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Testing Areal Interpolation Methods With Us Census 2010 Data

Author

Listed:
  • Huyen DO VAN

    (Toulouse School of Economics (GREMAQ))

  • Christine THOMAS-AGNAN

    (Toulouse School of Economics (GREMAQ))

  • Anne VANHEMS

    (Toulouse School of Economics (GREMAQ))

Abstract

The areal interpolation problem is that of projecting a characteristic of interest on a partition of space called target partition from the knowledge of the same characteristic on a different partition, so called source partition, using some auxiliary information. The objective of this paper is to use a demographic database available in the R package ‘US census 2010’ (Almquist, 2010) in order to test several areal interpolation methods based on regression in the case of count related data. The fact that data is available at many different spatial scales in this database make this comparison study unique. Another innovative point of view is that we compare the extensive approach versus the intensive approach for a variable which is a ratio of counts. We also include the comparison with the scaled regression for the extensive case introduced in Do et al. (2015) and with a scaled regression for the intensive case proposed here. Finally we give some empirical guidelines for the choice of auxiliary information.

Suggested Citation

  • Huyen DO VAN & Christine THOMAS-AGNAN & Anne VANHEMS, 2014. "Testing Areal Interpolation Methods With Us Census 2010 Data," Region et Developpement, Region et Developpement, LEAD, Universite du Sud - Toulon Var, vol. 40, pages 83-96.
    • Handle: RePEc:tou:journl:v:40:y:2014:p:83-96
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    References listed on IDEAS

    as
    1. Flowerdew, Robin & Green, Mick, 1992. "Developments in Areal Interpolation Methods and GIS," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 26(1), pages 67-78, April.
    2. Almquist, Zack W., 2010. "US Census Spatial and Demographic Data in R: The UScensus2000 Suite of Packages," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 37(i06).
    3. Calcagno, Vincent & de Mazancourt, Claire, 2010. "glmulti: An R Package for Easy Automated Model Selection with (Generalized) Linear Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 34(i12).
    4. Robin Flowerdew & Mick Green & Evangelos Kehris, 1991. "Using Areal Interpolation Methods In Geographic Information Systems," Papers in Regional Science, Wiley Blackwell, vol. 70(3), pages 303-315, July.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    AREAL INTERPOLATION; SPATIAL DISAGGREGATION; PYCNOPHYLACTIC PROPERTY;
    All these keywords.

    JEL classification:

    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods

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