1 / 26

Modelling propensity to move house after job change using event history analysis and GIS

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).

shalin
Download Presentation

Modelling propensity to move house after job change using event history analysis and GIS

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. 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

  2. Introduction • 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

  3. Our project in the MCRI programme 2nd MCRI/PROCESSUS Colloquium, Toronto, June 12-15, 2005

  4. Purpose • 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 Social changes Long-term dynamics of residential location behaviour Travel behaviour 2nd MCRI/PROCESSUS Colloquium, Toronto, June 12-15, 2005

  5. Objective 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

  6. 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

  7. Complex mix of real world phenomena Personal Biography Complex Evolution Processes Leading to at least one episode Change in status Combining facts describing a specific aspect of life Set of related lifelines using application-specific semantic relationships 2nd MCRI/PROCESSUS Colloquium, Toronto, June 12-15, 2005

  8. Management of Evolution in Trajectories • We developped a generic spatio-temporal datamodel to handle historical orderings and querying patterns of facts in order to produce flat files needed for event-history analysis Application semantics Historical ordering of facts Facts : events and episodes Location of facts 2nd MCRI/PROCESSUS Colloquium, Toronto, June 12-15, 2005

  9. Specifying spatial distance condition Specifying duration condition Specifying spatial location condition Specifying patterns of facts Specifying temporal conditions Specifying time ordering Specifying target fact Specifying other status condition Spatio-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 2nd MCRI/PROCESSUS Colloquium, Toronto, June 12-15, 2005

  10. Methodology: 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

  11. 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

  12. Probability to move home after a job change: 2nd MCRI/PROCESSUS Colloquium, Toronto, June 12-15, 2005

  13. Number of pair of events (change of job-workplace versus moving house or not) Basic 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) 2nd MCRI/PROCESSUS Colloquium, Toronto, June 12-15, 2005

  14. Basic variables for the Event History analysis 2nd MCRI/PROCESSUS Colloquium, Toronto, June 12-15, 2005

  15. 2nd MCRI/PROCESSUS Colloquium, Toronto, June 12-15, 2005

  16. Descriptive Statistics 2nd MCRI/PROCESSUS Colloquium, Toronto, June 12-15, 2005

  17. 2nd MCRI/PROCESSUS Colloquium, Toronto, June 12-15, 2005

  18. 2nd MCRI/PROCESSUS Colloquium, Toronto, June 12-15, 2005

  19. Empirical Results: 1. Cross-tables X2: 1,281 ddl:1 P: 0,258 X2: 0,495 ddl:1 P: 0,482 2nd MCRI/PROCESSUS Colloquium, Toronto, June 12-15, 2005

  20. X2: 89,601 ddl:4 P< 0,000 C= 0,280 X2: 19,192 ddl:2 P< 0,000 C= 0,134 2nd MCRI/PROCESSUS Colloquium, Toronto, June 12-15, 2005

  21. X2: 131,327 ddl: 4 P< 0,000 C= 0,333 X2=152,63 ddl: 2 P< 0,000 C= 0,355 2nd MCRI/PROCESSUS Colloquium, Toronto, June 12-15, 2005

  22. Empirical Results: 2. Event History Analysis Tests of Model coeff. X2: 845,29 Df: 22 Sig.: 0,000

  23. For how long will they delay that decision? 2nd MCRI/PROCESSUS Colloquium, Toronto, June 12-15, 2005

  24. 2nd MCRI/PROCESSUS Colloquium, Toronto, June 12-15, 2005

  25. Discussion 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

  26. 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 2nd MCRI/PROCESSUS Colloquium, Toronto, June 12-15, 2005

More Related