IDEAS home Printed from https://ideas.repec.org/a/kap/jgeosy/v25y2023i1d10.1007_s10109-022-00394-6.html
   My bibliography  Save this article

Rents and wages derived from spatial interaction analysis in Shanghai

Author

Listed:
  • Liying Yue

    (East China Normal University)

  • Morton E. O’Kelly

    (The Ohio State University)

Abstract

Using the 1% National Population Sampling Survey, collected in 2015, this paper performs sensitivity analysis of the parameters in a spatial interaction model to evaluate and compare the locational benefits of origins and destinations among different hukou (locals and migrants) and educational types in a large Chinese city (Shanghai). While the macro patterns are consistent with other case studies, Shanghai presents some unique features that include residency status and differential educational levels, and these factors result in notable patterns of spatial organization. Compared with migrants, locals have longer trip lengths, and higher rents and wages. Well-educated workers travel longer and have higher rents and wages than the poorly-educated. The presence of high-tech, high-prestige employers (e.g., Huawei) in the east-central area both attracts longer distance educated commuters, as well as generating higher wages, and potentially higher rents for those who choose to live and work in the same area, especially for locals. However, it is reassuring to see that there is a marked rent gradient over the distance from the CBD.

Suggested Citation

  • Liying Yue & Morton E. O’Kelly, 2023. "Rents and wages derived from spatial interaction analysis in Shanghai," Journal of Geographical Systems, Springer, vol. 25(1), pages 59-75, January.
    • Handle: RePEc:kap:jgeosy:v:25:y:2023:i:1:d:10.1007_s10109-022-00394-6
    DOI: 10.1007/s10109-022-00394-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10109-022-00394-6
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10109-022-00394-6?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. Prashker, Joseph & Shiftan, Yoram & Hershkovitch-Sarusi, Pazit, 2008. "Residential choice location, gender and the commute trip to work in Tel Aviv," Journal of Transport Geography, Elsevier, vol. 16(5), pages 332-341.
    2. El-Geneidy, Ahmed & Levinson, David & Diab, Ehab & Boisjoly, Genevieve & Verbich, David & Loong, Charis, 2016. "The cost of equity: Assessing transit accessibility and social disparity using total travel cost," Transportation Research Part A: Policy and Practice, Elsevier, vol. 91(C), pages 302-316.
    3. Hanson, Andrew & Schnier, Kurt & Turnbull, Geoffrey K., 2012. "Drive 'Til You Qualify: Credit quality and household location," Regional Science and Urban Economics, Elsevier, vol. 42(1-2), pages 63-77.
    4. 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.
    5. Frost, Martin & Linneker, Brian & Spence, Nigel, 1998. "Excess or wasteful commuting in a selection of British cities," Transportation Research Part A: Policy and Practice, Elsevier, vol. 32(7), pages 529-538, September.
    6. van Ommeren, Jos & Rietveld, Piet & Nijkamp, Peter, 1997. "Commuting: In Search of Jobs and Residences," Journal of Urban Economics, Elsevier, vol. 42(3), pages 402-421, November.
    7. Wheaton, William C., 1974. "Linear programming and locational equilibrium : The Herbert-Stevens model revisited," Journal of Urban Economics, Elsevier, vol. 1(3), pages 278-287, July.
    8. Kanaroglou, Pavlos S. & Higgins, Christopher D. & Chowdhury, Tufayel A., 2015. "Excess commuting: a critical review and comparative analysis of concepts, indices, and policy implications," Journal of Transport Geography, Elsevier, vol. 44(C), pages 13-23.
    9. Morton E O'Kelly & Wook Lee, 2005. "Disaggregate Journey-to-Work Data: Implications for Excess Commuting and Jobs–Housing Balance," Environment and Planning A, , vol. 37(12), pages 2233-2252, December.
    10. Li, Si-ming & Liu, Yi, 2016. "The jobs-housing relationship and commuting in Guangzhou, China: Hukou and dual structure," Journal of Transport Geography, Elsevier, vol. 54(C), pages 286-294.
    Full references (including those not matched with items on IDEAS)

    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. Mark W. Horner & Bernadette M. Marion, 2009. "A Spatial Dissimilarity-based Index of the Jobs—Housing Balance: Conceptual Framework and Empirical Tests," Urban Studies, Urban Studies Journal Limited, vol. 46(3), pages 499-517, March.
    2. Saadi, Ismaïl & Boussauw, Kobe & Teller, Jacques & Cools, Mario, 2016. "Trends in regional jobs-housing proximity based on the minimum commute: The case of Belgium," Journal of Transport Geography, Elsevier, vol. 57(C), pages 171-183.
    3. Matt Kures & Steven C. Deller, 2023. "Growth in Commuting Patterns and Their Impacts on Rural Workforce and Economic Development," Economic Development Quarterly, , vol. 37(1), pages 54-63, February.
    4. Kim, Kyusik & Horner, Mark W., 2021. "Examining the impacts of the Great Recession on the commuting dynamics and jobs-housing balance of public and private sector workers," Journal of Transport Geography, Elsevier, vol. 90(C).
    5. Yue, Liying & O'Kelly, Morton E., 2023. "Variations in excess commuting by educational and occupational worker subgroups: A case study of Shanghai," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    6. Ta, Na & Zhao, Ying & Chai, Yanwei, 2016. "Built environment, peak hours and route choice efficiency: An investigation of commuting efficiency using GPS data," Journal of Transport Geography, Elsevier, vol. 57(C), pages 161-170.
    7. Goliszek Sławomir, 2022. "The potential accessibility to workplaces and working-age population by means of public and private car transport in Szczecin," Miscellanea Geographica. Regional Studies on Development, Sciendo, vol. 26(1), pages 31-41, January.
    8. Mark W. Horner, 2008. "`Optimal' Accessibility Landscapes? Development of a New Methodology for Simulating and Assessing Jobs—Housing Relationships in Urban Regions," Urban Studies, Urban Studies Journal Limited, vol. 45(8), pages 1583-1602, July.
    9. Bwire, Hannibal & Zengo, Emil, 2020. "Comparison of efficiency between public and private transport modes using excess commuting: An experience in Dar es Salaam," Journal of Transport Geography, Elsevier, vol. 82(C).
    10. Morton E O'Kelly & Michael A Niedzielski, 2009. "Are Long Commute Distances Inefficient and Disorderly?," Environment and Planning A, , vol. 41(11), pages 2741-2759, November.
    11. Jiangping Zhou & Enda Murphy & Jonathan Corcoran, 2020. "Integrating road carrying capacity and traffic congestion into the excess commuting framework: The case of Los Angeles," Environment and Planning B, , vol. 47(1), pages 119-137, January.
    12. Michael A. Niedzielski, 2006. "A Spatially Disaggregated Approach to Commuting Efficiency," Urban Studies, Urban Studies Journal Limited, vol. 43(13), pages 2485-2502, December.
    13. Chen, Ruoyu & Zhang, Min & Zhou, Jiangping, 2023. "Jobs-housing relationships before and amid COVID-19: An excess-commuting approach," Journal of Transport Geography, Elsevier, vol. 106(C).
    14. 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.
    15. Goliszek Sławomir & Połom Marcin & Duma Patryk, 2020. "Potential and cumulative accessibility of workplaces by public transport in Szczecin," Bulletin of Geography. Socio-economic Series, Sciendo, vol. 50(50), pages 133-146, December.
    16. Schleith, Daniel & Widener, Michael & Kim, Changjoo, 2016. "An examination of the jobs-housing balance of different categories of workers across 26 metropolitan regions," Journal of Transport Geography, Elsevier, vol. 57(C), pages 145-160.
    17. Zhang, Hong & Xu, Shan & Liu, Xuan & Liu, Chengliang, 2021. "Near “real-time” estimation of excess commuting from open-source data: Evidence from China's megacities," Journal of Transport Geography, Elsevier, vol. 91(C).
    18. Cheng, Mingyang & Yansui Liu, & Zhou, Yang, 2019. "Measuring the symbiotic development of rural housing and industry: A case study of Fuping County in the Taihang Mountains in China," Land Use Policy, Elsevier, vol. 82(C), pages 307-316.
    19. 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].
    20. Cassel, Susanna Heldt & Macuchova, Zuzana & Rudholm, Niklas & Rydell, Alexis, 2013. "Willingness to commute long distance among job seekers in Dalarna, Sweden," Journal of Transport Geography, Elsevier, vol. 28(C), pages 49-55.

    More about this item

    Keywords

    Commuting; Land use; Sensitivity analysis; Accessibility; Hukou; Shanghai;
    All these keywords.

    JEL classification:

    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)
    • R23 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Regional Migration; Regional Labor Markets; Population
    • O18 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Urban, Rural, Regional, and Transportation Analysis; Housing; Infrastructure

    Statistics

    Access and download statistics

    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:kap:jgeosy:v:25:y:2023:i:1:d:10.1007_s10109-022-00394-6. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.