IDEAS home Printed from https://ideas.repec.org/a/eee/transa/v46y2012i7p1097-1107.html
   My bibliography  Save this article

A behavioral housing search model: Two-stage hazard-based and multinomial logit approach to choice-set formation and location selection

Author

Listed:
  • Rashidi, Taha Hossein
  • Auld, Joshua
  • Mohammadian, Abolfazl (Kouros)

Abstract

Residential location search has become an important topic to both practitioners and researchers as more detailed and disaggregate land-use and transportation demand models are developed which require information on individual household location decisions. The housing search process starts with an alternative formation and screening stage. At this level households evaluate all potential alternatives based on their lifestyle, preferences, and utilities to form a manageable choice set with a limited number of plausible alternatives. Then the final residential location is selected among these alternatives. This two-stage decision making process can be used for both aggregate zone-level selection as well as searching disaggregate parcel or building-based housing markets for potential dwellings. In this paper a zonal level household housing search model is developed. Initially, a household specific choice set is drawn from the entire possible alternatives in the area based on the average household work distance to each alternative. Following the choice set formation step, a discrete choice model is utilized for modeling the final residential zone selection of the household. A hazard-based model is used for the choice set formation module while the final choice selection is modeled using a multinomial logit formulation with a deterministic sample correction factor. The approach presented in the paper provides a remedy for the large choice set problem typically faced in housing search models.

Suggested Citation

  • Rashidi, Taha Hossein & Auld, Joshua & Mohammadian, Abolfazl (Kouros), 2012. "A behavioral housing search model: Two-stage hazard-based and multinomial logit approach to choice-set formation and location selection," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(7), pages 1097-1107.
    • Handle: RePEc:eee:transa:v:46:y:2012:i:7:p:1097-1107
    DOI: 10.1016/j.tra.2012.01.007
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S096585641200016X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tra.2012.01.007?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Frejinger, E. & Bierlaire, M. & Ben-Akiva, M., 2009. "Sampling of alternatives for route choice modeling," Transportation Research Part B: Methodological, Elsevier, vol. 43(10), pages 984-994, December.
    2. Taha Rashidi & Abolfazl Mohammadian & Frank Koppelman, 2011. "Modeling interdependencies between vehicle transaction, residential relocation and job change," Transportation, Springer, vol. 38(6), pages 909-932, November.
    3. Clark, William A. V. & Huang, Youqin & Withers, Suzanne, 2003. "Does commuting distance matter?: Commuting tolerance and residential change," Regional Science and Urban Economics, Elsevier, vol. 33(2), pages 199-221, March.
    4. Wen, Chieh-Hua & Koppelman, Frank S., 2001. "The generalized nested logit model," Transportation Research Part B: Methodological, Elsevier, vol. 35(7), pages 627-641, August.
    5. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    6. Ryuichi Kitamura & Lidia P. Kostyniuk & Kuo-Liang Ting, 1979. "Aggregation in Spatial Choice Modeling," Transportation Science, INFORMS, vol. 13(4), pages 325-342, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sudipa Choudhury & Apu Kumar Saha & Mrinmoy Majumder, 2020. "Optimal location selection for installation of surface water treatment plant by Gini coefficient-based analytical hierarchy process," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(5), pages 4073-4099, June.
    2. Arthur (Yan) Huang & David Levinson, 2015. "Axis of travel: Modeling non-work destination choice with GPS data," Working Papers 000113, University of Minnesota: Nexus Research Group.
    3. Dubey, Subodh & Bansal, Prateek & Daziano, Ricardo A. & Guerra, Erick, 2020. "A Generalized Continuous-Multinomial Response Model with a t-distributed Error Kernel," Transportation Research Part B: Methodological, Elsevier, vol. 133(C), pages 114-141.
    4. Samani, Ali Riahi & Mishra, Sabyasachee & Golias, Mihalis & Lee, David J.-H., 2023. "What influences the location choice of establishments? An analysis considering establishment types and activities interactions," Journal of Transport Geography, Elsevier, vol. 111(C).
    5. Tomás Cox & Ricardo Hurtubia, 2021. "Latent Segmentation of Urban Space through Residential Location Choice," Networks and Spatial Economics, Springer, vol. 21(1), pages 199-228, March.
    6. Rezaei, Ali & Patterson, Zachary, 2018. "Preference stability in household location choice: Using cross-sectional data from three censuses," Research in Transportation Economics, Elsevier, vol. 67(C), pages 44-53.
    7. Faghih-Imani, Ahmadreza & Eluru, Naveen, 2015. "Analysing bicycle-sharing system user destination choice preferences: Chicago’s Divvy system," Journal of Transport Geography, Elsevier, vol. 44(C), pages 53-64.
    8. Bhat, Chandra R. & Pinjari, Abdul R. & Dubey, Subodh K. & Hamdi, Amin S., 2016. "On accommodating spatial interactions in a Generalized Heterogeneous Data Model (GHDM) of mixed types of dependent variables," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 240-263.
    9. Dapeng Zhang & Xiaokun Wang & José Holguín-Veras & Wei Zou, 2019. "Investigation of carriers’ ability to transfer toll increases: an empirical analysis of freight agents’ relative market power," Transportation, Springer, vol. 46(6), pages 2291-2308, December.
    10. Bhat, Chandra R., 2015. "A new generalized heterogeneous data model (GHDM) to jointly model mixed types of dependent variables," Transportation Research Part B: Methodological, Elsevier, vol. 79(C), pages 50-77.
    11. Kim, Hyun No & Boxall, Peter C. & Adamowicz, W.L.(Vic), 2019. "Analysis of the economic impact of water management policy on residential prices: Modifying choice set formation in a discrete house choice analysis," Journal of choice modelling, Elsevier, vol. 33(C).
    12. Taha H. Rashidi & Abolfazl (Kouros) Mohammadian, 2015. "Behavioral Housing Search Choice Set Formation," International Regional Science Review, , vol. 38(2), pages 151-170, April.
    13. McClain, Verena & Waldorf, Brigitte, 2017. "Borrowing From The Demographer's Toolbox: Longitudinal Methods in Regional Science," Working papers 264970, Purdue University, Department of Agricultural Economics.
    14. Ferrari, Paolo, 2014. "The dynamics of modal split for freight transport," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 70(C), pages 163-176.
    15. Sánchez Navarro, Dennis, 2013. "Análisis de elasticidades en el mercado automotor colombiano (2009 - 2011) mediante un modelo logit anidado [Analysis Of Elasticity In Colombian Automotive Market (2009 - 2011) Through A Nested Log," MPRA Paper 46043, University Library of Munich, Germany.
    16. Bhat, Chandra R., 2015. "A comprehensive dwelling unit choice model accommodating psychological constructs within a search strategy for consideration set formation," Transportation Research Part B: Methodological, Elsevier, vol. 79(C), pages 161-188.
    17. Fatmi, Mahmudur Rahman & Chowdhury, Subeh & Habib, Muhammad Ahsanul, 2017. "Life history-oriented residential location choice model: A stress-based two-tier panel modeling approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 104(C), pages 293-307.
    18. Haque, Md Bashirul & Choudhury, Charisma & Hess, Stephane, 2020. "Understanding differences in residential location preferences between ownership and renting: A case study of London," Journal of Transport Geography, Elsevier, vol. 88(C).
    19. Robbennolt, Dale & Haddad, Angela J. & Mondal, Aupal & Bhat, Chandra R., 2024. "Housing choice in an evolving remote work landscape," Transportation Research Part A: Policy and Practice, Elsevier, vol. 190(C).
    20. Tim-Benjamin Lembcke & Mathias Willnat & Henrik Lechte & Maike Greve & Julia Heinsohn & Alfred Benedikt Brendel, 2021. "Mobility Need-Adaptive Housing Platforms: The Benefit of a Commute Time Search Feature," Sustainability, MDPI, vol. 13(6), pages 1-14, March.
    21. Taha H Rashidi & Milad Ghasri, 2019. "A competing survival analysis for housing relocation behaviour and risk aversion in a resilient housing market," Environment and Planning B, , vol. 46(1), pages 122-142, January.
    22. Verena McClain & Brigitte S. Waldorf, 2021. "Longitudinal methods in regional science: a review," Journal of Geographical Systems, Springer, vol. 23(2), pages 145-160, April.
    23. Subodh Dubey & Prateek Bansal & Ricardo A. Daziano & Erick Guerra, 2019. "A Generalized Continuous-Multinomial Response Model with a t-distributed Error Kernel," Papers 1904.08332, arXiv.org, revised Jan 2020.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lili Zheng & Tian Gao & Lin Meng & Tongqiang Ding & Wenhao Chen, 2024. "Research on the Route Choice Behavior of Urban Freight Vehicles Based on GPS Data," Mathematics, MDPI, vol. 12(2), pages 1-17, January.
    2. Lemp, Jason D. & Kockelman, Kara M., 2012. "Strategic sampling for large choice sets in estimation and application," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(3), pages 602-613.
    3. Lai, Xinjun & Bierlaire, Michel, 2015. "Specification of the cross-nested logit model with sampling of alternatives for route choice models," Transportation Research Part B: Methodological, Elsevier, vol. 80(C), pages 220-234.
    4. Konrad Menzel, 2021. "Structural Sieves," Papers 2112.01377, arXiv.org, revised Apr 2022.
    5. Brian Lee & Paul Waddell, 2010. "Residential mobility and location choice: a nested logit model with sampling of alternatives," Transportation, Springer, vol. 37(4), pages 587-601, July.
    6. Sirchenko Andrei, 2012. "A model for ordinal responses with an application to policy interest rate," EERC Working Paper Series 12/13e, EERC Research Network, Russia and CIS.
    7. Marcén, Miriam & Morales, Marina, 2021. "Culture and the cross-country differences in the gender commuting gap," Journal of Transport Geography, Elsevier, vol. 96(C).
    8. Thomas Skora & Heiko Rüger & Knut Petzold, 2024. "Migration, daily commuting, or second residence? The role of location-specific capital and distance to workplace in regional mobility decisions," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 50(33), pages 967-1004.
    9. Darima Fotheringham & Michael A. Wiles, 2023. "The effect of implementing chatbot customer service on stock returns: an event study analysis," Journal of the Academy of Marketing Science, Springer, vol. 51(4), pages 802-822, July.
    10. Song, Wei-Ling & Uzmanoglu, Cihan, 2016. "TARP announcement, bank health, and borrowers’ credit risk," Journal of Financial Stability, Elsevier, vol. 22(C), pages 22-32.
    11. Raymundo M. Campos-Vázquez, 2013. "Efectos de los ingresos no reportados en el nivel y tendencia de la pobreza laboral en México," Ensayos Revista de Economia, Universidad Autonoma de Nuevo Leon, Facultad de Economia, vol. 0(2), pages 23-54, November.
    12. Jonathan Gruber & Aaron Yelowitz, 1999. "Public Health Insurance and Private Savings," Journal of Political Economy, University of Chicago Press, vol. 107(6), pages 1249-1274, December.
    13. Campbell, Randall C. & Nagel, Gregory L., 2016. "Private information and limitations of Heckman's estimator in banking and corporate finance research," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 186-195.
    14. Leye Li & Louise Yi Lu & Dongyue Wang, 2022. "External labour market competitions and stock price crash risk: evidence from exposures to competitor CEOs’ award‐winning events," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 62(S1), pages 1421-1460, April.
    15. Calcagno, R. & Renneboog, L.D.R., 2004. "Capital Structure and Managerial Compensation : The Effects of Renumeration Seniority," Discussion Paper 2004-120, Tilburg University, Center for Economic Research.
    16. Son K. Lam & Thomas E. DeCarlo & Ashish Sharma, 2019. "Salesperson ambidexterity in customer engagement: do customer base characteristics matter?," Journal of the Academy of Marketing Science, Springer, vol. 47(4), pages 659-680, July.
    17. McCausland, David & Pouliakas, Konstantinos & Theodossiou, Ioannis, 2005. "Some are Punished and Some are Rewarded: A Study of the Impact of Performance Pay on Job Satisfaction," MPRA Paper 14243, University Library of Munich, Germany.
    18. Gary F. Peters & Andrea M. Romi & Juan Manuel Sanchez, 2019. "The Influence of Corporate Sustainability Officers on Performance," Journal of Business Ethics, Springer, vol. 159(4), pages 1065-1087, November.
    19. Fossen, Frank M. & König, Johannes, 2015. "Public health insurance and entry into self-employment," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112934, Verein für Socialpolitik / German Economic Association.
    20. Li, Chunyu & Lou, Chenxin & Luo, Dan & Xing, Kai, 2021. "Chinese corporate distress prediction using LASSO: The role of earnings management," International Review of Financial Analysis, Elsevier, vol. 76(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transa:v:46:y:2012:i:7:p:1097-1107. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/547/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.