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Dynamic life course analysis on residential location choice

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  • Yu, Biying
  • Zhang, Junyi
  • Li, Xia

Abstract

From a behavioral viewpoint, people choose where to live based on various factors, including their current situations, past experience, and plans for the future. Some aspects of residential preference might be constant over time, inherited from the initial stage of life, and other parts might be responses to residential biography or other biographical domains like household structure, employment/education, and travel. Capturing these intertemporal dependences needs a life course analysis of residential location choices. However, a serious methodological gap exists between the perceived importance of dynamic life course analyses and quantitative modeling approaches. This study developed a dynamic choice model with cross-sectional and longitudinal heterogeneities as well as discounted utility (called the DU-DCLH model) to describe the decision-making process for residential relocation by incorporating various intertemporal dependences over the life course. Model parameters were estimated using data collected from a life history survey conducted in Japan in 2010. The estimation results firstly confirm the effectiveness of the DU-DCLH model for portraying the dynamics of residential mobility over a life course. Next, it was found that previous experiences dominate decisions on residential location choice and can explain more than 75% of the total variations in choice. It was also revealed that as the mobility age increases, the influence of the past on their choices increases continuously. In contrast, the influence of the present situation is small and almost negligible. Furthermore, the study empirically confirmed not only the influence of time-constant and time-varying preference for residential neighborhoods but also the specific influence of household biography, employment/education biography, and travel biography. This study enriches the existing research by providing a systematic modeling framework incorporating broader behavioral mechanisms for residential location choice over the life course.

Suggested Citation

  • Yu, Biying & Zhang, Junyi & Li, Xia, 2017. "Dynamic life course analysis on residential location choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 104(C), pages 281-292.
    • Handle: RePEc:eee:transa:v:104:y:2017:i:c:p:281-292
    DOI: 10.1016/j.tra.2017.01.009
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    3. Susilo, Yusak & Liu, Chengxi & Börjesson, Maria, 2018. "The changes of activity-travel participation across gender, life-cycle, and generations in Sweden over 30 years," Working papers in Transport Economics 2018:8, CTS - Centre for Transport Studies Stockholm (KTH and VTI).
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    5. Sebastian Scheuer & Dagmar Haase & Annegret Haase & Nadja Kabisch & Manuel Wolff & Nina Schwarz & Katrin Großmann, 2020. "Combining tacit knowledge elicitation with the SilverKnETs tool and random forests – The example of residential housing choices in Leipzig," Environment and Planning B, , vol. 47(3), pages 400-416, March.
    6. Yusak O. Susilo & Chengxi Liu & Maria Börjesson, 2019. "The changes of activity-travel participation across gender, life-cycle, and generations in Sweden over 30 years," Transportation, Springer, vol. 46(3), pages 793-818, June.
    7. Xue, Fei & Yao, Enjian & Jin, Fanglei, 2020. "Exploring residential relocation behavior for families with workers and students; a study from Beijing, China," Journal of Transport Geography, Elsevier, vol. 89(C).
    8. Guo, Jia & Feng, Tao & Timmermans, Harry J.P., 2019. "Time-varying dependencies among mobility decisions and key life course events: An application of dynamic Bayesian decision networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 82-92.
    9. Zong, Weiyan & Zhang, Junyi & Yang, Xiaoguang, 2023. "Building a life-course intertemporal discrete choice model to analyze migration biographies," Journal of choice modelling, Elsevier, vol. 47(C).
    10. Zhenjun Zhu & Zhigang Li & Hongsheng Chen & Ye Liu & Jun Zeng, 2019. "Subjective well-being in China: how much does commuting matter?," Transportation, Springer, vol. 46(4), pages 1505-1524, August.

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