telmos: the transport/economic/ land-use model of … · • the telmos (the...
TRANSCRIPT
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TELMoS: the
Transport/Economic/
Land-use Model of
Scotland
David Simmonds David Simmonds Consultancy,
Cambridge & Edinburgh
Heriot-Watt University,
Edinburgh
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Presentation structure
• The DELTA package
• The Scottish context
• The TELMoS (the Transport/Economic/Land-use Model of Scotland)
family of models
• Implementing TELMoS
• Calibrating TELMoS
• Applications of TELMoS and related models
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Background – the DELTA package
• Development of DELTA started in 1995, to meet a perceived
demand for a land-use modelling system that could be linked to
fairly standard transport models
• Prototype was applied to Edinburgh, in collaboration with ITS
Leeds, MVA Consultancy and City of Edinburgh Council
• First major consultancy application was for GMPTE, as part of
GMSPM
• This was followed by the Trans-Pennine Corridor Model, which
involved adding a “regional” level in addition to the “urban” one
• Since then, DELTA has been quite widely used in the UK, plus a
major application in New Zealand and several small academic
applications elsewhere.
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Economic scenario Demographic scenario
Planning policies Transport plans
DELTA Transport
model
Base
year
data
Future
year
data
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LUTI model contents
Main land-use processes:
• Demographic change,
migration
• Economic output, employment
• Physical development –
floorspace, housing
• Car ownership
• Household and job location (in
property markets)
• Whether/where to work
• Change in quality of housing
Main transport choices (usually)
• how often to travel
• when to travel
• destination choice
• mode choice
• route choice
• congestion effects (roads,
public transport, parking)
[transport model is outside
DELTA]
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DELTA components: sequence within one time period
SPACE
Development
(of floorspace)
Residential
Quality
ACTIVITY
Car Ownership
Location
Employment
(commuting)
Urban (zonal) level
Transition
(Households )
Migration
ACTIVITY
Regional
Economic
Model
Migration
ACTIVITY
Regional
(area) level
transport-influenced
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Model forms – discrete choices
Discrete choice models user various forms of logit model:
• hierarchical, cross-sectional model of destination and mode use
used in calculating accessibilities (we use the resulting logsum
values, not the mode and destination shares)
• incremental logit models of location (zone) choice in locating jobs
and households
• incremental hierarchical logit (with saturation levels) for car
ownership [incremental, zonal application of a Department for
Transport model]
• absolute logit model to locate increments of development
• some forms of the model use incremental logit model of whether
and where to work
• trade model uses a cross-sectional model of where inputs will be
obtained.
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Model forms
Continuous models are quite diverse:
• Total development of each floorspace type started each year:
linear or multiplicative
• Household expenditure: Cobb-Douglas or Stone-Geary functions
• Input-output model: most of the coefficients are fixed, so
production is a linear function of demand
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transport
Land-use
database
2006
Land-use
database
2007
Land-use
database
2008
Land-use
database
2009
Land-use
database
2010
Land-use
database
2011
transport
DELTA DELTA DELTA DELTA DELTA
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household location
employment location
household migration household transformations,
formations, dissolutions;
migration to/from model
housing development
(quantity and location)
persons working/not-working
in households, commuting
car-ownership proportions
by household type
(conditional on location)
non-residential
rents by type
investment model
by sector
spatial I/O model
by sector
accessibility to market
(demand) for sector)
accessibility to
consumers
accessibility to
jobs/services etc
accessibility to
labour
housing quality changes
jobs by sector
and seg
employment
rates
demand by sector
Area-level variable Area-level model
Zonal variable Zonal model
Red outline –
influenced by
transport costs
Immediate linkage
Simultaneous
calculations
Time-lagged linkage
Linkage based on
changes over time
DELTA model linkages (c0.15 PN 22/08)
Employment status model
Developmen
t and quality
models
production by sector
Incomes by zone
Location
models
Regional
economic
model
Employment
status model
Car
ownership
model
Demo-
graphic
model
Regional economic model
Purple outline –
main outputs to
transport model
trade by sector
vacant housing
housing rent
non-residential development
by type ( quantity and location)
vacant floorspace
(by type)
capacity by
sector
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The Scottish context for modelling
• 1999: restoration of the Scottish Parliament, with a Scottish
Executive (renamed Scottish Government in 2007), with devolved
powers in planning, transport, environment and economic
development
• 2000:
– Edinburgh: New Transport Initiative – focus on public transport
investment supported by road user
– Glasgow: Central Scotland Transport Corridor Studies – focus on
highway investment
• Land-use/transport interaction modelling commissioned in both
areas
• The LUTI model developed for the Glasgow sub-region was
gradually adopted by Scottish Government (now through Transport
Scotland) and extended to cover the whole country as LATIS.
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TELMoS:07 definitions/key features
• 720 zones
– 712 fully-modelled
– 8 external
• 50 areas
– 47 areas - based on the 2001 Travel to Work Areas
– 3 external areas
• Rest of the UK
• Rest of the world via UK
• Rest of the world
• 20 household types * 4 person types, plus persons not in households
• 27 employment activities grouped into 10 economic sectors
• 7 floorspace types
• 5 purposes / 7 measures
• 3 Car-ownership levels
• Transport model every five years
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DELTA implementation and calibration
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Model design
Database
assembly
Data synthesis/
reconciliation
DELTA database
Initial DELTA model
DELTAMOD.DEF
DELTA recompilation
software modifications
calibration (1)
DELTA calibration (2)
DELTA/transport model
LUTI model calibration (3)
transport
model
interface
modifications
demonstration tests
using DELTA
pre-DELTA
policy inputs scenario inputs
new surveys?
generalised costs
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Starting database
• DELTA requires an extensive database for its base year
• Ideally this is a Census year
• Usually it isn’t!
• Usual procedure is to create the database in the most recent
Census year and to model the changes since then by running the
model with constraints to impose observed changes
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Scenarios
• Demographic scenario (households and persons) usually taken from
official projections
• This has to be reproduced in terms of household changes over time
• Economic/employment scenario also usually taken from official
projections
• This has to be reproduced in terms of changes in incomes and
exports (or more complex changes)
• [Other DELTA applications for smaller regions are implemented so
that a Base run of the model matches the given scenarios, then the
totals can vary in Alternative runs]
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Calibration approach Example applications
Own analysis of observed data LLITM residential relocation model
Analysis of synthetic data (from
microsimulation modelling)
Household transition models
Matching data reported by others Range of floorspace/worker values
Household mobility rates
Direct use of coefficients
estimated by others
Car-ownership model
Reproducing elasticities (etc)
reported by others
Effect of accessibility improvement on
residential rents
Reproducing elasticities (etc)
implied by the coefficients
reported by others
Effect of changing employment
opportunities on rates of migration
Matching to “stylized facts”,
professional judgement
Choice of variables in migration model
Overall “reasonableness” of each
component and of the model as a whole
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Ways of using coefficients from other research
Independent results may give
• coefficients which we can use directly as inputs [possibly with
adjustment over time]
• average coefficients, around which we estimate variations eg by
income group
• values we can check analytically eg by examining the ratios of our
own coefficients
• values we can check by running part of the model once
• values we can check by comparing two runs of parts of the model
• values we can check by comparing two runs of the full model (ie
over several years).
“Check” can mean that anything from “adjusting model coefficients
to match the independent result to 3 significant figures”, to
“comparing the general trends”.
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Statistical analysis of results to compare a
relationship with an independent coefficient
• Suriatini Ismail, for her Aberdeen PhD thesis, carried out a detailed
hedonic price analysis on Glasgow housing
• Among her (many) independent variables she included accessibility
values which we provided from the Central Scotland model (one of
TELMoS’ ancestors)
• She found that a one minute worsening in accessibility (ie a one
minute increase in expected generalised cost of getting to work)
was associated with a reduction of -1.7% to 2.4% in price [range is
from different model forms; considering the error of the estimates
would widen the range]
• Our models are incremental, so we can’t check this in the base
data [that would just redo Suriatini’s analysis with less data]
• The best way we have found to test this relationship is to run a
Reference Case, then make random changes to accessibility in one
year, rerun and look at impacts on prices in following year...
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Suriatini
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Using independent results to estimate an
elasticity-like value
• Bramley and Leishmann used panel data for Health Authority areas
to estimate a five equation model for house building, prices,
vacancies and gross migration flows
• We identified which variables would change with a “shock” to
employment in one area, including impacts of extra jobs on
incomes and unemployment rate
• Using the published coefficients, we estimated the impact on
annual net migration of 100 extra jobs in an average area
• We made explicit assumptions to get from the age group
represented in the migration model to the total working-age
population
All this led us to expect that
• 100 extra jobs would draw in a cumulative net total of 25 to 50
working-age persons over slightly more than five years,
• the effects would continue longer than five years
• both +ve and –ve feedback effects could apply.
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38 jobs per 100 additional
workers after 5 years
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Comparison of impact on a trend over time
Following two slides show
• our results from a new model of the Greater South-East (London,
East, SE), for a test where new housing development is doubled for
10 years, as percentage impacts on average house prices relative
to the Reference Case (ie the original rate of housing
development)
• results for a similarly-specified test, produced by Meen et al using
the CLG Housing Affordability model
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Maximising the value of future urban/regional
economic research
• Use of accessibility rather than distance-from-CBD in hedonic
price/rent analysis (and elsewhere)
• Express results as elasticities or odds ratios, or quote mean (or
median?) values of independent variables
• If showing example runs of a model, express the inputs in explicitly
quoted units (not in standard deviations)
• Generally need to represent the whole of each property markets:
difficult to use detail researched only for certain segments
• Likewise need to know how many people are moving (etc), not just
what influences them.
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TELMoS applications
• Multiple rounds of producing “business as usual” land-use forecasts
for input to the Transport Model for Scotland, used for
conventional transport modelling
• Preparation of alternative scenarios for use in TMfS
• Runs to forecast the impact of major development programmes
and plans (eg for Glasgow City Council, South-East Scotland
Planning Committee)
• Assessing impact of major public transport schemes, notably the
Airdrie-Bathgate reopening
• Assessing impact of major road investments, eg M74 Completion,
A8 upgrade, M80 Completion, A9/A96 Upgrades
• Possible future use as testbed for a method of Land-Use Transport
Economic Efficiency appraisal, as an advance from Transport
Economic Efficiency.
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TELMoS:07
Do-minimum
reference case
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M74 Completion
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Insert Fully Modelled Area map
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Insert areas map
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Employment BT-BS
-15000
-10000
-5000
0
5000
10000
15000
200002
00
5
20
07
20
09
20
11
20
13
20
15
20
17
20
19
20
21
20
23
20
25
20
27
20
29
Aberdeenshire
Perth and Kinross
Argyll and Bute
Stirling
Dumfries&G
E Ayrshire
G.Glasgow
Lothian
Highlands
Falkirk
Fife
Inverclyde
N Ayrshire
Lanarkshire
Borders
S Ayrshire
W Dunbartonshire
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Employment (percentage) BT-BS
-3
-2
-1
0
1
2
3
20
05
20
07
20
09
20
11
20
13
20
15
20
17
20
19
20
21
20
23
20
25
20
27
20
29
Aberdeenshire
Perth and Kinross
Argyll and Bute
Stirling
Dumfries&G
E Ayrshire
G.Glasgow
Lothian
Highlands
Falkirk
Fife
Inverclyde
N Ayrshire
Lanarkshire
Borders
S Ayrshire
W Dunbartonshire
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Population BT-BS
-10000
-8000
-6000
-4000
-2000
0
2000
4000
6000
8000
100002
00
5
20
07
20
09
20
11
20
13
20
15
20
17
20
19
20
21
20
23
20
25
20
27
20
29
Aberdeenshire
Perth and Kinross
Argyll and Bute
Stirling
Dumfries&G
E Ayrshire
G.Glasgow
Lothian
Highlands
Falkirk
Fife
Inverclyde
N Ayrshire
Lanarkshire
Borders
S Ayrshire
W Dunbartonshire
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Population (percentage) BT-BS
-1.5
-1
-0.5
0
0.5
12
00
5
20
07
20
09
20
11
20
13
20
15
20
17
20
19
20
21
20
23
20
25
20
27
20
29
Aberdeenshire
Perth and Kinross
Argyll and Bute
Stirling
Dumfries&G
E Ayrshire
G.Glasgow
Lothian
Highlands
Falkirk
Fife
Inverclyde
N Ayrshire
Lanarkshire
Borders
S Ayrshire
W Dunbartonshire
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Airdrie-Bathgate Railway
Reopening
• Plan was for a high frequency stopping service linking Glasgow and Edinburgh via Airdrie-Bathgate and intermediate communities
• The model is run twice with the scheme introduced in 2011- different costs
• Comparison of the job and population results in
2021 at different geographic levels
• The Airdrie – Bathgate rail link is a significant scheme in the context of Scottish passenger transport
• Re-opening was proposed in 2002
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Airdrie-Bathgate – Impacts: testing and results
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Airdrie-Bathgate – Impacts: testing and results
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Airdrie-Bathgate
Appraisal
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Airdrie-Bathgate – Conclusion
• Positive impacts in the corridor
• Positive impacts in West Lothian and North Lanarkshire
• Some support to deprived zones
• Will help achieve planning goals
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Conclusions
• TELMoS has made a significant contribution to the analysis of
major planning and transport decisions in Scotland over the
past decade
• Current work indicates that Transport Scotland intends to
make further use of TELMoS in future
• LUTI modelling in general is playing a gradually increasing part
in UK decision-making
• The development and use of DELTA has been an important part
of that trend, and also
• has established new links between LUTI modeling and a range
of urban and regional economic research
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Thank you for your attention!
With acknowledgements to our clients, Transport
Scotland. Views expressed are not
necessarily those of Transport Scotland or the
Scottish Ministers.
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55
TELMoS-07
definitions (1)
• 720 zones – 712 fully-modelled
– 8 external
• 50 areas – 47 areas - based on
the 2001 Travel to Work Areas
– 3 external areas
• Rest of the UK
• Rest of the world via UK
• Rest of the world
TELMoS_07 areas
©Crown copyright. All rights reserved Scottish
Government 100020540 2008.
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Lothian Development Plan
• New planning policy inputs
– Floorspace inputs taken as exogenous developments
– Additional floorspace is all occupied
• Economic scenario
– Extra floorspace converted into employment by sector
• Demographic scenario
– Young single and couple household types assumed to be the expected takers of the additional employment into the area
• LDP scenario ran as a LUTI model with transport costs in 2005, 2012 and 2017
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Lothian Development Plan - Results
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Employment changes against
commercial floorspace changes
Population changes against
residential floorspace changes
Lothian Development Plan - Results
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Lothian Development Plan - Conclusion
• Higher employment and full occupancy of newly developed sites
• Extra congestion from the additional people in work and living in
the area
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