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Spatially Disaggregating Employment Growth Estimates

Author

Listed:
  • Jonathan Corcoran
  • Alan T. Murray
  • Robert J. Stimson

Abstract

Planning for and managing urban growth and development are major issues facing planners and policy makers in achieving a sustainable future for a metropolitan region. Significant impacts are found in metropolitan regions because of jobs-housing imbalances. Such imbalance occurs when residential areas are a considerable distance from locations of employment, and as a result there is a need for substantial commuter travel. This article develops an approach for estimating future jobs by sector in local areas under conditions of growth and change, assuming that commuters will seek greater efficiencies in the journey to work. An optimization modeling approach is proposed to identify scenarios of improved jobs-housing balance. An application is illustrated for the South East Queensland (SEQ) region of Australia.

Suggested Citation

  • Jonathan Corcoran & Alan T. Murray & Robert J. Stimson, 2011. "Spatially Disaggregating Employment Growth Estimates," International Regional Science Review, , vol. 34(2), pages 138-156, April.
    • Handle: RePEc:sae:inrsre:v:34:y:2011:i:2:p:138-156
    DOI: 10.1177/0160017610386481
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    References listed on IDEAS

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    1. Jon R. Miller, 1998. "original: Spatial aggregation and regional economic forecasting," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 32(2), pages 253-266.
    2. Lothlorien Redmond & Patricia Mokhtarian, 2001. "The positive utility of the commute: modeling ideal commute time and relative desired commute amount," Transportation, Springer, vol. 28(2), pages 179-205, May.
    3. Aigner, Dennis J & Goldfeld, Stephen M, 1974. "Estimation and Prediction from Aggregate Data when Aggregates are Measured More Accurately than Their Components," Econometrica, Econometric Society, vol. 42(1), pages 113-134, January.
    4. Aigner, D.J. & Goldfeld, S.M., 1974. "Estimation and prediction from aggregate data when aggregates are measured more accurately than their components," LIDAM Reprints CORE 190, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. Ronald E. Miller & Peter Blair, 1981. "Spatial Aggregation In Interregional Input‐Output Models," Papers in Regional Science, Wiley Blackwell, vol. 48(1), pages 149-164, January.
    6. James Giesecke, 2008. "A Top-down Framework for Regional Historical Analysis," Spatial Economic Analysis, Taylor & Francis Journals, vol. 3(1), pages 45-87.
    7. Cervero, Robert, 1989. "Jobs-Housing Balancing and Regional Mobility," University of California Transportation Center, Working Papers qt7mx3k73h, University of California Transportation Center.
    8. Peter Nijkamp & John Baggen & Bert van der Knaap, 1996. "Spatial Sustainability And The Tyranny Of Transport: A Causal Path Scenario Analysis," Papers in Regional Science, Wiley Blackwell, vol. 75(4), pages 501-524, October.
    9. Douglas P. Ward & Alan T. Murray & Stuart R. Phinn, 2003. "Integrating spatial optimization and cellular automata for evaluating urban change," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 37(1), pages 131-148, February.
    10. R E Miller & G Shao, 1990. "Spatial and Sectoral Aggregation in the Commodity-Industry Multiregional Input-Output Model," Environment and Planning A, , vol. 22(12), pages 1637-1656, December.
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    Cited by:

    1. Niedzielski, Michael A. & Horner, Mark W. & Xiao, Ningchuan, 2013. "Analyzing scale independence in jobs-housing and commute efficiency metrics," Transportation Research Part A: Policy and Practice, Elsevier, vol. 58(C), pages 129-143.

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