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Supervised regionalization methods, a survey

Author

Listed:
  • Juan Carlos Duque

    (Regional Analysis Laboratory (REGAL). San Diego State University.)

  • Raul Ramos

    (Faculty of Economics, University of Barcelona.)

  • Jordi Suriñach

    (Faculty of Economics, University of Barcelona.)

Abstract

This paper reviews almost four decades of contributions on the subject of supervised regionalization methods. These methods aggregate a set of areas into a predefined number of spatially contiguous regions while optimizing certain aggregation criteria. The authors present a taxonomic scheme that classifies a wide range of regionalization methods into eight groups, based on the strategy applied for satisfying the spatial contiguity constraint. The paper concludes by providing a qualitative comparison of these groups in terms of a set of certain characteristics, and by suggesting future lines of research for extending and improving these methods.

Suggested Citation

  • Juan Carlos Duque & Raul Ramos & Jordi Suriñach, 2006. "Supervised regionalization methods, a survey," IREA Working Papers 200608, University of Barcelona, Research Institute of Applied Economics, revised Dec 2006.
  • Handle: RePEc:ira:wpaper:200608
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    File URL: http://www.ub.edu/irea/working_papers/2006/200608.pdf
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    regionalization; constrained clustering; analytical regions.;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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