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Making Location Quotients More Relevant as a Policy Aid in Regional Spatial Analysis

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  • Andrew Crawley
  • Malcolm Beynon
  • Max Munday

Abstract

Location Quotients (LQs) remain an important tool for geographical analysis, particularly in terms of assessing industrial specialisation and clustering. LQs as decision aids are typically understood through the use of arbitrarily set cut-off values. However, LQs are rarely accompanied by an associated level of variance that can be connected with the estimated data used to calculate them. This paper reveals the importance of understanding this variance and shows how confidence intervals can be estimated for employment-based LQs. A systematic process is introduced, through which the arbitrariness of cut-off-value choice can be mitigated and borderline industry cases in terms of their LQ values and the considered cut-off value, identified. A case from a UK region is used to illustrate the issues covered in the paper.

Suggested Citation

  • Andrew Crawley & Malcolm Beynon & Max Munday, 2013. "Making Location Quotients More Relevant as a Policy Aid in Regional Spatial Analysis," Urban Studies, Urban Studies Journal Limited, vol. 50(9), pages 1854-1869, July.
  • Handle: RePEc:sae:urbstu:v:50:y:2013:i:9:p:1854-1869
    DOI: 10.1177/0042098012466601
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    References listed on IDEAS

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    4. Reinhold Kosfeld & Timo Mitze, 2023. "Research and development intensive clusters and regional competitiveness," Growth and Change, Wiley Blackwell, vol. 54(4), pages 885-911, December.
    5. Andrew Crawley & Todd M. Gabe & Mariya Pominova, 2021. "The Pitfalls of Using Location Quotients to Identify Clusters and Represent Industry Specialization in Small Regions," International Finance Discussion Papers 1329, Board of Governors of the Federal Reserve System (U.S.).
    6. Yu, Haitao & Jiao, Junfeng & Houston, Eric & Peng, Zhong-Ren, 2018. "Evaluating the relationship between rail transit and industrial agglomeration: An observation from the Dallas-fort worth region, TX," Journal of Transport Geography, Elsevier, vol. 67(C), pages 33-52.
    7. Thomas Brenner, 2017. "Identification of Clusters - An Actor based Approach," Working Papers on Innovation and Space 2017-02, Philipps University Marburg, Department of Geography.
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