modelling propensity to move house after job change using event history analysis and gis...
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Modelling propensity to move house after job change using event history
analysis and GIS
Marie-Hélène Vandersmissen (CRAD, Laval University), Anne-Marie Séguin (INRS-UCS), Marius Thériault (CRAD,
Laval University) and Christophe Claramunt (Naval Academy Research Institute, France)
2nd MCRI/GEOIDE PROCESSUS Colloquium on the Foundations of Integrated Land-Use and Transportation Models
Toronto, June 12-15 2005
2nd MCRI/PROCESSUS Colloquium, Toronto, June 12-15, 2005
IntroductionIntroduction
Transportation land-use modelling must consider decision-making behaviour of urban actors using disaggregate data in order to relate– Activity location, home choice, commuting and travel decision– Household, individual and professional profiles of persons
Probabilistic discrete choice theory is becoming the central issue of urban and transport modelling research– Implemented using logistic and Cox regression techniques– Aimed at modelling individual’s and household’s behaviour
Need for spatio-temporal GIS for analysing urban and transport systems where – Uncertainties exist in the system (aggregation is not straightforward)
• Emergent behaviour occurs– Decision rules for individuals and households are intricate– System processes are time-path and location dependent
• Future system state depends partly on past and current states
2nd MCRI/PROCESSUS Colloquium, Toronto, June 12-15, 2005
Our project in the MCRI programmeOur project in the MCRI programme
2nd MCRI/PROCESSUS Colloquium, Toronto, June 12-15, 2005
PurposePurpose
Emergent residential behaviours of individual actors in context of profound social changes in the work sphere
Long term-view in the analysis of the relationship between social changes in the work sphere and these behaviours
Socialchanges
Long-term dynamicsof residential location
behaviour
Travel behaviour
2nd MCRI/PROCESSUS Colloquium, Toronto, June 12-15, 2005
Objective and Research IssuesObjective and Research Issues
Estimate the propensity for professional workers to move house after a change of workplace– How many will move house during the
following job episode?
– For how long will they delay that decision?
– What are the factors significantly influencing that move house decision?
2nd MCRI/PROCESSUS Colloquium, Toronto, June 12-15, 2005
Data: The 1996 Retrospective Survey for Quebec City Survey collecting, in one interview, information about all
changes occurred over a long period of time, since their departure of the respondent’s parental home
Spatially stratified sample of two cohorts of professional workers– 418 respondents living in Quebec CMA in 1995– Two cohorts (mid-thirty and mid-forty)
• 224 women; 194 men• 112 women and 100 men in their mid-thirty• 112 women and 94 men in their mid-forty
– Reporting on significant events occurred during their life time describing
• Residential trajectory (every home occupied with their location)• Household trajectory (each change in the household’s
composition) • Professional trajectory (each change in employer, each workplace)
– Collecting dates of every change
2nd MCRI/PROCESSUS Colloquium, Toronto, June 12-15, 2005
Complex Evolution ProcessesComplex Evolution Processes
Leaving Parent's HomeTime Line
RESIDENTIALTRAJECTORY
CAREER TRAJECTORY
CO NSULTANTUNEMPLO YED
STUDENT
CO NSULTANT
PRO FESSIO NAL
TECHNICIAN
UNEMPLO YED
Survey date
CONSULTANT MOTHER Episode Lifeline
HOUSEHOLD TRAJECTORY
Fam ilySPO USE
SO N MO THERUNCLE
SPO USE
IN CO UPLESING LE
MARRIEDDIVO RCEDSING LE
M aritalstatus
Otherspersons
3
Occupation
CHALET
Secondaryhouse
TO W N HO USE
M ainhom e
RO O M STUDIO FLATRO O MAPARTMENTSTUDIO FLAT APARTMENT
Event
TECHNICIAN
Roomm ate
Roomm ate
3
97 242321171210
1 2664
2 221614
19
151311853 252018
Location
Personal BiographyComplex mix ofreal world phenomena
Change instatus
Leading toat least one episode
Combining factsdescribing a specific aspect of life
Set of related lifelinesusing application-specificsemantic relationships
2nd MCRI/PROCESSUS Colloquium, Toronto, June 12-15, 2005
Management of Evolution in TrajectoriesManagement of Evolution in Trajectories We developped a generic spatio-temporal data model to handle
historical orderings and querying patterns of facts in order to produce flat files needed for event-history analysis
Generic part of the ST data model
Respondents
PK,FK1,FK2,U1 RespondId
I1 GenderI1 Cohort
Facts
PK FactId
FK2 OwnerIdFK3,I2 SpatialIdFK1,I1 LifeStateIdI3 PeriodBegI4 PeriodEndI5 ObsTime
belongs to
HistoricalOrdering
PK HistoryId
FK1,I1 FBeforeIdFK2,I2 FAfterId
is before
is after
ActingIndividuals
PK ActingId
FK2,I2 PersonIdFK1,I1 FactId
is involved in
Individuals
PK PersonId
I1 NameI1 SurNameI1 Gender
isis
LifeStates
PK LifeStateId
U2,U1 LifeStateNameU2,U1 Episode
belongs to
TrajectoryStates
PK LifeDimId
FK1,I1 LifeStateIdFK2,I2 TrajectId
uses
Trajectories
PK TrajectId
U2,U1 TrajectName
defines
Spatial
PK SpatialId
I1 LongitudeI2 Latitude
is located at
MapInfo_MapCatalog
I1 SpatialTypeU1 TableNameI1 CoordinateSystemI1 SymbolI1 XColumnNameI1 YColumnName
Link to Spatialw
are
FactOwners
PK OwnerId
I1 BirthDateI1 Survey Time
is
Application semantics
Historical ordering of facts
Facts : events and episodes
Location of facts
2nd MCRI/PROCESSUS Colloquium, Toronto, June 12-15, 2005
Spatio-temporal Query of Patterns of Facts within TrajectoriesSpatio-temporal Query of Patterns of Facts within Trajectories
We developped a query interface combining georelational GIS capabilities and temporal historical ordering of facts using ODBC links
Specifying target factSpecifying target factSpecifying time orderingSpecifying time orderingSpecifying patterns of factsSpecifying patterns of factsSpecifying temporal conditionsSpecifying temporal conditionsSpecifying duration conditionSpecifying duration conditionSpecifying spatial location conditionSpecifying spatial location conditionSpecifying spatial distance conditionSpecifying spatial distance condition
Specifying other status conditionSpecifying other status condition
2nd MCRI/PROCESSUS Colloquium, Toronto, June 12-15, 2005
Methodology: Event History AnalysisMethodology: Event History Analysis
Ordinary multiple regression is ill-suited to the analysis of biographies– Censoring: refers to the fact that the value of a
variable may be unknown at the time of survey – Considering time varying explanatory factors
• Need to consider time-varying information to study the effect of job change on house moving
Event history analysis can handle such a problem (survival tables and logistic regression)– The query interface enhance data restructuring
needed for this kind of statistical analysis
2nd MCRI/PROCESSUS Colloquium, Toronto, June 12-15, 2005
Event History Analysis (Cox Regression)Event History Analysis (Cox Regression)
Survival tables are using conditional probabilities to estimate the mean proportion of people experiencing some change in their life after a significant event occurs, computing the time delay after a specified enabling event
Specific conditions may influence propensity to change
Requires a combination of survival tables and logistic regression to estimate the marginal effect of other personal attributes on the probability that an event occurs
Event History Analysis to model specific variations of the
probability of state transition through time for individuals considering independent variables describing their personal situation on other lifelines
2nd MCRI/PROCESSUS Colloquium, Toronto, June 12-15, 2005
)(*)(1)( MoveHomepropensityeNotMoveHomsurvivalMoveHomeyprobabilit
)(1)()( MoveHomeodds
MoveHomeoddsMoveHomepropensity
Xbcohortbagebgenderb neeeeMoveHomeodds 321)(
Probability to move home after a job change:Probability to move home after a job change:
2nd MCRI/PROCESSUS Colloquium, Toronto, June 12-15, 2005
Basic statisticsBasic statistics 380 respondents (on 418) had a change of job or workplace at
least once during during their career 411 respondents moved their home at least once after
departure from parent’s home 1056 changes of job or workplace within or towards the
Quebec CMA (321 persons)– 458 of those changes of workplace were followed by at least
one move house during the subsequent employment episode-stability of job and workplace
– 598 of those changes of workplace were not followed by any move house during the subsequent employment episode (231 persons)
Cohort Mid-Thirty Mid-Forty Gender Men Women Men Women
Moving House 122 117 97 122 Not Moving House 129 170 136 163
Number of pair of events (change of job-workplace versus moving house or not)
2nd MCRI/PROCESSUS Colloquium, Toronto, June 12-15, 2005
Basic variables for the Event History analysisBasic variables for the Event History analysis
Gender 1 (Male); 2 (Female) Cohort 1 (Mid-Thirty); 2 (Mid-Forty) ChWPL_Type 1 (New Job); 2 (Change of Workplace keeping the same job) ChWPL_Order Ordering of this change of work place among those of the same respondent (E.g. 2
means that it is the second change of workplace for this respondent) ChWPL_Age Age of the respondent when the change of workplace was occurring (Years) ChWPL_Marital Marital status when changing of workplace (1: Single; 2: Couple – marriage or free
union; 3: Separated, divorced or widow) ChWPL_Persons Total number of persons living in the household when changing of workplace ChWPL_Children Number of children living at home when changing of workplace Move_House The respondent was effectively moving house after the change of work place (1: Yes;
0: No) --- CENSORING VARIABLE Elapsed_Time Time elapsed between change of work place and moving house (Weeks) ----
DEPENDENT VARIABLE – time elapsed at the end of the new job episode if not moving house
MoveH_Marital Marital status when moving home (1: Single; 2: Couple – marriage or free union; 3: Separated, divorced or widow) – at end of new job episode if not moving home during that period
MoveH_Persons Total number of persons living in the household when moving home – at end of new job episode if not moving home during that period
MoveH_Children Number of children living at home when moving home – at end of new job episode if not moving home during that period
ChWPL_Neig Location of the new work place (1: city core; 2 old suburbs; 3: new suburbs; 4: urban fringe)
2nd MCRI/PROCESSUS Colloquium, Toronto, June 12-15, 2005
PJob_Neig Location of the previous job (1: city core; 2 old suburbs; 3: new suburbs; 4: urban fringe; 5: outside the Quebec CMA)
PJob_Durat Duration of the previous job episode (Years) PJob_Regime Employment regime at previous job location (1: Full time, >30 hours per week; 0: Part
time) PJob_Stability Perceived stability of employment at previous job location (1: Very stable; 2: Mostly
stable; 3: Mostly unstable; 4: Precarious) NJob_Regime Employment regime at new job location (1: Full time, >30 hours per week; 0: Part time) NJob_Stability Perceived stability of employment at new job location (1: Very stable; 2: Mostly stable;
3: Mostly unstable; 4: Precarious) PHome_Tenure Tenure of previous home (1: owner; 2: tenant; 3: co-tenant) NHome_Tenure Tenure of new home if any; otherwise previous tenure (1: owner; 2: tenant; 3: co-
tenant) PHome_Durat Duration of previous residential episode (Years) PHome_Neig Location of the previous home (1: city core; 2 old suburbs; 3: new suburbs; 4: urban
fringe; 5: outside the Quebec CMA) NHome_Neig Location of the new home if any; otherwise location of the old one (1: city core; 2 old
suburbs; 3: new suburbs; 4: urban fringe) MoveH_Dist Euclidean Distance between the old and the new residential locations (Km) PHomeNJob_Dist Euclidean Distance between the previous home and the new job locations (Km) NHomeNJob_Dist Euclidean Distance between the new home (if any; otherwise previous home) and the
new job locations (Km) PJobNJob_Dist Euclidean Distance between the old and the new job locations (Km)
2nd MCRI/PROCESSUS Colloquium, Toronto, June 12-15, 2005
Descriptive StatisticsDescriptive Statistics
Change of workplace order in the respondent career
Change Frequency % Cumulative %2 183 17,3 17,33 197 18,7 36,04 192 18,2 54,25 144 13,6 67,86 105 9,9 77,77 83 7,9 85,68 55 5,2 90,89 36 3,4 94,2
10 25 2,4 96,611 16 1,5 98,112 9 0,9 99,013 6 0,6 99,514 3 0,3 99,815 1 0,1 99,916 1 0,1 100
Total 1056 100
2nd MCRI/PROCESSUS Colloquium, Toronto, June 12-15, 2005
Location of the previous job episode (PJE) workplace
Frequency % Cumulative %City Core 316 29,9 29,9Old Suburbs 386 36,6 66,5New Suburbs 39 3,7 70,2Urban Fringe 9 0,9 71,0Outside the Quebec CMA 306 29,0 100Total 1056 100
Location of the new workplace (NWP)
Frequency % Cum. %City Core 449 42,5 42,5Old Suburbs 515 48,8 91,3New Suburbs 76 7,2 98,5Urban Fringe 16 1,5 100Total 1056 100,0
2nd MCRI/PROCESSUS Colloquium, Toronto, June 12-15, 2005
Change of home Neighbourhood
Frequency % Cum. %From or To Outside of the Quebec CMA 100 9,47 9,4697Core 223 21,12 30,5871Core --> Suburbs 41 3,883 34,4697Suburbs --> Core 29 2,746 37,2159Old Suburbs 484 45,83 83,0492Old Suburbs --> New Suburbs 26 2,462 85,5114New Suburbs --> Old Suburbs 14 1,326 86,8371New Subs + Fringe 139 13,16 100Total 1056 100
Change of tenure
Frequency % Cum. %Owner --> Owner 431 40,8 40,8Owner --> Tenant 31 2,9 43,8Tenant --> Owner 125 11,8 55,6Tenant --> Tenant 396 37,5 93,1Co-tenant --> Tenant 12 1,1 94,2Being Co-tenant 61 5,8 100Total 1056 100,0
2nd MCRI/PROCESSUS Colloquium, Toronto, June 12-15, 2005
Empirical Results: 1. Cross-tablesEmpirical Results: 1. Cross-tables
Gender
WomanMan
%
100
90
80
70
60
50
40
30
20
10
0
Move home
1
0
X2: 1,281ddl:1P: 0,258
Cohort
Mid_FortyMid-thirty
%
100
90
80
70
60
50
40
30
20
10
0
Move home
1
0
X2: 0,495ddl:1P: 0,482
2nd MCRI/PROCESSUS Colloquium, Toronto, June 12-15, 2005
Marital Status when CWP occurs
Separated, divorced,
Married or free unio
Single
%
100
90
80
70
60
50
40
30
20
10
0
Move home
1
0
X2: 19,192ddl:2P< 0,000C= 0,134
Number of children living at home when CWP occurs
43210
%
100
90
80
70
60
50
40
30
20
10
0
Move home
1
0
X2: 89,601ddl:4P< 0,000C= 0,280
2nd MCRI/PROCESSUS Colloquium, Toronto, June 12-15, 2005Type of Neighbourhood during PHE
Outside the Q
uebec C
Urban Fringe
New Suburbs
Old Suburbs
City Core
%
100
90
80
70
60
50
40
30
20
10
0
Move home
1
0
X2: 131,327ddl: 4P< 0,000C= 0,333
Tenure during the Previous Home Episode (PHE)
Co-tenantTenantOw ner
%100
90
80
70
60
50
40
30
20
10
0
Move home
1
0
X2=152,63ddl: 2P< 0,000C= 0,355
Empirical Results: 2. Event History AnalysisEmpirical Results: 2. Event History Analysis
Tests of Model coeff.X2: 845,29Df: 22Sig.: 0,000
Variables B SE Wald Sig Exp(B)Gender (0=Woman;1=Man) 0,307 0,102 9,105 0,003 1,359 +Change of Home Neighbourhood (0= From or To Ouside of the Qc CMA) 49,077 0,000 1= Core -0,955 0,175 29,844 0,000 0,385 - 2= Core Suburbs -0,163 0,204 0,641 0,423 0,849 3= Suburbs Core -0,349 0,225 2,409 0,121 0,705 4= Old Suburbs -0,855 0,155 30,418 0,000 0,425 - 5= Old Suburbs New Suburbs -0,391 0,259 2,279 0,131 0,676 6= New Suburbs Old Suburbs -0,247 0,329 0,563 0,453 0,781 7= New Suburbs + Fringe -0,785 0,240 10,673 0,001 0,456 -Age -0,005 0,011 0,221 0,638 0,995Previous Job Duration 0,015 0,018 0,643 0,422 1,015Tenure (0= Owner Owner) 0,000 1= Owner Tenant 1,004 0,261 14,799 0,000 2,728 + 2= Tenant Owner 0,721 0,186 15,107 0,000 2,057 + 3= Tenant Tenant 0,612 0,175 12,221 0,000 1,845 + 4= Co-tenant Tenant 1,096 0,346 10,063 0,002 2,993 + 5= Staying Co-tenant 0,467 0,272 2,940 0,086 1,595Previous Home Duration -0,363 0,025 213,393 0,000 0,695 -Number of Children at home when CWP -0,204 0,098 4,327 0,038 0,815 -Distance New Home®New Job/Previous Home®New Job 0,052 0,019 7,284 0,007 1,053 +Employment Regime at New Job Location (0= Part Time; 1= Full Time) 0,016 0,154 0,010 0,920 1,016Perceived Stability of Employment at New Job (0= Very Stable) 0,894 0,827 1= Mostly Stable 0,071 0,114 0,386 0,535 1,073 2= Mostly Unstable 0,138 0,156 0,784 0,376 1,148 3= Precarious 0,058 0,223 0,067 0,796 1,059
2nd MCRI/PROCESSUS Colloquium, Toronto, June 12-15, 2005
For how long will they delay that decision?For how long will they delay that decision?
One Minus Survival Function
at mean of covariates
Elapsed time between CWP and MH (Weeks) - censoring at end of
120010008006004002000-200
One
Min
us C
um S
urvi
val
1,2
1,0
,8
,6
,4
,2
0,0
-,2
2nd MCRI/PROCESSUS Colloquium, Toronto, June 12-15, 2005
One Minus Survival Function
for patterns 1 - 2
Elapsed time between CWP and M H (Weeks) - censoring at end of
120010008006004002000-200
On
e M
inu
s C
um
Su
rviv
al
1,2
1,0
,8
,6
,4
,2
0,0
-,2
Gender
Woman
Man
2nd MCRI/PROCESSUS Colloquium, Toronto, June 12-15, 2005
Discussion and ConclusionDiscussion and Conclusion Results given by Event History Analysis:
– How many will move house during the following job episode?
• On 418 respondents, 271 moved home after a job change (64,8%)
– For how long will they delay that decision?
• Probability of changing home after a job change =0,2 after ~2 years
– What are the factors significantly influencing that move house decision?• Tenure
– Co-tenant Tenant +
– Owner Tenant +
– Tenant Owner +
– Tenant Tenant +
• Gender (man) +• Increased Distance home job +• Number of Children -• Previous home duration -• Change of Home Neighbourood
– New Suburbs + Fringe -
– Old Suburbs -
– Core -
2nd MCRI/PROCESSUS Colloquium, Toronto, June 12-15, 2005
Retrospective Survey– Inaccuracy of responses (limitations of human memory
with elapsed time)– Memory distorsions (individual’s account of the event)– But people tend to remember major events (year of
residential move, job change)– Results reflect situation in 80’s and 90’s
To the best of our knowledge, this type of application is original (residential move after a job change
– Positive contribution to transportation land-use modelling (Quebec)
– The query interface could be also used to analyse patterns of activity/travel decision coming from our panel surveys (Quebec & Toronto) and OD surveys
– Next stage: Elaborate separate models for owners and tenants