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Modeling propensity to move after job change using event history analysis and temporal GIS

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Abstract

The research presented in this paper analyzes the emergent residential behaviors of individual actors in a context of profound social changes in the work sphere. It incorporates a long-term view in the analysis of the relationships between social changes in the work sphere and these behaviors. The general hypothesis is that social changes produce complex changes in the long-term dynamics of residential location behavior. More precisely, the objective of this paper is to estimate the propensity for professional workers to move house after a change of workplace. Our analysis draws on data from a biographical survey using a retrospective questionnaire that enables a posteriori reconstitution of the familial, professional and residential lifelines of professional workers since their departure from their parents’ home. The survey was conducted in 1996 in the Quebec City Metropolitan Area, which, much like other Canadian cities, has experienced a substantial increase in “unstable” work, even for professionals. The approach is based on event history analysis, a Temporal Geographic Information System and exploratory spatial analysis of model’s residuals. Results indicate that 48.9% of respondents moved after a job change and that the most important factors influencing the propensity to move house after a job change are home tenure (for lone adults as for couple) and number of children (for couples only). We also found that moving is associated with changing neighborhood for owners while tenants or co-tenants tend to stay in the same neighborhood. The probability of moving 1 year after a job change is 0.10 for lone adults and couples while after 2 years, the household structure seems to have an impact: the probability increased to 0.23 for lone adults and to 0.21 for couples. The outcome of this research contributes to furthering our understanding of a familial decision (to move) following a professional event (change of job), controlling for household structure, familial, professional and spatial contexts.

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Notes

  1. These methodological papers delineate the stages of research and the difficulty inherent in the structuring of such a database for statistical and spatio-temporal analysis. The lengthy structuring period explains much of the delay between the conclusion of the data-collection process (1996) and subsequent publication.

  2. We only gathered information about the professional’s spouse at the moment of the survey. For ethical reasons, it would be impossible to collect information about a previous spouse without his/her consent. It would also be impossible to collect, from the respondent, reliable information about the past biography of their present spouse, especially in case of complex (many changes) biography. It was then decided to collect only the general information concerning the spouse at the moment of the survey.

  3. We are particularly grateful to one of our three anonymous reviewers whose suggestions have considerably helped us to reduce the negative impact of this situation.

  4. We used this approach to assess the statistical significance of the changes in the determinants of commuting between 1977 and 1996 (Vandersmissen et al. 2003).

  5. Statistics Canada, Family Microdata files, 1996 (desegregated population 2% sample).

  6. By definition, all new homes and new workplaces are localized in the QCMA.

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Acknowledgments

The authors thank the Social Sciences and Humanities Research Council of Canada, Major Collaborative Research Initiative Program (SSHRC/MCRI), Fonds pour la formation de chercheurs et l’aide à la recherche (FCAR) and the Geomatics for Informed Decisions (GEOIDE) Network for their financial support. The authors are grateful for the very helpful and encouraging comments provided by the three anonymous reviewers.

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Authors and Affiliations

  1. Centre de recherche en aménagement et développement (CRAD), Université Laval, Quebec, QC, G1V 0A6, Canada

    Marie-Hélène Vandersmissen & Marius Thériault

  2. Institut National de Recherche Scientifique, Centre Urbanisation Culture et Société (INRS-UCS), Montreal, Canada

    Anne-Marie Séguin

  3. Institut de Recherche de l’Ecole Navale, Brest Armées, France

    Christophe Claramunt

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  1. Marie-Hélène Vandersmissen
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  2. Anne-Marie Séguin
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  4. Christophe Claramunt
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Correspondence to Marie-Hélène Vandersmissen.

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Vandersmissen, MH., Séguin, AM., Thériault, M. et al. Modeling propensity to move after job change using event history analysis and temporal GIS. J Geogr Syst 11, 37–65 (2009). https://doi.org/10.1007/s10109-009-0076-x

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