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Household location in response to changes in transport/accessibility – a microsimulation approach using SimDELTA. Olga Feldman, David Simmonds ESRC seminar May 2009. Presentation structure. DSC focus DELTA SimDELTA. Developers. Residents. Firms. Transport infra- structure

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Household location in response to changes in transport/accessibility – a microsimulation approach using SimDELTA


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slide1

Household location in response to changes in transport/accessibility – a microsimulation approach using SimDELTA

Olga Feldman, David Simmonds

ESRC seminar

May 2009

presentation structure
Presentation structure
  • DSC focus
  • DELTA
  • SimDELTA
slide3

Developers

Residents

Firms

Transport

infra-

structure

suppliers

Transport

service

suppliers

DSC focus

Property market

Labour market

Product markets

Transport market

background to the delta package
Background to the DELTA package
  • Started in 1995
  • Two key characteristics:
    • 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.
structure of the delta model
Structure of the DELTA model
  • 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.

structure of the delta model1
Structure of the DELTA model
  • The transport model (to which DELTA is linked)
  • The economic model
  • The urban land-use model
  • The migration model.
delta a transport model sequence
DELTA+a transport model sequence

2011

2010

2008

2007

2009

2006

Land-use database

Land-use database

Land-use database

Land-use database

Land-use database

Land-use database

DELTA

DELTA

DELTA

DELTA

DELTA

Transport model

Transport model

links between main submodels and transport model

labour demand

Economic

model

(investment,

production

and trade)

Zonal model

(household

and job

location,

commuting)

Migration model

(longer distance

household

movements)

labour

population

property

housing costs

consumption

property costs

migration

transport

costs

freight

demands

transport

costs

travel

demands

Transport system

immediate

physical/demand quantities

costs or generalised costs

time-lagged

Links between main submodels and transport model
accessibility model logsum approach
Accessibility model – logsum approach

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

delta dynamics
DELTA dynamics

Simple sequence of processes within one year

Complex time-lagged linkages over time

Model is incremental in one year steps so

starts from an observed database

produces an updated database for each forecast year.

delta components within 1 year

Zonal model

Regional

Model

SPACE

ACTIVITY

Development

(of floorspace)

ACTIVITY

ACTIVITY

Transition

(Households )

Migration

Migration

Car Ownership

Regional

Economic

Model

Location

Residential Quality

Employment

(commuting)

DELTA components within 1 year
simdelta1
SimDELTA
  • 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

  • A new package named SimDELTA
    • 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
data sources
Data sources
  • 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
swysimm
SWYSimM
  • Full model – microsimulation and DELTA (linked to the transport model SWYSM but not the full land-use and transport model)
  • Microsimulation only – microsimulation only runs with some DELTA inputs
    • Static part 1 – to synthesise the initial database
    • Static part 2 – additional variables added
    • Dynamic part
delta components within 1 year1

Zonal model

Regional

Model

SPACE

ACTIVITY

Development

(of floorspace)

ACTIVITY

ACTIVITY

Transition

(Households )

Migration

Migration

Car Ownership

Regional

Economic

Model

Location

Residential Quality

Employment

(commuting)

DELTA components within 1 year
delta components within 1 year2

Zonal model

Regional

Model

SPACE

ACTIVITY

ACTIVITY

Development

(of floorspace)

ACTIVITY

Transition

(Households )

Migration

Migration

Car Ownership

Regional

Economic

Model

Household location

Job location

Residential Quality

Employment

(commuting)

DELTA components

New microsimulation components

DELTA components within 1 year
transport models
Transport models
  • The transport model inputs are taken from the models developed for SWYMMS.
  • 2 transport models:
    • 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).
static model
Static model
  • 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
    • Household incomes, driving licences
simulated annealing process 1
Simulated annealing process (1)
  • 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
simulated annealing process 2
Simulated annealing process (2)
  • 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.
additional inputs
Additional inputs
  • Socio-economic status
  • Economic status
  • Driving licences
  • Wage/Income
  • Assigning workplaces for workers in the base year
  • Potential cohabitees
  • Student households and shares
main outputs from the static model 1

Static model

Area data

Dwelling data

Household data

Job data

Person data

Main outputs from the static model (1)
main outputs from the static model 2
Main outputs from the static model (2)
  • 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.
main outputs from the static model 3
Main outputs from the static model (3)
  • 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.
main outputs from the static model 4
Main outputs from the static model (4)
  • Job data: job ID, seg, economic status, economic status, area code, current wage, vacant?, person ID if occupied
dynamic model processes

Individual demographics

Household changes

Dynamic model

Work related processes

Household location

Interface with DELTA

Dynamic model processes
individual demographics etc
Individual demographics etc
  • 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
household changes
Household changes
  • Student households and other shares
  • Absence from households
  • Separation
  • Couple formation/marriage
  • Household Division
  • Household expenditure
  • Housing income
  • Obtaining/losing car
work related processes
Work-related processes
  • Job supply
  • Identifying main earner(s)
  • Seeking to change job
  • Wages
  • Accepting/rejecting job/candidate
  • Job and workplace choices
household location
Household location
  • 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
swysm to microsimulation
SWYSM to microsimulation
  • 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.
other swysm outputs used as probabilities
Other SWYSM outputs used as probabilities
  • 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).
swysm dtm characteristics 1
SWYSM DTM characteristics (1)
  • 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
artificial test
Artificial test

Total population in the zones with improved accessibility

Total population in all other zones

conclusions
Conclusions
  • 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.
acknowledgements
Acknowledgements
  • 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

  • is published the DfT website
    • http://www.dft.gov.uk/pgr/economics/rdg/hlm/