13 Induced Broad Industry Group Changes 2021 ......................................................... 92
Table 14 Induced Broad Industry Group Changes 2046 ......................................................... 92
Table 15 Estimated Direct Construction Costs of Proposed Rowville Rail .................................. 96
Table 16 Estimated Total Impacts (Direct + Indirect) of Construction Phase of the Proposed Rowville
Line ................................................................................................................... 97
Table 17 Estimated Induced Direct Dwelling Consumption (in 2011$) ................................... 100
Table 18 Impacts of Induced Dwelling Changes in Knox (C) on Knox (C) ............................... 102
Table 19 Impacts of Induced Dwelling Changes in Knox (C) on South East Region ................. 102
Table 20 Impacts of Induced Dwelling Changes in Knox (C) on MSD ..................................... 103
Table 21 Impacts of Induced Dwelling Changes on Victoria ................................................. 103
Table 22 Impacts of Induced Employment Changes in Knox (C) on Knox (C) ......................... 105
Table 23 Impacts of Induced Employment Changes in Knox (C) on South East Region ............ 106
Table 24 Impacts of Induced Employment Changes in Knox (C) on MSD ............................... 106
Table 25 Impacts of Induced Employment Changes in Knox (C) on Victoria ........................... 107
Table 26 Impacts of Project Operations by 2046 ................................................................ 108
Table 27 Estimated Environmental Emissions Savings ......................................................... 111
Table 28 Impact of Project on GVA of Selected SLAs........................................................... 114
Table 29 Estimated Effective Job Density for South East Region ........................................... 135
Table 30 Estimated Relative Effective Job Density for South East Region ............................... 136
Table 31 Total Induced Impacts (by Industry) of Additional Households on Knox (C) Output ($
Million) ............................................................................................................ 149
Table 32 Total Induced Impacts (by Industry) of Additional Employment on Knox (C) Output .. 150
Table 33 Total Induced Impacts (by Industry) of Additional Employment on Knox (C) Employment
...................................................................................................................... 151
Table of Contents
List of Figures
Figure 1 SGS Study Method ................................................................................................ 2
Figure 2 Proposed Route of the Rowville Rail Line ................................................................ 10
Figure 3 Knox and the Surrounding South East Region ......................................................... 16
Figure 4 Education Profile of Residents, 2006 ...................................................................... 18
Figure 5 Education Profile of Residents, 1996 ...................................................................... 19
Figure 6 Residents Field of Study, 2006.............................................................................. 19
Figure 7 Occupation Profile of Resident Workers, 2006 ......................................................... 20
Figure 8 Occupation Profile of Resident Workers, 1996 ......................................................... 21
Figure 9 Employment Share by Broad Industry Category (Workers), 2011 .............................. 23
Figure 10 Knox (C) Employment and Value Added Contribution ............................................... 24
Figure 11 Knox (C) Manufacturing Employment and Value-Added, 2011................................... 24
Figure 12 Employment Growth by Broad Industry Category (Workers), 1996-2011 ................... 25
Figure 13 Occupation Profile of Workers (2006) .................................................................... 27
Figure 14 Destination LGAs of Knox (C) Resident Workers, 2006 ............................................. 28
Figure 15 Origin LGAs of Knox Workers, 2006 ....................................................................... 29
Figure 16 Mode of Travel, Origin of Resident Workers, 2006 ................................................... 30
Figure 17 Mode of Travel, Destination of Resident Workers, 2006 ............................................ 30
Figure 18 Weighted Travel Time of Destination Workers ......................................................... 32
Figure 19 Weighted Travel Time of Resident Workers ............................................................. 32
Figure 20 Industry Structure, Knox (C), 1996 - 2046 ............................................................. 41
Figure 21 Estimated Employment Growth (CAGR %) by 1-digit Industry, 2011-46 .................... 41
Figure 22 Estimated Knox (C) Employment Share in MSD ...................................................... 42
Figure 23 Declared Industrial Nodes, Urban Development Programme, 2010 ............................ 43
Figure 24 Effective Job Density Prior and Following EastLink ................................................... 56
Figure 25 Survey Respondent Profile ................................................................................... 61
Figure 26 Survey Outcome Summary .................................................................................. 64
Figure 27 Demand for Different Land Use as a Function of Accessibility .................................... 67
Figure 28 Effective Job Density MSD - 2006.......................................................................... 73
Figure 29 Relative EJD 2011 ............................................................................................... 76
Figure 30 Relative EJD Regression Coefficients ...................................................................... 78
Figure 31 Household Share Regression Coefficients ............................................................... 79
Figure 32 Change in Relative EJD 2021 ................................................................................ 81
Figure 33 Change in Relative EJD 2046 ................................................................................ 82
Figure 34 Induced Car Mode Share Changes ......................................................................... 83
Figure 35 Household Induced Changes 2021 ........................................................................ 86
Figure 36 Household Induced Changes 2046 ........................................................................ 87
Figure 37 Induced Employment Change 2021 ....................................................................... 90
Figure 38 Induced Employment Change 2046 ....................................................................... 91
Figure 39 Industry-Wide Impacts of Project Construction on Knox (C) Value Added ($ Million) .... 98
Figure 40 Industry-Wide Impacts of Project Operations on Knox (C) Value Added By 2046 ($ Million)
...................................................................................................................... 109
Figure 41 Employment Projections Methodology .................................................................. 120
Figure 42 Overview of Employment Projections Modules ...................................................... 121
Figure 43 Overview of Modules for Dwellings and Population Projections ................................ 125
Table of Contents
Figure 44 SPD to ERP by Age Method Overview ................................................................... 125
Figure 45 RAS Method ..................................................................................................... 129
Figure 46 Identified Employment Regions within Metropolitan Melbourne ............................... 148
SGS Economics & Planning ©
All rights reserved; these materials are copyright. No part may be reproduced or copied in any way form or by any
means without prior permission. The proposals, ideas, concepts and methodology set out and described in this
document are and remain the property of SGS and are provided in confidence. They may not be used or applied
by the recipient without SGS’s written consent.
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. i
GLOSSARY OF TERMS
ANZSIC Australia and New Zealand System of Industrial Classification
CAA Central Activity Areas
CAGR Compounded Annual Growth Rate
Council Knox City Council
DoT Department of Transport
EJD Effective Job Density
GVA Gross Value Added
JTW Journey to Work
LGA Local Government Area
MSD Melbourne Statistical Division
MSE Melbourne’s South East
MITM Melbourne Integrated Transport Model
Project Rowville Rail Project
RFP Request for Proposal
SKM Sinclair Knight and Merz
SKM Study Proposed Rowville Rail Feasibility Study
SGS SGS Economics & Planning
SLA Statistical Local Area
South East Region Combined municipalities of Knox, Monash, Casey and Greater Dandenong
TZ Travel Zone
UDP Urban Development Program
UCL Urban Centre Locality
VITM Victorian Integrated Transport Model
VKT Vehicle kilometre travelled
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. ii
EXECUTIVE SUMMARY
Objectives of Study
The Victorian Department of Transport is currently evaluating the feasibility for a rail line from
Huntingdale to Rowville, a distance of 12 kms. This proposed Rowville rail project is expected to
benefit the residents of Knox and neighbouring municipalities. This area does not currently have
access to the primary public transport network; consequently leading to issues such as constrained
access to economic opportunities, road congestion and excessive levels of greenhouse gas
emissions.
Knox City Council is taking its own actions in support of a positive outcome for the people of Knox
and elsewhere who will benefit from the provision of a modern rail service in their communities. To
understand and support its own advocacy efforts, Council commissioned SGS Economics & Planning
to undertake an economic and employment impacts analysis of the proposed rail on Knox City
Council; the South East Region (comprised of the combined municipalities of Knox, Monash, Casey
and Greater Dandenong); the wider Melbourne Statistical Division; and the State of Victoria.
Assessed Economic & Employment Impacts
SGS assessed and determined the following four impacts of the proposed project with results
shown overleaf:
Figure A 1 Estimated Economic and Employment Impacts
Accessibility & land use impacts(induced impacts on population &
employment)
Construction & operations phases impacts
(Impacts of construction, induced dwellings & employment)
Wider economic benefits(agglomeration & productivity
enhancements)
Environmental savings(due to shorter work trips &
mode shift)
Economic & employment impacts
Direct impacts of project
Indirect impacts of project
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. iii
Accessibility and land use impacts: Additional dwellings and employment that Knox and the
wider South East Region will host over and above the projected Base Case estimates as a result
of improved accessibility provided by the proposed rail. These constitute the direct impacts of
the operations phase of the project.
Construction and operations phase impacts: indirect impacts on the output, value added and
employment of the economies of Knox, the South East Region, the wider metropolis and
Victoria resulting from the initial change in dwellings and employment estimated for Knox at
two examined years – 2021 and 2046.
Wider economic benefits: estimated increase in metropolitan wide labour productivity of
firms due to induced changes in the density of firms; and
Environmental savings: estimated reduction in metropolitan wide greenhouse gas emissions
due to the provisioning of rail in the region, and the consequent reduction in travel time (due to
provisioning of more jobs closer to home) and reduced dependence on cars.
Estimated Accessibility & Land Use Impacts
Projections for the number of dwellings and employment levels were produced by SGS for both the
Base Case and Project Case scenarios. Base Case projections were made using official publications
and in-house modelling. When estimating the Project Case scenario, SGS made the assumption
that the estimated number of dwellings and employment levels across the metropolis would remain
constant. Shifts in households and employment would be observable across the metropolis as
residents and businesses move from other parts of the metropolis into the South East Region
following the improvements in accessibility. Refer to Table A 1 below.
Table A 1 Estimated Changes in Knox (C) Dwellings and Employment Due to
Proposed Project
1996 2011 2046
(Base Case)
2046
(Project Case)
Dwellings 43,200 55,250 71,790 72,820
Employment 60,000 75,000 99,000 100,000
The results suggest that:
Under the Base Case:
o Knox is projected to add approximately 16,000 dwellings over the 2011-46
timeframe hosting approximately ~72,000 households by 2046.
o Employment growth over the 2011-46 timeframe is expected to be just under
25,000 with the municipality hosting a total of 99,000 jobs by 2046.
o Most of this employment growth is concentrated within the commercial services
sector (~1.6% p.a.). In contrast, industrial employment is set to decline over time
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. iv
in line with trends observed for the broader MSD economy. Albeit industrial
employment is set to fall, value creation by the sector is set to continue. The
expected decline in industrial employment is a reflection of increasing productivity
in the sector.
Under the Project Case scenario and in the long run by 2046, when the effects of the Project
would have become fully manifest:
o Knox is likely to host an additional ~1,000 households and ~1,000 additional
employees over and above its projected Base Case of ~72,000 households and
~99,000 employees respectively.
o Approximately 75% of the additional employment over and above the Base Case is
on account of commercial services and 20% on account of industry based
employment (i.e. Manufacturing, Construction, Wholesale Trade etc.).
o The South East Region in turn is likely to host an additional ~1,350 households and
~1,100 additional employees over and above its projected Base Case of ~385,000
households and ~533,000 employees respectively.
While the estimated induced employment within the City of Knox in the Project Case over and
above the Base Case may appear small, it is rather significant; the estimated induced industry
based employment alone (equating to 200 employees) is nearly half the size of the current Ford
manufacturing facility in Geelong. If the existing industry base of Knox can be strengthened further
to have a large iconic manufacturing facility, it will certainly put the municipality on the Australian,
if not the world map.
Estimated Construction and Operation Phase Impacts (Indirect Impacts)
Construction Phase Impacts
The direct and total (direct + indirect) impacts of the construction phase spanning over the four
year construction timeframe of 2016 to 2020 are shown in Table A 2 below.
Table A 2 Estimated Impacts of Construction Phase (Cumulative Over 2016-
2020)
Direct Impacts Total Impacts -
Knox Total Impacts -
Victoria
Output ($ Million) $750 mn $1,665 mn $2,341 mn
Value-Added ($ Million) $173 mn $550 mn $865 mn
Employment (FTE Jobs) 645 3,599 5,600
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. v
Construction of the proposed project is likely to1:
Generate $750 million in direct output and $173 million in value-added, supporting
employment of nearly 650 jobs within the City of Knox.
Due to the industry’s backward and forward linkages, this direct spending and employment
generation is likely to generate a total of $1.6 billion in total output and $550 million in total
value added, supporting nearly 3,600 jobs within the Knox economy.
Support nearly 5,600 total jobs in the State of Victoria creating nearly $2.4 billion in total
output and $870 million in value added2.
Operations Phase Impacts
The estimated induced household changes and employment changes in the region over and above
the Base Case will increase the direct local expenditure in the Knox economy, which will flow
through to other sectors of the economy via economy wide linkages. The estimated induced
changes will in turn also impact expenditures in the South East Region, MSD and the Victorian
economies, because of the linkages of the Knox economy with these wider economies via
purchase/ sales. These impacts are shown in Table A 3.3
Table A 3 Estimated Impacts of Operations Phase at 2046
Direct Impacts Total Impacts –
Knox Total Impacts -
Victoria
Output ($ Million) $270 mn $440 mn $650 mn
Value-Added ($ Million) $140 mn $230 mn $320 mn
Employment (FTE Jobs) 950 1,570 2,160
1 Note that these impacts are based on the assessed direct construction stimuli in the Knox economy only, i.e.
$750 million. A larger bulk of the construction costs are likely to be spent in Monash due to the route alignment
of the proposed rail.
2 By their very scope, the estimated direct stimuli for each assessed region are equal. Because of the relatively
wider inter-linkages of metropolitan and Victorian economies compared to the Knox and South East Region
economies, the assessed indirect (and consequently, total) impacts for these former set of economies is larger
compared to those assessed for the municipality and its surrounds.
3 It should also be borne in mind that the assessment presented here only considers the impacts of the induced
changes within the City of Knox on its own regional economy and the wider economies of the South East
Region, the MSD and Victoria. A net assessment of the combined effects of the induced positive changes in
Knox and corresponding induced negative changes elsewhere (due to detractions of households and
employment away from these metropolitan locations into the South East Region) is beyond the scope of this
study due to unavailability of region specific multipliers across the MSD.
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. vi
By 2046, total effects of the operations of the proposed rail (including the effects of increased
household spending and new employment) were estimated to be:
$270 million in direct income and $140 million in direct value added for the City of Knox,
supporting nearly 950 jobs.
Due to the industry’s backward and forward linkages, this direct spending and employment
generation is likely to generate a total of $440 million in total output and $230 million in total
value added, supporting nearly 1,600 jobs within the Knox economy.
Victorian output and value-added created would be nearly $650 million and $320 million
respectively, supporting employment for nearly 2,200 employees.
Estimated Wider Economic Benefits
Over and above the estimated direct and indirect impacts, the reorganisation of employment across
the metropolis due to improved accessibility in Knox and surrounds will increase productivity of
firms throughout the metropolis. This is because, as more economic activity starts to concentrate
in the South East Region following the opening of the proposed rail line, firm and worker interaction
and their accessibility to suppliers, customers and labour markets will increase. The net effect
(even after accounting for the fall in employment in other metropolitan locations as employment is
detracted from these locations) is estimated to be positive and significant.
Labour productivity enhancements, i.e. an increase in Gross Value Added of the South East Region,
resulting from the project were estimated at $23 million in 2021 and increasing to $133 million by
2046. This will be a significant boost to the resilience of the local economy and community.
More importantly, wider economic benefits of a similar magnitude (if not higher) are likely to
continue annually as more employment and firms move in the South East Region.
Estimated Environmental Savings
SGS estimated environmental savings by estimating the overall travel distance saving across the
metropolis between the Base Case and Project Case scenarios. These savings arise due to the
following two counts, both of which reduce the dependence on car travel:
Due to the provisioning of rail, work and leisure trips by private vehicles are substituted in
favour of public transport.
As more dwellings and employment is induced within the South East Region, resident workers
of Knox and the South East Region are able to access more jobs in close proximity rather than
travelling further for work.
SGS estimated that the distance savings equate to an annual reduction in externality costs of $3.1
million at 2021 and $4 million by 2046. The scale of these savings appears small, and indeed is. It
is because the travel modelling by SKM indicates only a less than 1% mode shift in favour of public
transport from car use once the proposed Rowville rail line becomes operational.
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. vii
Significantly, Savings of a similar magnitude (if not higher) are likely to continue annually as more
people start using public transport over car use.
Results Summary
The SGS study shows that delivering the rail project will lead to several beneficial economic and
employment impacts for Knox, Melbourne’s South East and the Victorian economies.
First and foremost, construction of the rail line (only the section within Knox) is likely to support
nearly 5,600 total jobs in Victoria due to the backward and forward linkages of the construction
industry.
Secondly, the operational phase of the project is likely to contribute $320 million towards the
state’s value-added contribution by 2046.
However, as stated before, these estimated economic impacts only consider the impacts of the
induced changes within the City of Knox on its own regional economy and the wider economies of
the South East Region, the MSD and Victoria. A net assessment of the combined effects of the
induced positive changes in Knox and corresponding induced negative changes elsewhere (due to
detractions of households and employment away from these metropolitan locations into the South
East Region) is beyond the scope of this study due to unavailability of region specific multipliers
across the MSD.
Nonetheless, the wider economic benefits and estimated environmental cost savings have been
assessed taking into account the redistribution of population and employment across the
metropolitan economy. Aggregating annual environmental savings and wider economic benefits
over a 50 year timeframe from 2021 onwards yields a cumulative benefit to the Victorian economy
of over $5 billion to the Victorian economy, which is well above the $2.89 billion towards
constructing the project. Whilst a benefit cost ratio cannot be ascertained from these values (as
they are not net present values), it helps provide some indication of the magnitude of benefits
compared to costs.
In other words, the opportunity costs of not delivering the project are high; not only will the
economies of Knox and the South East Region lose out on the estimated impacts during the
construction phase, Victoria in turn stands to lose out on approximately $5 billion in environmental
and economic savings over a 50 year timeframe.
Upshot of Findings
These findings suggest that the proposed Rowville rail project will:
Help accelerate the growth trajectory of Knox and Melbourne’s South East. While not a
dramatic impact, the shift in dwellings and employment towards Melbourne’s South East does
begin to help to reshape the economic geography of South East Melbourne more in favour of
Knox.
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. viii
Enable the city of Knox to meet is stated vision and objectives of: consolidating the existing
industry base and provide for a well-networked, informed and knowledge intensive business
community in the City of Knox; and providing for more employment and housing opportunities
for the people of Knox. The project will reduce the vulnerability of Knox residents to future
economic shocks and the impacts of structural adjustment within the economy.
Lead to significant economic benefits not only for the local Knox and south East economies, but
for the wider metropolitan and Victorian economies.
Be vital to delivering significant and further productivity enhancements to Victoria. Victoria and
Australia, like most developed economies are at the frontier of productivity due to the
availability of skilled and well-trained workforce as well as established technology. Further
significant enhancements are possible only due to connectivity improvements brought about by
transport projects, which this project will deliver and consequently, help lift the economic
productivity of metropolitan firms.
In the absence of any intervention, there will be a high requirement for the people of Knox and the
wider South East Region to travel outside of their municipality boundaries to access employment
opportunities. The reliance on the private vehicle for accessibility to jobs and services will heighten
the vulnerability of the residents to congestion and fuel price increases. more importantly, the state
would also not be able to capture the suggested environmental and wider economic benefits that
the project will engender.
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 1
1 INTRODUCTION
1.1 Project in Context
The Victorian Department of Transport (DoT) is currently evaluating the feasibility for a rail line
from Huntingdale to Rowville, a distance of 13 kms. This proposed Rowville rail project is expected
to benefit the residents of Knox and neighbouring municipalities - an area which does not have
direct access to the heavy rail network. This has implications for the economic and social prosperity
of the area, road congestion and greenhouse gas emissions.
Sinclair Knight and Merz (SKM) has been commissioned by the DoT for the “Proposed Rowville Rail
Feasibility Study”, in association with Mott MacDonald, Hassell and Phoenix Facilitation. This study
(SKM study) will be conducted in two phases across two years – 2011 and 2012, with the first
phase report having been released in March 2012. SGS Economics & Planning (SGS) understands
that the feasibility study undertook extensive consultation and research to evaluate a number of
transport options and associated construction programme. However, the first phase report released
in February 2012 assessed likely demand for only one of the most feasible considered options.
Section 2 of this report describes the project in greater detail.
1.2 Project Objectives
Knox City Council is taking its own actions in support of a positive outcome for the people of its
municipality and elsewhere who will benefit from the provision of a modern rail service in their
communities.
In addition to the transport analysis being undertaken by SKM, Council decided to undertake an
economic and employment impacts analysis of the overall Project. With this in mind, Council issued
a Request for Proposal (RFP) with the following objectives:
Define and estimate the economic and employment impacts, (direct and indirect), that could
reasonably arise from the Rowville rail project on:
o The City of Knox;
o The City of Monash to the west, and the immediately adjacent areas of the cities of
Casey and Greater Dandenong to the south east and south respectively
(collectively termed as the ‘South East Region’ for the purposes of this report;
and
o The wider Melbourne Statistical Division (MSD) and the State of Victoria.
Provide comprehensive evidence and argument for the economic and employment impacts
identified in this study to assist Council in its advocacy activities.
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SGS Final Report – May 2012 P. 2
1.3 SGS Response
SGS was chosen as the preferred bidder and its response to the project objectives is summarised
below in Figure 1 and involved the following five stages:
Figure 1 SGS Study Method
1. Stage 1: Initialising the project at an inception meeting followed by SGS preparing a work plan
to respond to the tasks.
2. Stage 2: A desktop review which included:
o Preparation of a baseline socio-economic profile and review of the current journey
to work (JTW) patterns of Knox, with a specific focus on Rowville, to understand its
current role and performance. This profile was benchmarked against the wider
South East Region (comprising the municipalities of Knox, Monash, Casey and
Greater Dandenong) and the whole metropolitan area (i.e. the MSD).
o Development of baseline population and employment projections, out to 2046, for
Knox and the South East Region, to articulate, at a fine grained level (that of a
Statistical Local Area), the region’s development trajectory ‘without’ the Project.
o Examination of case studies from Australian and international jurisdictions to gain
an appreciation of the impacts of major transport projects on population and
employment in host regions of such projects.
o Reviewing the outputs/ inputs and assumptions used by the SKM study, in
particular, the travel time matrices ‘with’ and ‘without’ the Project out to 2046 and
the route alignment of the considered option.
o Concluding the desktop review with a Workshop with Council about the:
Lessons learnt from the socio economic profile.
Stage 1: INCEPTION
Inception meeting
Finalise work plan
Stage 2: DESKTOP REVIEW
Case study review
Prepare baseline profile and projections
Stage 3: CONSULTATION
Finalise questionnaire
design
Stakeholder workshops
Stage 4: ECONOMETRIC
ANALYSIS
SGS in-house accessibility modelling
Workshop with client
Input output modelling
Stage 5: IMPLICATIONS &
REPORTING
Draft report
Client presentation
Final reportSKM 1st stage report review
Workshop with client
Estimate impact on income,
employment, EJD and GHG
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Land use impacts (i.e. population and employment at a small area level of
a Statistical Local Area (SLA) level out to 2046 ‘without’ the project, based
on SGS’ in house forecasting techniques.
3. Stage 3: preparation of a questionnaire for discussion/ consultation with regional industry
stakeholders to gain insights regarding how the Project might reshape development patterns in
Knox and the South East Region. Thoughts on short-term nuisance impacts created during the
construction phase of the Project were also gauged.
4. Stage 4: Use of SGS’ in house accessibility modelling to quantify the movement of population
and employment to and within Knox and the South East region caused by the Project. That is,
ascertaining the direct impacts of the operational phase of the Rowville rail project. The
methodology and estimated results were workshopped with Council and feedback sought.
Further, insights gained from the above tasks were converted into an assessment of the
economic and employment impacts that are likely to arise from the Project, both during the
construction and operation phases of the project. This included:
o an assessment of both the direct and indirect impacts on output, employment and
value-added using the REMPLAN input-output model of the construction and
operation phases of the project.
o Estimating changes in Effective Job Density (EJD) for the MSD associated with the
delivery of the Project. This helped measure the wider economic benefits of the
Project.
o The associated changes in greenhouse gas emissions (GHG) and mode share shifts
providing an indication of the environmental savings brought about by the Project
on a metropolitan scale.
5. Stage 5: Finally, findings from all the above tasks were brought together in a Draft report
which was presented to the Council for review and comment. Following the delivery of the Draft
report, SGS presented key findings to Council and sought feedback, which was incorporated
into this Final report.
In sum, the five stages shown above respond to the project objectives of Council in full. The first
three stages provide the background contextual and strategic information as well as employment
and population forecasts which are used to inform both Stages 4 and 5. Stage 4 responds to the
first critical objective of the study (i.e. it defines and estimates the direct and indirect economic
and employment impacts of the project. As part of this assessment, SGS estimated the wider
economic benefits of the project which provide a comprehensive evidence base to assist Council in
its advocacy activities.
1.4 Assumptions and Limitations
Before presenting the estimated results in the following sections, the major assumptions/
limitations of these results are outlined below. Other model specific assumptions are outlined in the
relevent sections.
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Accessibility and land use change modelling as well as the estimation of wider economic
benefits is based on travel time matrices data provided to SGS by SKM. We understand that
these data are based on the Department of Transport’s Victorian Integrated Transport M<odel
(VITM). Whilst this model uses established techniques to estimate travel demand, it is subject
to certain limitations. For instance, the transport model assumes way any capacity constraints
on public transport. Consequently, the results produced by this study are also subject to the
same limitations as are inherent in VITM modelling.
When estimating the direct impacts of the operations phase of the project, i.e. when estimating
accessibility and land use change due to this project:
o The overall level of households and employment in metropolitan Melbourne was
held constant between the Base Case and Project Case, i.e. the ‘with’ and ‘without
project’ scenarios. That is, the accessibility and land use change analysis effectively
re-distributes households and employment across metropolitan Melbourne in favour
of Knox and Melbourne’s south-east from other locations within the MSD. In
summary, the assumption suggests that whilst this project is expected to
accelerate growth within Knox and Melbourne’s South East, it is not a trajectory
shifting project inasmuch as inducing net additional households/ employment in the
State of Victoria.
o The distribution of people and firms is purely based on the induced effects of
improved accessibility. While not captured in this analysis, in addition to these
impacts, there can often be one or more targeted intervention developments near
key locations (i.e. new stations) that may further capitalise on the improved
accessibility of the corridor.
When estimating the impacts of the construction phase of the project, we were unable to
estimate the proportion of inputs that will be sourced locally as against from inter-state/
overseas. Consequently, we have estimated that all employment generated due to construction
will be sourced locally from Knox, which indeed overstates the estimated impacts within the
Knox and south East economies. The extent of overestimation on the Victorian economy is
likely to be small, as most inputs and employment for the project is likely to be sourced from
Victoria.
Because of the imposed constraint on the number of households and employment across the
MSD in both Base and Project case scenarios, an increase in the estimated number of dwellings
and employment levels in favour of Knox and the South East Region causes a reduction in
dwellings and employment elsewhere in the metropolitan economy. When estimating the
induced effects of the operations phase of the Rowville rail project, the assessment considers
the impacts of induced changes within the City of Knox on its own regional economy and the
wider economies of the South East Region, the MSD and Victoria. A net assessment of the
combined effects of the induced positive changes in Knox and corresponding induced negative
changes elsewhere is beyond the scope of this study due to unavailability of region specific
multipliers across the MSD.
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1.5 Report Structure
This report is organised as follows:
Section 2: Discusses in brief the outcomes of the pre-feasibility and feasibility studies that
have been undertaken to date for a rail line from Huntingdale to Rowville. In
particular, the outcomes of the SKM study, Stage 1 report and the DoT’s Project
Scope reports are reviewed.
In addition, key findings and lessons that were gleaned from Council’s own
advocacy efforts to date in support of the Project are highlighted.
Section 3: Provides a baseline socio-economic profile and reviews the current JTW patterns
for Knox, with a specific focus on Rowville, to understand its current role and
performance in the municipality and the wider South East Region. This profile is
compared and contrasted against the wider South East Region and the MSD.
Section 4: Presents the results of SGS’s in house baseline population and employment
projections, out to 2046, for the City of Knox and the South East Region, to
articulate, at a fine grained level (that of a SLA), the region’s development
trajectory ‘without’ the Project. These projections were finalised by SGS after
workshopping with Council.
Section 5: Showcases the existing State and local strategic planning framework supporting
multi-modal and more sustainable modes of transport provision. A specific focus is
cast here on the support for high employment growth within Knox and its
immediate surrounds. The capacity of Council to accommodate this growth, i.e.
land supply and any constrains thereof are also identified.
Section 6: Reviews relevant case studies from Australian and international jurisdictions to
assess the short, medium and long-term impacts on residents and businesses
during the construction and operation phases of a major transport project.
Section 7: Reports insights gained from consultation with regional industry stakeholders on
how the Project might reshape development patterns in Knox and the South East
Region.
Consultees views on short-term nuisance impacts created during the construction
phase of the Project are also showcased.
Section 8: Presents the results of SGS’ in house accessibility modelling to quantify the impact
of the Project on the additional population and employment that Knox and the
South East region might host because of the Project over and above that which
would become manifest in a ‘Business As Usual’/ Base Case scenario.
In effect, the outcome of this section is the estimate of the ‘direct’ impacts of the
Project on the City of Knox during the operation phase of the project.
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Section 9: Presents the estimated economic and environmental impacts of the Project on
Knox, the South East Region and the wider metropolitan economy.
The estimated impacts include the direct and indirect impacts on income, value-
added and employment, both during the construction and operation phases of the
Project and environmental savings brought about by a reduction in greenhouse
gas emissions.
Section 10: Showcases the wider economic impacts via improvements in productivity
improvements to the whole metropolitan economy due to improvement in rail
services brought about by the Project.
The results of this analysis, it is hoped, will particularly help Council in its
advocacy efforts with Treasury, as this section highlights the advantages of a
transport project of a local scale on productivity improvements that might become
manifest at the metropolitan level.
Section 11: Provides concluding remarks.
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2 PROPOSED ROWVILLE RAIL
This section discusses in brief the outcomes of the pre-feasibility and feasibility studies that have
been undertaken to date for a rail line from Huntingdale to Rowville. In particular, the outcomes of
the SKM study, Stage 1 report submitted to the Victorian DoT are reviewed.
In addition, key findings and lessons that were gleaned from Council’s own advocacy efforts to date
in support of the Project are highlighted.
Victoria has witnessed relatively few new major rail transport infrastructure improvements over the
past decades, including the City Loop opening in the 1980s and more recently the Altona-Westona
link (extended to Laverton to form a loop). In addition, new routes (Cranbourne and South Morang
extensions and the Regional Rail Link4) have been added to serve changing needs.
The Melbourne Metro proposal (a new rail tunnel beneath the city, linking the western suburbs lines
at South Kensington with the Dandenong, Frankston and Sandringham lines at South Yarra) are
expected to enable further growth in rail services through central Melbourne as the City Loop
reaches capacity.
2.1 Project History and Background
The proposed Rowville rail extension was first proposed in the 1969 ‘Melbourne Transportation
Plan’, with the aim of improving transport linkages to the areas of Monash University, Waverley
Park, Stud Park and Rowville. The plan showed a rail line via Rowville and Knox from Huntingdale
to Ferntree Gully as well as City-East Doncaster and Frankston-Lyndhurst links and the City Loop.
While the proposition did not proceed beyond the planning phase, the concept has remained in the
public transport realm ever since.
Completed in 1998, the ‘Scoresby Transport Corridor Environmental Effects Statement’ revisited
the need for public transport in the Rowville area. Different options in the form of light rail or bus
rapid transit service were also conceptualised. This study ultimately went on to prefer a road
option, the Scoresby Arterial Road (now EastLink) and the option of more public transport was
discounted again (Department of Transport, 2011).
4 The Regional Rail Link is currently under construction.
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2.2 Council’s Advocacy Efforts for Improved Transport
2.2.1 2004 Pre Feasibility Study of the Rowville Rail
In 2004, Council commissioned an independent pre-feasibility study for the Rowville rail extension.
This Study estimated a single track line at $413 million, with an additional $66 million for rolling
stock (Russell et al, 2004). The then developed concept was for a single track line, mostly on a
viaduct in the median of Wellington Road and with passing loops at the Monash and Waverley Park
station locations, catering for 15-minute peak period service headways. The study concluded that a
Rowville line with 4 services per hour would yield the following benefits:
A reduction in public transport travel time to the centre of Melbourne, from around 80 minutes
to 30 minutes;
Improved public transport travel time to higher education institutions (notably Monash
University), employment (particularly in the Monash corridor), and leisure and entertainment
venues;
Reduced demand for car parking at Monash University, with up to 1,000 car journeys to the
university estimated to be replaced by train journeys;
Enhanced ability for the Rowville activity centre to attract and retain retail and employment
opportunities;
Improved attractiveness of the region for residents;
Reduced traffic congestion; for work trips the line was estimated to carry 2,350 passengers an
hour, which equates to an equivalent reduction in car traffic numbers;
With extended transport choice, potential avoidance of purchase of an additional car by Knox
households;
Direct and indirect economic and employment generation; and
Protection against increasing travel costs, particularly escalating costs attributed to the
consumption of oil in motor cars.
Following the release of the pre-feasibility study, community enthusiasm and Council advocacy
escalated; however the project was not cited in the 2008 Victorian Transport Plan. Nonetheless,
Council continued to advocate its efforts for a rail line, and conducted the ‘Who’s on Board?’
campaign to advocate for the Rowville Rail and the Knox Tram projects.
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2.2.2 Who’s on Board? Campaign
In November 2010, Council developed the
campaign “Who’s on Board?”, aimed at
promoting two major public transport
infrastructure projects in the Knox region; the
Rowville rail extension and the Knox Tram
(Knox City Council, 2011). Postcards
containing project information were sent to all
residents within the municipality, and
dedicated web links were provided on Councils
website to advocating local and state
government members in support of public transport improvements in the region. In total over
4,500 postcards were returned to Council as a sign of support for the two projects (Knox City
Council, 2011).
2.3 2012 SKM Draft Feasibility Study
In February 2011, the Minister for Public Transport announced the Rowville Rail Feasibility Study
(Department of Transport, 2011). This study is expected to be finalised by 2013, and is being
conducted by Sinclair Knight Merz (SKM) in collaboration with Mott MacDonald, Hassell and Phoenix
Facilitation. The study is an “investigation of a 13 kilometre rail line between Huntingdale railway
station and Rowville”, that will “include engineering, architectural and operational investigations as
well as extensive consultation with the public” (Department of Transport, 2011). The trigger to
explore such projects, as stated by the Department, is Melbourne’s continued and sustained
population growth.
This study (SKM study) will be conducted in two phases across two years – 2011 and 2012, with
the first phase report having been released in March 2012. The SKM study undertook extensive
consultation and research to evaluate a number of transport options and associated construction
programme. However, the first phase report released in February 2012 assessed likely demand for
only one of the most feasible considered options. The following sections summarise the results of
the SKM study.
2.3.1 Proposed Route
The proposed route for the Rowville rail extends from Huntingdale station on the Cranbourne and
Pakenham lines, running along Wellington Road to Rowville, i.e. passing through the municipalities
of Monash and Knox.
The proposed route would be double tracked and approximately 13 kilometres in length, and
follows the central median of North Road and Wellington Road from Huntingdale to Stud Road, then
turns north to terminate at Stud Park. A secondary 12 km route option was also analysed running
along Wellington Road with a station at the corner of Stud and Wellington Roads.
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Four new stations are expected to be provided at Monash University, Mulgrave, Waverley Park and
Rowville, with the possibility of a fifth in the vicinity of EastLink (Figure 2 overleaf). The proposed
stations at Monash University and Rowville are expected to be premium stations.
The rail line would link into the Dandenong line at Huntingdale; then run along the North
Road/Wellington Road corridor past Monash University, Mulgrave, Wheelers Hill and Waverley Park
to Rowville. Ultimately, train services on the Rowville line would run to and from central Melbourne,
thus reducing the need for passengers to change trains.
Figure 2 Proposed Route of the Rowville Rail Line
Source: SKM et al, 2012
The design contained in the feasibility study is intended to avoid any new level crossings, and also
preserve the existing road environment with as little traffic impact as possible. The route would
consist of a tunnel or retained cutting at the western end (from Huntingdale to Monash University),
before emerging onto a viaduct over Blackburn and Springvale Roads and return to road level
across the Monash Freeway. It would go into a tunnel again past Waverley Park, and onto an
elevated structure as it crosses the Dandenong Creek Valley and EastLink. East of EastLink, the rail
route would again go below ground, turning north and in tunnel beneath Stud Road to a station at
Stud Park.
The recommended station at Stud Park by the feasibility study would be best located underground
just north of the existing Stud Park Shopping Centre (south of Sam’s Warehouse). Redevelopment
opportunities could provide a bus interchange and surrounding transit-oriented development.
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2.3.2 Community/ Stakeholder Consultation
SKM engaged the Knox community when developing its draft report. As part of this consultation
process the SKM team conducted three community workshops in July of 2011, with approximately
130 people in attendance. The main themes that arose from these workshops was the community’s
concerns for the generally poor level of public transport in the area; the need to preserve the
area’s character and amenity; and the need to further boost the employment prospects of the
area.
SKM reported that there was “very little opposition” to the project. Nonetheless, some other
concerns were noted as follows:
Concern over potential amenity impacts, including noise, visual impacts and vibrations;
Questions over the impact train stations may have on property values and security;
The alternative options to heavy rail, such as light rail or buses which may offer better value
for money; and
Questions over the possibility of future extensions beyond Rowville, e.g. to Ferntree Gully or
Lysterfield (SKM et al, 2012).
In addition to these workshops, the SKM team also conducted an online survey to gauge
stakeholder’s expectations on the level of engagement; preferred methods of communication; and
the nature of the project.
The upshot of these campaigns and survey responses is that the Knox community wants to be
engaged at every step of the process and showcases strong support for the project.
2.3.3 Traffic Modelling Method
The SKM study assessed the travel demand effects of the proposed Rowville rail line using the
Victorian Department of Transport’s Victorian Integrated Transport Model (VITM) and the
consequent effects on travel demand and road traffic.
The model includes representation of the land use (population and employment), roads and public
transport networks in and around the MSD. The model uses established techniques to estimate
travel demand, mode choice and route choice before ‘assigning’ the travel to the transport network
to provide estimated volumes of people and vehicles.
The following aspects of traffic modelling undertaken by the feasibility report are noteworthy:
Traffic modelling was undertaken for two future years: at 2021 and 2046. Key forecasts were
sourced from the Victoria in Future (VIF) 2008 publication released by the Victorian
Department of Planning and Community Development. Though, these forecasts are subject to
change with the new metropolitan planning strategy underway, They include most of the
expected ‘business-as-usual’ development in the area (including significant growth at Monash
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University Clayton campus). The modelling considers future relative changes in key variables
like fuel prices, parking costs and public transport fares.
The modelling considered committed or expected improvements to transport elsewhere in
Melbourne so that the effect of the Rowville rail line can be separated from the effects of other
initiatives.
The transport model considered anticipated capacity constraints on roads, but not on public
transport. Consequently, the study could forecast more patronage than the modelled public
transport services can physically carry.
The estimated traffic and rail volumes are to be treated with reasonable confidence whilst bus
patronage is likely to be underestimated in the results presented.
2.3.4 Traffic Modelling Results
Modelling results from the SKM study indicate that:
A key finding of the study was that most of the patronage comes from diversion of trips from
other rail lines, rather than mode shift from car to rail. This could be an underestimate of
future demand, especially if future changes in fuel prices are much larger than currently
assumed in the model.
The four stations on the Rowville rail line could together attract about 68,000 users on a typical
weekday by 2046, with about 16,000 of these in the morning two-hour peak (7 am – 9 am).
On an average per-station basis, this is high compared with the modelled results on other
eastern suburbs lines It is similar to the stations on the Lilydale line east of Camberwell, about
15% higher than the Dandenong line stations between Dandenong and Caulfield, and more
than double that of Pakenham and Cranbourne lines east of Dandenong.
City bound Rowville trains in the morning two-hour peak in 2046 would carry a total of about
6,000 passengers – averaging 500 per train – as they arrive at Huntingdale station; from there
on, there is expected to be ‘standing room only’.
Similar loads are forecast in the opposite direction, because of the strong attraction of Monash
University’s Clayton campus to students and staff living in the inner suburbs.
Monash University station is expected to be the busiest on the line with around 23,000 users
on a typical weekday in 2046, followed by Rowville and Mulgrave (17,000 each) and Waverley
Park (10,000).
The redeveloped Huntingdale station would attract about 16,000 users and an additional 8,000
people transferring between trains.
Estimated activity at the proposed new stations are likely to mirror current estimated activity at
suburban stations in eastern Melbourne; Huntingdale and Monash University stations would be
comparable to Caulfield; Rowville and Mulgrave would be similar to Glen Waverley; and
Waverley Park would be similar to, say, Noble Park.
Overall the model predicts 13,000 more public transport trips and 15,000 fewer car trips on a
typical weekday in 2046. Most of the 68,000 daily users of the Rowville line would be public
transport users diverting from other services (particularly the bus services that the Rowville
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line would replace, but also from Clayton, Springvale, Glen Waverley and Ferntree Gully
stations).
Consequently, the relatively small mode shift would probably not give rise to noticeable traffic
reductions on roads in the area. Though, the model probably underestimates this mode shift,
partly because of arguably conservative assumptions about changing circumstances (such as
petrol prices) in the future.
2.3.5 Construction and Operations
The construction phase is expected to last four years. The construction is likely to involve
conventional construction techniques (cut and cover, elevated structures) which are available from
Australian construction suppliers. Consequently, at this stage, requirements for imported
equipment and expertise are not envisaged.
The soonest construction commencement date is estimated to be 2016 with estimated construction
completion by 2020.
The SKM study did not carry any construction cost estimates for the option under consideration;
however, based on their experience on other projects, ball-park all-in capital costs of a twin-track
electric rail line like Rowville would be broadly as shown in the table below.
Table 1 Estimated Rail Construction Cost of Rowville Line
Length (in kms) Cost ($mn per km)
Total Cost ($ mn) by municipality of rail construction
Monash (C) Knox (C) Monash (C) Knox (C) Total
Below ground 5.5 2.0 $200 mn $1,100 mn $400 mn $1,500 mn
Above ground 4.4 1.5 $100 mn $440 mn $150 mn $590 mn
Total 9.9 3.5
$1,540 mn $550 mn $2,090 mn
Source: SKM
Construction of the railway line is expected to cost a total of $2.09 billion, with a bulk of it to be
spent in the municipality of Monash ($1.54 billion). Construction in Knox is expected to cost $550
million. This represents more than a five-fold increase in construction cost estimates from the
estimate of $413 million provided by the 2004 pre-feasibility study.
Over and above construction of the rail, construction of each station is expected to cost $200
million each, taking total construction cost of four stations to $800 million. With three stations
falling in Monash, total construction cost of stations is likely to be $600 million for Monash and
$200 million for Knox.
Although the long-run impacts observable at 2046 appear favourable, the SKM study highlights the
following short term nuisance and adverse impacts during the construction stage:
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Noise and vibration will be highly sensitive to nearby residents, business and special facilities,
including the Australian Synchrotron and nearby biomedical facilities on Blackburn Road. The
feasibility study identifies techniques to mitigate these effects during construction.
Underground stations in Wellington Road would require temporary lane closures and/or
diversions to enable cut-and-cover construction, and the high water table would probably entail
waterproofed, retained temporary cuttings. A feasible staging method has been identified to
mitigate impacts.
Access to temporary land would be required given the heavy traffic in the area. Careful traffic
and access management techniques would be required, given the high levels of traffic on the
affected roads. Maintaining traffic flows on Monash Freeway and Eastlink in particular would be
a high priority given their regional significance.
2.3.6 SKM Study Recommendations
The study recommends that the feasibility of the proposed Rowville rail line would be critically
dependent on upgrading existing infrastructure. Currently, only two tracks operate between
Dandenong and Caulfield; they carry all the Dandenong, Pakenham and Cranbourne services plus
Bairnsdale V/Line trains and freight trains from the south east. During the morning peak these
services presently total 18 trains per hour in each direction. Peak period trains on the Dandenong
corridor are regularly crowded.
The SKM study estimated that if the frequency of trains is increased after extending the line from
Huntingdale to Rowville, without adding more tracks, existing express trains would have to be
reduced in number. Consequently, Cranbourne and Pakenham passengers would probably
experience longer travel times. Moreover, additional trains per hour will mean more frequent
and/or longer closures on the four level crossings between Huntingdale and Caulfield, which would
increase the already lengthy delays to road traffic (including buses), cyclists and pedestrians.
The SKM study estimates that the existing Cranbourne/ Pakenham/ Dandenong lines cannot
provide much more peak passenger capacity than it does now without allowing for longer trains,
re-signalling and/or additional tracks, and grade separation of level crossings to avoid excessive
delays to traffic.
Given that addressing the outlined critical requirements is likely to be an exhaustive exercise, the
earliest that the Rowville Rail Line can be provided is 2020.
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3 BASELINE SOCIO ECONOMIC PROFILE
This section provides a baseline socio-economic profile and reviews the current journey to work
patterns of the City of Knox, with a specific focus on Rowville, to understand its current role and
performance in the municipality. This profile is benchmarked against the wider South East Region
and the whole metropolitan area (i.e. the Metropolitan Statistical Division or MSD).
3.1 Geographical Scope
For the purposes of profiling, clear statistical collection precincts have been defined. The Local
Government Area (LGA) or municipality of Knox consists of the three Statistical Local Areas (SLA)
of:
Knox – North-East,
Knox - North-West; and
Knox – South (refer Figure 3 overleaf).
Rowville falls within the SLA of Knox – South.
For the purposes of this study, the broader South East Region has been defined to consist of the
LGAs of:
Monash (C);
Knox (C);
Greater Dandenong (C); and
Casey (C).
The Melbourne Statistical Division (MSD) consists of all 31 metropolitan LGAs that make up
metropolitan Melbourne.
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Figure 3 Knox and the Surrounding South East Region
Source: SGS Economics & Planning
3.2 Resident Profile
3.2.1 Population, Dwellings and Growth
The resident population of Knox was estimated at approximately 160,000 in 2011. Since 1996 the
population grew modestly, with an annual growth of 1.02%, much lower than that of the South
East Region and the MSD (Table 2 overleaf).
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However, while growth across the whole of Knox was modest, growth in the southern area that
hosts Rowville has been exceptionally high since 1996, with population increasing annually at over
3%, and outpacing growth of all comparator regions. This growth was particularly strong between
the Census periods of 1996 and 2001, where 10,000 people moved to the Knox - South area.
Table 2 Growth in Population, 1996-2011
1996 2001 2006 2011 CAGR %
(1996-2011)
Knox - North-East 64,200 64,000 64,300 66,800 0.3%
Knox - North-West 45,100 46,100 45,800 48,600 0.5%
Knox - South 27,500 37,300 41,700 43,900 3.2%
Knox (C) 136,800 147,400 151,800 159,300 1.0%
South East Region 578,300 620,700 674,600 741,500 1.7%
MSD 3,283,300 3,471,600 3,743,000 4,170,600 1.6%
Source: Estimated Resident Population, Australian Bureau of Statistics 1996-2006 and SGS projections for 2011
Note: Values rounded to the nearest hundred, CAGR – Compounded Annual Growth Rate
Growth in households over the same corresponding period has outpaced population growth, a trend
exhibited across the rest of Melbourne (Table 3). This reflects a broad trend towards shrinking
household sizes. The average household size in Knox declined from 3.2 persons per dwelling in
1996 to 2.8 persons per dwelling in 2011. Notably, growth in the number of dwellings in Knox –
South has outpaced that in the South East Region and the MSD.
Table 3 Growth in Dwellings, 1996-2011
1996 2001 2006 2011 CAGR %
(1996-2011)
Knox - North-East 21,600 22,800 24,600 25,900 1.2%
Knox - North-West 13,600 14,600 15,600 16,700 1.4%
Knox - South 8,000 10,900 12,800 13,400 3.5%
Knox (C) 43,200 48,300 53,000 56,000 1.7%
South East Region 186,300 206,800 235,600 252,900 2.1%
MSD 1,136,900 1,247,500 1,408,500 1,527,100 2.0%
Source: Estimated Resident Population, Australian Bureau of Statistics 1996-2006 and SGS projections for 2011
Note: Values rounded to the nearest hundred, CAGR – Compounded Annual Growth Rate
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 18
3.2.2 Skills Profile
The education profile of Knox generally compares to the South East Region, but differs to the MSD
in terms of bachelor qualifications and above (Figure 4). Knox and the South East Region comprise
a high proportion of vocational and tertiary qualified residents than the MSD, with 45% and 41%
respectively of further educated residents holding certificate level qualifications.
Figure 4 Education Profile of Residents, 2006
Source: Census of Population and Housing, Australian Bureau of Statistics 2006
Interestingly though, the proportion of Knox’s residents with bachelor degrees or above has
increased since 1996, mirroring the trend in comparator regions (Figure 5 overleaf). This transition
to a more qualified workforce would increase demand for more jobs in advanced Manufacturing and
in the tertiary/ services sector.
Of the Knox residents with further education, almost a quarter have studied in the field of
Engineering (Figure 6 overleaf). A high proportion of residents are also qualified in Management
and Commerce. This presents an opportunity to develop a specialisation and clustering of
engineering, scientific services and other services related industry in Knox, sourcing local labour
and reinforcing existing local industry.
0%
25%
50%
75%
100%
Knox (C) South East Region MSD
45%41%
34%
20%20%
18%
27%29%
35%
8% 10% 13%
Certificate Level Advanced Diploma and Diploma Level
Bachelor Degree Level Graduate Dipl. / Cert. / Post Grad. Degree
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 19
Figure 5 Education Profile of Residents, 1996
Source: Census of Population and Housing, Australian Bureau of Statistics 1996
Figure 6 Residents Field of Study, 2006
Source: Census of Population and Housing, Australian Bureau of Statistics 2006
0%
25%
50%
75%
100%
Knox (C) South East Region MSD
51%47%
38%
20%20%
20%
22%25%
31%
7% 8% 11%
Certificate Level Advanced Diploma and Diploma Level
Bachelor Degree Level Graduate Dipl. / Cert. / Post Grad. Degree
0%
5%
10%
15%
20%
25%
Knox (C) South East Region MSD
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 20
3.2.3 Occupation Profile
The occupation profile of Knox residents is similar to that of the South East Region (Figure 7).
Contrasted to the profile of the MSD, a relatively lower proportion of Knox residents are employed
as managers and professionals.
Figure 7 Occupation Profile of Resident Workers, 2006
Source: Census of Population and Housing, Australian Bureau of Statistics 2006
Over the period from 1996 to 2006, the proportion of resident workers employed in higher order
trades such as managers and professionals grew at the expense of trades (Figure 8 overleaf). This
trend also occurred in the South East Region and MSD, although to a greater degree in the MSD.
0%
25%
50%
75%
100%
Knox (C) South East Region MSD
36% 34%43%
34%32%
31%
22%23%
19%
8% 11% 8%
Managers and Professionals Clerical and Service Workers
Tradespersons, Labourers and Related Workers Intermediate Production and Transport Workers
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 21
Figure 8 Occupation Profile of Resident Workers, 1996
Source: Census of Population and Housing, Australian Bureau of Statistics 1996
3.3 Employment Profile
3.3.1 Industry Profile
Based on SGS estimates there are approximately 75,000 jobs located in Knox in 2011 (Table 4
overleaf)5. As can be observed, employment in Knox is largely centred in Manufacturing followed
by Retail Trade, Construction, Health Care and Social Assistance and Wholesale Trade.
12% of the total jobs within the City of Knox are located within Knox – South, with higher
concentration of services oriented jobs observable.
5 Estimates for 2011 are not available from the ABS. SGS has estimated employment for 2011. The estimation methodology is shown in Appendix A.
0%
25%
50%
75%
100%
Knox (C) South East Region MSD
34% 32%39%
33%31%
31%
23%25%
21%
9% 12% 9%
Managers and Professionals Clerical and Service Workers
Tradespersons, Labourers and Related Workers Intermediate Production and Transport Workers
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 22
Table 4 Employment by Industry (Workers), 2011
Knox (C) Knox - South
South East Region
MSD
Agriculture, Forestry and Fishing 150 20 1,890 11,900
Mining 80 60 240 4,700
Manufacturing 15,010 470 63,970 233,100
Electricity, Gas, Water and Waste Services 390 40 3,410 21,000
Construction 8,540 1,590 37,460 190,100
Wholesale Trade 7,100 390 26,330 94,300
Retail Trade 9,870 850 43,060 234,400
Accommodation and Food Services 3,900 420 15,320 135,900
Transport Postal and Warehousing 2,560 300 17,780 107,500
Information Media and Telecommunications 460 40 3,280 54,400
Financial and Insurance Services 1,800 130 8,160 112,600
Rental, Hiring and Real Estate Services 1,210 150 6,160 38,300
Professional, Scientific and Technical Services 3,580 570 19,040 207,500
Administrative and Support Services 2,030 310 9,820 70,600
Public Administration and Safety 1,750 110 9,160 105,500
Education and Training 4,120 960 29,790 176,500
Health Care and Social Assistance 7,790 2,100 36,360 245,700
Arts and Recreation Services 880 60 3,400 47,900
Other Services 3,530 380 14,560 85,300
Total 74,750 8,950 349,190 2,177,200
Source: SGS estimates based on Australian Bureau of Statistics, 2006 Journey to Work Data.
Notes: Values are rounded off to the nearest tenth.
Grouping industries into broad categories (primary, industry, retail and commercial), one can
observe that Knox – South mirrors employment concentrations observations for the metropolitan
average (Figure 9 overleaf). Commercial employment surpasses all other categories.
Overall though, City of Knox has a relatively high concentration of primary industry jobs compared
to the South East Region and the MSD, and a lower concentration of commercial jobs. Taken
together, primary industrial activities comprise approximately 45% of total employment within the
City of Knox with an almost equal proportion of employment centred within commercial activities.
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 23
Figure 9 Employment Share by Broad Industry Category (Workers), 2011
Source: Census of Population and Housing (ABS, 1996, 2001 and 2006), and SGS internal modelling
Notes: Primary industry includes Agriculture, forestry and fishing; and Mining. Industry group includes
Manufacturing; Wholesale trade; Transport and warehousing; Electricity, gas and water services; and
Construction. Retail comprises Retail trade; and Commercial includes all other service based industries. Total
for all broad industry groups equals 100%.
Comparing the share of employment by industry in Knox against value-added generated by
industry (derived as sum of all outputs minus sum of inputs used in production), several notable
disparities are evident (Figure 10 overleaf). The proportional contributions to value-added made by
Manufacturing; Wholesale Trade; and certain higher order services including Finance & Insurance;
and Information, Media and Telecommunications is comparatively higher to the proportional
contributions of these industries towards employment. In turn, this suggests that these sectors of
the economy are high value adding.
Given that Manufacturing contributes nearly one-fifth towards the municipality’s employment and
more than a quarter of the region’s value-added, it is beneficial to look at the composition of
manufacturing employment and value-added (shown in Figure 11 overleaf). Interestingly, much of
the value-added and employment created by Manufacturing is concentrated within higher-order
Manufacturing, including Technical Equipment & Appliances; Pharmaceutical Products; Metals &
Metal Products; Chemicals and so on and so forth. Taken together, production of technical
equipment, appliances and pharmaceuticals contribute nearly one-third of total manufacturing
value-added in the municipality.
0%
20%
40%
60%
Primary Industry Retail Commercial
Sh
are
of
Em
plo
ym
en
t
Knox (C) Knox - South SLA
South East Region MSD
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 24
Figure 10 Knox (C) Employment and Value Added Contribution
Source: Value Added contributions from REMPLAN (2011. Employment contribution from SGS internal modelling
Figure 11 Knox (C) Manufacturing Employment and Value-Added, 2011
Source: REMPLAN (2011)
0%
5%
10%
15%
20%
25%
30%
Contribution to Employment
Contriobution to Value Added
0%
4%
8%
12%
16%
20%
$0
$100
$200
$300
$400
Co
ntr
ibu
tio
n t
o M
fg. E
mp
loym
en
t (%
)
Val
ue
Ad
de
d ($
Mil
lio
n)
Value Added ($M)
Contribution to Mfg. Employment
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 25
3.3.2 Employment Growth
Over the period 1996 to 2011, the total number of jobs within the City of Knox increased by
approximately 15,000. Employment growth over this period both within Knox and Knox – South
was below the metropolitan and South East Region’s average (Figure 12), mirroring the trend
observable for population growth across these regions. Overall industrial employment has grown in
all observed regions, but within industry, Manufacturing employment has experienced an across
the board decline. Employment in the Commercial sector has been strongest over this period in all
observed regions, but employment within the sector at the wider metropolitan scale has outpaced
that in Knox and Knox – South. Retail employment in Knox – South has in fact declined over this
period.
Figure 12 Employment Growth by Broad Industry Category (Workers), 1996-
2011
Source: Census of Population and Housing (ABS, 1996, 2001 and 2006), and SGS internal modelling
In terms of GRP growth over the last 5 year period, the GRP of Knox rose 11.6% from 2005-06 to
2009-10 (Table 5 overleaf). The highest growth was seen in Health Care and Social Assistance,
followed by Financial and Insurance Services. Notably, while the Information Media and
Telecommunications industry substantially shrunk in terms of jobs since 1996, the GRP grew by
almost 4.6% annually since 2006. The value-added contribution of Manufacturing still remains the
highest growing modestly at just under 1% p.a. over this period.
-4%
-2%
0%
2%
4%
Primary Industry Retail Commercial Total
Co
mp
ou
nd
ed
An
nu
al
Gro
wth
Ra
te
Knox (C) Knox - South
South east Region MSD
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 26
Table 5 Knox (C) Gross Regional Product by Industry, 2011
2005-06
$M 2009-10
$M CAGR % (2006-
10)
Agriculture, Forestry and Fishing 12.8 13.5 1.3%
Mining 55.7 66.2 4.4%
Manufacturing 1,551.9 1,602.9 0.8%
Electricity, Gas, Water and Waste Services 70 67 -1.1%
Construction 544.8 646.9 4.4%
Wholesale Trade 916.7 1,079.3 4.2%
Retail Trade 387.7 454.1 4.0%
Accommodation and Food Services 140.9 136.4 -0.8%
Transport Postal and Warehousing 228.6 267.2 4.0%
Information Media and Telecommunications 107.2 128.5 4.6%
Financial and Insurance Services 426.5 520.9 5.1%
Rental, Hiring and Real Estate Services 196.7 201.8 0.6%
Professional, Scientific and Technical Services 343.7 336.1 -0.6%
Administrative and Support Services 164.1 184.8 3.0%
Public Administration and Safety 123.2 144.2 4.0%
Education and Training 244.6 276.8 3.1%
Health Care and Social Assistance 376.7 474.1 5.9%
Arts and Recreation Services 47 55.9 4.4%
Other Services 174 163.6 -1.5%
Total 6,112.8 6,820.2 2.8%
Source: KEFS (2011)
3.3.3 Occupation Profile
Managers and Professionals make up the largest occupation group in Knox, accounting for 35% of
jobs within the municipality (Figure 13). The occupation profile of employment located within Knox
largely mirrors that of the broader South East Region; however the municipality hosts considerably
less proportion of managers and professionals when compared with the MSD.
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 27
Figure 13 Occupation Profile of Workers (2006)
Source: Australian Bureau of Statistics 2006, Journey to Work Data
3.4 Journey to Work Patterns
3.4.1 Origin and Destination of Workers
Destination of Resident Workers
The location of employment for Knox residents at the 2006 Census is shown in Figure 14 overleaf.
The data indicates that a high proportion of resident workers from Knox are employed within the
municipality (34%) followed by surrounding LGAs of Monash (11%), Whitehorse (8%), Maroondah
and Greater Dandenong (7% each) and Casey (2%). Approximately 14% of the resident workforce
travels to the inner city municipalities of Melbourne, Stonington, Port Phillip and Yarra for work.
Origin of Destination Workers
The host LGAs of workers who were employed within Knox at 2006 (i.e. destination workers’ place
of residence) is shown overleaf in Figure 15. This does not exhibit the same relationship as the
destination of Knox residents.
Comparatively, a much higher proportion of Knox’s workforce is drawn from within the municipality
(41%); followed by Monash (5%), with only 2% of its workforce drawn from the inner city
municipalities.
0%
25%
50%
75%
100%
Knox (C) South East Region MSD
35% 38%45%
32%30%
32%
22% 20%
16%
11% 11%8%
Managers and Professionals Clerical and Service Workers
Tradespersons, Labourers and Related Workers Intermediate Production and Transport Workers
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 28
Figure 14 Destination LGAs of Knox (C) Resident Workers, 2006
Source: SGS Economics & Planning & Census of Population and Housing (ABS, 2006)
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 29
Figure 15 Origin LGAs of Knox Workers, 2006
Source: SGS Economics & Planning & Census of Population and Housing (ABS, 2006)
3.4.2 Travel Mode
ABS data confirms that resident workers of Knox – South rely on cars as a form of transport far
more than other modes of transport and when compared with other municipalities across
metropolitan Melbourne. Car use to access work is pronounced compared even to growth area
municipalities of Hume and Wyndham (refer Figure 16 overleaf).
Furthermore, the use of public transport in the SLA is significantly under the MSD average and that
of surrounding and growth areas municipalities. Public transport is used to access 14% of jobs
across the MSD whereas only 5% of Knox – South residents use public transport to access
employment.
Employment within the SLA of Knox – South by destination workers is further skewed in favour of
car usage than resident workers. Over 80% of employment in the SLA is accessed by cars in the
area and the use of public transport is observed at just 2%. This compares to 78% and 14%
respectively for the overall metropolitan average (refer Figure 17 overleaf).
These data suggest that the SLA significantly suffers from accessibility problems.
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 30
Figure 16 Mode of Travel, Origin of Resident Workers, 2006
Source: Census of Population and Housing, ABS
Notes: Other modes of transport include cycling, working from home and methods not stated.
Figure 17 Mode of Travel, Destination of Resident Workers, 2006
Source: Census of Population and Housing, ABS
Notes: Other modes of transport include cycling, working from home and methods not stated.
0%
25%
50%
75%
100%
Car Public Transport Walked Other
Sha
re o
f Tr
av
el M
od
e
Knox - South SLA Monash (C) Melbourne (C)
Wyndham (C) Hume (C)
0%
25%
50%
75%
100%
Car Public Transport Walked Other
Sha
re o
f Tr
av
el M
od
e
Knox - South SLA Monash (C) Melbourne (C)
Wyndham (C) Hume (C)
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 31
3.4.3 Travel Time
SGS observed the travel time for resident and destination workers for Knox – South and compared
it with other outer area growth municipalities and also with a benchmarked well-connected region
of the MSD, i.e. Melbourne CBD, findings indicate that, on average:
Destination workers to Knox – South spend at least 35% longer commuting to work using
public transport when compared to the time spent travelling to work by employed workers in
Melbourne CBD. Travel times for destination workers to Knox - South are only a shade below
those observed for destination workers to growth area municipalities of Wyndham and Hume.
Resident workers of Knox – South spend almost 3 times longer travelling to work by car and up
to 2.8 times the time travelling by public transport to work when compared to the time spent
travelling to work by resident workers of Melbourne CBD. Yet again, travel times for resident
workers of Knox – South when taking public transport are much the same compared to the
growth area cities of Hume and Wyndham.
Both resident and destination workers travelling from and to Knox – South spend at least 3.2
times and up to 4 times travelling to their work destination when travelling by public transport
compared to driving. Consequently, the incentives to drive are high.
Compared to Monash and Melbourne CBD, travel times on public transport for Knox residents
and workers are indeed high. In fact, time taken by the residents and workers of Knox is
almost as high as those experienced by residents and workers of growth area municipalities.
When undertaking this analysis, SGS adopted the following methodology:
Using ABS’s JTW data, we observed all destination SLAs for the resident workers of Knox –
South SLA and the cities of Melbourne, Hume, Monash and Wyndham.
We used the same dataset to observe all origin SLAs for destination workers to Knox – South
SLA and the cities of Melbourne, Hume, Monash and Wyndham.
Subsequently, we estimated the:
o Average travel time from Knox – South to all SLAs across the MSD, and
subsequently repeating the same calculation for all the selected SLA’s.
o Average travel time to Knox – South to all SLAs across the MSD, and subsequently
repeating the same calculation for all the selected SLA’s.
Estimated the weighted travel time by car and public transport from and to the selected SLAs
using the proportion of workers from and to these work destinations of the total, acting as
weights.
Results of this exercise are reported below in Figure 18 and Figure 19 overleaf. It must be borne in
mind that Melbourne CBD is by far the most well-connected municipalities by public transport. Most
workers within the central municipality are also employed in close proximity to the CBD.
Consequently, all other regions within the metropolis are not as well connected compared to the
CBD and time taken by public transport to access employment from all these locations would not
be as small when compared to the CBD. Nonetheless, the results highlight that Rowville’s transport
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 32
connectivity, indeed public transport connectivity is worse compared to other regions and at par
with growth area municipalities.
Figure 18 Weighted Travel Time of Destination Workers
Source: Census of Population and Housing (ABS, 2006) and SGS estimations
Figure 19 Weighted Travel Time of Resident Workers
Source: Census of Population and Housing (ABS, 2006) and SGS estimations
0
20
40
60
80
100
120
Destination Weighted Travel Time by Car Destination Weighted Travel Time by PT
Min
ute
s o
f Tra
vel
Knox - South SLA Monash (C)
Melbourne (C) Wyndham (C)
Hume (C)
0
20
40
60
80
100
120
140
Origin Weighted Travel Time by Car Origin Weighted Travel Time by PT
Min
ute
s o
f Tra
vel
Knox - South SLA Monash (C)
Melbourne (C) Wyndham (C)
Hume (C)
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 33
3.4.4 Accessibility
The following analysis of employment accessibility was performed using geographic locations of
Rowville, Flinders Street, Monash, Werribee and the designated Central Activities Areas (CAAs)
across the MSD of Footscray, Box Hill, Dandenong, Broadmeadows, Ringwood and Frankston. The
purpose was to measure the number of jobs (i.e. employment) that could be accessed from these
nodes by public transport and car within a 30 minute timeframe. Results of this analysis are
presented below.
Table 6 Jobs Accessibility by Car and Public Transport, 2011
Car Public Transport
Number of Jobs
Proportion of
MSD jobs accessible Number of Jobs
Proportion of
MSD jobs accessible
Rowville 235,000 12.3% 4,000 0.2%
Flinders Street 1,248,000 65.4% 537,000 28.1%
Footscray 810,000 42.4% 277,000 14.5%
Monash 668,000 35.0% 21,000 1.1%
Box Hill 543,000 28.5% 53,000 2.8%
Dandenong 361,000 18.9% 27,000 1.4%
Broadmeadows 296,000 15.5% 5,000 0.3%
Ringwood 273,000 14.3% 24,000 1.2%
Werribee 131,000 6.9% 7,000 0.4%
Frankston 129,000 6.8% 13,000 0.7%
Source: SGS estimations using travel time matrices and SGS’s employment data
Note: The results for car accessibility are based on using ‘unloaded’ travel time matrices, i.e. non-peak travel times without considerations for road elevations, traffic congestion and traffic signals. Consequently, the estimated results for car accessibility appear optimistic.
The following conclusions can be drawn from this analysis:
When considering public transport accessibility, job accessibility from those closer to Flinders
Street far exceeds the small amount of jobs that residents of Rowville can access
(approximately 28% c.i.f. to a meagre 0.2% of total MSD jobs.)
Accessibility for Knox’s residents improves considerably when considering car use. Whilst
residents closer to Flinders Street can assess approximately 65% of all metropolitan jobs within
a 30 minute drive, residents of Rowville can access a much lower proportion, i.e. 12% of all
metropolitan jobs.
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 34
The difference in accessibility within a 30 minute timeframe between car and public transport
use for residents of Rowville is pronounced and considerably favours car use.6
3.5 Section Summary
The City of Knox has been a destination of choice to live and work. This is evident in the growth in
both population and employment compared to the metropolitan average. In fact, growth in
population in Knox – South (the SLA that hosts Rowville) has far outpaced growth in the
municipality and the wider metropolis.
Employment and value creation in the municipality continues to be driven by both industrial and
commercial activities. In fact, a higher share of the municipality’s employment is concentrated in
industrial activities (defined as comprising the sectors of Manufacturing; Wholesale Trade;
Transport & Logistics; Utilities and Construction) compared to the wider South East Region and the
MSD economies. Interestingly, much of the value-added and employment created by
Manufacturing within Knox is concentrated within higher-order Manufacturing, including Technical
Equipment & Appliances; Pharmaceutical Products; Metals & Metal Products; Chemicals and so on
and so forth.
Much like the wider Australian and metropolitan Melbourne economies undergoing a structural shift
over the past 15 year timeframe, i.e. a shift towards more services based employment the City of
Knox was no exception either. Indeed it is plausible that the growth in services based employment
(including growth in Financial & Insurance Services and Professional, Scientific & Technical
Services) observed in the municipality and Knox – South SLA over this period was fuelled not only
to service the needs of the growing local/ regional population but also to service the demands of a
growing sophisticated manufacturing sector.
The education and skills profile of resident workers in the municipality has also responded to the
underlying change and has notched up more toward higher education and more white collared
trades.
Whilst growth in employment opportunities within Knox has indeed been robust, it has been shy of
the rates observed in the wider comparator economies of the South East Region and the MSD.
More importantly, access to employment opportunities for resident workers of the municipality and
to employment opportunities within the municipality is constrained by longer travel times on public
transport.
Compared to a benchmarked location (Melbourne CBD) and other growth area municipalities,
resident and destination workers from and to Knox – South take longer to commute to work,
especially when taking public transport, regardless of the mode of travel. In fact, public transport
can take between 2 and nearly up to 5 times more time accessing work opportunities.
6 The results for car accessibility are based on using ‘unloaded’ travel time matrices, i.e. non-peak travel times without considerations for road elevations, traffic congestion and traffic signals. Consequently, the estimated results for car accessibility are perhaps optimistic and overestimate job accessibility.
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 35
Job accessibility on a 30 minute trip on public transport is pretty constrained too, compared to
cars. In fact, accessibility to jobs for a resident worker located in Rowville is low compared to
resident workers of growth area municipalities and other designated CAAs of the MSD. It is not
surprising then that over 90% of work trips originating from and ending in Knox – South rely on
cars compared to 5% or less on public transport.
Consequently, a high proportion of resident workers of Knox and destination workers within the
municipality travel to and from neighbouring municipalities for work as shown by the following
data:
A high proportion (~70%) of the resident workforce of Knox is employed within the
municipality and surrounding LGAs of Monash, Whitehorse, Maroondah, Greater Dandenong
and Casey.
A smaller proportion of the municipality’s residents work in the inner city municipalities of
Melbourne, Stonnington, Port Phillip and Yarra (~14%), compared to the residents of Monash
(29%) and even the growth area municipalities of Wyndham (27%) and Hume (20%).
Destination LGAs for Resident Workers Origin LGAs of destination workers
Knox (C)
Knox (C) 34% Knox (C) 41%
Inner city 14% Inner city 2%
Monash (C)
Monash (C) 32% Monash (C) 25%
Inner city 29% Inner city 6%
Melbourne (C)
Melbourne (C) 62% Melbourne (C) 7%
Inner city 79% Inner city 23%
Wyndham (C)
Wyndham (C) 38% Wyndham (C) 53%
Inner city 27% Inner city 2%
Hume (C)
Hume (C) 21% Hume (C) 37%
Inner city 20% Inner city 3%
*inner city includes the municipalities of Melbourne, Port Phillip, Stonnington and Yarra.
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 36
4 BASELINE FORECASTS
Presented in this section are baseline population and employment forecasts, out to 2046, for the
City of Knox and the South East Region. They articulate, at a fine grained level (that of a SLA), the
region’s development trajectory ‘without’ the Project, i.e. ‘Business As Usual’ scenario.
Whilst the population forecasts are based on official data releases and SGS’s estimates,
employment projections were developed using SGS in-house modelling and refined after
consultations with Council.
4.1 Population Forecasts
Future population projections are based on a combination of data sourced from the State
Government’s publication, ‘Victoria in Future (2008)’ and SGS’s estimates developed in previous
assignment experience. Appendix A outlines the methodology used in developing these forecasts.
Table 7 illustrates the projected population of Knox, the South East Region and the MSD out to
2046. To 2046, Knox is anticipated to grow relatively slower than the broader South East Region
and the MSD, adding just over 25,000 people between 2011 and 2046 with a compounded annual
growth rate (CAGR) of 0.4%.
Within Knox, the Knox - South SLA, which exhibited the most growth between 1996 and 2011, is
projected to grow modestly in the coming decades relative to other SLAs within the municipality
and the wider comparator regions. The more established areas in the north of Knox, particularly
North-West Knox which contains Knox Central are anticipated to increase in population at a greater
rate due to a degree of urban renewal and densification.
Table 7 Estimated Population Projections, 2011-46
2011 2021 2031 2046 CAGR %
(2011-2046)
Knox - North-East 66,800 70,600 72,500 76,800 0.4%
Knox - North-West 48,600 52,900 56,000 59,300 0.6%
Knox - South 43,900 45,700 47,000 50,000 0.4%
Knox (C) 159,300 169,200 175,500 186,100 0.4%
South East Region 741,500 852,000 928,900 1,014,800 0.9%
MSD 4,170,600 4,820,100 5,410,600 6,170,800 1.1%
Source: Victoria in Future 2008 and SGS Projections
Note: Values rounded to the nearest hundred
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 37
As with population growth, the anticipated dwelling growth in Knox is expected to be slow relative
to wider benchmarked regions. Nonetheless, dwellings growth in Knox is projected to increase at a
faster rate than population (Table 8), with the trend towards shrinking household sizes anticipated
to continue.
Growth in dwellings in Knox – South is likely to equate in average to the wider metropolis and is
expected be slower compared to other SLAs within the municipality. This is largely a reflection of
the age of the housing stock, most of which was constructed between 1996 and 2011, with the
relatively newer houses of Knox - South unlikely to be redeveloped before 2046.
Table 8 Estimated Dwelling Projections, 2011-46
2011 2021 2031 2046 CAGR %
(2011-2046)
Knox - North-East 26,600 28,400 30,200 32,500 0.6%
Knox - North-West 17,500 19,300 20,600 22,200 0.7%
Knox - South 13,700 14,600 15,800 17,100 0.6%
Knox (C) 57,800 62,300 66,600 71,800 0.6%
South East Region 264,100 307,500 344,900 384,800 1.1%
MSD 1,619,400 1,904,900 2,187,000 2,512,800 1.3%
Source: Victoria in Future 2008 and SGS Projections
Note: Values rounded to the nearest hundred
4.2 Employment Forecasts
SGS has made ‘Business As Usual’ or the ‘without project’ forecasts of employment within Knox,
South East Region and the MSD using its in house modelling techniques. The detailed methodology
describing these techniques is shown in Appendix A. Suffice here to say that SGS adopted a ‘top
down’ approach to projecting employment by industry for each SLA across Melbourne based on
data obtained from a variety of sources used to develop a set of industry projections for the entire
Australian economy. These industry projections are forecast over the short term (2016), long term
(2031) and beyond (2046), with total growth for all industries benchmarked against GDP
projections. This ensures that the projected industry growth can be resourced with the finite level
of resources at the disposal of Australia. At a State level, Victorian estimates are derived from the
current State share of Gross Value Added (GVA) and employment for each industry. Projections are
made on the future share of each industry in Victoria. Employment projections for Melbourne are
derived from these Melbourne GVA projections and projections of Melbourne’s labour productivity
growth. Employment growth is then capped using future labour force constraints.
Employment projections for SLAs are based on a combination of observable past growth rates and
expected changes in employment distribution over time. When contemplating expected changes
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over time, SGS considered each sub-region’s: prospects and capacity for growth, transport
connections, resident workforce characteristics, employment lands availability and Government
spatial policy considerations. Importantly, this analysis was undertaken separately for each major
industry and occupation groups to ensure that the level of granularity appropriately reflects
respective location drivers.
These forecasts have been used by the Victorian State Departments of Transport and Planning and
Community Development in previous SGS projects.
Indeed, discussions with Knox City Council suggested that further finer adjustments were required
to the specific forecasts for the City of Knox to better reflect Council policy and its advocacy efforts
towards consolidating its existing industry base and providing support for a thriving services sector.
In addition, insights gained from the Knox Economy Future Study (KEFS 2011) – providing a
review of the Council’s economic development program and scenario analysis of possible future
economic outcomes for the municipality - was used by SGS to inform and refine its employment
estimates for the municipality.7
The final estimated employment projections for the City of Knox by 1-digit Australia and New
Zealand System of Industry Classification (ANZSIC) industry are shown overleaf in Table 9. A time-
series view of the industrial structure for the municipality is provided in Figure 20 with comparisons
of industry-wide growth between Knox and benchmarked comparator regions shown in Figure 21
overleaf.
Notable observations from these business as usual projections are as follows:
Almost 100,000 jobs are projected to be located in Knox by 2046.
Employment in the municipality is expected to grow by just under 25,000 between 2011 and
2046, nearly matching population growth over this period (refer Table 7).
The largest increases in employment are seen in Health Care and Social Assistance, followed by
Professional, Scientific and Technical Services, Education and Training and the population
servicing industries of Retail Trade and Accommodation and Food Services.
Such strong growth in services is expected to increase the share of the Knox’s services
economy observed at 42% in 2011 to 55% by 2046. This transformation could be observed
between 1996 and 2011 (refer Figure 20).
7 It must be borne in mind that employment projections made out to 2031 contained within the KEFS (2011) study were different to those produced by SGS. In projecting future
employment by industry, differing projection methodologies will invariably result in differing forecasts. This is not to discredit either of the projections, but does articulate how varying modelling methods can impact upon projection findings. The KEFS (2011) study applied the AECgroup Economic Growth Model, based on a Knox Input-Output table to model future employment by industry. The model uses population growth and industry growth estimates to forecast the economic growth of the City of Knox, utilising projections of GRP based on
expected real growth rates in production by industry, using 2008-09 as a base. Contrasted to
this ‘bottom up’ approach adopted by the KEFS study, SGS uses a ‘top down’ approach as explained in the text.
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Services sector growth is due at the expense of primary and secondary industries (including
the sectors of Agriculture, Mining, Manufacturing, Utilities, Construction, Wholesale Trade and
Transport). Share of primary industries is expected to continue to fall.
Though the data indicate a fall in industrial based employment, it must be borne in mind that
this does not imply a declining industrial sector. Indeed, value created by the Manufacturing
sector will continue to rise. There has been a long term trend towards greater capital
intensiveness of most industry sectors driven by technological change underpinning the
productivity increases required to maintain competitiveness. Productivity growth (industry
value add per person employed) in Manufacturing as a whole in Victoria was 4.7% per year
from 2002 to 2006, well above the average inflation rate of 2.8% for the period, giving a real
increase in output of 1.8% per annum. Such productivity increases in Manufacturing (and
indeed, all industry sectors) are forecast to continue for Knox. Indeed, forecasts indicate that
Manufacturing sector GVA between 2021 and 2046 under the Base Case would rise by 1.2%
annually, compared to 0.8% p.a. between 2006 and 2010.
Presumably, productivity growth in industry will be driven by the already existing higher order
Manufacturing base of the region. The expanding services sector employment, especially in
Finance & Insurance and Property, Scientific & Technical Services, is expected to service the
increasing value created by this sector.
Overall, total employment growth over time is expected to slow down (Table 9) – reflection of a
trend observable across the whole of Melbourne due to slower labour force growth resulting
from an ageing population.
Compared to the wider benchmarked regions (South East Region and MSD), employment
growth within the City of Knox is low across the board (refer Figure 21). The anticipated decline
in Manufacturing is evident across all three compared regions, but lowest in the City of Knox.
This further underscores the resilience of the municipality’s manufacturing base.
Because of the changes mentioned above, Knox’s share in total metropolitan employment is
expected to remain fairly stable across most service based industries, (Figure 22). On the
contrary, Knox’s employment share in Construction and Wholesale Trade is set to fall over
time. This is on account of industrial activity likely to move away from Knox. Moreover,
Wholesale Trade employment is increasingly being concentrated in Melbourne’s west and north
where the intermodal hubs are being set up. Figure 23 overleaf in shows the declared industrial
nodes of Melbourne from the Urban Development Programme (UDP). These are the nodes
where the industrial sector of the metropolitan economy is most likely to congregate in the
future.
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Table 9 Estimated Employment Projections by 1-digit ANZSIC Industry, Knox (C)
Employment Levels Growth in Employment (CAGR %)
1996 2011 2031 2046 1996-2011 2011-2031 2011-2046
Agriculture, Forestry and Fishing 263 141 74 69 -4.1% -3.2% -2.0%
Mining 20 73 59 60 9.0% -1.1% -0.6%
Manufacturing 16,840 15,010 13,111 11,495 -0.8% -0.7% -0.8%
Electricity, Gas, Water and Waste Services 238 384 545 634 3.2% 1.8% 1.4%
Construction 4,604 8,534 9,403 9,393 4.2% 0.5% 0.3%
Wholesale Trade 6,201 7,097 6,163 5,926 0.9% -0.7% -0.5%
Retail Trade 8,477 9,867 11,560 12,594 1.0% 0.8% 0.7%
Accommodation and Food Services 2,707 3,893 5,936 6,546 2.5% 2.1% 1.5%
Transport Postal and Warehousing 2,158 2,555 4,411 5,044 1.1% 2.8% 2.0%
Information Media and Telecommunications 921 458 940 933 -4.6% 3.7% 2.1%
Financial and Insurance Services 1,127 1,797 2,613 3,510 3.2% 1.9% 1.9%
Rental, Hiring and Real Estate Services 474 1,203 1,571 1,883 6.4% 1.3% 1.3%
Professional, Scientific and Technical Services 2,681 3,570 5,853 7,684 1.9% 2.5% 2.2%
Administrative and Support Services 1,249 2,022 2,119 2,183 3.3% 0.2% 0.2%
Public Administration and Safety 1,405 1,749 2,106 2,264 1.5% 0.9% 0.7%
Education and Training 2,734 4,119 5,724 7,117 2.8% 1.7% 1.6%
Health Care and Social Assistance 3,774 7,781 12,200 15,598 4.9% 2.3% 2.0%
Arts and Recreation Services 462 870 1,337 1,560 4.3% 2.2% 1.7%
Other Services 3,191 3,523 4,292 4,893 0.7% 1.0% 0.9%
Total Employment 59,525 74,647 90,017 99,385 1.5% 0.9% 0.8%
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Figure 20 Industry Structure, Knox (C), 1996 - 2046
Source: ABS and SGS Projections
Figure 21 Estimated Employment Growth (CAGR %) by 1-digit Industry,
2011-46
Source: SGS Projections
0%
25%
50%
75%
100%
1996 2011 2031 2046
0% 0% 0% 0%
50%45%
37%33%
14%
13%
13%
13%
35%42%
50%55%
Primary Industry Retail Commercial
-3%
-2%
-1%
0%
1%
2%
3%
4%
Knox (C) South East Region MSD
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Figure 22 Estimated Knox (C) Employment Share in MSD
Source: SGS Projections
0.0%
2.5%
5.0%
7.5%
10.0%
1996 2011
2031 2046
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Figure 23 Declared Industrial Nodes, Urban Development Programme, 2010
Source: SGS Economics & Planning using data from Department of Planning & Community Development
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4.3 Section Summary
Population and employment projections to 2046 for the SLAs of Knox, the South East Region and
the MSD were developed using official government forecasts complemented with SGS modelling.
To 2046 the City of Knox is projected to grow by just over 26,000 people, housing around 185,000
people in total. However, this future rate of growth is half that of the projected growth rate of the
South East Region and the MSD as a whole.
Levels Annual Change CAGR %
1996 2011 2046 1996-2011
2011-46 1996-2011
2011-46
Population:
Knox (C)
South East Region
MSD
137,000
578,000
3,283,000
159,000
742,000
4,171,000
186,000
1,015,000
6,171,000
1,500
11,000
59,000
765
7,800
57,000
1.0%
1.7%
1.6%
0.4%
0.9%
1.1%
Employment:
Knox (C)
South East Region
MSD
60,000
260,250
1,560,000
75,000
350,000
2,177,000
99,000
532,000
3,473,000
1,000
5,900
41,000
700
5,250
37,000
1.5%
2.0%
2.2%
0.8%
1.2%
1.3%
Note: values are rounded off
Employment growth over the 2011-46 period is expected to be just shy of population growth over
this period, i.e. just under 25,000. Whilst commercial services employment is set to rise quite
robustly (~1.6% p.a.), industrial employment is set to decline over time in line with trends
observed for the broader MSD. Albeit industrial employment is set to fall, value added creation is
set to continue reflecting increasing productivity in the sector.
Employment in Knox (C)
1996 2011 2021 2046 CAGR %
1996-2011 CAGR % 2011-46
Primary 290 220 190 130 -1.8% -1.5%
Industry 30,100 33,600 34,900 32,500 0.7% -0.1%
Retail 8,500 9,900 11,100 12,600 1.0% 0.7%
Commercial 20,800 31,000 37,600 54,200 2.7% 1.6%
Total Employment 59,690 74,720 83,790 99,430 1.5% 0.8%
As a consequence of these changes, Knox’s share in total metropolitan employment is expected to
remain fairly stable across most service based industries. On the contrary, Knox’s employment
share in Construction and Wholesale Trade is set to fall over time. This is likely because industrial
activity is likely to move away from Knox over time.
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5 STRATEGIC POLICY CONTEXT
This section showcases that the existing regional and local strategic planning framework favours
high employment growth for the City of Knox and the wider South East Region, especially in higher
order services to sustain the regional economy into the future. This strategic framework also
identifies that the envisaged growth will require investments in multi-modal and more sustainable
modes of transport.
Some focus is also cast here on the capacity of Knox City Council to accommodate this growth, i.e.
land supply and any constrains thereof.
5.1 Metropolitan Policy Context
The present Victorian State Government has, at this point in time, not yet released a strategic land
use or transport plan for metropolitan Melbourne. The most recent State Government land use and
transport policies, compiled by the former Labour Government are inappropriate to review given
that the policies and strategies denoted in such plans are not necessarily endorsed by the present
Government. However, it should be noted that public transport to Rowville has, in some form or
another been in the public and political realm for several decades, regardless of the Government.
While no formal metropolitan land use or transport policy exists, the Liberal party’s pre-election
document, ‘Plan for Planning’ articulates an outcomes based approach to sustainable strategic
planning, one based on community and industry dialogue in the provision of services and
infrastructure. Council’s advocacy efforts that became manifest in community consultation as well
as SKM’s efforts at engaging the Knox community are thus in line with the government’s envisaged
policies.
5.2 South East Region Planning Context
5.2.1 Melbourne South East Regional Economic Strategy 2009-2030
Melbourne's South East (MSE) is a regional economic development alliance of eleven Local
Government municipalities, utility providers and the State and Federal Governments. The area
represented more than one million people and nearly 530,000 jobs as of 2006.
The MSE developed its Regional Economic Strategy with a forward focus over the next 20 years
and with the aim to attract more high value-adding, knowledge based and export orientated
businesses to the region. Among other things, this regional strategy identifies the following as
critical to achieve its aim:
Developing a business investment prospectus for the Region;
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Accelerating the development of the Advanced Business Services sector;
Capitalising on the MSE Technology Network;
Harnessing business leadership to drive regional clusters;
Making MSE climate change ready; and
Encouraging the adoption of best practice by the Region’s business community.
The Strategy clearly identifies the services sector as leading growth and change in the South East
economy. More importantly, attracting the services sector, especially Advanced Business Services,
and initiating change, will need to be underpinned and perhaps preceded by the provisioning of
high quality and fast public transport to the region. This is because the successful formation and
operation of these businesses will rely on the ability of the region to tap into the agglomeration
benefits already generated by the central Melbourne economy. As discussed by the World Bank
(2009), attempting to create central places or ‘growth poles’ in locations which are disconnected
from existing investment magnets is likely to end in failure.
5.3 Knox City Council Planning Context
Several of Council’s plans and strategies establish Knox’s local strategic planning framework.
Primary among these that were reviewed for the purposes of this study due to their pertinence
were:
The Knox Economic Development Strategy, 2008-18;
Knox City Council Vision 2025;
Knox City Council Plan 2009-13; and
Knox Economy Futures Study (2011).
This planning framework identifies Knox’s strengths and challenges over the next few years;
establishes priority objectives for progressing with the social and economic aspirations for the
community and actions to fulfil these objectives; and foreshadows a vision for what Knox should
embody by 2025. These issues are discussed in turn below.
5.3.1 Strengths and Challenges for Knox
Taken together, the following strengths and challenges for the City of Knox are identified by the
Knox Economic Development Strategy and the Futures Study:
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Strengths Challenges
A relatively diversified industry base with a
balance of sectoral employment between goods-
based, commerce-based and information and
finance-based industries.
Expected slowdown in population and household
growth over the next 15-20 years with a ageing
resident workforce.
Established industry infrastructure and linkages
with high quality business precincts, including
linkages with the National Centre for
Sustainability, Swinburne University of
Technology and TAFE, and proximity to Monash
University and the Australian synchrotron
project.
High reliance on Manufacturing with broader
metropolitan and nation-wide trends suggesting
a gradual economic transformation toward a
more services-oriented economy.
A low unemployment rate. Limited greenfield sites may constrain
development of land zoning, to accommodate
future land demand for residential and
commercial/ industrial purposes.
High purchasing power with comparatively high
levels of household income.
Lower order skill of resident workforce requires
import of skills and labour from other
municipalities.
Locational advantages including proximity to
Eastlink.
Poor provisioning of high quality public transport
services results in a high level of car
dependency, increased levels of congestion,
increased greenhouse gas emissions and more
sedentary lifestyles.
5.3.2 Opportunities and Actions for Sustainable Growth
The principal goal of the Knox Economic Development Strategy 2008-18 is to improve liveability
and wellbeing in the City through economic growth that creates high quality jobs; generates wealth
and investment; and helps ensure the City’s long term fiscal health. The strategy puts forth a
number of objectives to leverage opportunities for growth.
In addition, the Council Plan identifies a number of priority actions for Council to tackle the
challenges identified. These objectives and actions can be grouped into the following broad
categories:
Supporting and developing a network and hierarchy of integrated activity centres
o Development of Knox Central principal activity centre;
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o Fully developed and highly functional major, neighbourhood and local activity
centres.
o Work in partnership with key stakeholders and the Victorian State Government to
develop Knox Central to be the ‘Capital of the Eastern Suburbs’;
o Position Knox as a centre of excellence for environmental technologies and
services;
o Deliver catalyst projects to progress Knox Central and stimulate business
investment.
Establishing industry clusters and knowledge networks supporting them
o Establishment of sustainable energy efficient industry clusters and high-tech
learning centres;
o Support the development of the Scoresby/Rowville Employment Precinct,
incorporating best practice design to provide 7,000 new jobs by 2025; and
o Support development of the Bayswater/Bayswater North Industrial precinct.
o Strong secondary, tertiary and industry linkages providing for the needs of high
tech industries (support services, technical backup and marketing);
Facilitation of entrepreneurial activity
o A more balanced business mix, including more business support services and
tertiary industries;
o A strong Knox-wide industry network promoting Knox products and services
nationally and internationally;
o Establishment of a centre for entrepreneurial development integrating education,
new start-ups and business incubators.
Availability of world-competitive infrastructure including telecommunications and supporting
services.
Enhance liveability and amenity to live and work in the City of Knox
o Support greater opportunities for residents to live and work in Knox;
o Attract businesses to Knox through the provision of enhanced local amenity and
supportive infrastructure.
Advocacy efforts for availability of better transport provision
o Engage in advocacy to encourage improved integrated transport options for the
Knox Community;
o Advocate for the construction of a heavy rail link between Huntingdale and Rowville
to achieve improved accessibility within the southern half of the municipality and to
the wider metropolitan area;
o Promote non-car based transport modes through the municipality;
o Advocate for real options for transport to and from Activity Centres and residents’
homes which are of high quality and comparable to each other;
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o Facilitate the linking of public transport to employment precincts to provide
improved access for employees and movement of goods and services.
5.3.3 Vision for City of Knox
Vision 2025 consists of seven key themes that describe what Knox will be known for in 2025. These
themes and the attributes they incorporate are outlined below.
Accessible transport choices
o Excellent public transport options;
o Seamless connectivity to services and facilities within the municipality;
o Free flowing vehicular traffic.
A prosperous modern economy
o Leading edge, environmentally sustainable industry and technology;
o Contemporary business opportunities;
o Support for nationally recognised business precincts with support for
entrepreneurship;
o Retail and industrial business attraction.
Dynamic services and facilities
o Provide for quality medical, health and wellbeing services;
o Forge cutting edge partnerships with Government, public and private sectors in
education, research and knowledge sharing;
o Provide education and employment opportunities for one and all;
o Facilitate services that meet the changing demographic needs of the municipality.
Healthy, connected communities
o Supportive and inclusive communities;
o A safe haven to live;
o An abundance of community leaders;
o Motivated and valued community members;
o Communities which value diversity and provide diverse living spaces
Culturally rich and active communities
o Supporting community wide and local events, festivals and activities;
o Diverse cultural and artistic opportunities;
o Diverse leisure and recreational opportunities;
o Open spaces shared by all;
o Promote lifelong learning.
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Sustainable natural environment
o Leader in environmental management;
o A healthy, green and leafy environment.
Attractive and vibrant places
o Enhanced garden ambience;
o Great spaces and public places;
o Targeted activity-centred urban development;
o Quality urban landscape and design standards;
o Neighbourhood parks and open spaces.
The future Knox economy is envisaged to have a global reputation for innovation in the emerging
high technology and knowledge based industries, particularly specialising in the design and
production of sustainability and energy efficiency products and services. The established industries
of Advanced Manufacturing and Biotechnology would be further developed, profiting from their
proximity to the Scoresby Rowville Employment Precinct and the Synchrotron. In regards to
transport accessibility, the Council would like Knox to be a place in the future where car use is a
choice, not a necessity due to the availability of high quality public transport.
5.4 Section Summary
The Australian and metropolitan Melbourne economies are and will continue to be subject to
economic and structural shifts over time. The City of Knox would not be an exception to this. In
order for the municipality to embrace this structural change, it is imperative that it capitalises on
its strengths and overcomes identified challenges.
Notable priorities that have been identified include:
Consolidating the existing industry base (Advanced Manufacturing and a rapidly growing
services base) and provide for a well-networked, informed and knowledge intensive business
community in the City of Knox; and
Building on the existing activity centre hierarchy to provide for more employment and housing
opportunities for the people of Knox.
Crucial to achieving these priorities and the vision for Knox is the ability to provide improved
integrated transport options for the Knox Community, namely faster connectivity into a well-
established agglomeration hub of metropolitan Melbourne, i.e. the city centre. If the benefits
outlined via examined case studies later in the study in section 6 are any indication, several
advantages can be gained via better public transport provisioning for the City of Knox and the
wider metropolitan economy in general.
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6 CASE STUDY INVESTIGATIONS
This section reviews relevant case studies from Australian and international jurisdictions to assess
the short, medium and long-term impacts on residents and businesses during the construction and
operation phases of a major transport infrastructure project.
6.1 Introduction
Major transport projects are known to have both positive and adverse impacts, both during their
construction and operation phases.
The positive impacts of the construction phase of a project are increased trades employment as
well as transport related employment. On the contrary, there are nuisance costs, such as
construction noise and air pollution, vibration, disruption to existing services (such as road or rail
closures) and potentially reduced accessibility to homes, businesses and services that abut the
construction area. The adverse impacts are relatively easy to conceptualise, although difficult to
measure.
In contrast, the benefits and costs that derive over a longer time period from the operation of such
infrastructure are generally more difficult to capture and monetise. This is because major transport
projects yield changes to urban form, in particular, changes to population and employment
distribution which occur over a long period of time and are influenced by a range of factors. That is
to say the changes to a city are not only the result of a relative improvement in transport access,
but a result of a combination of other factors including macroeconomic forces, demographic shifts,
or targeted local initiatives. This is not to underwrite the value or necessity of transport
infrastructure. The history of cities is as good an indicator of the significant influence transport
infrastructure has on their development.
In investigating case studies to inform the costs and benefits that may flow from the proposed
Rowville rail extension, a local and international perspective has been adopted. Additionally, given
that transport projects tend to increase mobility and access, this section has reviewed both rail and
road projects It is acknowledged that while a rail project may derive slightly different spatial
outcomes to a road project, in principle some of the mobility and access benefits are comparable.
Consequently, SGS has reviewed the available evidence from both rail and road projects in gauging
potential consequences of the proposed Rowville rail extension on the local and wider metropolitan
economy.
6.2 Short Term Construction Phase Impacts
The construction of a railway or a road project, particularly in an established urban area brings
about a set of costs related to the nuisance of construction, such as noise and air pollution,
vibration, disruption to existing services (such as road or rail closures) and potentially decreased
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accessibility to homes, businesses and services that abut the construction area. Indeed,
consultation held by SKM when producing their feasibility study reinforced these concerns.
The immediate upshot or the primary benefit from the construction phase of rail infrastructure, as
with any major infrastructure project, is the employment that such construction generates.
6.2.1 Australian Experience
Recent experience from Australia highlights that whilst the nuisance impacts are inevitable, some
measures can be adopted during the design and construction phase to attenuate these impacts.
Rail investments in Perth and Sydney have followed processes to ensure the nuisance of
construction is addressed in the planning phase.
The Southern Suburbs Railway in Perth, Western Australia began operation in 2007. The line
originates at Perth Railway station and terminates 72 kilometres south in Mandurah, with 9 new
stations along the route. As part of the planning process, a Public Environmental Review was
carried out by the governing body, New Metro Rail. The guidelines of the review required full
consultation with members of the public and management of the operational noise and vibration
pollution emitted from the rail line. Day time and night time maximums were set for both sound
and vibration levels. Additional vibration criteria for regenerated noise from ground borne vibration
were set, with different maximums set for various built forms around the train line (Stedman,
2007). There were several mechanisms installed across the Southern Suburbs Railway to mitigate
noise and vibration. Approximately 6 kilometres of noise walls were installed, along with 1.4
kilometres of stone mastic asphalt road surfacing, 1.3 kilometres of double track vibration isolation
in City tunnels and 680 metres of double track ballast matting.
Similarly, in Sydney the Epping to Chatswood line, which began operation in 2009, confronted
nuisance issues, both during construction and operation. The line links the North Shore Line from
Chatswood to the Main North Line at Epping. The line consists of 12.5 kilometres of new rail, three
new stations (including one at Macquarie University) and the complete redevelopment of Epping
station. Noise reduction was a key concern for the Epping to Chatswood rail line, particularly in the
form of noise during construction and vibration from trains in the tunnel section during operation.
Mechanisms were put in place to protect the local communities from the impacts of the
construction phase of the Epping to Chatswood Line outside of the tunnel section. Noise reduction
techniques included the erection and construction of hoardings and the restriction of surface work
hours (Railcorp, 2011). To mitigate operating noise, rubber bearings were installed between the
concrete track slab and the tunnel structure (Design Build Source, 2011).
6.2.2 International Experience
Looking overseas, the Crossrail project in London currently under construction, is a 21 km rail
tunnel under central and east London. The link connects commuter and suburban services and key
locations such as Heathrow Airport, the West End, the City of London and Canary Wharf.
Construction is anticipated to take approximately 7 years.
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The construction of such a large tunnel creates economic stimulus on its own, with up to 14,000
people likely to be employed on the construction of Crossrail at its peak, with further jobs required
to supply the project during construction and providing services to those directly employed.
In addition, there are opportunity costs associated with delaying or failing to proceed with a
project. The cost increases can be ‘in scheme costs’ and planning and transport blight, reductions
in agglomeration benefits and delayed user benefits (Buchanan, 2007). A study into the London
Crossrail project identified that each year of delay significantly increases the costs of
implementation. Every one year delay to scheme implementation increases the scheme costs in
real terms due to expected price inflation within the construction sector at a faster rate than in the
economy as a whole. In addition changes over time in the relevant design standards and legislation
further raise the cost. The Crossrail team conclude that the cost of the project rises by some 3% in
real terms every year (Buchanan, 2007).
6.3 Long Term Operational Phase Impacts
In evaluating the costs and benefits of rail projects, a Cost Benefit Analysis (CBA) is the most
commonly used tool used to justify and prioritise projects. Traditional CBA encapsulates the cost of
infrastructure and other costs such as time, congestion and accidents, with the reductions in these
factors being the direct benefits of transport projects.
However many major projects have wider impacts. These wider impacts have not generally been
included in traditional Benefit Cost Ratios (BCR), but are often significant. Given the transformative
nature of the Rowville rail extension, wider economic benefits are of particular relevance to this
study, and as such are evaluated in detail in section 10. Wider impacts include effects on
agglomeration, productivity, competition and labour markets, as well as impacts on urban form,
and while it is widely accepted that the effects of such impacts are real, there is less agreement on
what this means for a project appraisal (Preston and Wall, 2008; OECD, 2011; Litman, 2011). By
placing rail investments in the broader context of helping to achieve wider national, regional and
local development objectives, analysis to consider the benefits that are not only attributed to
transport becomes possible (Banister and Thurstain-Goodwin, 2011). Some examples of standard
and wider economic impacts are as follows.
Standard Economic Impacts Wider Economic Impacts
Reductions in:
Travel time
Congestion
Accidents
Pollution
Noise
Waste
Improvements in:
Agglomeration
Productivity
Labour market benefits
Enhanced competition
Changes in urban form
Rowville Rail Project/ Economic Impact Study
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Although including wider economic benefits in transport related CBA projects is not uncommon,
many commentators acknowledge that there is difficultly in assessing such benefits. This can be
because the wider benefits of rail vary greatly from case to case, are difficult to predict, may be
redistributive benefits rather than net additional benefits, and may be difficult to distinguish from
other developments in the area, particularly given the time span of projects (Nash, 2009; Preston
and Wall, 2008). However, excluding impacts based on the grounds that they are poorly
understood becomes problematic when these impacts are essential to the project. Not including
these benefits where they are likely to exist tends to understate the benefits of transport projects
and risks the chance of underinvestment. As such, many CBAs that include wider benefits account
explicitly for uncertainty, and give BCRs with a high and low impact range (OECD, 2011).
6.3.1 Australian Experience
The urban form of major Australian cities has undergone a sea change due to major investments in
rail and road over the years. By way of example, pre 1950s Melbourne, based on rail and tram
mobility is drastically different in job and household clustering and density compared with the post
1950s car based suburbs of middle and outer Melbourne. More broadly it is difficult to gauge the
significance of past transport infrastructure investments on the rise and continued strength of
global cities such as New York, London, Paris and Tokyo, although it is inconceivable to imagine
these cities being as strong as they are today without their respective metros, tubes, subways and
above ground rail networks.
Unfortunately, there does not exist much evidence evaluating the impacts of past major transport
investments on the present day urban form or economic productivity of the city. Part of the reason
for this is data limitations and the inability to disentangle the specific effects of rail investments
from all other significant investments taking place simultaneously. More importantly, rail
investments in Australia made in the past were that of a metropolitan scale, with significant
investments in particular suburban locations a rare occurrence.
More recently, Ernst and Young (2010) evaluated the traditional and wider economic benefits of the
Victorian Transport Plan released in 2009. The wider benefits of the plan were evaluated at $30.3
billion, more than the estimated $28.1 billion of capital expenditure needed to implement the plan.
The wider economic benefits comprise of:
Imperfect competition ($4.4 billion) - the reduction in the cost of travel over the course of work
typically resulting in firms reducing prices and increasing output;
Increased labour supply ($11.7 billion) - reducing travel times for commuters increasing gross
product by attracting new workers, allowing existing workers to use their time savings to work
longer hours, and allowing existing workers to take up more desirable and productive jobs that
are located further away; and
Agglomeration ($14.2 billion) - the benefit firms receive from being in close proximity to one
another, with transport playing a role in reducing travel times of workers and freight, therefore
increasing the effective density of firms and workers that are within reach of a certain point.
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SGS’s modelling for previous assignment experience with the Victorian Departments of Planning
and Community Development and Transport, has also revealed the improvements in accessibility
brought about significant investments in road infrastructure in Victoria.
The improved road connections and the ensuing strengthening of agglomeration economies in
Melbourne has been measured by SGS by reference to Effective Job Density (EJD). SGS has used
the level of employment relative to the time taken to gain access to that employment and the
mode split that is currently experienced by those employees to better reflect the accessibility of
jobs to certain regions.
EastLink is a recent example of a change in EJD brought about by a transport project. Figure 24
overleaf presents the estimated impact on EJD before and post opening of the EastLink (and
employment growth and other minor transport improvements). The LGA of Greater Dandenong
experienced a significant uplift in EJD as a result of EastLink. Employment growth in Greater
Dandenong from 1999-2004 was 1.1 per cent. Once the construction road had commenced (pre-
empting the uplift in accessibility) employment growth increased to 2.1 per cent from 2005-2010
(which includes a period of flat employment growth related to the global economic slowdown).
There are a range of factors at play which could explain employment growth, but the changes in
accessibility appear related to improved economic outcomes.
Rowville Rail Project/ Economic Impact Study
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Figure 24 Effective Job Density Prior and Following EastLink
Prior Following
Source: SGS Economics and Planning
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6.3.2 International Experience
Internationally too, studies evaluating the benefits of investments in rail and road transport made
several years ago are hard to come by. Nonetheless, the available evidence points out that when
aggregating both the traditional forms of benefits of investing in transport and the wider economic
benefits, at least the new planned investments in metropolitan and suburban rail systems is
expected to yield higher benefits than planned costs.
An investigation into the benefits of improving rail services through the centre of Wales yielded a
BCR of 0.6 excluding the wider economic benefits. Including these benefits in turn boosted the BCR
in the range of 1.2 to 1.6 (Jacobs Consulting, 2010).
Wider economic impacts also contributed substantially to the viability of the Channel Tunnel Rail
Link in the UK. This rail project, linking London to the European fast rail network returned a BCR of
1.1 when excluding wider economic benefits. However, urban regeneration benefits were estimated
to be as high as £8 billion, leading to wider-economic benefits being critical to the justification of
the project (Preston and Wall, 2008).
The Crossrail project in London was identified to enable the regeneration of areas around other
stations along its route through improving accessibility with shorter journey times, and giving
employers better access to a larger, more highly skilled labour market with more choice of skilled
employees. In total, Crossrail’s wider impacts are estimated to be between £6 billion and £18
billion in welfare terms (at 2002 prices), exceeding the initial public sector funding required to build
Crossrail. Additionally, about 1,000 net additional jobs are anticipated to be created to operate and
maintain the railway once it is completed.
It has also been showcased that access increases total wealth through agglomeration, but it also
redistributes wealth through allowing relative greater access to wealth generating activities
(Levinson, 2010). By contrast poor transport is seen by business as a serious constraint on their
growth potential (Clayton et al, 2011). High car dependency and the risk of congestion are
exacerbated by limited public transport and relieving or alleviating the risk of congestion through
rail can help support future growth (Clayton et al, 2011).
However, for the effects of rail investments to have maximum impact certain conditions are stated
to be important. These include: stations being at the centre of regeneration and redevelopment;
regional services being well integrated with local and other regional transport services; and high
frequency services (Preston and Wall, 2008; Nuworsoo and Deakin, 2009).
However, improved accessibility is not necessarily sufficient to revitalise or act as a catalyst to
growth, and investments generally need to be accompanied by supporting land use policies,
transport ridership incentives, consumer acceptance and private investment (Litman, 2011a;
Banister and Thurstain-Goodwin, 2011). Private investment was identified as critical to achieve the
benefits of transport investments, but private investment was generally only found to take place
after transport funding was secured (Banister and Thurstain-Goodwin, 2011).
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6.4 Section Summary
In reviewing relevant literature to the Rowville rail extension, impacts from the construction and
operation phases were investigated using both rail and road case studies from within Australia and
internationally. It is acknowledged that while a rail project may derive slightly different spatial
outcomes to a road project, in principle some of the mobility and access benefits are comparable.
Consequently, SGS has reviewed the available evidence from both rail and road projects in gauging
potential consequences of the proposed Rowville rail extension on the local and wider metropolitan
economy.
These studies suggest that the positive impacts during the construction phase of a major transport
infrastructure project include employment generation (especially trades employment). Adverse
impacts include nuisance costs such as noise, vibrations and temporary road closures. Given the
inevitability of such costs, mitigating or alleviating the extent of such costs is best addressed
during the planning stage of the project.
Evaluating the long term operational costs and benefits of transport investments are typically
investigated through Cost Benefit Analysis (CBA). CBA has traditionally evaluated the direct costs
of construction and operation with the standard benefits delivered by such projects, those being
reduced travel time, congestion and accidents. However, increasingly the wider economic benefits
of infrastructure investment are becoming commonplace in project evaluation. These wider
economic benefits, such as agglomeration, competition and labour markets, and impacts on urban
form are acknowledged as being difficult to evaluate yet critical outcomes of large scale transport
projects.
Whilst the long-term impacts of investments made in post-war infrastructure development on the
current urban form of cities is unavailable, several studies from international jurisdictions have
pointed to the significant wider economic impacts of investing in infrastructure for the metropolis
and locality under considerations.
SGS’s modelling also indicates that within Victoria, the opening of the Eastlink improved jobs
accessibility for residents along the corridor serviced by the project. A similar outcome is also
envisaged for Peninsula Link.
The available evidence has shown that improved transport and accessibility provides for better
connectivity between a firm and its suppliers and customers, which promotes healthy competition
between firms as reduced travel costs helps firms reduce prices and increase output. Such
investments also tend to benefit both Manufacturing and service oriented firms, and their workers
alike, as not only travel times are reduced promoting productivity enhancements and
agglomeration of firms in close proximity.
If the outcomes of the available evidence are any indication, the proposed rail extension to
Rowville will yield an array of benefits. The magnitude of the increases in population and
employment likely to be brought about due to the project is shown in section 8 below. In addition,
the wider economic benefits from investing in Rowville Rail project are measured in section 10.
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7 CONSULTATION FINDINGS
Over and above consultations held by SKM, SGS held its own discussions with local businesses of
Knox to gauge their response on how the Project might reshape development patterns in the City
and the South East Region. Opinions were sought using both a face to face interactive forum as
well as via an online forum where the community/ businesses were asked to fill out a
questionnaire. Consultees views on short-term nuisance impacts created during the construction
phase of the Project were also gauged. This section summarises the findings from this consultation.
If the case studies are any indication, the proposed Rowville rail extension will have both positive
long term and adverse short-term impacts during the construction and operation phases of the
project. Maximising the benefits and mitigating the adverse impacts is greatly assisted by
community engagement and consultation.
The focus of community consultation held by SKM for its feasibility report was different and
perhaps more extensive compared to that held by SGS, and was to gauge among other things,
stakeholders’ opinion on best aligned rail routes, alternative transport options apart from rail and in
general, support for the project.
In contrast, the purpose of SGS’s consultation was to focus more on short-term impacts and to
gauge the extent of impacts on various industry sectors of the local/ wider region. The qualitative
analysis collected via this consultation process was used to cross-check results of the accessibility
modelling undertaken by SGS to forecast the direct impacts of the project.
Consultation with local businesses took two forms: Council and SGS held a consultation session
with businesses of Knox, and a survey was distributed to businesses within the municipality, with
responses collated by Council. In total, 117 responses were collated by Council with further
representation available at the consultation session.
The survey allowed for both qualitative and quantitative responses. Whilst the detailed survey
questionnaire is shown in Appendix B, suffice here to say that survey participants were asked to
provide details of their business, their transport requirements, and the impact the proposed rail
project may have on both their business and the broader regional economy.
7.1 Respondent Profile
Of businesses that responded to the survey, almost one third were in the Manufacturing industry.
Wholesale and Retail traders each accounted for 16% of respondents, followed by Professional and
Business Services firms, which made up 10% of respondents (refer Figure 25).
A majority of respondent businesses employed between 5 and 19 employees (43%) and have been
in continuous operation on their present site for between 10 and 20 years (33%).
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Businesses surveyed drew customers from a wide and varied geographic area, with 34% primarily
drawing customers from the wider Melbourne area and 21% primarily drawing customers from
within Knox itself. Almost 10% of businesses sold primarily to overseas clients.
Suppliers were also generally sourced from across the wider metropolitan region, although a
substantial number of suppliers were primarily sourced from overseas (over 25%). This perhaps
reflects the higher order manufacturing nature of the businesses in the region requiring more
sophisticated inputs. Interestingly, the local businesses surveyed sourced employees from across
the metropolitan region, with almost an equal spread of employees being located within Knox, its
surrounding LGAs and the broader Melbourne region.
The dominance of the private vehicle as the mode of transport for customers, suppliers and
employees was quite evident. Suppliers were identified as being the most likely to travel by private
vehicle, followed by customers and finally employees. Public transport was most commonly used by
employees.
Given the high dependence on the private vehicle, not just in Knox, but more broadly in the outer
suburbs of Melbourne, road congestion and the subsequent travel delays were unsurprisingly
frequently raised as a problem in accessing businesses. However, few businesses (14%) identified
that they had considered changing locations or business operations as a result of such congestion
(please refer to the Figure 26 overleaf).
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Figure 25 Survey Respondent Profile
Industry sector of survey
respondents
Employment size of survey
respondents
Mode of travel of customers,
suppliers and employees of
survey respondents
0%
10%
20%
30%
40%
Manufacturing Wholesale Trade
Other Services Retail Trade Professional & Business Services,
Construction Education and Training
Accomodation and Food Services
0%
15%
30%
45%
5-19 20-150 0-4 150+
0%
25%
50%
75%
100%
Customers Supplers Employees
Car/Private Transport Public Transport Bus/Train/Tram etc.) Walk
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7.2 Consultation Outcomes
After developing a profile of local businesses and transport issues the survey turned to the impacts
of the proposed Rowville rail extension, both during the construction and operation.
Overall, local businesses were highly supportive of the proposed rail line, with 80% believing that
business and residential growth would strengthen with the construction of the rail line. That is,
respondents were of the view that population and employment growth within Knox will be over and
above business as usual trends with the construction of the project (refer Figure 26).
Over 80% of the businesses responded in the affirmative that the proposed rail line will help their
business operations. This high degree of affirmation was echoed by respondents from nearly all
industry sectors. The only two exceptions were Wholesale Trade and Education & Training with
nearly 35% of respondents from these industry sectors suggesting that the proposed train line will
not have any impact on their business.
The overwhelming view is that Manufacturing; Retail Trade; Professional, Scientific & Technical
Services; and Education and Training, will benefit most from the provision of the rail line.
Qualitatively a raft of long term benefits were identified associated with the construction and
operations of the proposed rail line. These included:
A greater ability for businesses to attract workers, drawing employees from further afield;
Improved reliability in employees getting to work, both due to transport alternatives being
available and through reduced congestion on the road network;
Improved transport efficiencies leading to reduced costs, particularly in the movement of
freight and supplies;
Increased customer base, through accessibility improvements and residential growth and
densification in the local area;
Enabling employment opportunities for people who do not own a car or cannot drive;
Improved accessibility of businesses to visiting interstate customers or employees; and
Intensification of land uses leading to a greater number of business support firms.
Additionally, some businesses saw the construction phase as a potential benefit, with construction
requiring goods and or labour that could be sourced locally. However, there were concerns
regarding the negative impacts that could be brought about during the construction phase. These
included:
Temporary delays and congestion on the road network, notably Wellington Road;
Reduced clientele due to access inconveniences; and
Reduced access to Stud Park shopping centre.
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Interestingly though, while many businesses supported the construction of the rail line and
believed its provision would improve business prospects, few considered that these benefits would
persuade them to relocate closer to the proposed route to improve accessibility to either to
customers, suppliers or employees. Only between 25% and 50% of the respondents belonging to
Construction; Retail Trade; and Professional, Scientific & Business Services, suggested that they
might consider relocation. Incidentally, a large proportion of businesses within these particular
sectors had perceived the rail line to have a beneficial impact on their operations. It appears that
businesses which perceive the rail line to have any positive impacts are more likely to relocate
while others are likely to be sticky with their location choice.
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Figure 26 Survey Outcome Summary
Would business & residential
growth strengthen with the
construction of the rail line
over and above business as
usual growth?
Would the proposed rail line
help your business?
0%
25%
50%
75%
100%
Wholesale Trade
Manufacturing Other Services Construction Retail Trade Education and Training
Accomodation and Food Services
Professional & Business Services,
Total
Business & residential growth would strengthen
Business & residential growth would NOT strengthen
0%
25%
50%
75%
100%
Wholesale Trade
Manufacturing Other Services Construction Retail Trade Education and Training
Accomodation and Food Services
Professional & Business Services,
Total
Proposed rail line will help my business
Proposed rail line will NOT help my business
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Which sectors are likely to
be benefit the most?
Are you likely to relocate
closer to a proposed rail
station to improve your
access to suppliers/
customers/ employees?
0%
25%
50%
75%
100%
Retail Trade Education and Training
Manufacturing Professional and Business
Service
Wholesale Trade
Transport and Logistics
Construciton Other Firms Utilities
0%
25%
50%
75%
100%
Wholesale Trade
Manufacturing Other Services Construction Retail Trade Education and Training
Accomodation and Food Services
Professional & Business Services,
Total
Likely to relocate closer to a proposed station
UNLIKELY to relocate closer to a proposed station
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7.3 Section Summary
There is widespread belief that the provision of the rail line will help businesses and boost the
employment and residential growth of the corridor over and above forecast business as usual
trends.
Businesses from currently established industry sectors within the City of Knox, namely,
Manufacturing and Professional & Business sectors were highly optimistic of the positive spinoffs of
the project. On the other hand, a relatively high proportion of firms belonging to Wholesale Trade &
Education & Training (~35%) suggested that the rail line will not help improve their business
operations.
Nonetheless, it was widely perceived by respondents that businesses within the Education &
Training sector, amongst firms in other sectors, including Manufacturing; Professional & Business;
and Retail Trade firms will benefit the most from the provision of the rail line.
Whilst the belief of beneficial impacts of the project was widespread, relatively few businesses are
likely to relocate closer to a proposed rail station to improve accessibility to customers, suppliers,
employees.
There are some concerns about nuisance impacts during the construction phase but their extent or
scope could not be gauged from the responses received.
In sum, respondent views from consultation suggest positive spinoffs for the local community and
economy of Knox.
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8 ACCESSIBILITY CHANGE ANALYSIS
This section presents the results of SGS’ in house accessibility modelling to quantify the impact of
the Project on the additional population and employment that the City of Knox and the South East
region might host because of the Project over and above that which would become manifest in a
business as usual/ Base Case scenario.
In effect, the outcome of this section is the estimate of the ‘direct’ impacts of the Project on the
economy of Knox during the operations phase of the project.
8.1 Land Use and Accessibility
Well established economic theory indicates that over time firms will tend to locate closer to areas
that improve their land use efficiency. Locating in areas with superior accessibility reduces
transaction costs through ease of contact with suppliers and customers. Crucially, this also
increases access to a skilled labour force.
The theoretical underpinnings of the relationship between land price and accessibility can be seen
graphically in Figure 27.
Figure 27 Demand for Different Land Use as a Function of Accessibility
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Whilst all firms prefer locations of high levels of accessibility their ability to pay for locational
advantages will differ, as do their aggregate land use demands. Land use demands between
industries and the collar of the workers (Blue and White) generally differ based on the functioning
of their industries.
Land use demands by service industries are small relative to other industries, such as
Manufacturing and Wholesale Trade. Those industries require large amounts of land, relative to
service firms. Furthermore, land rents can be shared across multiple firms as office towers use the
relatively cheaper option of expanding vertically, rather than having large parcels of land. This
contributes to the ability of service firms to locate within the confines of a heavily dense area of
employment and population such as the CBD, whereas Manufacturing and Wholesale Trade tend to
locate further away from highly dense areas for their larger land requirements.
Ways to improve accessibility of firms differ across industries based on their customer and supplier
base. Generally, Manufacturing requires quality road infrastructure and as a consequence tend to
locate closer to areas where they have access to major road networks. Both their suppliers and
customers also tend to have a similar accessibility requirement and therefore efficiencies can be
gained for those industries when they locate closer to points of road infrastructure. This is not
necessarily the case for service industries.
Whilst all firms require timely access to their suppliers, employees and customers their strategic
ability to access those people differ based on the function of their business models.
Opportunities for access to employment apply in a similar way to households as they do for
industries. People, over time, will adjust their residential location due to a wide range of factors,
some of which are access to employment, education, essential services and recreation. Literature
indicates that these choices tend to be constrained due to factors such as family and historical ties
to a region or corridor.
For these reasons many people and families may tend to locate ‘within corridors’, rather than
moving ‘across town’. However, when moves are made within this context the relative accessibility
of the two areas is a key consideration.
These theoretical predications are amply borne out by recent experience in Australian cities,
particularly with respect to the Western Ring Road, CityLink, EastLink and Westlink (M7) in Sydney.
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8.2 Accessibility Shifts Model
To estimate the induced change in households and employment for the new rail corridor resulting
from the introduction of the Rowville rail line a detailed analysis of changes in accessibility was
undertaken by SGS. With the introduction of the new rail line into the region two key components
related to an areas access to jobs and services will be impacted and subsequently estimated.
These are:
Changes in travel times; and/or
Changes in mode share uses (Public Transport versus Private Vehicles)
The biggest impact will be focused around the new rail corridor, which will likely receive improved
travel times to many locations right across metropolitan Melbourne. However, there will be varying
impacts right across the metropolitan landscape as the relative “rankings” of different locations
accessibility changes.
In order to quantify the level of change resulting from the Rowville rail line two key pieces of
analysis related to accessibility have been undertaken:
A historical analysis looking at changes in accessibility caused by recent major infrastructure
projects, such as Citylink, and the subsequent actual changes in the spatial distribution of
population and firms; and
Quantifying the likely changes in accessibility as a result of the Rowville rail line and applying
the historical analysis results to provide a robust evidence based estimate of the induced land
uses changes.
It should be noted that for this analysis the change in the distribution of people and firms is purely
based on the induced effects of improved accessibility. While not captured in this analysis, in
addition to these impacts, there can often be one or more targeted intervention developments near
key locations (i.e. new stations) that may further capitalise on the improved accessibility of the
corridor.
The historical analysis and subsequent application to the Rowville rail corridor is outlined in greater
detail in the following sections.
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8.2.1 Historical Relationship Analysis
Over the past 15 years there have been several major road infrastructure projects that have had a
very significant impact on the accessibility of certain locations across metropolitan Melbourne, such
as:
1996 to 2001 – Western Ring Road
2001 to 2006 – Citylink
2006 to 2011 – Eastlink and major improvements to the Monash Freeway and the West Gate
Bridge
Furthermore, over this period detailed information regarding the distribution and accessibility
changes of Melbourne has been made available from the ABS Census and the DoT (Melbourne
Integrated Transport Model). This data has all been aggregated to the Statistical Local Area level
for four time periods; 1996, 2001, 2006 and 2011 for this analysis.
While all these projects are road based projects they help to provide an evidence base for
understanding the degree to which firms and households change their locational preferences as a
result of shifts in the metropolitan accessibility contours.
A detailed statistical regression analysis was undertaken using this historical data to test and
quantify this conceptual theory. This statistical analysis tests the following theory:
All else being equal, a SLAs share of metropolitan Melbourne’s total employment by industry sector
is based on two broad factors:
Share of population/dwellings8; and
Accessibility9
In addition, if all else was equal, a SLAs share of metropolitan Melbourne’s total housing stock is
based on two key factors:
the urban land supply10; and
Accessibility.
This concept suggests that the strong growth within a growth area is a result of increased land
supply, while the recent strong growth within the inner city is a result of increased accessibility.
Furthermore, if a location’s accessibility is improved it will increase the level of demand and in turn
8 The share of population/housing has been included to capture the distributional changes of underlying population serving employment.
9 Where, accessibility is defined in its broadest sense. That is, a locations access to activity centres, skilled workers, employment opportunities, services, education, transport infrastructure, restaurants, etc.
10 The amount of urban land has been included to capture the varying geographic sizes of SLAs. That is, if SLA X is 10 times larger than SLA Y, all else being equal, it should have 10 times the amount of dwellings.
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growth rate, similar to releasing land within a growth area. The strength of this relationship varies
from industry to industry depending on its requirements and willingness/capacity to pay for more
accessible locations.
For this analysis these two factors have been identified as the key considerations in the distribution
of households and employment. However, it is noted that in reality the exact spatial distribution of
households and employment is far more complex, particularly at a very local level, where in fact
there is a wide range of other localised issues, historical factors and development trends that also
determine the locational choices of firms and people.
We have assumed that all these other factors bearing out of localised issues are indeed
inherent and therefore captured within the base case projections. Consequently, any
changes observed under the Project Case scenario are over and above these other
contextual issues.
In order to undertake this statistical analysis three key data variables were synthesised by SGS for
each SLA across metropolitan Melbourne from 1996 to 2011;
SLAs share of total employment by industry sector and households;
SLAs share of total urban land; and
SLAs relative accessibility.
Population and Employment
Historical employment and housing data for 1996, 2001, 2006 and 2011 by SLA has been collated
from a range of ABS data sets including the past three Censuses (1996, 2001 and 2006), the ABS
labour force survey data11 and ABS estimated resident population12. See Appendix A for a full
methodological overview of how historical household and employment estimates were developed.
Total employment by industry sector and households for each SLA is converted to a share of
overall metropolitan Melbourne levels. The share of metropolitan Melbourne was used as it was
assumed that there is a wide range of other external factors such as international and interstate
migration, economic trends etc that influence the total amount of population and employment in a
city as a whole. Furthermore, it is assumed that a project such as this will only have an influence in
the reorganisation (or locational decisions) of people/firms within Melbourne and will not be able to
influence a person from Sydney, for example. In other words, it was assumed that a project of this
scale is unlikely to affect the overall employment outcomes for the MSD with only reorganisation of
employment within the metropolitan economy envisaged.
Urban Land
There is a range of data sources that could be utilised (such as the Victorian Planning Provisions) to
calculate the amount of total urban land that an SLA has as a proportion of metropolitan
11 ABS Cat. No. 6202.0
12 ABS Cat. No 3201.0
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Melbourne. However, many of these datasets are difficult to get consistently across a 15 year
historical time period (1996-2011). Therefore, a geographic unit referred to as Urban Centre
Locality (UCL) was used as a broad estimate of the amount of urban land. A UCL measures the
broad extent of urbanisation for a city/town and is published by the ABS for the 1996, 2001 and
2006 Censuses. An estimate of the Melbourne UCL for 2011 was made by adding in all future 2010
Urban Development Program broad hectare sites to the 2006 UCL. This provided a consistent
measure across all time periods.
As the UCL grows for an area (i.e. due to green-field land being released) the proportion of total
Melbourne UCL for other established locations was found to decrease. This statistic isolates dwelling
growth related to changes in accessibility from dwelling growth related to increased development
opportunities.
Accessibility
SGS has developed a measure of accessibility within a specified geographical region and the ability
to access overall economic activity across the wider MSD, known as Effective Job Density (EJD).
EJD measures the total number of jobs across the MSD and weights them according to the time
taken to access those jobs by different modes of transport, i.e. public transport and private
vehicles.
This analysis relies on travel time matrices that estimate the length of time taken to travel from
one SLA to another SLA within the MSD, both by private car and public transport.
EJD enables a more ‘real life’ representation of the proximity (in terms of travel time) of
employment and services. EJD has been estimated as follows:
Where:
= Effective Job Density for SLA i
= per cent of work trips which involve public transport for zone j
= number of jobs/employment within zone j
= time it takes to travel on public transport from zone i to zone j
= time it takes to travel by private vehicle from zone i to zone j
The equation constructs an EJD for each Statistical Local Area (SLA) across the MSD. A graphic
representation of the estimated EJD across the MSD at 2006 is shown in Figure 28.
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 73
Figure 28 Effective Job Density MSD - 2006
Source: SGS Economics & Planning
The EJD of an SLA reveals at least two things.
Firstly, it reveals how interconnected an area is to all the jobs in Melbourne. The smaller the
time to access other areas of the MSD the lower the level of discounting those jobs receive,
thus increasing the overall EJD score. Due to this reason the Melbourne (C) – Inner SLA
consistently receives the highest EJD score across all years analysed. This is due to a high
concentration of employment in the areas surrounding Melbourne (C) – Inner and the
significant transport infrastructure that allows speedy transport between the inner areas.
Secondly, the EJD score is also a proxy for the access to other businesses, which may
represent customers, competitors, suppliers and access to services. The tendency of businesses
to locate in areas with high EJD reveals a preference for certain characteristics of an area and
also reveals those industries that have a negative relationship with EJD.
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 74
The choice to locate in different areas of the city is driven by many factors, including accessibility.
Furthermore, absolute accessibility is not necessarily the most crucial factor in locational choice. If
this were the case there would be a relatively higher demand for residential dwellings within the
CBD. A more logical measure is relative accessibility across different areas. This allows the
comparison of areas that have similar characteristics to be compared to each other more
objectively. For example, if two growth corridors had the same distribution of services, housing etc.
and only differed in terms of accessibility then the growth corridor with relatively higher
accessibility would be expected to have stronger population and employment growth.
Quantifying changes to relative accessibility was performed through translating the absolute EJD’s
across the four years of analysis into a 0 to 1 index, i.e. a relative EJD index. The index is created
using the SLA that has the highest EJD. This was found to be Melbourne (C) – Inner consistently
across all years of analysis), which provides a ceiling for the index (a score of 1). To provide a floor
to the index the converse is performed. Consistently Yarra Ranges (C) – Central was found to have
the lowest EJD and is thus given a score of 0.
The equation used to calculate the relative EJD ranking is shown below and a ranking of selected
SLAs is shown in Table 10.
Where:
= Effective Job Density for SLA i
= the SLA found to have the lowest EJD amongst all MSD SLAs
= the SLA found to have the highest EJD amongst all MSD SLAs
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 75
Table 10 Relative EJD Index, Selected SLAs, 1996-2011
SLA 1996 2001 2006 2011
Melbourne (C) - Inner 1.00 1.00 1.00 1.00
Melbourne (C) - S'bank-D'lands 0.77 0.82 0.82 0.77
Melbourne (C) - Remainder 0.63 0.64 0.65 0.61
Knox (C) - North-East 0.23 0.23 0.24 0.22
Knox (C) - North-West 0.28 0.28 0.30 0.27
Knox (C) - South 0.28 0.27 0.29 0.27
Monash (C) - South-West 0.44 0.44 0.45 0.42
Monash (C) - Waverley East 0.36 0.35 0.37 0.34
Monash (C) - Waverley West 0.40 0.40 0.42 0.39
Gr. Dandenong (C) - Dandenong 0.33 0.33 0.35 0.32
Gr. Dandenong (C) Bal 0.32 0.31 0.32 0.30
Casey (C) - Berwick 0.17 0.17 0.22 0.18
Casey (C) - Cranbourne 0.19 0.19 0.21 0.20
Casey (C) - Hallam 0.26 0.26 0.28 0.26
Casey (C) - South 0.09 0.09 0.10 0.09
Source: SGS Economics and Planning
A spatial example of Relative EJD is shown in Figure 29. The inner areas of Melbourne clearly have
a significantly higher ranking on the relative EJD scale. This reduces as the distance from the CBD
increases. Melbourne south-east region with its employment concentrations, substantial road and
rail infrastructure tends to maintain a higher EJD score relative to the other areas of the MSD as
distance from the CBD increases.
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 76
Figure 29 Relative EJD 2011
Source: SGS Economics and Planning
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 77
Regression Analysis
The regression equation used to estimate the relationship between industry movements,
accessibility and households is shown below.
Where:
= Relative Effective Job Density for SLA i
= The share of an industry’s metropolitan employment within SLA i
= The share of metropolitan Households within SLA i
= Constant term
= Error term
Accessibility also induces locational change for households, given they can access a greater amount
of services and employment opportunities.
The regression equation that estimates accessibility induced household changes is shown below.
Where:
= Relative Effective Job Density for SLA i
= The share of Households within SLA i
= The share of overall urbanised areas within SLA i
= Constant term
= Error term
When applying this statistical relationship to the Rowville Rail project the key coefficient relates to
Relative EJD. This coefficient represents the increase in a location’s share of metropolitan
Melbourne’s total households or employment if a location was to shift from being the least
accessible location to being the most accessible location.
Figure 30 presents the relative EJD coefficient for each employment industry sector and
households. This can be interpreted as follows: If the accessibility of a location increased from 0 to
1 it would increase its share of metropolitan Melbourne’s total housing stock by 0.02 (or 2%), for
example.
Given much of the total housing and employment stock is already established, we see that the
coefficient is relatively small (i.e. 2%). However, as a share of growth within a defined period this
could potentially represent a substantial proportion of total growth.
Over the past 15 years much of Melbourne’s housing growth has been focused on two broad
regions, fringe growth areas (about half) or inner city Melbourne (about one fifth). Greenfield
growth is predominately a result of large amounts of land supply from significant areas of land
being rezoned as urban residential. While strong growth within the inner city can be predominately
attributed to a preference to be close to jobs, services and the city’s core (i.e. accessibility). As a
result Households have been estimated to have a strong propensity to relocate due to changes in
accessibility.
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 78
In relation to a firm’s locational preference, it can be seen that as previously suggested the service
sector and higher value added industries exhibit a higher preference for more accessible locations.
Information Media & Telecommunications, Professional, Scientific & Technical Services and Finance
& Insurance are some of the most susceptible industries to changes in accessibility.
Agriculture experiences the only negative coefficient with relative EJD. Agriculture uses typically
require large and relatively cheap land parcels away from major centres. Furthermore, particularly
within the fringe growth areas, farm land within the MSD has been rezoned and changed uses to
housing or other employment.
Figure 30 Relative EJD Regression Coefficients
Source: SGS Economics and Planning
For employment there is a secondary effect resulting from the estimated shifts in households. That
is, many industries depend on a local population as either customers or skilled workers. Therefore,
an increase in population in an area often results in a further increase in population servicing
employment. Figure 31 displays the coefficients related to a change in household share for each of
the employment industry sectors.
As expected industries that thrive on proximity to population, such as Retail Services, Health Care,
Education and Training and Accommodation and Food Services all have a strong positive
relationship with an induced change in households.
-0.01 -0.005 0 0.005 0.01 0.015 0.02 0.025
Households
Information Media and Telecommunications
Professional, Scientific and Technical Services
Public Administration and Safety
Financial and Insurance Services
Arts and Recreation Services
Administrative and Support Services
Accommodation and Food Services
Electricity, Gas, Water and Waste Services
Rental, Hiring and Real Estate Services
Other Services
Transport Postal and Warehousing
Mining
Health Care and Social Assistance
Education and Training
Wholesale Trade
Retail Trade
Construction
Manufacturing
Agriculture, Foresty and Fishing
Relative EJD Regression Coefficient
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 79
Figure 31 Household Share Regression Coefficients
Source: SGS Economics and Planning
-0.2 -0.15 -0.1 -0.05 0 0.05 0.1 0.15 0.2 0.25 0.3
Manufacturing
Wholesale Trade
Retail Trade
Health Care and Social Assistance
Other Services
Construction
Education and Training
Rental, Hiring and Real Estate Services
Transport Postal and Warehousing
Accommodation and Food Services
Administrative and Support Services
Electricity, Gas, Water and Waste Services
Public Administration and Safety
Arts and Recreation Services
Professional, Scientific and Technical Services
Financial and Insurance Services
Mining
Agriculture, Foresty and Fishing
Information Media and Telecommunications
Household Share Coefficient
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 80
8.2.2 Accessibility Induced Land Use Shifts
The statistical relationships derived from the previous section (the historical analysis) have been
applied to estimated changes in accessibility (EJD) resulting from the introduction of the Rowville
rail line at 2021 and 2046. The choice of these two years was dictated by the availability of travel
time matrices provided by SKM. Consequently, any adverse impacts during the operations phase of
the project, whilst being acknowledged, were unable to be quantified.
Forecasting land use scenarios due to proposed infrastructure projects depends largely on the
accessibility changes that the proposed project will deliver. SKM have provided projected travel
times and trip shares (for car and public transport) for the Base and Project case at 2021 and
2046.
Using the provided travel time matrices and SGS base case forecasts (see Appendix C for
methodology) future EJD calculations were produced for 2021 and 2046 for both the Base and
Project cases.
Figure 32 and Figure 33 display the relative EJD changes that have been estimated.
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 81
Figure 32 Change in Relative EJD 2021
Source: SGS Economics and Planning
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 82
Figure 33 Change in Relative EJD 2046
Source: SGS Economics and Planning
EJD calculations in 2021 and 2046 not only reflect travel time savings, but also include changes to
the public transport mode shares. As the rail corridor is completed and people begin to use the
public transport network to access employment and services it adjusts the share of public transport
use. SKM provided projected trips by mode that indicated the base and project uses of the public
transport and the subsequent changes to mode share as shown below in Figure 34.
The inclusion of the rail corridor reduces the reliance of the area on car transport. Knox – South
gains the largest mode share change within the City of Knox with a reduction in car usage of 1% in
2021 and 1.4% in 2046. Monash experiences the largest reduction in car usage with the LGA as a
whole reducing car usage by 1% and 1.5% in 2021 and 2046, respectively.
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 83
Figure 34 Induced Car Mode Share Changes
Source: SGS Economics & Planning
The difference in the relative EJD index for each SLA between the project and base cases was
applied to the results from the historical regression analysis to estimate the induced changes to the
spatial distribution of households and employment by industry. Constraints were applied to ensure
that the total employment and population level of metropolitan Melbourne was unchanged and that
no single location saw an unrealistic reduction in employment or households relative to current
levels and base case trends. That is, the analysis removed any outliers from the analysis.
Population estimates were finally developed based on households size estimates from the base
case projections.
-1.0%
-0.3%-0.2%
-1.3% -1.3%
-0.7%
0.03%
-0.01% -0.03% -0.02%
0.17%
0.05%
-0.5%
-1.4%
-0.5%
-0.2%
-2.1%-2.0%
-0.8%
0.07%0.03% 0.07% 0.05% 0.08% 0.05%
-0.8%
-2.5%
-2.0%
-1.5%
-1.0%
-0.5%
0.0%
0.5%
South North-West
Knox (C) -North-East
Monash (C) - South-
West
Monash (C) - Waverley
East
Monash (C) - Waverley
West
Gr. Dandenong
(C) -
Dandenong
Gr. Dandenong
(C) BalCasey (C) - Hallam
Casey (C) - Berwick
Casey (C) - Cranbourn
e
Casey (C) - South
Knox (C) Monash (C) Greater Dandenong (C) Casey (C)
Eastern Region
Pro
ject
Ind
uce
d C
ar S
har
e C
han
ge
2021 Car Share Reduction 2046 Car Share Reduction
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 84
8.3 Anticipated Induced Impacts
8.3.1 Households
The greatest beneficiary of the project is expected to be Knox with an anticipated increase of 410
and 1,030 households respectively in 2021 and 2046 over and above Base case projections.
Overall the South East Region experiences a household increase of 450 in 2021 and 1,230 in 2046
over and above the Base Case.
Household growth rates between 2011 and 2021 are significantly smaller in absolute number and
growth rate when compared with 2021 and 2046 period. This is because households and indeed
firms are likely to respond with a lag in delivery of superior transport infrastructure. Indeed, results
from the consultation exercise held by SGS suggested that businesses were reluctant to change
location due to the provision of rail infrastructure. Consequently, induced household and
employment changes as estimated by SGS are small. The results of the consultation exercise
therefore seem to conform with estimated changes by SGS using the accessibility modelling.
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 85
Table 11 Induced Household Changes
Number of Households (#) Change in Households (#)
Average Annual Growth Rate (%)
LGA Scenario 2011 2021 2046 2011-21 2021-46 2011-21 2021-46
Knox (C)
Base Case 55,250 62,200 71,790 6,940 9,590 1.19% 0.58%
Project Case 55,250 62,610 72,820 7,360 10,210 1.26% 0.61%
Change from
Base Case
410 1,030 410 620 0.07% 0.03%
% Change
from Base
Case
0.67% 1.44% 5.98% 6.44% 5.58% 5.37%
Monash
(C)
Base Case 64,690 75,700 91,650 11,010 15,950 1.58% 0.77%
Project Case 64,690 75,740 91,960 11,050 16,220 1.59% 0.78%
Change from
Base Case
40 310 40 270 0.01% 0.01%
% Change
from Base
Case
0.05% 0.34% 0.36% 1.72% 0.34% 1.50%
Gr.
Dandenong (C)
Base Case 48,990 57,310 80,660 8,330 23,340 1.58% 1.38%
Project Case 48,990 57,300 80,660 8,310 23,360 1.58% 1.38%
Change from
Base Case
-20 0 -20 20 0.00% 0.00%
% Change
from Base
Case
-0.03% 0.00% -0.22% 0.09% -0.11% 0.05%
Casey (C)
Base Case 86,650 112,340 140,730 25,690 28,390 2.63% 0.91%
Project Case 86,650 112,330 140,740 25,680 28,410 2.63% 0.91%
Change from
Base Case
-10 10 -10 20 0.00% 0.00%
% Change
from Base
Case
-0.01% 0.01% -0.03% 0.07% -0.03% 0.07%
South East
Region
Base Case 255,580 307,550 384,820 51,970 77,280 1.87% 0.90%
Project Case 255,580 307,980 386,180 52,400 78,210 1.88% 0.91%
Change from
Base Case
430 1,360 430 930 0.01% 0.01%
% Change
from Base
Case
0.14% 0.35% 0.83% 1.20% 0.76% 0.95%
Source: SGS Economics and Planning
Overall MSD changes for households are displayed in Figure 35 and Figure 36 for the two examined
time periods. Households that relocate into the South East Region are centred around Knox in both
the 2021 and 2046 intervals. Initially, these households are drawn from the inner areas, and in
particular, the south eastern corridor. By 2046, established households from Melbourne’s north
east are also anticipated to move towards Knox due to better transport connections that the area is
likely to become host to.
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 86
Figure 35 Household Induced Changes 2021
Source: SGS Economics and Planning
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 87
Figure 36 Household Induced Changes 2046
Source: SGS Economics and Planning
Household and population movements are small relative to other infrastructure projects undertaken
in the recent past (Westlink, Eastlink, the Western Ring Road etc.). However, this is merely a
reflection of the relative size of the project and the use of public transport across the MSD.
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 88
8.3.2 Employment
Changes in employment are similar to the estimated induced changes in households, i.e., the
magnitude of employment changes is observed to be smaller up to 2021, but is seen to grow by
2046.
Overall, the employment impact to the South East Region raises employment levels by 280 in 2021
and by 820 in 2046.
The City of Knox experiences the largest increase to employment over and above the Base Case.
Employment increases by 260 and 420 across the two periods of analysis over and above the Base
Case, in the two examined periods of 2021 and 2046.
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 89
Table 12 Induced Employment Changes
Employment Number (#) Employment Change (#)
Average Annual Growth Rate (%)
LGA Scenario 2011 2021 2046 2011-21 2021-46 2011-21 2021-46
Knox (C)
Base Case 74,650 83,640 99,390 8,990 15,750 1.14% 0.69%
Project Case
74,650 83,900 100,060 9,250 16,170 1.18% 0.71%
Change
from Base Case
260 680 260 420 0.03% 0.01%
% Change
from Base
Case
0.31% 0.68% 2.91% 2.64% 2.75% 2.10%
Monash (C)
Base Case 117,720 137,980 173,870 20,270 35,890 1.60% 0.93%
Project
Case
117,720 138,010 174,080 20,290 36,070 1.60% 0.93%
Change
from Base
Case
20 210 20 180 0.00% 0.00%
% Change
from Base
Case
0.02% 0.12% 0.12% 0.50% 0.14% 0.43%
Gr.
Dandenong (C)
Base Case 95,430 115,050 145,310 19,620 30,260 1.89% 0.94%
Project
Case
95,430 115,040 145,310 19,610 30,270 1.89% 0.94%
Change
from Base
Case
-10 0 -10 10 0.00% 0.00%
% Change
from Base
Case
-0.01% 0.00% -0.06% 0.04% -0.05% 0.04%
Casey (C)
Base Case 61,290 71,150 113,720 9,860 42,570 1.50% 1.89%
Project
Case
61,290 71,150 113,730 9,860 42,580 1.50% 1.89%
Change
from Base
Case
0 10 0 10 0.00% 0.00%
% Change
from Base
Case
-0.01% 0.01% -0.04% 0.03% 0.00% 0.02%
South East
Region
Base Case 349,090 407,820 532,290 58,740 124,470 1.57% 1.07%
Project
Case
349,090 408,100 533,180 59,010 125,090 1.57% 1.08%
Change
from Base
Case
270 890 270 620 0.01% 0.00%
% Change
from Base
Case
0.07% 0.17% 0.46% 0.50% 0.44% 0.37%
Source: SGS Economics and Planning
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 90
Induced employment growth resulted in Knox contributed the majority of the employment
increases during both periods examined and comprised 92% of the overall South East Region
employment increase in the period to 2021 and then 51% in the period 2021 – 2046.
Figure 37 displays the employment changes across the MSD. The inner areas, such as Melbourne
(C), Yarra (C) and Port Phillip (C) incur the largest employment losses as these areas can be
considered within the sphere of influence of the suggested project, with the economic literature
suggesting that accessibility induced locational changes are generally fall within the corridor, rather
than across town. Employment increases are clustered within the Knox LGA and even more within
Knox - South.
Figure 37 Induced Employment Change 2021
Source: SGS Economics and Planning
The rate of employment change increases dramatically in the second period of analysis and
therefore further increases the employment increase for the City of Knox and the South East
Region as a whole (see Figure 38).
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 91
Figure 38 Induced Employment Change 2046
Source: SGS Economics and Planning
Whilst employment change in the region resulting from the project is not trajectory shifting, it is
important to note the changes across broad industrial categories. At 2021 Knox is estimated to
have an additional 280 jobs over and above the Base Case. Of these jobs 71.7% are commercial,
knowledge intensive jobs (i.e. Professional and Scientific Services, Education, Financial and
Insurance Services etc.). Growth of industry based jobs, (i.e. Manufacturing, Construction,
Wholesale Trade etc.) represents the remaining 19.9% of overall growth.
Table 13 displays the projected changes to the broad industry categories at 2021 and their
respective contribution to overall growth.
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 92
Table 13 Induced Broad Industry Group Changes 2021
Primary Industry Retail Commercial Total
Knox (C) -1 54 24 194 270
Monash (C) 0 5 2 18 26
Gr. Dandenong (C) 0 -2 -1 -8 -12
Casey (C) 0 -1 0 -3 -4
South East Region -1 56 25 201 280
Contribution to Growth % -0.5% 19.9% 8.9% 71.7% 100.0%
Source: SGS Economics and Planning
Between the 2021-46 period, the contribution of commercial services employment rises to 76.8%
in 2046 towards overall growth, as shown in Table 14. On the other hand, absolute industrial and
retail employment will also rise but the relative contribution of industry is expected to fall in total
employment growth to 15%.
Table 14 Induced Broad Industry Group Changes 2046
Primary Industry Retail Commercial Total
Knox (C) -2 95 52 478 622
Monash (C) -1 29 16 145 189
Gr. Dandenong (C) 0 0 0 1 2
Casey (C) 0 1 1 6 7
South East Region -3 125 68 630 820
Contribution to Growth % -0.4% 15.2% 8.3% 76.8% 100.0%
Source: SGS Economics and Planning
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 93
8.4 Section Summary
SGS used past observed relationships between changes in accessibility and the induced land use
changes to quantitatively model the induced land use changes, i.e. changes in the locations of
households and employment across metropolitan Melbourne following the delivery of the proposed
Rowville rail line.
This analysis suggested that whilst the Project will not alter the metropolitan scale of households
and employment, more households and employment will move into the examined South East
Region of this study, and in particular, the City of Knox.
The analysis suggested that by 2021:
An additional ~410 households will reside in Knox over and above the estimated Base Case of
62,200.
Knox will be the largest beneficiary due to the Project with total households in the South East
Region rising by ~430 by this timeframe due to the Project over and above the projected Base
Case.
Employment in Knox will be ~260 higher compared to the projected Base Case of ~84,000.
Most change will be in Commercial Services employment followed by Industry based
employment, i.e. the Project is likely to induce more industrial and commercial based
businesses in the local economy.
Employment in the South East Region would be ~280 over and above the projected Base Case.
In the long run however, by 2046, when the effects of the Project would have become fully
manifest:
Knox is likely to host an additional ~1,000 households and ~700 additional employees over
and above its projected Base Case of ~72,000 households and ~99,000 employees
respectively.
The South East Region in turn is likely to host an additional ~1,350 households and ~1,100
additional employees over and above its projected Base Case of ~385,000 households and
~533,000 employees respectively.
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 94
9 ESTIMATED IMPACTS OF PROJECT
This section presents the estimated economic impacts of the Project on the local municipality, the
South East Region and the wider metropolitan and state-wide economies.
The estimated impacts include the direct and indirect impacts on income, value-added and
employment, both during the construction and operation phases of the Project.
9.1 Estimation Methodology
SGS has used the REMPLAN model13 to estimate the indirect impacts of the initial induced changes/
stimuli. REMPLAN is a user friendly regional economic analysis package which provides detailed
region specific data for up to 111 different industry sectors. Economic data is sourced from the
ABS. The indirect impacts of the initial stimuli are estimated using input output tables and
multipliers.
In essence, the REMPLAN model takes the inter-industry relationships (buyer–supplier
transactions) that are measured by the ABS in the National Accounts,14 and scales these
relationships down to a state level initially and then, subsequently, to a regional level, i.e. using
available datasets and accepted mathematical techniques.
A regional input-output model provides several advantages. The first of these is to offer a better
understanding of the relative performance of economic sectors in the regional economy.
Information gained from the model includes estimates of regional output, regional exports, regional
imports, wages paid by each of the sectors and the value of their local interactions, which can be
viewed alongside sectoral employment figures. It is possible to examine the types of inputs used
by each sector and determine the source of supply of these inputs, be it local or from outside the
defined region of interest. The destination of outputs and whether this is to be used as an input for
other sectors in the region, for final consumption by local consumers, or whether these outputs will
go beyond the region in the form of intermediate or final goods and services for exports can also
be determined. The most important outcome of all this is to provide a picture of the interdependent
nature of the regional economy and the way all these individual pieces of data fit together. Actions
by one sector will have ramifications on many of the other sectors operating in the region.
The most useful results of the input-output model are a set of regional industry specific multipliers
which estimate how spending in a specific regional industry, via the assessed direct impacts
(stimuli), flows through to total regional:
Output (or income);
13 February 2012 release provided to SGS by Compelling Economics, the producers of REMPLAN.
14 Particularly the Australian Input-Output Tables (ABS Cat. No. 5209.0).
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 95
Value added; and
Full time equivalent employment levels.
The direct/ flow-on impacts for the region’s economy comprise industrial effects (the increased
output generated by servicing industry sectors in response to the direct change in output and
demand) and consumption effects (As output increases, so too does employment and wages and
salaries paid to local employees. Part of this additional income to households is used for
consumption in the local economy which leads to further increases in demand and output). Taken
together, the direct and indirect impacts are aggregated to estimate the overall economic impact of
the project during its construction and operational phases.
Quantification of impacts can alert regional planners to the need for additional work skills,
retraining, employment programs, infrastructure changes and further opportunities for industrial
support in the region, or indeed, more advocacy efforts. It can also help planners prioritise in terms
of competing strategies and help determine which strategy best matches the particular need of the
region in terms of output, value added and employment.
9.1.1 Assumptions and Limitations
Input output modelling has some limitations, as follows, but it is a cost effective technique,
recognising that the only feasible alternative is utilising partial or general equilibrium econometric
models, which are expensive and which are calibrated for estimation using geographic regions
which do not align well with municipal boundaries.
The input output (econometric) model assumes relationships between industries are static over
the forecast period. That is, productivity improvements are not factored in and historic
relationships are assumed to hold.
The input output (econometric) model derives relationships between industries using total
production estimates. Consequently, the relationships are ‘average’, whereas the stimulus used
as an input is ‘marginal’. Such an approach does not account for any ‘underutilised capacity’ at
the industry level or additional economies of scale that might ensue, as production expands
from its existing base. In other words, a $10 direct impact in industry X will have the same
multipliers associated with the impact as would a $10 million impact.15
As already mentioned, all of the stimuli are assumed to be ‘new’ economic activities for each
regional economy. That is, crowding out or industry substitution effects are assumed to be
negligible, meaning that key economic inputs such as labour and capital are assumed to be
unconstrained, i.e. there is sufficient slack in the economy to service these stimuli without
transferring significant resources from other productive uses. It also means that the activities
that are promoted by the subject project do not adversely affect operations elsewhere.
15 SGS understands that the REMPLAN model takes the capacity of a region to service the initial stimulus into consideration.
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 96
9.2 Estimated Impacts of Construction Phase
The estimated cumulative costs (over the 4 years construction period) and derived annual
construction costs are shown below. It should be noted that these costs do not include the costs of
procuring trains, as these carriages/ trains might be imported.
Table 15 Estimated Direct Construction Costs of Proposed Rowville Rail
Cumulative (4 year construction period)
Rail Construction Stations Total
Monash (C) $1,540 mn $600 mn $2,140 mn
Knox (C) $550 mn $200 mn $750 mn
Annual
Rail Construction Stations Total
Monash (C) $385 mn $150 mn $535 mn
Knox (C) $138 mn $50 mn $188 mn
Source: SGS Economics and Planning
Over the construction phase spanning from 2016 onto 2020, $188 million is likely to be spent
annually on construction in the City of Knox, which is taken to be the estimated annual direct
stimulus for the local economy. In total, $750 million is likely to be spent in Knox over the 4 year
construction period. At this stage, SGS does not have any advice whether any of the construction
will be outsourced or not. For the purposes of this assessment, we have assumed that all
construction and associated services will be sourced from within the municipality. Consequently,
the estimated indirect impacts for the Knox economy could be overstated; nonetheless, the
estimated indirect impacts for the wider MSD and Victorian economies would perhaps be more
robust.
For the purposes of this assessment, the relevant multipliers used pertain to the industry of ‘Heavy
& Civil Engineering Construction’.
The results indicate that the total construction phase of the project (over the 4 year period) will:
Generate approximately 650 jobs and $173 million in value added in Knox.
Generate a total of $1.6 billion in total output and $550 million in total value added for the
Knox economy, and generate approximately 3,600 jobs due to the flow on effects on other
industries and worker spending.
For Victoria, the total induced impacts are estimated at:
o $2.3 billion in output;
o $865 million in value added; and
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 97
o Create approximately 5,600 jobs.
Table 16 Estimated Total Impacts (Direct + Indirect) of Construction Phase
of the Proposed Rowville Line
Knox (C)
Direct Impacts Total Impacts
Output ($ Million) $750 mn $1,665 mn
Employment (Jobs) 645 3,599
Value-Added ($ Million) $173 mn $553 mn
South East Region
Direct Impacts Total Impacts
Output ($ Million) $750 mn $1,789 mn
Employment (Jobs) 645 3,935
Value-Added ($ Million) $173 mn $603 mn
MSD
Direct Impacts Total Impacts
Output ($ Million) $750 mn $2,124 mn
Employment (Jobs) 645 4,923
Value-Added ($ Million) $173 mn $775 mn
Victoria
Direct Impacts Total Impacts
Output ($ Million) $750 mn $2,341 mn
Employment (Jobs) 645 5,607
Value-Added ($ Million) $173 mn $865 mn
Source: SGS Economics and Planning
The industry-wide breakdown of direct and total impacts on the value added of City of Knox is
presented in Figure 39 overleaf. The analysis shows that apart from the construction sector, the
proposal rail construction will benefit Manufacturing; Rental, Hiring & Real Estate Services;
Financial & Insurance Services; Professional, Scientific & Technical Services; Wholesale & Retail
Trade; and other industries.
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 98
Figure 39 Industry-Wide Impacts of Project Construction on Knox (C) Value
Added ($ Million)
Source: SGS Economics and Planning
9.3 Estimated Impacts During Operations Phase
As pointed out in the aforementioned section, construction of the Project will induce more residents
and employment within Knox. The extent of these impacts is shown in section 8.3 above (refer
Table 11 and Table 12).
Indeed, both induced household changes and induced employment changes in the region will
increase the direct local expenditure in the Knox economy, which will flow through to other sectors
of the economy via economy wide linkages. These impacts would be mutually exclusive too and
consequently, their impacts would be additive.
The estimated induced changes will in turn also impact expenditures in the South East Region, MSD
and the Victorian economies, because of the linkages of the Knox economy with these wider
economies via purchase/ sales.
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9.3.1 Scope and Assumptions
It must be borne in mind that the induced dwelling and employment changes within Knox are
detracting dwellings and employment from other parts of the MSD, i.e. the metropolitan wide
number of households and employment is held constant by the analysis in the Base Case and
Project Case, i.e. with and without project scenarios. A reduction in dwellings and employment
elsewhere in the metropolitan economy as they move towards the South East Region will have
consequential adverse impacts on these respective local economies.
The assessment presented here only considers the impacts of the induced changes within the City
of Knox on its own regional economy and the wider economies of the South East Region, the MSD
and Victoria. A net assessment of the combined effects of the induced positive changes in Knox and
corresponding induced negative changes elsewhere is beyond the scope of this study due to
unavailability of region specific multipliers across the MSD.
Nonetheless, the analysis of the wider economic benefits presented in the next section (i.e. section
10 of this report) provides a net assessment of the metropolitan wide effects of changes in
productivity due to the proposed Rowville rail project.
9.3.2 Impacts of Induced Dwellings
The induced number of households in Knox at 2021 and 2046 because of the project over and
above the Base Case will induce local consumption, within the economy, too. In order to estimate
the direct/ initial stimulus on local expenditures generated by these households, SGS:
Estimated per household expenditure in 2011 by dividing total local household consumption
with the total number of households in the municipality in the year. It was found that on
average, a household in the City of Knox spent $67,000 annually on local consumption, with
total household consumption in the municipality measured at ~$3.8 billion in the year.
Estimated the total induced consumption of the additional households by multiplying the
estimated per household consumption (estimated in 2011 dollars) with the induced number of
households in the region at 2021 and 2046 over and above the Base Case.
Results of this exercise are reported in Table 17 overleaf. Assuming that consumption patterns of
households stay fairly consistent over time, these results suggest that total induced consumption
within Knox would be ~$27.6 million in 2021 and increased further to ~$69 million by 2046 over
and above the Base Case due to the induced increase in the number of dwellings in the
municipality.
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 100
Table 17 Estimated Induced Direct Dwelling Consumption (in 2011$)
Total Dwelling Consumption
in 2011 ($ Million)
Per Dwelling Consumption
in 2011
Induced Dwelling Consumption (Estimated in 2011 $ Million)
Total Induced Consumption
in 2021
Total Induced Consumption
in 2046
Agriculture, Forestry & Fishing $4 $66 $0.03 $0.07
Mining $0 $0 $0.00 $0.00
Manufacturing $708 $12,266 $5.09 $12.67
Electricity, Gas, Water & Waste Services $35 $605 $0.25 $0.62
Construction $8 $137 $0.06 $0.14
Wholesale Trade $327 $5,675 $2.35 $5.86
Retail Trade $527 $9,140 $3.79 $9.44
Accommodation & Food Services $258 $4,465 $1.85 $4.61
Transport, Postal & Warehousing $69 $1,193 $0.50 $1.23
Information Media & Telecommunications $60 $1,041 $0.43 $1.08
Financial & Insurance Services $276 $4,788 $1.99 $4.94
Rental, Hiring & Real Estate Services $1,062 $18,416 $7.64 $19.02
Professional, Scientific & Technical Services $15 $265 $0.11 $0.27
Administrative & Support Services $6 $106 $0.04 $0.11
Public Administration & Safety $5 $80 $0.03 $0.08
Education &Training $114 $1,974 $0.82 $2.04
Health Care & Social Assistance $173 $3,006 $1.25 $3.10
Arts & Recreation Services $65 $1,125 $0.47 $1.16
Other Services $137 $2,368 $0.98 $2.44
Local Expenditure $3,849 $66,717 $27.68 $68.89
Source: SGS Economics & Planning
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 101
The estimated total impacts (i.e. direct and indirect impacts) of the induced dwelling changes in
Knox on its own economy, and the economies of the South East Region, MSD and Victoria, due to
the estimated induced direct consumption in Knox are shown below. Refer to Table 18, Table 19,
Table 20 and Table 21 overleaf for results. More detailed data showing the industry-wise
breakdown of output, value-added and employment is provided in Appendix E.
Impacts on Knox (C)
From an estimated induced increase in household consumption of $27.6 million within the City of
Knox by 2021:
Total output, including all direct, industrial and consumption effects is estimated to increase by
up to $45.18 million, representing an aggregate output multiplier of 1.63.
The corresponding creation of direct jobs is estimated at 109 jobs. From this direct expansion
in the economy, total employment, including all direct, industrial and consumption effects is
estimated to increase by up to 167 jobs, representing an aggregate employment multiplier of
1.53.
The corresponding increase in direct value-added is estimated at $14.4 million. From this direct
expansion in the economy, total value-added, including all direct, industrial and consumption
effects is estimated to increase by up to $22.5 million, representing an aggregate value-added
multiplier of 1.56.
By 2046, total induced household consumption would have risen by $68.9 million within the
municipality over and above the Base Case. This estimated increase in consumption will support:
Total output of $112.4 million;
Creation of 272 direct jobs and gain of a further 143 jobs due to the indirect impacts; and
Direct value-added to the tune of $35.9 million and total value-added of up to $56 million
within the Knox economy.
Of course, the economy of Knox is not insulated. Any induced changes within Knox will have ripple
effects throughout the South East Region, metropolitan and Victorian economies because of income
leakages and regional imports and exports from and to Knox. These impacts are assessed below.
By its very scope, it is taken as a given that the economic activity generated in the wider
benchmarked economies will be greater than the municipality. This reflects the depth and scope of
economic linkages that the more diverse South East Region, metropolitan and Victorian economies
encompass, i.e. when compared to the City of Knox.
Rowville Rail Project/ Economic Impact Study
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Table 18 Impacts of Induced Dwelling Changes in Knox (C) on Knox (C)
Effects in 2021
Direct Impacts Total Impacts
Output ($ Million) $28 mn $45 mn
Employment (Jobs) 109 167
Value-Added ($ Million) $14 mn $23 mn
Effects in 2046
Direct Impacts Total Impacts
Output ($ Million) $69 mn $112 mn
Employment (Jobs) 272 415
Value-Added ($ Million) $36 mn $56 mn
Source: SGS Economics & Planning
Table 19 Impacts of Induced Dwelling Changes in Knox (C) on South East
Region
Effects in 2021
Direct Impacts Total Impacts
Output ($ Million) $28 mn $48 mn
Employment (Jobs) 109 176
Value-Added ($ Million) $14 mn $24 mn
Effects in 2046
Direct Impacts Total Impacts
Output ($ Million) $69 mn $121 mn
Employment (Jobs) 272 439
Value-Added ($ Million) $36 mn $59 mn
Source: SGS Economics & Planning
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 103
Table 20 Impacts of Induced Dwelling Changes in Knox (C) on MSD
Effects in 2021
Direct Impacts Total Impacts
Output ($ Million) $28 mn $59 mn
Employment (Jobs) 109 208
Value-Added ($ Million) $14 mn $29 mn
Effects in 2046
Direct Impacts Total Impacts
Output ($ Million) $69 mn $148 mn
Employment (Jobs) 272 517
Value-Added ($ Million) $36 mn $73 mn
Source: SGS Economics & Planning
Table 21 Impacts of Induced Dwelling Changes on Victoria
Effects in 2021
Direct Impacts Total Impacts
Output ($ Million) $28 mn $63 mn
Employment (Jobs) 109 219
Value-Added ($ Million) $14 mn $31 mn
Effects in 2046
Direct Impacts Total Impacts
Output ($ Million) $69 mn $158 mn
Employment (Jobs) 272 545
Value-Added ($ Million) $36 mn $77 mn
Source: SGS Economics & Planning
Impacts on South East Region
By 2046, total induced household consumption within the City of Knox would have risen by $68.9
million over and above the Base Case. This estimated increase in consumption will support:
A total output of $121 million;
Creation of 272 direct jobs and gain of a further 167 jobs due to the indirect impacts; and
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 104
Direct value-added to the tune of $36 million and total value-added of up to $59 million
within the South East Region.
Impacts on MSD
By 2046, total induced household consumption within the City of Knox would have risen by $68.9
million over and above the Base Case. This estimated increase in consumption will support:
A total output of $148 million;
Creation of 269 direct jobs and gain of a further 248 jobs due to the indirect impacts; and
Direct value-added to the tune of $35.9 million and total value-added of up to $73 million
within the metropolitan economy.
Impacts on Victoria
The estimated impacts on the Victorian economy by 2046 would be as follows:
$158 million in total output;
269 direct jobs with further support for 277 indirect jobs; and
$36 million in initial value-added and $77 million in total value-added.
9.3.3 Impacts of Induced Employment
The estimated total impacts (i.e. direct and indirect impacts) of the induced employment change in
Knox on its own economy and the economies of the South East Region, MSD and Victoria, due to
the estimated induced direct employment in Knox are shown below. Refer to Table 22, Table 23,
Table 24 and Table 25 overleaf for results. More detailed data showing the industry-wise
breakdown of output, value-added and employment is provided in Appendix E.
Impacts on Knox (C)
By 2021, the economy of Knox would host ~262 additional jobs over and above the Base Case due
to induced employment changes (refer Table 22 overleaf). This initial induced employment change
is expected to support:
A direct increase in output of $76 million and total output, including all direct, industrial and
consumption effects of up to $131 million, representing an output multiplier of 1.73;
Total employment, including all direct, industrial and consumption effects, of up to 447 jobs;
and
A direct increase in value-added of ~$37.6 million with total value-added, including all direct,
industrial and consumption effects, rising by up to $63 million, representing a value-added
multiplier of 1.68
within the Knox economy.
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 105
By 2046, Knox would host an additional ~678 jobs over and above the Base Case in that year .
This induced employment change is expected to support:
A direct increase in output of $188 million and total output, including all direct, industrial and
consumption effects of up to $327 million;
Total employment, including all direct, industrial and consumption effects, of up to 1,151 jobs;
and
A direct increase in value-added of ~$99 million with total value-added, including all direct,
industrial and consumption effects, rising by up to $165 million
within the Knox economy.
As stated before, the economy of Knox is not insulated. Any induced changes within the Knox
economy will have ripple effects throughout the South East Region, metropolitan and Victorian
economies because of income leakages and regional imports and exports from and to Knox. These
impacts are assessed below. By its very scope, it is taken as a given that the economic activity
generated in the wider benchmarked economies will be greater than the municipality. This reflects
the depth and scope of economic linkages that the more diverse South east Region, metropolitan
and Victorian economies encompass, i.e. when compared to the City of Knox.
Table 22 Impacts of Induced Employment Changes in Knox (C) on Knox (C)
Effects in 2021
Direct Impacts Total Impacts
Employment (Jobs) 262 447
Output ($ Million) $76 mn $131 mn
Value-Added ($ Million) $38 mn $63 mn
Effects in 2046
Direct Impacts Total Impacts
Employment (Jobs) 678 1,151
Output ($ Million) $188 mn $327 mn
Value-Added ($ Million) $99 mn $165 mn
Source: SGS Economics & Planning
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 106
Table 23 Impacts of Induced Employment Changes in Knox (C) on South
East Region
Effects in 2021
Direct Impacts Total Impacts
Employment (Jobs) 262 477
Output ($ Million) $76 mn $141 mn
Value-Added ($ Million) $38 mn $67 mn
Effects in 2046
Direct Impacts Total Impacts
Employment (Jobs) 678 1226
Output ($ Million) $188 mn $351 mn
Value-Added ($ Million) $99 mn $175 mn
Source: SGS Economics & Planning
Table 24 Impacts of Induced Employment Changes in Knox (C) on MSD
Effects in 2021
Direct Impacts Total Impacts
Employment (Jobs) 262 591
Output ($ Million) $76 mn $182 mn
Value-Added ($ Million) $38 mn $87 mn
Effects in 2046
Direct Impacts Total Impacts
Employment (Jobs) 678 1,522
Output ($ Million) $188 mn $455 mn
Value-Added ($ Million) $99 mn $226 mn
Source: SGS Economics & Planning
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 107
Table 25 Impacts of Induced Employment Changes in Knox (C) on Victoria
Effects in 2021
Direct Impacts Total Impacts
Employment (Jobs) 262 626
Output ($ Million) $76 mn $194 mn
Value-Added ($ Million) $38 mn $92 mn
Effects in 2046
Direct Impacts Total Impacts
Employment (Jobs) 678 1,606
Output ($ Million) $188 mn $483 mn
Value-Added ($ Million) $99 mn $238 mn
Source: SGS Economics & Planning
Impacts on South East Region
By 2046, an increase of ~678 jobs within the City of Knox over and above the Base Case is
expected to support:
$351 million in output;
A total of 1,226 jobs; and
$175 million in total value-added
Within the south East Region.
Impacts on MSD
By 2046, an increase in ~678 jobs within the City of Knox is expected to support:
A total output of $455 million;
Creation of a total of 1,522 jobs (both direct and indirect); and
Total value-added of up to $226 million
within the metropolitan economy.
Impacts on Victoria
The estimated impacts on the Victorian economy by 2046 would be as follows:
$483 million in total output;
Over 1,600 total jobs; and
$238 million in value-added.
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 108
9.3.4 Total Estimated Impacts of Project Operations
Aggregating the impacts of induced households’ consumption and induced employment, it is found
that the direct impacts on output for the City of Knox are estimated at $270 million by 2046 with
approximately $140 million in additional value-added and 950 additional jobs over and above the
Base scenario (refer Table 26 below).
Table 26 Impacts of Project Operations by 2046
Knox (C)
Direct Impacts Total Impacts
Output ($ Million) $270 mn $440 mn
Employment (Jobs) 950 1,570
Value-Added ($ Million) $140 mn $230 mn
South East Region
Direct Impacts Total Impacts
Output ($ Million) $270 mn $480 mn
Employment (Jobs) 950 1,670
Value-Added ($ Million) $140 mn $240 mn
MSD
Direct Impacts Total Impacts
Output ($ Million) $270 mn $610 mn
Employment (Jobs) 950 2,040
Value-Added ($ Million) $140 mn $300 mn
Victoria
Direct Impacts Total Impacts
Output ($ Million) $270 mn $650 mn
Employment (Jobs) 950 2,160
Value-Added ($ Million) $140 mn $320 mn
Source: SGS Economics & Planning
Notes: Values are rounded off.
Indeed, total impacts (including both direct and indirect/ flow-on impacts) are found to be much
higher: $440 million in output, $230 million in value-added and ~1,570 jobs.
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 109
Industry-wide breakdown of direct and total impacts on the City of Knox are presented in Figure
40. The analysis shows that the total induced changes (dwellings and employment) are most likely
to benefit the higher-order services, including Finance & Insurance and Professional, Scientific &
Technical Services. These services are likely to service the local residents of the region, but more
importantly, provide support and advice to the highly sophisticated manufacturing sector, which in
turn, is likely to benefit to the tune of $14 million by then.
Figure 40 Industry-Wide Impacts of Project Operations on Knox (C) Value
Added By 2046 ($ Million)
Source: SGS Economics & Planning
The Victoria economy is expected to gain ~$650 million in output, $320 million in value-added and
2,160 jobs by 2046.
As mentioned before though, the assessment for the wider economies of the South East Region,
the MSD and Victoria does not take into effect the adverse effects of induced negative changes in
household consumption and employment elsewhere in the economy as households and
employment is redistributed within metropolitan Melbourne towards Knox due to the Project.
The next section considers the net impacts on changes to metropolitan environmental emissions
and productivity due to the proposed Rowville rail. It incorporates both the adverse effects of a loss
in employment locations in certain parts of the MSD at the expense of the others to consider a net
effect on the metropolitan economy.
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9.4 Section Summary
Results indicate that the construction of the proposal rail spanning over the four year construction
phase is likely to;
Generate $750 million in direct output and $173 million in value-added, supporting
employment of nearly 650 jobs within the City of Knox.
Due to the industry’s backward and forward linkages, this direct spending and employment
generation is likely to generate a total of $1.6 billion in total output and $553 million in total
value added, supporting nearly 3,600 jobs within the Knox economy.
Support nearly 5,600 total jobs in the State of Victoria creating nearly $2.4 billion in total
output and $870 million in value added.
By 2046, total effects of the operations of the proposed rail (including the effects of increased
household spending and new employment) were estimated as follows:
$260 million in direct income and $140 million in direct value added for the City of Knox,
supporting nearly 950 jobs.
Due to the industry’s backward and forward linkages, this direct spending and employment
generation is likely to generate a total of $440 million in total output and $230 million in total
value added, supporting nearly 1,600 jobs within the Knox economy.
Victorian output and value-added created would be nearly $650 million and $320 million
respectively, providing employment to nearly 2,200 employees.
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 111
10 WIDER ECONOMIC BENEFITS OF PROJECT
This section presents the estimated environmental impacts and wider economic benefits of the
Project on the municipality of Knox and the wider metropolitan economy. This includes the
environmental savings brought about by reduction in greenhouse gas emissions; and wider
economic impacts showcased via improvements in effective job density.
10.1 Estimated Environmental Savings
The Victorian Department of Transport produces default costs of externalities associated with
vehicle transport. Third party costs of private vehicle transport were estimated to be 0.77 cents for
every vehicle kilometre travelled (vkt) in 2006, equating to 0.87 cents per vkt expressed in current
value dollars. These third party costs include: cost of air pollutants including carbon monoxide,
nitrous oxide, particulate matter, non methane volatile organic compounds, as well as greenhouse
gases.
Using the hypothetical trip matrices produced by SKM for years of analysis (2021 and 2046) that
detail the number of car based trips travelling from point to point across the MSD, and
complementing this with estimates of distance between travel zones, SGS estimated the difference
between the base and project case car trip matrices to yield an overall travel distance saving
across the metropolis.
In 2021 the daily travel distance is calculated to be 1.31 billion km in the base case and 1.30 in the
project case. 2046 displays a similar trend with total distance travelled in the base case amounting
to 1.45 billion km and 1.44 billion km in the project case. Multiplying the estimated distance saved
across the metropolis by the DoT default values suggests that the distance savings equate to an
annual reduction in externality costs of $3.1 million in 2021 and $3.9 million in 204616.
Table 27 Estimated Environmental Emissions Savings
Daily VKT Base Case (million
kms)
Daily VKT Project Case (million kms)
Daily VKT Change (Base Case – Project Case) (million kms)
Annual Environmental
Emissions Savings ($ Million)
2021 6,328 6,311 1.6 $3.14 million
2046 7,010 6,987 2.0 $3.94 million
Source: SKM and SGS Economics and Planning
16 This saving assumes that there are 250 working days in a year
Rowville Rail Project/ Economic Impact Study
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10.2 Estimated Agglomeration Effects
Connectivity enhancements, due to the inclusion of rail based transport along the proposed train
corridor have been shown to impact on land use by households and by industry. Both the changes
to land use and connectivity have impacts on the productivity of industries, as measured by Gross
Value Added (GVA) and by the productive capacity of workers, i.e. Human Capital.
This section details the estimated benefits to both these aspects of agglomeration due to the
proposed rail extension project.
10.2.1 What is Agglomeration
Economic theory tells us that several factors contribute to productivity of firms, regardless of
locations. These include:
Scale/ geography;
Technological progress/ innovation – through own efforts or spillovers of knowledge; and
Human capital development.
However, another crucial factor is agglomeration, or the density of economic activity. This factor is
related more to the spatial organisation of the city.
Consider two cities, A and B, each with a population of five million people. Both will gain a labour
productivity premium from their size. However, economic activity in City A is poorly linked while
City B features distinct employment centres which are well integrated via a robust transport
network. In this case the labour productivity in City B is likely to be higher than City A.
Firms gain the following advantages from locating in areas of dense economic activity:
The ability to achieve economies of scale and scope through specialisation given the large
numbers of potential customers that are readily accessible;
The availability of numerous supply sources and potentially specialised infrastructure, and the
competitive environment that stems from this; and
Access to a deep and diverse pool of skilled labour, often complemented by high levels of
technological/ knowledge transfer between firms, which helps bolster innovation.
Although a well recognized factor driving productivity growth, it is only recently that availability of
data at a fine grained level which has enabled the quantification of agglomeration.
Agglomeration has historically been measured in a number of ways including city population
(Aaberg, 1973; Tabuchi, 1986), industry employment (Nakamura, 1985; Henderson, 1986), the
number of industrial plants (Henderson, 2003b) and effective job density (Graham, 2006)
depending on availability of data. But it is not density itself that leads to agglomeration.
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 113
Accessibility plays an equally important role. One does not need to be in the midst of economic
activity but should be able to access that location too.
A simple measure such as looking at the employment density of an area does not adequately
reflect the phenomenon of agglomeration. A firm in a relatively low-employment area but located
on the edge of a Central Business District (CBD) could potentially capture agglomeration benefits
through such proximity. Thus a measure of agglomeration must incorporate both the local scale
and accessibility to economic activity (as measured by employment) and be able to be calculated
for small geographical regions.
So, what happens if policy decisions can drive spatial land use change which would change the EJD
of a location? We have evaluated this relationship using statistical regression analysis.
A more detailed description of productivity enhancements and agglomeration is relegated to
Appendix D, including an explanation of the full methodology used to estimate the economic impact
of the proposed Rowville rail. Results are summarised below.
10.2.2 Estimated Productivity Enhancements
Labour productivity enhancements, i.e. an increase in GVA of the South East Region, resulting from
the project were estimated at $23 million in 2021 and $133 million in 2046 (refer Table 28
overleaf). Note that these are net impacts after accounting for employment and household shifts
across the metropolitan economy, i.e. the firm’s productivity in the South East Region increases by
$133 million by 2046 due to the Project. Some SLAs within the examined area are expected to bear
some short term adverse impacts due to structural and locational shifts. However, by 2046, after
all adjustments are taken into account, all SLAs are expected to receive a GVA uplift.
Relative to the Base Case, the Project is expected to have the strongest impact on Knox – South
SLA within the municipality of Knox (C), which is 0.63% higher in 2021 and 0.93% in 2046 over
and above the estimated Base Case GVA in those years.
Rowville Rail Project/ Economic Impact Study
SGS Final Report – May 2012 P. 114
Table 28 Impact of Project on GVA of Selected SLAs
GVA Impact ($) % Change to SLA GVA
SLA 2021 2046 2021 2046
Knox (C) - North-East $1,168,000 $10,049,000 0.03% 0.16%
Knox (C) - North-West $3,439,000 $26,742,000 0.17% 0.69%
Knox (C) - South $14,330,000 $45,662,000 0.63% 0.93%
Monash (C) - South-West $2,792,000 $14,266,000 0.05% 0.12%
Monash (C) - Waverley East $1,223,000 $22,157,000 0.06% 0.56%
Monash (C) - Waverley West $16,000 $6,134,000 0.00% 0.04%
Gr. Dandenong (C) - Dandenong -$114,000 $2,000,000 0.00% 0.01%
Gr. Dandenong (C) Bal $262,000 $3,762,000 0.00% 0.03%
Casey (C) - Berwick -$22,000 $343,000 0.00% 0.01%
Casey (C) - Cranbourne -$36,000 $424,000 0.00% 0.01%
Casey (C) - Hallam $76,000 1,495,000 0.00% 0.03%
Casey (C) - South -$44,000 495,000 -0.01% 0.02%
Total South East Region $23,000,000 $133,000,000
Source: SGS Economics and Planning
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11 CONCLUDING REMARKS
The Victorian Department of Transport (DoT) is currently evaluating the feasibility for a rail line
from Huntingdale to Rowville, a distance of 13 kms. This proposed Rowville rail project is expected
to benefit the residents of Knox and neighbouring municipalities - an area which is currently devoid
of an extensive public transport network, leading to problems of road congestion and greenhouse
gas emissions.
Knox City Council is taking its own actions in support of a positive outcome for the people of its
municipality and elsewhere who will benefit from the provision of a modern rail service in their
communities. With this in mind, Council engaged SGS to undertake a study with the following
scope:
Define and estimate the economic and employment impacts, (direct and indirect), that could
reasonably arise from the proposed rail project on:
o The City of Knox;
o The City of Monash to the west, and the immediately adjacent areas of the cities of
Casey and Greater Dandenong to the south east and south respectively
(collectively termed as the ‘South East Region’ for the purposes of this report; and
o The wider Melbourne Statistical Division (MSD) and the State of Victoria.
Provide comprehensive evidence and argument for the economic and employment impacts
identified in this study to assist Council in its advocacy activities.
In its response, SGS assessed and determined the following four impacts of the proposed project:
Accessibility and land use impacts: Additional dwellings and employment that Knox and the
wider South East Region will host over and above the projected Base Case estimates as a result
of improved accessibility provided by the proposed rail. These constitute the direct impacts of
the operations phase of the project.
Construction and operations phase impacts: indirect impacts on the output, value added and
employment of the economies of Knox, the South East Region, the wider metropolis and
Victoria resulting from the initial change in dwellings and employment estimated for Knox at
two examined years – 2021 and 2046.
Wider economic benefits: estimated increase in metropolitan wide labour productivity of
firms due to induced changes in the density of firms; and
Environmental savings: estimated reduction in metropolitan wide greenhouse gas emissions
due to the provisioning of rail in the region, and the consequent reduction in travel time (due to
provisioning of more jobs closer to home) and reduced dependence on cars.
The results show that delivering the rail project will lead to several beneficial economic and
employment impacts for Knox, Melbourne’s South East and the Victorian economies.
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First and foremost, construction of the rail line (only the section within Knox) is likely to support
nearly 5,600 total jobs in Victoria due to the backward and forward linkages of the construction
industry.
Secondly, the operational phase of the project is likely to contribute $320 million towards the
state’s value-added contribution by 2046.
However, as stated before, these estimated economic impacts only consider the impacts of the
induced changes within the City of Knox on its own regional economy and the wider economies of
the South East Region, the MSD and Victoria. A net assessment of the combined effects of the
induced positive changes in Knox and corresponding induced negative changes elsewhere (due to
detractions of households and employment away from these metropolitan locations into the South
East Region) is beyond the scope of this study due to unavailability of region specific multipliers
across the MSD.
Nonetheless, the wider economic benefits and estimated environmental cost savings have been
assessed taking into account the redistribution of population and employment across the
metropolitan economy. Aggregating annual environmental savings and wider economic benefits
over a 50 year timeframe from 2021 onwards yields a cumulative benefit to the Victorian economy
of over $5 billion to the Victorian economy, which is well above the $2.89 billion towards
constructing the project. This falls within the range of estimates of wider economic benefits
provided for various similar transport projects in the UK (as per the case study investigations).
Whilst a benefit cost ratio cannot be ascertained from these values (as they are not net present
values), it helps provide some indication of the magnitude of benefits compared to costs of
delivering the project.
In other words, the opportunity costs of not delivering the project are high; not only will the
economies of Knox and the South East Region lose out on the estimated impacts during the
construction phase, Victoria in turn stands to lose out on approximately $5 billion in environmental
and economic savings over a 50 year timeframe.
Findings suggest that the proposed Rowville rail project will:
Help accelerate the growth trajectory of Knox and Melbourne’s South East. While not a
dramatic impact, the shift in dwellings and employment towards Melbourne’s South East does
begin to help to reshape the economic geography of South East Melbourne more in favour of
Knox.
Enable the city of Knox to meet is stated vision and objectives of: consolidating the existing
industry base and provide for a well-networked, informed and knowledge intensive business
community in the City of Knox; and providing for more employment and housing opportunities
for the people of Knox. The project will reduce the vulnerability of Knox residents to future
economic shocks and the impacts of structural adjustment within the economy.
Lead to significant economic benefits not only for the local Knox and south East economies, but
for the wider metropolitan and Victorian economies.
Be vital to delivering significant and further productivity enhancements to Victoria. Productivity
levels in developed economies are quite high to start with due to high entrenchment of skills
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and technology. Further significant enhancements are possible only due to connectivity
improvements, which this project will deliver and consequently, help lift the economic
productivity of metropolitan firms.
In the absence of any intervention, there will be a high requirement for the people of Knox and the
wider South East Region to travel outside of their municipality boundaries to access employment
opportunities. The reliance on the private vehicle for accessibility to jobs and services will heighten
the vulnerability of the residents to congestion and fuel price increases. more importantly, the state
would also not be able to capture the suggested environmental and wider economic benefits that
the project will engender.
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APPENDIX A: SGS POPULATION AND EMPLOYMENT FORECAST METHODOLOGY
11.1 Projection Methodology
This section outlines the SGS methodology for employment, population and enrolments.
11.1.1 Employment
The SGS approach to projecting employment by industry and occupation for each Statistical Local
Area (SLA) and Travel Zone (TZ) in Melbourne is summarised in Figure 41 below.
In essence, the Treasury Macroeconomic Model (TRYM) and data obtained from a variety of
different sources17 was used to develop a set of industry projections for the Australian economy.
These industry projections, which include gross value added (GVA) and employment projections,
were developed for the short (2016), long term (2031) and beyond (2046), with total growth for all
industries benchmarked against GDP projections from TRYM. This ensures that the projected
industry growth can be resourced with the finite level of resources at the disposal of Australia.
At a State wide level, Victorian estimates were derived from the current State share of GVA and
employment for each industry. Projections were made on the future share of each industry in
Victoria. Employment projections for Melbourne have been derived from these Melbourne GVA
projections and projections of Melbourne’s labour productivity growth.
Employment growth was capped using future labour force constraints. The labour force was based
on the 2011 Victoria in Future (VIF 2011) and projections for labour force participation for each five
year age group. Labour force projections were made separately for men and women to account for
observed differences in their participation by age profiles. The Intergenerational Report18 was used
as a guide to workforce participation amongst various age groups into the future. A projection of
unemployment was also made to ensure a coherent picture of the future labour force.
This set of metropolitan projections were the cap to which the small area employment projections
were limited. The Australian Bureau Statistics (ABS) Census Journey to Work data has been used
to estimate employment in each SLA for 1996, 2001, and 2006. However, due to the
undercounting of this dataset, the estimates for Melbourne were benchmarked to annual average
employment estimates for each industry from the Labour Force Survey for each year. An
adjustment has been made to the Labour Force Survey to account for people who live in Regional
Victoria but travel to Melbourne for work. For 2002, 2004, 2006, 2008 and 201019, data from the
17 Including the Australian Bureau of Statistics (ABS), Australian Bureau of Agricultural & Resource Economics and the Joint Economic Forecasting Group.
18 Treasury, Australian Government, 2010
19 For 2010 only estimates for Docklands have been released.
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City of Melbourne Census of Land Use and Employment (CLUE) has been used to adjust the Census
Journey to Work data industries shares for the most recent years.
These employment figures were also split into blue collar and white collar employment using
Census Journey to Work and Labour Force Survey data.
In projecting future industry employment by SLA the following process was followed:
Initially, the 2016-46 projections for each SLA’s employment by industry was assumed to
follow the growth pattern observed in Melbourne industry share between 1996 and 2011;
In 2026 and 2046 adjustments were made to this industry to share to account for known
information about the development of Melbourne;
VIF population projections for each SLA were used to adjust the projections for population
serving industries. This was done by observing the trends in population to industry employment
between 1996 and 2011;
A factor analysis of each of Melbourne’s SLA was utilised to appropriately cater for expected
changes in employment distribution over time. This factor analysis included an assessment of
each SLAs prospects and capacity for growth, transport connections, resident workforce
characteristics, employment lands availability and Government spatial policy considerations.
Importantly, this factor analysis was undertaken separately for each of major industry and to
ensure that the level of granularity appropriately reflected their respective location drivers;
For the years between 2016 and 2026, the projections were interpolated. That is, the assumed
spatial changes at 2026 were progressively introduced; and
For the 2031, 2036 and 2041 the employment projections were extrapolated using the 2026
and 2046 SLA industries employment shares.
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Figure 41 Employment Projections Methodology
The 2006 Journey to Work estimates by industry and occupation at the ABS Destination Zone were
used to allocate each SLA’s total employment to the TZ in that SLA. CLUE data for 2008 and 2010
was also used as a data input. Further factor analysis was undertaken at the travel zone level to
adjust the 2006 shares for future forecast years. Finally, a detailed review of TZ employment by
industry and occupation projections was undertaken and adjustments made as necessary. This
included a review of the employment densities and a cross check against background conditions
(including known structure plans and the scale of major redevelopments).
11.1.2 Module Description
This section provides a more detailed description of each Module in the employment projection
methodology.
2006 Journey to WorkBy Industry
LGA Employment by Industry
LGA 2001 – 2006 Trends
Labour Force Survey
SGS Employment ProjectionsTRYM, Industry Analysis, Labour Force Projections
2006: ABS 2011 to 2016: Trend 2021 to 2026: Interpolated 2031: Factor Adjustment 2036 to 2046: Extrapolated
Small Areas 2006 Share of LGA
Factor Analysis:-Activity Centres-Capacity Constrained Small Areas-UDP Greenfield and Brownfield-Employment lands availability-Blue Collar Construction employment linked to residential and non-residential growth
2011 – 2046 Employment by Industry and Small Area
Factor Analysis:-Major road and rail projects-Business preferences-Leading jobs vs following jobs-Population distribution-Real income of residents-Agglomeration impacts-Other factors
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Figure 42 Overview of Employment Projections Modules
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Module 1: Labour Force Participation
This module estimates the total pool of labour available in Melbourne overall. It aggregates a
number of data sources that are used to generate total employment for the MSD from 2011 to
2046. These are:
ABS Labour Force Survey
ERP by age and sex from VIF2011
Intergenerational Report
Module 2: MSD Industry Projections
The forecasts of total employment by industry for the MSD are estimated in this module. Three
methods were used to estimate future employment, depending on the characteristics of each
industry. The three categories of industries were:
Population driven – Construction, Retail trade, Accommodation & food services, Education &
training, Health care & social assistance, Arts & recreation services, Other services, Electricity,
gas, water & waste services
Non-population driven – Agriculture, forestry & fishing, Mining, Manufacturing, Wholesale
trade, Transport, postal & warehousing, Rental, hiring & real estate services
Knowledge intensive services – Information, media & telecommunications, Financial &
insurance services, Professional, scientific & technical services, Administrative & support
services, Public administration & safety
Population driven industries were projected using historical data on employment by industry and
population to estimate and extrapolate the ratio between population and employment in each
industry. This trended ratio is then multiplied by the population by age projections for the MSD at
five yearly intervals from 2011 to 2046.
Non-population driven industries were projected using a moving average growth rate estimated
from the historical employment data. Given the nature of these industries it was assumed they
were likely to follow the historical trend in the long term.
A factor analysis of industry trends in the last 10 years was undertaken for the industries classified
as knowledge intensive services. A projected five yearly average annual growth rate was used to
extrapolate the base year estimates out to 2046.
The aggregate of all industries determined the split of workers into blue and white collar
employment. The number of resident workers is also estimated from the total number of workers
to account for people who live outside of the MSD but commute into the region for work.
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Module 3: SLA Employment
Estimates of employment by industry for each SLA in Regional Victoria from 1996 to 2046 are
produced in this module. It compiles the ABS Census data from 1996, 2001 and 2006 for each SLA
and industry of employment by place of work. The SLA share of each industry is estimated for
these three years and interpolated for the remaining years to 2011. For 2002, 2004, 2006, 2008
and 201020, data from the CLUE has been used to adjust the Census Journey to Work data
industries shares for the most recent years. A factor analysis is then undertaken for the future
years to generate a final share for each of the forecast years. The MSD total employment by
industry from module 2 is then distributed to the SLAs based on these shares.
Module 4: TZ Employment Shares
ABS Census data on employment by industry (place of work) at a small area level from 1996 to
2011 is compiled using this module. The ABS releases the data by destination zones which are a
similar size to TZ and have been aligned to the MITM TZ for 1996, 2001 and 2006. The shares for
the remaining non-Census years have been interpolated to produce a time series from 1996 to
2011. This has been supplemented using CLUE data for the available years, to ensure that 2011 is
as accurate as possible.
Module 5: TZ Employment Projections
This module distributes the SLA employment estimates generated by module 3 to each travel zone
using the travel zone shares from module 4. Historical employment by TZ for each year from 1996
to 2011 uses the current year TZ share. Employment by TZ for the years from 2016 to 2046 is
forecast using the same method as 2011, with the shares for each future year being projected for
2026 and 2046 with factor analysis and the time periods in between interpolated.
Module 6: TZ Employment by Collar Projections
Estimates of employment (by place of work) by collar projections by TZ are produced here. The
module compiles ABS Census data (2006) on the occupation of workers at the detailed four digit
level by SLA to determine the percentage split between blue and white collar workers for each SLA.
The list of occupations by Blue and White Collar can be found in Error! Reference source not
ound. in the appendix.
The total employment by SLA estimated in module 3 is divided into blue and white collar using
shares from the Census data. The SLA totals of blue and white collar employment are then
distributed to TZs based on the TZ share of total employment from modules 4 and 5.
20 For 2010 only estimates for Docklands have been released.
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11.1.3 Dwellings and Population
Figure 43 below summarises the approach used by SGS to project dwellings and population at a
small area level (travel zone). The method has been split into 6 modules which link to each other
to produce the final set of results.
SGS took the preliminary VIF 2011 projected structural private dwellings (SPD) for each LGA as the
starting point. These were combined with historical data from the Housing Development Data
(HDD) and ABS Census data to generate a time series from 1996 out to 2046. The estimates of
total ERP were then split into the MITM11 age breakdown using the ABS ERP by Age, VIF 2008
projections and 2006 Census data (ABS) to determine the appropriate share of each age cohort.
This was completed in module 1. Figure 44 illustrates how the SPD was split into its components
and age cohorts.
These LGA level projections were then apportioned to the travel zone (TZ) level over the entire
MSD. This apportionment was based on the trends in housing demand and capacity for dwellings
evident from a variety of sources. The data sets used were the 2009 Urban Development Program
(UDP), Growth Area Authority (GAA) estimates, Targeted Urban Renewal information, Housing
Development Data (HDD), 1996, 2001 and 2006 Census (from ABS) and the Housing Capacity
Assessments (HCA) draft capacity results. Assumptions around the density of Central Activity Areas
(CAAs) and the CBD were also made. This was completed in module 2.
Upon synthesising structural private dwellings for each TZ in Melbourne, SGS applied the housing
unit method to estimate the number of occupied private dwellings, persons in occupied private
dwellings and estimated resident population by TZ. This was completed in module 3.
The RAS method/ ‘iterative proportional fitting’ method was then used to map total population by
TZ into population by age cohorts that were consistent with VIF 2011 projected population by LGA.
This was completed in module 4.
SGS then examined the labour force participation rates by age group for each labour force region in
Melbourne (as defined by ABS) and projected these into the future. This dataset was combined
with the LGA projections of ERP from VIF 2011 to determine LGA estimates of the resident
workforce by both labour force status and collar of employment. This was completed in module 5.
The resident labour force by age group and collar of employment for each TZ was then estimated
via the RAS method. This was completed in module 6, with the LGA totals taken from module 5 and
the TZ distribution taken from module 4.
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Figure 43 Overview of Modules for Dwellings and Population Projections
Figure 44 SPD to ERP by Age Method Overview
Module 1: LGA (SPD to ERP by age)
Inputs:VIF 2011 (DPCD), VIF2008 (DPCD), 2006 Census (ABS), ERP (ABS), Population Projections (ABS)
Outputs:SPD, UOPD, OPD, PNPD, POPD, ERP by Age
Module 3: TZ (SPD to ERP)
Inputs:M1, M2, 2006 Census (ABS)
Module 2: TZ (SPD)
Inputs:M1, 2006 Census (ABS), HDD (DPCD & SE), Previous MITM Projections, 2009 UDP, etc
Outputs:SPD
Module 4: TZ (ERP by age)
Inputs:M3, 2006 Census (ABS)
Outputs:ERP by Age
Outputs:SPD, UOPD, OPD, PNPD, POPD, ERP
Module 5: LFR (ERP by Age to LF)
Inputs:M1, LFS (ABS), Employment Projections M01
Outputs:NLF, LF, UnEmpd, Empd, Blue, White
Module 6: TZ (ERP by Age to LF)
Inputs:M5, M4, 2006 Census (ABS)
Outputs:NLF, LF, UnEmpd, Empd, Blue, White
SPD
OPDUOPD
POPD PNPD
ERP
SPD: Structural Private Dwellings
OPD: Occupied Private Dwelling
UOPD: Un-occupied Private Dwelling
ERP: Estimated Resident Population
POPD: Population in Occupied Private Dwellings
PNPD: Population in Non-Private Dwellings
NiLF: Not in Labour Force
LF: Labour Force
UnEmpd: Unemployed (residence)
Empd: Employed (residence)
0-4 5-9 15-17 18-19 10-11 20-25 26-64 65+12-14
0-4 yrs 5-11 yrs 12-17 yrs 18-25 26-64 65+
VIF08 Age Breakdown
MITM11 Age Breakdown
0-4 yrs 5-9 yrs 15-19 yrs 20-25 26-64 65+10-14 yrs
Not in Labour Force Labour Force
EmployedUnemployed
Blue White w Ties
For each MITM11 age cohort
Time Periods:1996, 2001, 2006, 2007, 2008, 2009, 2010, 2011, 2016, 2021, 2026, 2031, 2036, 2041 & 2046
White w/o Ties
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11.1.4 Module Description
Module 1: Local Government Area Structural Private Dwellings to Estimated Resident Population by Age
Module 1A: Local Government Area Totals
This module estimates the structural private dwellings (SPD) and its components (OPD, UOPD,
POPD, and ERP) for each local government area (LGA) in the Melbourne Statistical Division (MSD)
for the years 1996, 2001, 2006, 2007, 2008, 2009, 2010, 2011, 2016, 2021, 2026, 2031, 2036,
2041 and 2046.
A variety of data sources are used as inputs into this module. These include:
ABS Census Data: 1996, 2001, 2006 dwellings and population in dwellings by place of usual
residence
ABS Estimated Resident Population by LGA (ERP 3218.0): 1996 to 2009
ABS Estimated Resident Population by LGA by 5 year Age Group (ERP 3235.0): 1996 to 2009
VIF2008 LGA population and household projections: 2006 to 2009
VIF2008 LGA population and household projections by Age Group: 2011, 2016, 2021, 2026
VIF 2011 LGA population and household projections: 2010 to 2046
Housing Development Data LGA dwellings: 2006 to 2009
The housing unit method was used to estimate the components of SPD using occupancy rate,
household size, ratio of people in non-private dwellings and ERP where VIF 2011 data was not
available. The following formulas and definitions were assumed to hold:
SPD(t) = SPD(t-1) + Additional PD(t)
SPD = Structural Private Dwellings; any building or structure in which people live
OPD(t) = SPD(t) * Occupancy Rate(t)
OPD = Occupied Private Dwellings; normally a house, flat, room or caravan, houseboat, tent,
shoptop
UOPD(t) = SPD(t) – OPD(t)
UOPD = Unoccupied Private Dwellings; structures built specifically for living purposes which are
habitable, but unoccupied on Census Night, eg holiday houses, vacant houses
POPD(t) = OPD(t) * Household Size(t)
POPD = Persons in Occupied Private Dwellings
PNPD(t) = POPD(t) * PNPD Ratio
PNPD = Persons in Non Private Dwellings
Non-private dwellings provide communal or transitory type accommodation, eg hotels, prisons,
boarding school, hospital, defence establishments
ERP(t) = POPD(t) + PNPD(t)
ERP = Estimated Resident Population; official measure of population in Australia based on concept
of usual residence, refers to all people regardless of nationality, citizenship or legal status who
usually live in Australia
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Module 1B: Local Government Areas Age Breakdown
This module takes the LGA distribution of ERP by MITM11 age breakdown and balances it to the
Total ERP for each LGA and each age group. The VIF 2011 estimates of ERP were not yet available
at the detailed age breakdown at the time of this study. Therefore, this module uses the RAS
method to do estimate an age breakdown, which is explained in the following sections. The output
of this module is ERP by Age by LGA from 1996 to 2046. The sources of data used as input into this
module are from module 1A. These include ABS ERP by age and VIF 2008.
Module 2: Travel Zone Structural Private Dwellings
This module takes the LGA estimates of SPD and distributes down to the travel zone level using a
variety of data sources. These include:
Housing development data, dwelling estimates for 2004 to 2009
VIF 2011 projections, SPD by LGA from 2010 to 2041
Urban Development Program 2009
Growth Area Authority (GAA) Estimates
Housing Capacity Assessment (HCA) draft capacity results
Targeted Urban Renewal information from DPCD
Activity Centre density assumptions
The historical stock and growth rate of this stock was based on the ABS Census data and the HDD
data from 2004 to 2009. The 2009 HDD data was used as the pivot point for the future projections.
A comprehensive staging of capacity for dwellings at the travel zone level was estimated using
these combined data sets. The LGA level projections were then distributed to travel zones based on
the level of capacity in each time period from 2010 to 2046. Adjustments were made to the timing
of new development when demand for dwellings did not match the capacity that was available in a
particular area.
Module 3: Travel Zone Structural Private Dwellings to Estimated Resident Population
This module converts the estimates of SPD by TZ from module 2 into estimates of occupied private
dwellings (OPD) and estimated residential population (ERP) by TZ. This was done using the housing
unit method, as outlined in Section 11.1.4 previously.
This approach determines the current trends in the occupancy rate, household size and adjusts
them over time based on regional trends. The following assumptions have been made regarding
household size, occupancy rates and persons in non private dwellings to occupied private dwellings.
The occupancy rate (i.e. ratio of private dwellings to occupied private dwellings) for each
zone was initially calculated based on 2006 Census data. The rates for each zone were then
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adjusted over time based on VIF 2011 projected LGA trends (i.e. if the occupancy rate was
projected to increase for the LGA then the occupancy rate for each zone within the LGA was
projected to increase at the same rate).
Zones with low occupancy rates are assumed to gradually approach the LGA average
occupancy rate.
Greenfield areas that previously had no dwellings were assumed to have the similar occupancy
rate to the average for that LGA.
The Household Ratio (i.e. average number of persons per occupied private dwelling) was
initially calculated based on 2006 Census data. Each zone’s household ratio was then adjusted
over time based on the VIF 2011 projected LGA trend.
Greenfield areas that previously had no dwellings were assumed to have the similar household
ratio to the average for that LGA.
The share of persons in non private dwellings was held constant at the 2006 Census level.
At each stage of the housing unit method all zones within each LGA were benchmarked to the
respective VIF 2011 LGA total for:
Structural Private Dwellings
Occupied Private Dwellings
Persons in Occupied Private Dwellings
Persons in Non-Private Dwellings
Estimated Residential Population
Module 4: Travel Zone Estimated Resident Population by Age Breakdown
This module disaggregates the estimates of ERP by TZ completed in module 3 into the six age
cohorts of 0-4, 5-11, 12-17, 18-25, 26-64 and 65 and over. This was done using the RAS method
outlined below.
At the time of this study VIF 2011 population by age group was not yet available. Therefore, ABS
Estimated Resident Population by Age and 2006 Census population by age were used to estimate
the TZ level age breakdown. This was undertaken using a RAS method. The RAS/‘iterative
proportional fitting’ method is commonly used for the purpose of estimating regional input-output
tables by economists21.
Through a series of iterations the RAS method adjusts the age distribution until all row and column
totals match the VIF 2011 total population by TZ and population by age group for each LGA (see
Figure 45 below). This process was repeated for each Census year between 1996 and 2046. A
rolling TZ by age group distribution has been used to estimate future years.
21 It should be noted that DSE (now DPCD) in 2006 used this approach to project population by age by TZ using VIF 2004 SLA level projections
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The 2006 population by age group by TZ distribution was based on the 2006 Census data,
converted from Census collection district (CCD) to TZ based on land area apportioning. 2011
population by age group by TZ was estimated using a RAS method where row and column totals
are fixed at 2011 population by LGA by age group and 2011 total population by TZ. The internal
population by age by TZ for each LGA is determined using the 2006 distribution. 2016 population
by age group by TZ was estimated in a similar approach using the newly estimated 2011
population by age by TZ distribution in each LGA. This process of using the subsequent time
period’s distribution is repeated for each Census year to 2046.
Figure 45 RAS Method
Module 5: Local Government Area Estimated Resident Population by Age Breakdown to Labour Force Status
This module generates LGA estimates of resident workers in the labour force, not in the labour
force, employed, unemployed and white and blue collar workers from 2011 to 2046. The data
sources used in this module include the ABS Labour Force Survey and VIF 2011 projections of ERP.
The employment projections (place of work) are also used as an input.
Participation rates and unemployment rates by five year age group were estimated and applied to
the ERP by age group generated in module 1. Additionally the blue and white collar split taken from
the 2006 Census (ABS) was applied to the estimates of employed people in each forecast year to
2046.
RAS Method
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Module 6: Travel Zone Estimated Resident Population by Age Breakdown to Labour Force Status & Collar
This module distributes the LGA estimates of resident workers by age (LF, NLF, Employed,
Unemployed, Blue Collar, White Collar) to the travel zone level for each forecast year. The two
sources of input data were from module 5, the LGA estimates of resident worker variables and
module 4, the TZ estimates of ERP by age.
The process of estimating these resident worker variables by age by travel zone was split into two
parts. Module 6A was concerned with the labour force status of residents (in the labour force, not
in the labour force), whilst module 6B focused on the collar of employment of the resident
workforce.
Module 6A: Travel Zone Estimated Resident Population by Age Breakdown to Labour Force Status
This module estimates the number of people employed, unemployed and not in the labour force by
age group from 1996 to 2046 at five yearly intervals. The age groups estimated were 12-17, 18-
19, 20-25, 26-64 and 65 and over. The 2006 Census distribution was used as the base year for
each age category, with each successive year out to 2046 based on the previous year’s
distribution. It was assumed that the number of people employed and unemployed equalled the
total labour force, and that the number of people in the labour force and not in the labour force
was equal to the total population.
Module 6B: Travel Zone Estimated Resident Population to Blue & White Collar Split
This module estimates the number of people employed in blue and white collar industries using the
RAS method. The 2006 Census (ABS) TZ distribution of blue and white collar is balanced to the
total employed by TZ and to the total blue and white collar resident workers in each LGA. The 2011
numbers are equal to the 2006 distribution with each following year equal to the previous period’s
distribution.
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APPENDIX B: SURVEY QUESTIONNAIRE FOR SGS CONSULTATION
(Please complete the following questions)
1. Name of business/organisation
2. What is your primary business activity?
(Please tick one that applies)
Manufacturing
Wholesale Trade
Transport & Logistics
Utilities (Electricity, Water, Gas and Waste Services)
Construction
Retail Trade
Education and Training
Accommodation and Food Services
Professional & Business Services (Finance, ICT, Accounting, Legal, Scientific etc.)
Other Services
3. How many people do you employ full-time?
(Please tick one that applies)
Non-employing family owned business
0-4
5-19
20-150
150+
4. How long have you been in continuous operation within the City of Knox?
Less than a year
1 to less than 5 years
5 to less than 10 years
10 to less than 20 years
More than 20 years
1/4
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5. On a scale of 1 (most) to 5 (least) where are most of your customers located? (Pease assign a value of between 1 and 5 against each listed option)
Within Knox
Surrounding municipalities of Dandenong, Monash and Casey
Rest of Melbourne/Victoria
Australia inter-state
Overseas
6. On a scale of 1 (most) to 5 (least) where are most of your suppliers located?
(Please assign a value of between 1 and 5 against each listed option)
Within Knox
Surrounding municipalities of Dandenong, Monash and Casey
Rest of Melbourne/Victoria
Australia inter-state
Overseas
7. On a scale of 1 (most) to 3 (least) where are most of your employees located?
(Please assign a value of between 1 and 3 against each listed option)
Within Knox
Surrounding municipalities of Dandenong, Monash and Casey
Rest of Melbourne/Victoria
8. What model(s) of transport do your customers, suppliers and employees use to reach you?
(Please tick all that apply)
Customers Suppliers Employees
Car/ Private transport
Public Transport (Bus/ Train/
Tram etc)
Walk
Other
2/4
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9. In the past three years, have your customers, suppliers and employees faced any of the following problems to access your services:
(Please tick all that apply)
Congestion on roads
Congestion on public transport
Longer travel times on roads
10. Have any of these problems above prompted you to consider changing your business operation?
Yes
No
Not sure
If so what?
11. Do you have any concerns about any adverse impacts during the construction of the proposed rail line?
Yes
No
If so what are these?
12. On constructing the proposed rail line what are the potential growth opportunities for your business?
13. In the long term, will the proposed rail line help you as a business entity to expand
operations, attract more employees and reach out to other markets within the metropolitan economy?
Yes
No
Not sure
3/4 14. Considering the longer term beneficial impacts, are you likely to locate closer to a new
proposed train station to improve your access to either your customers, suppliers and
employees?
Yes
No
Not sure
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15. In the long term, will the proposed rail line help attract more residents and businesses like yours to Knox and surrounding municipalities?
a. Residents Yes/No b. Businesses Yes/No
If so, why do you think so?
16. In the long term, which sectors of the Knox and surrounding economies is the proposed rail line likely to help the most and why?
(Please tick all that apply)
Manufacturing firms
Wholesale Trade firms
Transport & Logistics firms
Utilities (Electricity, Water, Gas and Waste Services)
Construction firms
Retail firms
Education and Training Organisations
Professional & Business Services firms (Finance, ICT, Accounting, Legal, Scientific etc.)
Other firms
Why?
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APPENDIX C: EFFECTIVE JOB DENSITY CALCULATIONS
Table 29 Estimated Effective Job Density for South East Region
EJD 2021 EJD 2046
SLA Base Case
Project Case
Change Base Case
Project Case
Change
Monash (C) - South-West 85,211 85,327 116 105,973 106,329 356
Monash (C) - Waverley East 78,418 78,469 51 96,461 97,028 566
Monash (C) - Waverley West 84,493 84,444 -49 104,721 104,829 108
Knox (C) - North-East 60,933 60,992 60 76,309 76,602 293
Knox (C) - North-West 71,046 71,212 166 86,244 86,932 688
Knox (C) - South 60,246 61,431 1,185 74,399 76,815 2,415
Gr. Dandenong (C) - Dandenong 73,575 73,518 -57 91,153 91,148 -4
Gr. Dandenong (C) Bal 71,921 71,886 -35 89,357 89,388 31
Casey (C) - Berwick 42,912 42,902 -10 56,404 56,408 4
Casey (C) - Cranbourne 42,846 42,837 -10 52,167 52,174 7
Casey (C) - Hallam 53,113 53,108 -5 69,075 69,100 26
Casey (C) - South 36,145 36,136 -9 42,439 42,442 3
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Table 30 Estimated Relative Effective Job Density for South East Region
EJD 2021 EJD 2046
SLA Base Case
Project Case
Change Base Case
Project Case
Change
Monash (C) - South-West 0.46616 0.46706 0.00090 0.44718 0.44935 0.00217
Monash (C) - Waverley East 0.41328 0.41368 0.00040 0.38918 0.39263 0.00345
Monash (C) - Waverley West 0.46058 0.46019 -0.00039 0.43955 0.44021 0.00066
Knox (C) - North-East 0.27720 0.27766 0.00046 0.26628 0.26807 0.00179
Knox (C) - North-West 0.35591 0.35720 0.00129 0.32687 0.33107 0.00420
Knox (C) - South 0.27185 0.28107 0.00922 0.25464 0.26937 0.01473
Gr. Dandenong (C) - Dandenong 0.37559 0.37515 -0.00044 0.35681 0.35678 -0.00003
Gr. Dandenong (C) Bal 0.36272 0.36245 -0.00027 0.34585 0.34605 0.00019
Casey (C) - Berwick 0.13693 0.13685 -0.00008 0.14490 0.14493 0.00002
Casey (C) - Cranbourne 0.13642 0.13635 -0.00007 0.11906 0.11911 0.00004
Casey (C) - Hallam 0.21633 0.21629 -0.00004 0.22217 0.22233 0.00016
Casey (C) - South 0.08427 0.08420 -0.00007 0.05974 0.05976 0.00002
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APPENDIX D: SGS METHODOLOGY TO MEASURE AGGLOMERATION
11.2 Review of the Evidence on the Nature and Sources of Agglomeration Economies
This section provides a short review of the literature on the topic of agglomeration. Rosenthal and
Strange (2002) provides a more comprehensive investigation of the literature.
The uneven spatial distribution of access to inputs to production provides a partial explanation for
the existence of agglomeration economies. Agglomeration economies occur specifically in some
locations which have access to raw materials and not in others – as with the concentration of US
furniture manufacturing in North Carolina and not in other states (such as Oregon) that also have
large forestry sectors. Agglomeration economies also occur in industries that do not depend on
unevenly distributed raw materials, but depend on intensive labour inputs from a relatively small
workforce – such as the agglomeration of computer software manufacturers in the San Francisco
Bay area of California. If agglomeration were solely driven by the need to locate close to raw
materials then this industry would instead seek to locate adjacent to electrical and plastic
component manufacturers.
In understanding agglomeration economies, a number of questions can be considered. What is the
nature and source of the increasing returns (external economies of scale) that lead to
agglomeration economies? Is the agglomeration economy regional or local? Is the agglomeration
economy restricted to an individual industry or does it extend across multiple industries? Are the
economies of scale impacts felt immediately or is there a lag between the agglomeration economy
being established and productivity improving? Is the agglomeration economy driven by the volume
of interactions occurring or is it driven by the nature of these interactions?
The limiting the interaction between people and business due to a lack of accessibility can impact
on the economy in three key ways; these are described by the National Cooperative Highway
Research Program as:
“By increasing business costs of current delivery operations.”
“By limiting or reducing business sales through a reduction in effective market size.”
“By increasing unit costs through loss of opportunities for scale economies in production and
delivery processes”.
The first of these impacts are effectively captured by the traditional transport benefits. The wider
economic benefits capture the improvements covered in remaining two impacts. The second two
points can also be as easily applied to households. Providing workers with an increased number of
jobs also allows them to become more productive. This has not been fully appreciated in past
studies of the economic benefits of significant land use changes and / or transport projects.
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The remainder of this section attempts to answer some of these questions by providing a review of
available literature on the topic of agglomeration. At times, reference is made to the Australian
context and the method outlined in this paper.
11.3 The Scope of Increasing Returns
External economies exist where the scale of the urban environment and its component economic
activities, infrastructure and resources add to the productivity of an individual firm. External
economies are defined across three dimensions of scope:
Industrial Scope: The degree to which agglomeration economies extend across industries
rather than being confined to firms within an industry classification or boundary.
Geographic Scope: The propensity by which firms that achieve agglomeration economies
seek to cluster in a geographically confined area to increase the potential for interactions.
Temporal Scope: The extent of continuing impact from a firm or agent’s previous interactions
with another firm or agent. The concept that much business intelligence and Human Capital can
only accrue gradually and is also subject to a degree of decay over time is central to
understanding the temporal scope of agglomeration economies.
Rosenthal and Strange seek to evaluate the scope of agglomeration economies. Firstly they
consider whether external economies enhance labour or other co-determinants of productivity.
Empirical evidence from Henderson (1986) suggests that external economies affect productivity
independently of land, labour, capital and materials and are thus ‘Hicks Neutral’.
Rosenthal and Strange specify that the
aggregate agglomeration effect is the
sum of many individual external
economy effects experienced by
individual firms and agents across the
three identified dimensions of scope. If
the two firms ‘j’ and ‘k’ are considered,
then the agglomeration impact of j on k
depends on the geographic distance
between the two firm’s premises defined as dGjk; the similarity of the industrial activity that
occurs at each firm, referred to as industrial distance and defined as dIjk ; and on the length of
time since the last interaction occurred, a temporal dimension of distance defined as dTjk. An
increase in any one of these distances will diminish an agglomeration effect between j and k.
The full set of benefits that accrue from an agglomeration effect is defined as K. In addition to the
impact of the geographic, industrial and temporal distance between the two firms, the scale of
activities at j and k also help determine the scale of agglomeration benefits experienced. The
benefit accrued depending on the scale of activities at both firms is represented as q(xj,xk). If we
hold the scale of activities constant, the benefit accruing from firm j’s interaction with firm k can be
defined as a(dGjk, dIjk, dTjk).
Hicks Neutral is when a technology (or in this
case agglomeration) change does not alter the
ratio of the marginal product of capital to the
marginal product of labour. That is, after the
change, the ratio between the extra output
gained by employing one additional unit of
capital and the output gained by employing one
unit of labour remains unchanged.
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The total benefit of agglomeration can be expressed as:
Aj = ∑ K E K q(xj,xk) (dGjk, dIjk, dTjk), (1.0)
The construction of the equation (1.0) indicates that A varies across different firms and agents
because each firm or agent belongs to a particular industry at a unique location and exists for a
given period of time. Rosenthal and Strange assert that most of the research on agglomeration
economies to date, has grouped industries and firms into politically defined regions. Activity in
neighbouring regions is assumed to have little or no effect on the grouped industries and firms and
productive activity in the region is assumed to be location unspecific.
SGS Conclusion: The method outlined in section Agglomeration Economies and Labour
Productivity section does take into account the surrounding geographical units.
The measure of agglomeration benefit (above) can be further adapted to form part of an
estimation of industrial output by firm j where industrial output is a function of agglomeration
benefits and the size of the firm:
Yj= g(Aj) f(xj) (1.1)
Estimates of the above equation should provide measures of the productivity effect of the
geographic, industrial and temporal dimensions of agglomeration. However, there are many
challenges to estimating 1.1. Gathering the information required to estimate all three dimensions
of agglomeration benefits presents a daunting exercise and would involve considering measuring all
forms of economic activity by industry and distance from j across a wide history of interaction.
Therefore most agglomeration models only consider one or two of the three dimensions of
agglomeration scope.
In estimating (1.1), measures of labour material and land inputs into a firm’s production process
can be made from public data sets (especially in the case of labour but also for material). Measures
of land use and other production inputs (such as capital) are more difficult to obtain where the
stock of information is not available publically. Where data is made available to the researcher at
the level of an individual plant within a firm, more accurate estimates of external economies of
scale are possible such as those made by Henderson (2003b).
Measurement error is another central challenge to estimating productivity effects and has been
surveyed considerably by Eberts and McMillen (1999). In larger cities, firms use capital and land
more intensively than in smaller cities and this can create bias in the coefficient estimates when
taken for firms operating in cities of different sizes (Moonmax 1981).
In response to the challenges presented when trying to estimate the production function of a firm
or plant, four other indirect means of investigating the scope of agglomeration economies have
been developed.
Study the growth in total employment resulting from agglomeration across a region or local
area.
Identify new firm or plant start ups and the number of jobs created.
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Study the change in wages resulting from agglomeration across a region or local area.
Study the change in rents resulting from agglomeration across a region or local area.
There continues to be a debate as to whether agglomeration economies can be ascribed to the
benefits from having localised and concentrated industries (localisation) or whether agglomeration
economy benefits relate more to the size of the city in which the firms or plants are located
(urbanisation).
Clearly, the increased density of economic activity brought about by transport projects would drive
the localisation component of agglomeration.
SGS Conclusion: Although currently the analysis is only focused on a single city
(Melbourne), the method outlined in section Agglomeration & Labour Productivity does
provide the capacity for both the localisation and urbanisation effects to be accounted for.
11.3.1 Industrial Scope
It is known that related firms choosing to stay in a common location for a long period of time
benefit in terms of reduced training requirements, from the informal transfer of skills between
skilled workers and from skilled workers to their children and others in these locations (Marshall
1920). Jacobs (1969) puts forward an alternative argument that diversity rather than commonality
of spatially concentrated firms fosters innovation via a ‘cross fertilization of ideas’ process. This in
turn leads to the creation of new industry sectors with inter firm linkages that create external
economies of scale.
SGS Conclusion: The method outlined in this paper has made no assumptions about
industry interactions. That is, the uplift for a particular industry’s labour productivity
resulting from agglomeration is a function of access to total employment rather than access
to employment in other selected industries.
Various studies have sought to identify the impact of increasing city size on firm productivity - also
known as urbanisation economies. Shefer (1973) considers a cross section of municipalities and a
group of industries and concludes that doubling city size would increase firm productivity by 14 -
27%. Sveikauskas (1975) found that there would be an increase of only 6 -7%, in line with the
projections of later studies. Nakamura (1985) and Henderson (1986) examined the relative impact
of both localisation and urbanisation economies on productivity.
Nakamura looked at Japan and concluded that doubling the scale of an industry leads to a 4.5%
increase in productivity while doubling the size of a city leads to a 3.4% increase. Henderson
looked at the United States and Brazil and found almost no evidence of urbanisation economies and
a lot of evidence of localisation economies. Together with research by Moomaw (1983), Henderson
(2003) and Rosenthal and Strange (2003) these papers point to localisation effects being stronger
than urbanisation effects.
Another way of measuring agglomeration economies is to measure the extent to which a city’s
employment is specialised; measured as a share of employment by a particular industry sector by
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Glaeser et al (1992) and Henderson et al (1995). Glaeser’s work found that specialisation did not
encourage growth, when the development of a city’s top six industries in 1956 was tracked over
the period 1956 – 1987. Henderson investigated eight different industries (three evolving as high
tech and five mature industries) from 1970 – 1987 and concluded that specialisation has a positive
influence on growth for mature industries but that evolving industries perform better in cities with
diverse industry profiles. Duranton and Puga (2003) use French data to show that as some
industries reach maturity they move from diverse cities to those with a less varied industrial
profile.
Theories on the origin of agglomeration economies have almost always been grounded in the
concept that increasing the absolute scale of an industrial activity always brings benefits. For
example – having more workers to choose from means workers are employed in jobs better suited
to their skills, Helsey and Strange (1990). The flip side to this argument is that diversity of
industries brings cross fertilisation of technologies and leads to the birth of new industries and
growth and innovation in existing ones, Chinitz (1961). Combes (2000) finds that specialisation
and diversity both have negative effects on growth for all but a few industry sectors within
Manufacturing. But when the same analysis is made for service industries, Coombes found that
while specialisation continued to have a negative effect on growth, diversity had a positive effect.
The question of how agglomeration economies subside as nearby activity becomes increasingly
dissimilar remains little explored in the literature. It is difficult to measure ‘industrial distance’ i.e.
the distance between the function of two industries. Cluster mapping based on supply relationships
and the similarity of production processes such as by Ellison and Glaeser (1997) is the closest
approximation available.
11.3.2 Geographic Scope
Until recently, research into agglomeration economies has defined geography on the basis of
political boundaries and not assumed the gradation of effects within and in response to firms from
outside these boundaries. Ciccone and Hall (1996) departed from this approach and measured
employment density across New York State at the local (county) level. They found that doubling
county population density led to an approximately 5% increase in productivity.
Dekle and Eaton (1999) used rents to identify minor agglomeration economies for Finance and
Manufacturing in Japanese prefectures related weakly to increasing urban size – a 1% increase in
productivity for a doubling of population. Rosenthal and Strange (2003) found that industries which
relied more heavily on manufactured or natural products inputs or which produced perishable
products were more inclined to concentrate in geographic proximity. Ellison and Glaeser (1997)
and Duranton and Overmans (2002) measured industry concentration and agglomeration effects at
different scales and concluded that the effects are localised. Duranton and Overman found that
localisation benefits dissipate beyond fifty kilometres of distance.
Graham (2006) found that an elasticity of 0.125 for the whole economy, 0.052 for Manufacturing
(with large variation within the industry) and 0.20 for services. These results are in line with the
SGS findings. Graham’s findings confirm the role that transport projects have in increasing the
density of a city and the subsequent productivity improvements.
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The European Conference of Transport Minister’s Round Table 119 outlines that, by widening the
area of goods markets, transport improvements may promote competition, thereby enhancing
economic efficiency. The effect may be analogous to the removal of customs barriers. The removal
of such barriers results in higher productivity and raises the purchasing power of populations,
which benefit from the specialisation of trade.
Second, improved transport links which increase transport speeds may have the same effect as
increasing the size of the employment market, as a greater number of job-seekers will be able to
travel to more distant jobs. This will allow for greater productivity as employers are better able to
find employees qualified for the jobs they are seeking to fill.
SGS Conclusion: The method in this paper draws upon the distinct outlined by the
Minister’s Round Table that there are two distinct impacts which are at work. The first that
increase the size of the economy (in this case via improved access to jobs) will lead to
improve productivity brought about by increased economies of scale and scope. The second
is productivity improvements brought about by improved job matching.
The Commonwealth Treasury22 outlines that “The Government also has a role in investing directly
in infrastructure, innovation and Human Capital. Such direct investment may be necessary where
markets for a good or service are incomplete, goods have public good characteristics, or there are
positive spillovers associated with the production of a good or service”.
While the Treasury recognised that there are “spillovers” which come from infrastructure and
Human Capital investments, a methodological framework to measure the benefits from these
investments is not provided.
11.3.3 Temporal Scope
A key issue that is considered in the literature about agglomeration economies is the question as to
whether past economic environments (say from previous decades) can continue to impact
agglomeration economies many years later, albeit indirectly. Glaeser et al (1992) and Henderson et
al (1995) both incorporate this consideration into their growth models. A direct dynamic effect
(often referred to as ‘knowledge spill over’) involves industrial activity from many years ago
positively influencing today’s productivity.
A paper by Glaeser and Mare (2001) estimates the temporal scope of agglomeration economies by
regressing data on wage rates against a range of worker and location attributes. This analysis
shows that there is an urban wage premium of circa 20% but that this premium is enjoyed more
by long time city residents than by recent immigrants. Also, when long time urban workers leave
their city, the wages they earn in their new location are higher the larger the city they move from.
SGS Conclusion: This is no doubt reflecting the Human Capital accumulation opportunities
which these workers have had access to.
22 www.treasury.gov.au/.../4_Productivity_Growth_Submission.rtf
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11.4 ‘Culture’ and the Transmission of Agglomeration Economies
Porter (1990) argues from case evidence that competition encourages innovation by forcing firms
to innovate or fail. Competitive pressures are therefore seen to improve productivity. Conversely,
Marshall (1920), Arrow (1962), Romer (1986) and Glaeser et al (1992) assert than competition
decreases productivity because firms in a competitive local market cannot guard their intellectual
property as effectively – they are subject to churn and transfer of staff to competitors. Saxenian
(1994) compares the performance of two centres of computer software - Silicon Valley and
Boston’s Route 128.
Saxenian argues that the extent of local technological capabilities stemming from protected
intellectual property is not the main source of differences in industry performance; instead having
an open and flexible industry culture that allows for entrepreneurialism is advanced as the main
performance driver. Rosenthal and Strange found that when smaller firms hired an additional
skilled employee this tended to have a positive effect on the entire local industry and correlated
with the birth and increased labour force of other small local businesses. The same effect was not
observed when larger firms added employees. This is consistent with Saxenian’s findings.
Another agglomeration effect comes from the different incentives that drive urban residents to
perform in the workplace. Cities may either inspire or require hard work from their residents. Cities
requiring hard work of their residents are colloquially referred to as ‘rat races’ by Rosenthal and
Strange (2002). This issue has been examined by Rosenthal and Strange who looked at the nexus
between agglomeration and work behaviour. The research found that professional workers in their
30’s and 40’s work longer hours in locations where the density of employment in their occupation is
high. Further investigation showed that both the presence of competitors and the opportunity to
advance (both agglomeration effects) motivated this behaviour. No significant effect was found for
non professional workers.
SGS Conclusion: This result is in line with the Human Capital analysis presented in section
Error! Reference source not found. Error! Reference source not found.. The analysis
ghlights that a person with a Higher Degree will reap higher benefits from increased
agglomeration than a person without qualifications.
11.5 Sources of Agglomeration Economies
Agglomeration arises both from the benefits of firms locating in an area where they can exploit a
natural advantage and from firms locating together to take advantage of agglomeration economies.
The relative contribution of each of these factors has been explored by Kim (1995, 1999) and
Ellison and Glaeser (1999). Kim looked at agglomeration between 1860 and 1987 and regressed a
location quotient – measuring the concentration of industry against plant size, natural resource
availability and dummy variables for industry sector and time. The positive coefficient returned for
the natural resources variable suggested that this was highly significant. Ellison and Glaeser
showed that 20% of agglomeration can be predicted by the presence of natural advantages.
However it is likely that over time the role of natural advantage in determining agglomeration has
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been decreasing because labour has become more mobile – enabling industries to continue to
concentrate in an area and enjoy agglomeration economies by importing labour.
The research reveals little about the micro foundations of agglomeration economies.
Agglomeration economies typically involve knowledge sharing, labour pooling and input sharing.
Any one or multiple combination of these micro foundations can increase productivity which
increases profitability and leads to firm growth, Helsey and Strange (2001). This does not help
reveal the individual role of each of these micro foundations in fostering growth; a more structured
approach is necessary. Glaeser and Mare (2001) propose that by looking at the dynamic structure
of agglomeration economies, the micro foundations can be identified; the lag in wage increases in
response to urbanisation suggests that this effect is a result of knowledge spillovers. Alternatively,
Henderson (2003a) suggests that looking at the impact of the number of firms in a location on the
productivity of their neighbours will capture the impact of knowledge spillovers.
SGS Conclusion: SGS provides a clear framework for understanding productivity changes
brought about by agglomeration but also acknowledges that micro foundations still require
further more detailed research.
11.5.1 Input Sharing
The concept of input sharing depends on the existence of scale economies in purchasing production
inputs, Marshall (1920). Without scale economies, an isolated firm could request a small batch of a
production input and pay the same per unit price as a larger order from a collective of firms. Where
producers receive collective or multiple demands for an input, they can achieve the cost
advantages from an efficient scale of production and pass some of this gain on to their customers.
Holmes (1999) investigates the connection between whether a firm locates in close concentration
with similar firms and whether it engages in input sharing with other firms. Holmes uses Census
data on Manufacturing sales at the establishment (firm) level and Census data on purchased
inputs. Purchased inputs are divided by sales to give purchased input intensity which is also a
measure of vertical disintegration or input sharing.
The differences in purchased input intensity between locations of concentrated similar firms and
other locations across the USA were then examined. It was found that across all industries, moving
from an un-concentrated location (fewer than 500 employees in the same industry) to a
concentrated location (10,000 – 24,999 neighbouring employees in the same industry) resulted in
a 3% increase in purchased input intensity. It can also be expected that in the presence of input
sharing by purchasers, input suppliers would carry out more specialised functions. Because
industry classification protocols typically place vertically integrated stages of production in the
same category, it is difficult to test this theory. Holmes looks at the textile industry for which
specialised textile finishing plants are afforded a separate industry classification from the rest of
the industry.
Holmes found that where the industry was more concentrated, the ratio of specialised finishing
plants to total plants tended to be higher. Holmes and Stevens (2002) found that firm size is larger
in locations where an industry is concentrated. A ‘size coefficient’ was developed equivalent to the
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ratio between mean firm size in a location and mean firm size for that industry across the USA.
This does provides indirect evidence of vertical integration.
11.5.2 Knowledge / Technological Spillovers
With knowledge / technological spillovers, information is often exchanged between firms without
being bought or sold – in contrast to input sharing, Helsey and Strange (2002). Where exchanges
do occur, these are likely to be compacted joint ventures for which data is not routinely collected.
To address the challenges of a lack of official data about knowledge spillovers, Jaffee et al (1993)
use the location of firm patent citations to create a ‘paper trail’ of knowledge / technological
spillovers. They found that patent citations are spatially concentrated, with citations five to ten
times more likely to come from the same municipal area than control patents. This effect is
expected to vary with industry scope – being most pronounced in those industries that are highly
innovative, Audretsch and Feldman (1996).
Workers are the primary carriers of knowledge / technological spillovers. Rauch (1993a) looks at
the impact of education levels on wages and rents. Where average education levels were high; this
sharing of information as a public good was shown to increase wages across the sector. Rents were
also shown to be higher, because the productivity enhanced higher wages were capitalised by the
housing market. Charlot and Duranton (2002) find that workplace communication is more
extensive in urban areas but that this accounts for only 10% of the urban education effect. This
suggests that other knowledge / technological spillovers are taking place or that improved
education levels impact other micro foundations of agglomeration economies. In summary, the
exact channel of interaction whereby increased levels of education flows through to increase
productivity across an industry sector is poorly understood.
SGS Conclusion: The method employed by SGS allows a good understanding of changing
education and experience levels have on Human Capital and the subsequent productivity
improvements are the aggregate level. But industry specific Human Capital productivity
impacts are more different to assess as Human Capital is not fixed to a particular industry
(that is workers can move between industries) but industry specific experience is strong
linked to Human Capital.
11.5.3 Labour Market Pooling
There are two related explanations for labour market pooling. One is that workers in large cities or
industrial concentrations should be better matched to their roles. This can be examined by looking
at termination rates, controlling for conditions in the local economy and industry sector. However
because employers of firms in smaller cities have fewer options with which to replace an employee
should they decide to terminate that person, the actual termination rates might not indicate the full
extent of matching unsuitability. Alternatively, rates of employee turnover could be studied to
identify labour market pooling; high employee turnover rates indicate that workers can readily
change jobs and firms can readily hire new employees. Baumgartner (1988) looks at medical
practitioners and shows that in larger markets, practitioners perform a narrower range of activities,
confirming that agglomeration can foster specialisation.
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The other explanation for labour market pooling is that it is based on risk. When a new employee
commences employment with a firm, both the employee and the firm carry risks if the relationship
is unsuccessful and the employee is terminated. The worker will need to find another job and the
employer will need to find another employee. Where the worker’s skills and the firm’s requirements
are specific to an industry, both of these needs are thus more easily met where the industry is
concentrated and there are alternative firms and alternative potential employees. Worker and firm
risk are both reduced by localisation. However, industries are subject to periodic ‘shocks’ that
result in workers losing their jobs. Locating in a specialised city exposes workers to the risk of
losing their job and being unable to find alternative employment locally.
SGS Conclusion: Australia’s limited number of major cities means that there is not the level
of city specialisation which is observed in the United States or Europe.
The risk of industry shocks therefore discourages localisation in opposition to the benefits of
specialisation for firms and employees. Simon (1988) considers the relationship between the
unemployment rate and a city’s level of specialisation. Unemployment rates are shown to be
greater in cities with higher degrees of specialisation - consistent with the idea of industry shocks
being an important issue. It could therefore be expected that workers in specialised cities demand
higher wages to compensate them for this risk. Diamond and Simon (1990) show that workers
demand higher wages in more specialised cities and that these higher wages are also related to the
cyclical variability of employment by industry.
Costa and Kahn (2000) advance the argument that risk is lower and matches of employee to role
are better in larger cities. By looking at “power couples” – married couples who both have at least
a bachelor degree qualification; Costa and Kahn documented a substantial increase over time in
the population proportion of large cities that these couples comprise – from 32% in 1940 to 50% in
1990. This may result from these couples having met, married and stayed in large cities or it may
be explained by large cities being better able to offer career opportunities that closely match the
abilities of both partners than smaller cities. To test for each of these explanations, Costa and Kahn
look at the differences between the location patterns of “power couples”, other types of couples,
single persons and unmarried couples and concluded that 36% of the increase in concentration of
“power couples” in large cities can be ascribed to the dual career hypothesis.
Therefore, if the productivity of the highly educated is important for economic performance, then
large cities have a productivity advantage in so far as their ability to better match employees to
roles that meet their abilities and achievable aspirations.
11.5.4 Home Market Effect
Suppose that increasing returns result in concentration of employment into a large factory. This in
turn creates a large market for suppliers who seek to locate close to the large factory to reduce
their transport costs. This leads to a ‘magnification’ effect where the ‘home market’ (the large
factory and its suppliers) expand in a self reinforcing process of agglomeration.
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Krugman (1980) and Davis & Weinstein (1996) formally investigated this phenomenon. Davis and
Weinstein (1999) looked at regional agglomeration across Japanese prefectures. They identified
substantial increasing return effects on industrial concentration in eight of nineteen prefectures.
They concluded that the home market effect is an important determinant of regional concentration
in both large cities and smaller localities. Hanson (1998a) looked at the shift in Mexican industrial
production from Mexico City to cities along the US border in response to the NAFTA trade
liberalisation agreement. In this instance, the opportunities from trade with international markets
began to outweigh home market advantages from locating in the Mexico City mega polis and the
home market effect was diluted.
11.5.5 Consumption
While it is relatively accepted that cities contribute to industry agglomeration because of their
effect on industry productivity, recent research also looks at the role of consumers in large cities in
encouraging consumption driven agglomeration economies of city firms. Glaeser (2001) argues
that there are four processes by which this can happen.
Firstly, the population of the city is large enough to create a viable local market for some goods
and services that are not available in smaller centres (such as operatic performances). Secondly, a
large city may create an aesthetic charm (‘pace’, ‘style’ or ‘mood’) which enhances citizen and
visitor’s sense of wellbeing and in doing so encourages citizens and visitors to spend more money
on leisure, food and beverage and retail goods. Thirdly, the population of the city is large enough
for the provision of public goods and services that are not available in smaller centres (such as
specialised medical services). Fourthly, the dense settlement pattern of cities allows goods and
information to be exchanged rapidly.
SGS Conclusion: Given the geographical size of Melbourne (and other Australian cities)
Glaeser thinking can be applied to the distinct regions which have formed within the city.
Figure 46 highlights the different employment / economic regions identified in Melbourne. For
example, Footscray CAD should be able to provide a range of services to western Melbourne.
But a relatively small population and relatively poor links to the central core prevent it from
being able to fulfil this role.
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Figure 46 Identified Employment Regions within Metropolitan Melbourne
Source: SGS Economics & Planning
Glaeser presents evidence to show the importance of consumption in driving the agglomeration of
activities in cities. The phenomenon of reverse commuting indicates that some workers are willing
to live in inner city locations and drive to work in suburban locations – presumably because inner
city living – despite the high cost of dwellings – offers the resident a high amenity environment in
which to live, socialise and shop. Glaeser also regresses rates of urban growth against measures
of the four processes identified as encouraging consumption driven agglomeration in cities. The
analysis showed that having a temperate climate and/or specialised leisure facilities promoted a
cities growth.
Waldfogel (2003) takes the work of Glaeser further by investigating the concept that the larger
markets in cities enable goods to be more closely tailored to individual consumer tastes. Waldfogel
looked at radio listening patterns and identified that as a cities population increased by one million
residents, the proportion of the population who listened to radio increased by 2%. Waldfogel
identified that the number of radio stations targeting particular ethno linguistic subcultures (African
and Hispanic) also increased with city population size. This suggested that radio stations were able
to diversify their offer in larger cities and thus increase their total listening audience (market size).
Tabuchi and Yoshida (2000) found that the real wages (spending power) of city residents was
elastic (by between -7% and 12%) depending on city size. This is evidence that some city
residents are willing to forego wages to enjoy the consumption benefits of living in a large city.
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APPENDIX E: DETAILED INDUSTRY WIDE BREAKDOWN OF INDUCED IMPACTS
Table 31 Total Induced Impacts (by Industry) of Additional Households on
Knox (C) Output ($ Million)
Estimated Direct Impacts of Household Consumption
Estimated Total (Direct + Indirect) Impacts of Household
Consumption
At 2021 At 2046 At 2021 At 2046
Agriculture, Forestry & Fishing $0.03 $0.07 $0.06 $0.15
Mining $0.00 $0.00 $0.02 $0.04
Manufacturing $5.09 $12.67 $9.79 $24.36
Electricity, Gas, Water & Waste Services $0.25 $0.63 $0.45 $1.13
Construction $0.06 $0.14 $0.68 $1.69
Wholesale Trade $2.35 $5.86 $3.77 $9.38
Retail Trade $3.79 $9.44 $4.95 $12.33
Accommodation & Food Services $1.85 $4.61 $2.40 $5.96
Transport, Postal & Warehousing $0.50 $1.23 $1.18 $2.93
Information Media & Telecommunications $0.43 $1.08 $0.82 $2.04
Financial & Insurance Services $1.99 $4.94 $4.18 $10.39
Rental, Hiring & Real Estate Services $7.64 $19.02 $10.09 $25.10
Professional, Scientific & Technical Services $0.11 $0.27 $1.15 $2.87
Administrative & Support Services $0.04 $0.11 $0.79 $1.97
Public Administration & Safety $0.03 $0.08 $0.13 $0.32
Education &Training $0.82 $2.04 $1.07 $2.65
Health Care & Social Assistance $1.25 $3.10 $1.54 $3.84
Arts & Recreation Services $0.47 $1.16 $0.61 $1.52
Other Services $0.98 $2.45 $1.52 $3.78
Local Expenditure $27.68 $68.89 $45.18 $112.45
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Table 32 Total Induced Impacts (by Industry) of Additional Employment on
Knox (C) Output
Estimated Direct Induced Employment
Estimated Total (Direct + Indirect) Impacts of Induced
Employment on Output ($ Million)
At 2021 At 2046 At 2021 At 2046
Agriculture, Forestry & Fishing -1 -3 -$0.34 -$0.60
Mining 0 0 $0.15 $0.26
Manufacturing 16 19 $24.89 $45.01
Electricity, Gas, Water & Waste Services 2 5 $1.76 $4.30
Construction 13 29 $8.14 $19.42
Wholesale Trade 10 22 $8.12 $18.98
Retail Trade 23 56 $5.81 $14.60
Accommodation & Food Services 19 45 $4.11 $10.25
Transport, Postal & Warehousing 11 28 $5.26 $12.73
Information Media & Telecommunications 10 19 $5.90 $11.94
Financial & Insurance Services 18 56 $16.68 $49.36
Rental, Hiring & Real Estate Services 4 11 $16.07 $42.14
Professional, Scientific & Technical Services 44 153 $15.69 $51.12
Administrative & Support Services 9 18 $4.32 $9.81
Public Administration & Safety 15 30 $3.04 $6.40
Education &Training 17 39 $2.71 $6.43
Health Care & Social Assistance 35 112 $4.50 $13.77
Arts & Recreation Services 6 14 $1.38 $3.37
Other Services 10 24 $3.13 $7.76
Local Expenditure 262 678 $131.32 $327.04
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Table 33 Total Induced Impacts (by Industry) of Additional Employment on
Knox (C) Employment
Estimated Direct Induced Employment
Estimated Total (Direct + Indirect) Induced Employment
At 2021 At 2046 At 2021 At 2046
Agriculture, Forestry & Fishing -1 -3 -1 -2
Mining 0 0 0 0
Manufacturing 16 19 38 70
Electricity, Gas, Water & Waste Services 2 5 3 8
Construction 13 29 24 57
Wholesale Trade 10 22 21 48
Retail Trade 23 56 60 152
Accommodation & Food Services 19 45 34 85
Transport, Postal & Warehousing 11 28 20 49
Information Media & Telecommunications 10 19 13 27
Financial & Insurance Services 18 56 28 84
Rental, Hiring & Real Estate Services 4 11 9 23
Professional, Scientific & Technical Services 44 153 61 198
Administrative & Support Services 9 18 18 42
Public Administration & Safety 15 30 17 36
Education &Training 17 39 25 59
Health Care & Social Assistance 35 112 45 136
Arts & Recreation Services 6 14 9 23
Other Services 10 24 22 55
Local Expenditure 262 678 447 1,151
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