IDEAS home Printed from https://ideas.repec.org/p/trn/utwprg/2016-04.html
   My bibliography  Save this paper

Incomplete geocoding and spatial sampling: the effects of locational errors on population total estimation

Author

Listed:
  • Maria Michela Dickson
  • Giuseppe Espa
  • Diego Giuliani

Abstract

Due to the increasing availability of georeferenced microdata in several fields of research, surveys can benefit greatly from the use of the most recent spatial sampling methods. These methods allow to select spatially balanced samples, which lead to particularly efficient estimates, by incorporating the distances among the exact locations of statistical units into the design. Unfortunately, since locations of units are rarely exact in practice due to imperfections in the geocoding processes, the implementation of spatial sampling designs is actually often limited. This paper aims at demonstrating that spatial sampling designs can be implemented even when spatial information is not completely accurate. In particular, by means of a Montecarlo sampling simulation study about the estimation of water pollution, it is proved that the use of spatial sampling methods still lead to more spatially balanced samples, and more efficient estimates, also when the geocoding of population is not exact.

Suggested Citation

  • Maria Michela Dickson & Giuseppe Espa & Diego Giuliani, 2016. "Incomplete geocoding and spatial sampling: the effects of locational errors on population total estimation," DEM Working Papers 2016/04, Department of Economics and Management.
    • Handle: RePEc:trn:utwprg:2016/04
    as

    Download full text from publisher

    File URL: http://www.economia.unitn.it/alfresco/download/workspace/SpacesStore/ca1b7d54-e356-4b88-914f-ba74c35730db/DEMWP2016_04.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dale L. Zimmerman, 2008. "Estimating the Intensity of a Spatial Point Process from Locations Coarsened by Incomplete Geocoding," Biometrics, The International Biometric Society, vol. 64(1), pages 262-270, March.
    2. Lennart Bondesson & Daniel Thorburn, 2008. "A List Sequential Sampling Method Suitable for Real‐Time Sampling," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 35(3), pages 466-483, September.
    3. Luc Anselin, 2010. "Thirty years of spatial econometrics," Papers in Regional Science, Wiley Blackwell, vol. 89(1), pages 3-25, March.
    4. Jean-Claude Deville & Yves Tille, 2004. "Efficient balanced sampling: The cube method," Biometrika, Biometrika Trust, vol. 91(4), pages 893-912, December.
    5. Stevens, Don L. & Olsen, Anthony R., 2004. "Spatially Balanced Sampling of Natural Resources," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 262-278, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wilmer Prentius, 2024. "Locally correlated Poisson sampling," Environmetrics, John Wiley & Sons, Ltd., vol. 35(2), March.
    2. Roberto Benedetti & Federica Piersimoni & Paolo Postiglione, 2017. "Spatially Balanced Sampling: A Review and A Reappraisal," International Statistical Review, International Statistical Institute, vol. 85(3), pages 439-454, December.
    3. Anton Grafström & Lina Schelin, 2014. "How to Select Representative Samples," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(2), pages 277-290, June.
    4. Xin Zhao & Anton Grafström, 2020. "A sample coordination method to monitor totals of environmental variables," Environmetrics, John Wiley & Sons, Ltd., vol. 31(6), September.
    5. Linda Altieri & Daniela Cocchi, 2021. "Spatial Sampling for Non‐compact Patterns," International Statistical Review, International Statistical Institute, vol. 89(3), pages 532-549, December.
    6. B. L. Robertson & J. A. Brown & T. McDonald & P. Jaksons, 2013. "BAS: Balanced Acceptance Sampling of Natural Resources," Biometrics, The International Biometric Society, vol. 69(3), pages 776-784, September.
    7. Maria Michela Dickson & Yves Tillé, 2016. "Ordered spatial sampling by means of the traveling salesman problem," Computational Statistics, Springer, vol. 31(4), pages 1359-1372, December.
    8. Guillaume Chauvet & Ronan Le Gleut, 2021. "Inference under pivotal sampling: Properties, variance estimation, and application to tesselation for spatial sampling," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(1), pages 108-131, March.
    9. Yves Tillé, 2022. "Some Solutions Inspired by Survey Sampling Theory to Build Effective Clinical Trials," International Statistical Review, International Statistical Institute, vol. 90(3), pages 481-498, December.
    10. ak Tomasz B, 2021. "Spatial sampling methods modified by model use," Statistics in Transition New Series, Polish Statistical Association, vol. 22(2), pages 143-154, June.
    11. Tomasz Bąk, 2021. "Spatial sampling methods modified by model use," Statistics in Transition New Series, Polish Statistical Association, vol. 22(2), pages 143-154, June.
    12. Raphaël Jauslin & Bardia Panahbehagh & Yves Tillé, 2022. "Sequential spatially balanced sampling," Environmetrics, John Wiley & Sons, Ltd., vol. 33(8), December.
    13. Cindy L. Yu & Jie Li & Michael G. Karl & Todd J. Krueger, 2020. "Obtaining a Balanced Area Sample for the Bureau of Land Management Rangeland Survey," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 25(2), pages 250-275, June.
    14. R. Benedetti & F. Piersimoni & P. Postiglione, 2017. "Alternative and complementary approaches to spatially balanced samples," METRON, Springer;Sapienza Università di Roma, vol. 75(3), pages 249-264, December.
    15. Raphaël Jauslin & Yves Tillé, 2020. "Spatial Spread Sampling Using Weakly Associated Vectors," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 25(3), pages 431-451, September.
    16. Maria Michela Dickson & Giuseppe Espa & Diego Giuliani & Emanuele Taufer, 2016. "Metodi di campionamento spaziale per la selezione di campioni rappresentativi di imprese," RIVISTA DI ECONOMIA E STATISTICA DEL TERRITORIO, FrancoAngeli Editore, vol. 2016(3), pages 89-99.
    17. Vicente Rios Ibañez, 2014. "What drives regional unemployment convergence?," ERSA conference papers ersa14p924, European Regional Science Association.
    18. Lorenzo Fattorini & Timothy G. Gregoire & Sara Trentini, 2018. "The Use of Calibration Weighting for Variance Estimation Under Systematic Sampling: Applications to Forest Cover Assessment," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 23(3), pages 358-373, September.
    19. Ageliki Anagnostou & Ioannis Panteladis & Maria Tsiapa, 2015. "Disentangling different patterns of business cycle synchronicity in the EU regions," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 42(3), pages 615-641, August.
    20. Marrocu, Emanuela & Paci, Raffaele, 2013. "Different tourists to different destinations. Evidence from spatial interaction models," Tourism Management, Elsevier, vol. 39(C), pages 71-83.

    More about this item

    Keywords

    GPS uncodified; Locational Accuracy; Spatial Sampling Methods; Estimation;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:trn:utwprg:2016/04. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: roberto.gabriele@unitn.it (email available below). General contact details of provider: https://edirc.repec.org/data/detreit.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.