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A data-driven predictive model for residential mobility in Australia – A generalised linear mixed model for repeated measured binary data

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  • Namazi-Rad, Mohammad-Reza
  • Mokhtarian, Payam
  • Shukla, Nagesh
  • Munoz, Albert

Abstract

Household relocation modelling is an integral part of the Government planning process as residential movements influence the demand for community facilities and services. This study will address the problem of modelling residential relocation choice by estimating a logit-link class model. The proposed model estimates the probability of an event which triggers household relocation. The attributes considered in this study are: requirement for bedrooms, employment status, income status, household characteristics, and tenure (i.e. duration living at the current location). Accurate prediction of household relocations for population units should rely on real world observations. In this study, a longitudinal survey data gathered in the Household, Income and Labour Dynamics in Australia (HILDA) program is used for modelling purposes. The HILDA dataset includes socio-demographic information such as general health situation and well-being, lifestyle changes, residential mobility, income and welfare dynamics, and labour market dynamics collected from the sampled individuals and households. The technique presented in this paper links possible changes in households' socio-demographic characteristics to the probability of residential relocation by developing a mixed effects discrete-choice logit model (MEDCLM) for longitudinal binary data using the HILDA dataset. The proposed model captures the effect of repeated measurements together with the area-specific random effects.

Suggested Citation

  • Namazi-Rad, Mohammad-Reza & Mokhtarian, Payam & Shukla, Nagesh & Munoz, Albert, 2016. "A data-driven predictive model for residential mobility in Australia – A generalised linear mixed model for repeated measured binary data," Journal of choice modelling, Elsevier, vol. 20(C), pages 49-60.
    • Handle: RePEc:eee:eejocm:v:20:y:2016:i:c:p:49-60
    DOI: 10.1016/j.jocm.2016.04.006
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    References listed on IDEAS

    as
    1. Vega, Amaya & Reynolds-Feighan, Aisling, 2009. "A methodological framework for the study of residential location and travel-to-work mode choice under central and suburban employment destination patterns," Transportation Research Part A: Policy and Practice, Elsevier, vol. 43(4), pages 401-419, May.
    2. Mohammad-Reza Namazi-Rad & Payam Mokhtarian & Pascal Perez, 2014. "Generating a Dynamic Synthetic Population – Using an Age-Structured Two-Sex Model for Household Dynamics," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-16, April.
    3. Ibeas, Ángel & Cordera, Ruben & dell’Olio, Luigi & Coppola, Pierluigi, 2013. "Modelling the spatial interactions between workplace and residential location," Transportation Research Part A: Policy and Practice, Elsevier, vol. 49(C), pages 110-122.
    4. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555.
    5. Kan, Kamhon, 1999. "Expected and Unexpected Residential Mobility," Journal of Urban Economics, Elsevier, vol. 45(1), pages 72-96, January.
    6. Nicole Watson & Mark Wooden, 2014. "Re-engaging with survey non-respondents: evidence from three household panels," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 177(2), pages 499-522, February.
    7. Francesca Pagliara & Alan Wilson, 2010. "The State-of-the-Art in Building Residential Location Models," Advances in Spatial Science, in: Francesca Pagliara & John Preston & David Simmonds (ed.), Residential Location Choice, pages 1-20, Springer.
    8. repec:rre:publsh:v:38:y:2008:i:1:p:67-88 is not listed on IDEAS
    9. Ejaz Ahmed, S. & Fallahpour, Saber, 2012. "Shrinkage estimation strategy in quasi-likelihood models," Statistics & Probability Letters, Elsevier, vol. 82(12), pages 2170-2179.
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