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Joint Determination of Residential Relocation and Commuting: A Forecasting Experiment for Sustainable Land Use and Transportation Planning

Author

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  • Jaewon Lim

    (School of Public Policy and Leadership, Greenspun College of Urban Affairs, University of Nevada Las Vegas, 4505 Maryland Parkway, Las Vegas, NV 89154, USA)

  • Jae Hong Kim

    (Department of Urban Planning and Public Policy, School of Social Ecology, University of California Irvine, 206E Social Ecology I, Irvine, CA 92697, USA)

Abstract

This article applies matrix forecasting methods to the investigation of residential relocation and commuting patterns that are highly interconnected, but often analyzed separately. More specifically, using recent inter-county migration and commuting pattern data for the three largest metropolitan areas in California, it examines how residential relocation and commuting are associated in the regions and whether a unified framework—in which household relocation and commuting flow matrices are jointly determined—can improve the forecasting performance. The relocation–commuting association is found to differ substantially by region, suggesting the importance of region-specific factors in shaping the interrelationship. Joint forecasting, however, can attain a higher accuracy compared to the two separate projections, although the forecasting performance varies based on the method employed.

Suggested Citation

  • Jaewon Lim & Jae Hong Kim, 2019. "Joint Determination of Residential Relocation and Commuting: A Forecasting Experiment for Sustainable Land Use and Transportation Planning," Sustainability, MDPI, vol. 11(1), pages 1-24, January.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:1:p:182-:d:194294
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    1. Oshan, Taylor M., 2020. "Potential and pitfalls of big transport data for spatial interaction models of urban mobility," OSF Preprints gwumt, Center for Open Science.

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