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A Comment on Tobias Kronenberg’s “Construction of Regional Input-Output Tables Using Nonsurvey Methods: The Role of Cross-Haulingâ€

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  • Anthony T. Flegg
  • Timo Tohmo

Abstract

This article examines the effectiveness of a new non-survey regionalization method: Kronenberg’s Cross-Hauling Adjusted Regionalization Method (CHARM). This aims to take into account the fact that regions typically both import and export most commodities. Data for Uusimaa, Finland’s largest region, are employed to carry out a detailed empirical test of CHARM. This test gives very encouraging results. CHARM is suitable for studying environmental questions, but it can only be applied in situations where foreign imports have been included in the national input–output table. Where the focus is on regional output and employment, location quotients (LQs) can be used for purposes of regionalization. On both theoretical and empirical grounds, the FLQ appears to be the most suitable LQ currently available. It should be applied to national input–output tables that exclude foreign imports. Both types of table are available at the national level for all European Union members as well as for some other countries.

Suggested Citation

  • Anthony T. Flegg & Timo Tohmo, 2013. "A Comment on Tobias Kronenberg’s “Construction of Regional Input-Output Tables Using Nonsurvey Methods: The Role of Cross-Haulingâ€," International Regional Science Review, , vol. 36(2), pages 235-257, April.
    • Handle: RePEc:sae:inrsre:v:36:y:2013:i:2:p:235-257
    DOI: 10.1177/0160017612446371
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    References listed on IDEAS

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    1. Kronenberg, Tobias, 2011. "Regional input-output models and the treatment of imports in the European System of Accounts," MPRA Paper 30797, University Library of Munich, Germany.
    2. Tobias Kronenberg, 2009. "Construction of Regional Input-Output Tables Using Nonsurvey Methods," International Regional Science Review, , vol. 32(1), pages 40-64, January.
    3. Timo Tohmo, 2004. "New Developments in the Use of Location Quotients to Estimate Regional Input-Output Coefficients and Multipliers," Regional Studies, Taylor & Francis Journals, vol. 38(1), pages 43-54.
    4. Anthony Flegg & Timo Tohmo, 2011. "Regional Input-Output Tables and the FLQ Formula: A Case Study of Finland," ERSA conference papers ersa11p334, European Regional Science Association.
    5. Geoff Riddington & Hervey Gibson & John Anderson, 2006. "Comparison of Gravity Model, Survey and Location Quotient-based Local Area Tables and Multipliers," Regional Studies, Taylor & Francis Journals, vol. 40(9), pages 1069-1081.
    6. Andrea Bonfiglio & Francesco Chelli, 2008. "Assessing the Behaviour of Non-Survey Methods for Constructing Regional Input-Output Tables through a Monte Carlo Simulation," Economic Systems Research, Taylor & Francis Journals, vol. 20(3), pages 243-258.
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    Cited by:

    1. Anthony T. Flegg & Timo Tohmo, 2013. "Estimating regional input coefficients and multipliers: The Use of the FLQ is not a Gamble," Working Papers 20131302, Department of Accounting, Economics and Finance, Bristol Business School, University of the West of England, Bristol.
    2. Sunggoan Choi & Haemyoung Ji & Xiaoyun Zhao, 2014. "Identifying key sectors using regional input-output model at sub-national level," ERSA conference papers ersa14p995, European Regional Science Association.

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