Transcript HOUSEHOLD LOCATION PROJECT

Household location in response to
changes in transport/accessibility
– a microsimulation approach
using SimDELTA
Olga Feldman, David Simmonds
ESRC seminar
May 2009
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Presentation structure
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DSC focus
DELTA
SimDELTA
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DSC focus
Developers
Property market
Residents
Firms
Labour market
Product markets
Transport
infrastructure
suppliers
Transport market
Transport
service
suppliers
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Background to the DELTA package
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Started in 1995
Two key characteristics:
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Add-on to otherwise free-standing transport models
The model be constructed in terms of processes of change.
Various applications in collaboration with transport
specialists.
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Structure of the DELTA model
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The economic model
The urban land-use model
The migration model.
The transport model (to which DELTA is linked)
The meaning of “land use”:
Land-use modelling is usually concerned mainly with
• households and population
• employment
• building stocks (housing, commercial)
• the interactions between all of these
and less concerned with land itself.
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Structure of the DELTA model
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The transport model (to which DELTA is linked)
The economic model
The urban land-use model
The migration model.
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DELTA+a transport model sequence
2006
2007
2008
2009
2010
2011
Land-use
database
Land-use
database
Land-use
database
Land-use
database
Land-use
database
Land-use
database
DELTA
Transport
model
DELTA
DELTA
DELTA
DELTA
Transport
model
Links between main submodels and
transport model labour demand
Economic
model
(investment,
production
and trade)
labour
property
consumption
Zonal model
(household
and job
location,
commuting)
propert
y costs
transport
costs
freight
demands
Migration model
(longer distance
household
housing costs movements)
population
migration
transport
costs
travel
demands
Transport system
physical/demand quantities
costs or generalised costs
immediate
time-lagged
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Accessibility model – logsum approach

  W j exp  D g ij
1   j
 ln 
Ai 
D
    W(base _ year) j

  j
 


 

Ai = accessibility of zone i
Wj = opportunities at j (jobs by seg or retail floorspace)
gij = generalised cost from i to j
λD = distribution coefficient
The logsum approach avoids arbitrary thresholds, and adding new opportunities
or new modes always improves accessibility or leaves it unchanged
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Accessibility use in DELTA
Household
location
Development
model
(through
rents)
Regional
Economic
model
Employment
location
Accessibility
Car ownership
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DELTA dynamics
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Simple sequence of processes within one year
Complex time-lagged linkages over time
Model is incremental in one year steps so
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starts from an observed database
produces an updated database for each forecast year.
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DELTA components within 1 year
Zonal model
SPACE
Development
(of floorspace)
ACTIVITY
Transition
(Households )
Car Ownership
Location
Residential
Quality
Regional
Model
ACTIVITY
ACTIVITY
Migration
Migration
Regional
Economic
Model
Employment
(commuting)
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Linkages within DELTA
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SimDELTA
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SimDELTA
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A research project commissioned by DfT
The overall aim was to develop a new,
microsimulation - based model of household location
and related processes of change
Main result
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A new package named SimDELTA
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has been developed and
Calibrated for the South and West Yorkshire – SWYSimM
model; this area is chosen because of the existence of the
modelling system for this area known as SWYSM (South
and West Yorkshire Strategic Model) – DELTA + START
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Microsimulation modelling area&2001 LA
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SWYSimM modelling area
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Data sources
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1991 and 2001 UK Census of population
1991 Sample of Anonymised Records (SARs)
National Statistics
The British Household Panel Survey
Annual Survey of Hours and Earnings
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SWYSimM
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Full model – microsimulation and DELTA (linked to
the transport model SWYSM but not the full landuse and transport model)
Microsimulation only – microsimulation only runs
with some DELTA inputs
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Static part 1 – to synthesise the initial database
Static part 2 – additional variables added
Dynamic part
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DELTA components within 1 year
Zonal model
SPACE
Development
(of floorspace)
ACTIVITY
Transition
(Households )
Car Ownership
Location
Residential
Quality
Regional
Model
ACTIVITY
ACTIVITY
Migration
Migration
Regional
Economic
Model
Employment
(commuting)
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DELTA components within 1 year
Zonal model
SPACE
ACTIVITY
Development
(of floorspace)
Transition
(Households )
Regional
Model
ACTIVITY
ACTIVITY
Migration
Migration
Car Ownership
Household location
Job location
Residential
Quality
DELTA
components
Regional
Economic
Model
Employment
(commuting)
New microsimulation
components
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SimDELTA
diagram
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Transport models
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The transport model inputs are taken from the
models developed for SWYMMS.
2 transport models:
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a Strategic model with about 90 zones, and involving
aggregate representation of highway and public transport
supply, linked to a DELTA land-use model to form a full
land-use/transport interaction model; and
a ‘detailed’ model, employing 570 zones and involving
explicit representation of individual highway links and
public transport services.
The Detailed Transport Model (DTM) has been used
as the main source of transport inputs for the
household location research project (base year 2000).
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Static model
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JAVA coded simulated annealing model
1991 Census and 1991 SAS data are used in the
process
Output from simulated annealing contains all the
Census variables from the SARS for each member of
every household, not all needed
‘Not defined’, ‘not adequately described’ variables
had to be assigned values
Other variables had to be synthetically added,
particularly
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Household incomes, driving licences
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Simulated annealing process (1)
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A number of household records for one ward are
taken at random from the microdata (SARs)
The characteristics of these households are tabulated
and the resulting synthetic tables compared with real
Census tables for this ward, and the error (mismatch)
is calculated
Assuming there is a significant error between the
synthetic and real tables, some of the selected
households are swapped for an equivalent number of
household records randomly chosen from the
microdata, and the error recalculated
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Simulated annealing process (2)
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If the error has substantially increased, that swap is
rejected, otherwise the swapped records are retained
Swapping continues until a best fit to the
synthesized data to the real Census tables is reached
The analogy with the physical process of annealing
centres on the “temperature” variable which is used
to control the swapping of records: at high
temperatures more records are swapped than at low
temperatures.
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Additional inputs
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Socio-economic status
Economic status
Driving licences
Wage/Income
Assigning workplaces for workers in the base year
Potential cohabitees
Student households and shares
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Main outputs from the static model (1)
Person data
Area data
Job data
Dwelling data
Household data
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Main outputs from the static model (2)
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Area data: area ID, population, households, families,
jobs taken internally by seg, jobs available internally
by seg, jobs taken externally by seg, accessibility,
deprivation index, area centroid coordinates (easting,
nothing), dummy: is external?, DELTA zone,
DELTA area.
Dwelling data: dwelling ID, number of rooms,
tenure, area code, dwelling type.
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Main outputs from the static model (3)
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Household data: household ID, dwelling ID, area
ID, student house?, share house?, cars, income,
tenure, families, preferred tenure, preferred number
of rooms, mortgage value outstanding, mortgage
years outstanding, savings, DELTA household type
Person data: person ID, household ID, family ID,
area, age, sex, relation to head of household, marital
status, seg, ethnicity, economic category, work area,
driving licence, parent (for children), education level,
job ID, preferred economic status.
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Main outputs from the static model (4)
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Job data: job ID, seg, economic status, economic
status, area code, current wage, vacant?, person ID if
occupied
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Dynamic model processes
Individual
demographics
Household changes
Work related
processes
Household location
Interface with DELTA
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Individual demographics etc
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Ageing
Survival
Moving to institution
Birth/multiple birth
Redundancy
Entering labour market/Staying in education
Leaving/re-entering labour market
Change job
Retiring from labour market
Becoming permanently sick
Becoming other inactive
Driving licence losing and acquiring
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Household changes
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Student households and other shares
Absence from households
Separation
Couple formation/marriage
Household Division
Household expenditure
Housing income
Obtaining/losing car
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Work-related processes
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Job supply
Identifying main earner(s)
Seeking to change job
Wages
Accepting/rejecting job/candidate
Job and workplace choices
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Household location
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Housing stock process
Housing prices or rents
Household in/out migration
Whether the household is seeking to move
Housing tenure choice
Dwelling choice
Location choice
Household location/relocation
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SWYSM to microsimulation
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Changes in labour demand (conversion of aggregate
model results for employment into effects on job
availability and redundancy)
Changes in housing supply (convert aggregate model
results for housing development or demolition into
addition/removal of dwelling objects)
Conversion of SWYSM forecasts of migration from
the rest of the world into new household objects.
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Other SWYSM outputs used as
probabilities
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Changes in car ownership
Migration between different parts of the
microsimulated area
Migration from the microsimulated area to the rest of
the world (i.e. leaving the model).
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SWYSM DTM characteristics (1)
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The base year is 2000
Three time periods (morning peak, inter-peak,
evening peak)
Validated road traffic assignment models for each
time period, using SATURN software, with junctions
explicitly modelled on the inter-urban network and
link based speed/flow relationships used for major
urban areas
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Tests
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Transport test
M18 spur
New junction
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Artificial test
Total population in the zones with improved accessibility
20000
18000
Population Improved Zones
Reference Case
16000
14000
Population Improved Zones
5% Improvement in
Accessibilities
12000
Population Improved Zones
10% Improvement in
Accessibilities
10000
8000
Population Improved Zones
20% Improvement in
Accessibilities
6000
Population Improved Zones
1% Improvement in
Accessibilities
4000
2000
20
01
20
00
19
99
19
98
19
97
19
96
19
95
19
94
19
93
19
92
19
91
0
345000
Population All Other
Zones Reference Case
340000
Population All Other
Zones 5%
Improvement in
Accessibilities
Population All Other
Zones 10%
Improvement in
Accessibilities
Population All Other
Zones 20%
Improvement in
Accessibilities
Population All Other
Zones 1%
Improvement in
Accessibilities
335000
330000
325000
320000
315000
1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001
Total population in all other zones
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Conclusions
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We believe that the present project has achieved a
significant step forward in developing the first
application of a working dynamic microsimulation of
household change, location and commuting.
There are many modelling issues in need of further
work.
Nevertheless we believe that the model as it stands
can make a useful contribution to a range of other
ongoing studies.
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Acknowledgements
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We are grateful to the former DfT Project Officers,
Russell Harris and Mo Shahkarami, and to members
of the project Steering Group for a number of
helpful discussions during the course of the project,
and for their patience during the delays which the
project has incurred.
Full report
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is published the DfT website
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http://www.dft.gov.uk/pgr/economics/rdg/hlm/
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