IDEAS home Printed from https://ideas.repec.org/a/sae/inrsre/v34y2011i2p138-156.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0160017610386481
    Download Restriction: no
    File URL: https://libkey.io/10.1177/0160017610386481?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
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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).
    4. 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.
    5. 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.
    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.
    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. 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.

    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. Giacomini, Raffaella & Granger, Clive W. J., 2004. "Aggregation of space-time processes," Journal of Econometrics, Elsevier, vol. 118(1-2), pages 7-26.
    2. Edward E. Leamer, 1982. "Optimal Aggegation of Linear Systems," UCLA Economics Working Papers 240, UCLA Department of Economics.
    3. Monteforte, Libero, 2007. "Aggregation bias in macro models: Does it matter for the euro area?," Economic Modelling, Elsevier, vol. 24(2), pages 236-261, March.
    4. Ariel Pakes & Mark Schankerman, 1984. "An Exploration into the Determinants of Research Intensity," NBER Chapters, in: R&D, Patents, and Productivity, pages 209-232, National Bureau of Economic Research, Inc.
    5. M. Faruk Aydin & Ugur Ciplak & Eray M. Yucel, 2004. "Export Supply and Import Demand Models for the Turkish Economy," Working Papers 0409, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    6. Giacomo Sbrana, 2007. "Testing for Model Selection in Predicting Aggregate Variables," Giornale degli Economisti, GDE (Giornale degli Economisti e Annali di Economia), Bocconi University, vol. 66(1), pages 3-28, March.
    7. Shingal, Anirudh, 2007. "Examining responsiveness of India’s trade flows to exchange rate movements," MPRA Paper 32820, University Library of Munich, Germany, revised 18 Mar 2010.
    8. Cobb, Marcus P A, 2017. "Forecasting Economic Aggregates Using Dynamic Component Grouping," MPRA Paper 81585, University Library of Munich, Germany.
    9. Marcus Cobb, 2009. "Forecasting Chilean Inflation From Disaggregate Components," Working Papers Central Bank of Chile 545, Central Bank of Chile.
    10. Carson, Richard T. & Cenesizoglu, Tolga & Parker, Roger, 2011. "Forecasting (aggregate) demand for US commercial air travel," International Journal of Forecasting, Elsevier, vol. 27(3), pages 923-941.
    11. Keone Kelobonye & Feng Mao & Jianhong (Cecilia) Xia & Mohammad Shahidul Hasan Swapan & Gary McCarney, 2019. "The Impact of Employment Self-Sufficiency Measures on Commuting Time: Case Study of Perth, Australia," Sustainability, MDPI, vol. 11(5), pages 1-21, March.
    12. Bernardina Algieri, 2004. "Price and Income Elasticities of Russian Exports," European Journal of Comparative Economics, Cattaneo University (LIUC), vol. 1(2), pages 175-193, December.
    13. Leon, Jorge, 2012. "A Disaggregate Model and Second Round Effects for the CPI Inflation in Costa Rica," MPRA Paper 44484, University Library of Munich, Germany, revised 2012.
    14. Duncan Simester & Artem Timoshenko & Spyros I. Zoumpoulis, 2020. "Targeting Prospective Customers: Robustness of Machine-Learning Methods to Typical Data Challenges," Management Science, INFORMS, vol. 66(6), pages 2495-2522, June.
    15. Eisenhauer, Joseph G., 2008. "Ethical preferences, risk aversion, and taxpayer behavior," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 37(1), pages 45-63, February.
    16. Roy E. Welsch & Edwin Kuh, 1974. "The Variances of Regression Coefficient Estimates Using Aggregate Data," NBER Working Papers 0060, National Bureau of Economic Research, Inc.
    17. Bahman Rostami‐Tabar & M. Zied Babai & Aris Syntetos & Yves Ducq, 2013. "Demand forecasting by temporal aggregation," Naval Research Logistics (NRL), John Wiley & Sons, vol. 60(6), pages 479-498, September.
    18. Chen, Argon & Blue, Jakey, 2010. "Performance analysis of demand planning approaches for aggregating, forecasting and disaggregating interrelated demands," International Journal of Production Economics, Elsevier, vol. 128(2), pages 586-602, December.
    19. Ariel Pakes, 1979. "Aggregation Effects And Panel Data Estimation Problems: An Investigationof the R&D Intensity Decision," NBER Working Papers 0344, National Bureau of Economic Research, Inc.
    20. Ronald Bewley & Thomas Parry, 1991. "Predicting the Monthly and Annual Current Account Balance from Provisional Data," The Economic Record, The Economic Society of Australia, vol. 67(4), pages 317-330, December.

    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:sae:inrsre:v:34:y:2011:i:2:p:138-156. 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: SAGE Publications (email available below). General contact details of provider: .

    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.