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Commuting distances in a household location choice model with amenities

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  • Ng, Chen Feng

Abstract

Observed commuting distances generally exceed those predicted by standard models of household location choice. This paper develops a model with locational amenities and two job centers. It is shown that differences in household preferences for amenities can lead to various types of residential location patterns, some of which result in higher average commuting distances in the city.

Suggested Citation

  • Ng, Chen Feng, 2008. "Commuting distances in a household location choice model with amenities," Journal of Urban Economics, Elsevier, vol. 63(1), pages 116-129, January.
    • Handle: RePEc:eee:juecon:v:63:y:2008:i:1:p:116-129
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    References listed on IDEAS

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    Cited by:

    1. Mariya Letdin & Hyoung S. Shim, 2019. "Location choice, life cycle and amenities," Journal of Regional Science, Wiley Blackwell, vol. 59(3), pages 567-585, June.
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    3. Tscharaktschiew, Stefan & Hirte, Georg, 2010. "How does the household structure shape the urban economy?," Regional Science and Urban Economics, Elsevier, vol. 40(6), pages 498-516, November.
    4. Rafa Madariaga & Joan Martori & Ramon Oller, 2014. "Income, distance and amenities. An empirical analysis," Empirical Economics, Springer, vol. 47(3), pages 1129-1146, November.
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    6. Dong, Tao & Jia, Ning & Ma, Shoufeng & Xu, Shu-Xian & Ping Ong, Ghim & Liu, Peng & Huang, Hai-Jun, 2022. "Impacts of intercity commuting on travel characteristics and urban performances in a two-city system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    7. J. Ignacio Gimenez-Nadal & José Alberto Molina, 2016. "Commuting Time And Household Responsibilities: Evidence Using Propensity Score Matching," Journal of Regional Science, Wiley Blackwell, vol. 56(2), pages 332-359, March.
    8. Wrede, Matthias, 2014. "Continuous Logit Polycentric City Model," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100488, Verein für Socialpolitik / German Economic Association.
    9. Tscharaktschiew, Stefan & Hirte, Georg, 2012. "Should subsidies to urban passenger transport be increased? A spatial CGE analysis for a German metropolitan area," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(2), pages 285-309.
    10. Brian H Y Lee & Paul Waddell & Liming Wang & Ram M Pendyala, 2010. "Reexamining the Influence of Work and Nonwork Accessibility on Residential Location Choices with a Microanalytic Framework," Environment and Planning A, , vol. 42(4), pages 913-930, April.
    11. Yuting Hou, 2017. "Traffic congestion, accessibility to employment, and housing prices: A study of single-family housing market in Los Angeles County," Urban Studies, Urban Studies Journal Limited, vol. 54(15), pages 3423-3445, November.
    12. Reichelt, Malte & Haas, Anette, 2015. "Commuting farther and earning more? : how employment density moderates workers commuting distance," IAB-Discussion Paper 201533, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    13. Traoré, Sidnoma, 2019. "Residential location choice in a developing country: What matter? A choice experiment application in Burkina Faso," Forest Policy and Economics, Elsevier, vol. 102(C), pages 1-9.
    14. Anette Haas & Malte Reichelt, 2015. "Larger pay, longer drives? Location specific wage effects on commuting distances," ERSA conference papers ersa15p1139, European Regional Science Association.
    15. Ke, Yue & Gkritza, Konstantina, 2019. "Light rail transit and housing markets in Charlotte-Mecklenburg County, North Carolina: Announcement and operations effects using quasi-experimental methods," Journal of Transport Geography, Elsevier, vol. 76(C), pages 212-220.
    16. Corentin M Fontaine & Mark D A Rounsevell & Anne-Christelle Barbette, 2014. "Locating Household Profiles in a Polycentric Region to Refine the Inputs to an Agent-Based Model of Residential Mobility," Environment and Planning B, , vol. 41(1), pages 163-184, February.
    17. 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.
    18. Wrede, Matthias, 2015. "A continuous spatial choice logit model of a polycentric city," Regional Science and Urban Economics, Elsevier, vol. 53(C), pages 68-73.
    19. Nitzsche, Eric & Tscharaktschiew, Stefan, 2013. "Efficiency of speed limits in cities: A spatial computable general equilibrium assessment," Transportation Research Part A: Policy and Practice, Elsevier, vol. 56(C), pages 23-48.
    20. Marois, Guillaume & Lord, Sébastien & Morency, Catherine, 2019. "A mixed logit model analysis of residential choices of the young-elderly in the Montreal metropolitan area," Journal of Housing Economics, Elsevier, vol. 44(C), pages 141-149.
    21. Vincent Viguié, 2015. "Cross-commuting and housing prices in a polycentric modeling of cities," Policy Papers 2015.03, FAERE - French Association of Environmental and Resource Economists.
    22. Martijn Smit, 2017. "Following Your Job," Papers in Evolutionary Economic Geography (PEEG) 1718, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Jul 2017.
    23. Wrede, Matthias, 2017. "Urban land use, sorting, and population density: A continuous logit model," Transportation Research Part B: Methodological, Elsevier, vol. 101(C), pages 283-294.
    24. Jia Guo & Tao Feng & Harry J. P. Timmermans, 2020. "Modeling co-dependent choice of workplace, residence and commuting mode using an error component mixed logit model," Transportation, Springer, vol. 47(2), pages 911-933, April.

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