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Design of homogenous territorial units: a methodological proposal

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  • Juan Carlos Duque

    ()

  • Raúl Ramos

    ()

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. In fact, in those cases where territorial information is aggregated, ad-hoc criteria are usually applied as there are not regionalization methods flexible enough. Moreover, and without taking into account the aggregation method applied, there is an implicit risk that is known in the literature as Modifiable Areal Unit Problem (MAUP) (Openshaw, 1984). This problem is related with the high sensitivity of statistical and econometric results to different aggregations of geographical data, which can negatively affect the robustness of the analysis. In this paper, an optimization model is proposed with the aim of identifying homogenous territorial units related with the analyzed phenomena. This model seeks to reduce some disadvantages found in previous works about automated regionalisation tools. In particular, the model not only considers the characteristics of each element to group but also, the relationships among them, trying to avoid the MAUP. An algoritm, known as RASS (Regionalization Algorithm with Selective Search) it also proposed in order to obtain faster results from the model. The obtained results permit to affirm that the proposed methodology is able to identify a great variety of territorial configurations, taking into account the contiguity constraint among the different elements to be grouped.

Suggested Citation

  • Juan Carlos Duque & Raúl Ramos, 2004. "Design of homogenous territorial units: a methodological proposal," ERSA conference papers ersa04p6, European Regional Science Association.
  • Handle: RePEc:wiw:wiwrsa:ersa04p6
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    References listed on IDEAS

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    1. Gordon, A. D., 1996. "A survey of constrained classification," Computational Statistics & Data Analysis, Elsevier, vol. 21(1), pages 17-29, January.
    2. 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.
    3. 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.
    4. Anuška Ferligoj & Vladimir Batagelj, 1982. "Clustering with relational constraint," Psychometrika, Springer;The Psychometric Society, vol. 47(4), pages 413-426, December.
    5. 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.
    6. 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.
    7. Anuška Ferligoj & Vladimir Batagelj, 1983. "Some types of clustering with relational constraints," Psychometrika, Springer;The Psychometric Society, vol. 48(4), pages 541-552, December.
    8. 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.
    9. 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.
    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 Carlos Duque & Raúl Ramos, 2004. "Spanish unemployment: normative versus analytical regionalisation procedures," ERSA conference papers ersa04p7, European Regional Science Association.
    2. 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.
    3. 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.

    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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