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Design of Homogeneous Territorial Units: A Methodological Proposal

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  • Juan Carlos Duque
  • Raul Ramos Lobo
  • Jordi Surinach Caralt

    (Universitat de Barcelona)

Abstract

One of the main questions to solve when analysing geographically added information consists of the design of territorial units adjusted to the objectives of the study. This is related with the reduction of the effects of the Modifiable Areal Unit Problem (MAUP). In this paper an optimisation model to solve regionalisation problems is proposed. This model seeks to reduce some disadvantages found in previous works about automated regionalisation tools.

Suggested Citation

  • Juan Carlos Duque & Raul Ramos Lobo & Jordi Surinach Caralt, 2004. "Design of Homogeneous Territorial Units: A Methodological Proposal," Working Papers in Economics 115, Universitat de Barcelona. Espai de Recerca en Economia.
  • Handle: RePEc:bar:bedcje:2004115
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    References listed on IDEAS

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    1. C G Amrhein & R Flowerdew, 1992. "The Effect of Data Aggregation on a Poisson Regression Model of Canadian Migration," Environment and Planning A, , vol. 24(10), pages 1381-1391, October.
    2. Gordon, A. D., 1996. "A survey of constrained classification," Computational Statistics & Data Analysis, Elsevier, vol. 21(1), pages 17-29, January.
    3. A S Fotheringham & D W S Wong, 1991. "The Modifiable Areal Unit Problem in Multivariate Statistical Analysis," Environment and Planning A, , vol. 23(7), pages 1025-1044, July.
    4. Anuška Ferligoj & Vladimir Batagelj, 1983. "Some types of clustering with relational constraints," Psychometrika, Springer;The Psychometric Society, vol. 48(4), pages 541-552, December.
    5. C G Amrhein & R Flowerdew, 1992. "The effect of data aggregation on a Poisson regression model of Canadian migration," Environment and Planning A, Pion Ltd, London, vol. 24(10), pages 1381-1391, October.
    6. Anuška Ferligoj & Vladimir Batagelj, 1982. "Clustering with relational constraint," Psychometrika, Springer;The Psychometric Society, vol. 47(4), pages 413-426, December.
    7. A S Fotheringham & D W S Wong, 1991. "The modifiable areal unit problem in multivariate statistical analysis," Environment and Planning A, Pion Ltd, London, vol. 23(7), pages 1025-1044, July.
    8. Openshaw, Stan, 1992. "Some Suggestions Concerning the Development of Artificial Intelligence Tools for Spatial Modelling and Analysis in GIS," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 26(1), pages 35-51, April.
    9. S Openshaw & R S Baxter, 1977. "Algorithm 3: A Procedure to Generate Pseudo-Random Aggregations of N Zones into M Zones, Where M is Less Than N," Environment and Planning A, , vol. 9(12), pages 1423-1428, December.
    10. J. Gower & P. Legendre, 1986. "Metric and Euclidean properties of dissimilarity coefficients," Journal of Classification, Springer;The Classification Society, vol. 3(1), pages 5-48, March.
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    Citations

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    Cited by:

    1. Juan Duque & Manuel Artís & Raúl Ramos, 2006. "The ecological fallacy in a time series context: evidence from Spanish regional unemployment rates," Journal of Geographical Systems, Springer, vol. 8(4), pages 391-410, October.
    2. M. Pilar Alonso & M. Asunción Beamonte & Pilar Gargallo & Manuel Salvador, 2016. "Evolutionary and classification methods for local labor markets delineation," Computational and Mathematical Organization Theory, Springer, vol. 22(4), pages 444-466, December.
    3. Juan Carlos Duque & Raul Ramos Lobo & Manuel Artis Ortuno, 2004. "Spanish unemployment: Normative versus analytical regionalisation procedures," Working Papers in Economics 118, Universitat de Barcelona. Espai de Recerca en Economia.

    More about this item

    JEL classification:

    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)
    • R22 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Other Demand
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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