IDEAS home Printed from https://ideas.repec.org/a/cup/polals/v10y2002i03p276-297_01.html
   My bibliography  Save this article

Spatial Effects and Ecological Inference

Author

Listed:
  • Anselin, Luc
  • Tam Cho, Wendy K.

Abstract

This paper examines the role of spatial effects in ecological inference. Both formally and through simulation experiments, we consider the problems associated with ecological inference and cross-level inference methods in the presence of increasing degrees of spatial autocorrelation. Past assessments of spatial autocorrelation in aggregate data analysis focused on unidimensional, one-directional processes that are not representative of the full complexities caused by spatial autocorrelation. Our analysis is more complete and representative of true forms of spatial autocorrelation and pays particular attention to the specification of spatial autocorrelation in models with random coefficient variation. Our assessment focuses on the effects of this specification on the bias and precision of parameter estimates.

Suggested Citation

  • Anselin, Luc & Tam Cho, Wendy K., 2002. "Spatial Effects and Ecological Inference," Political Analysis, Cambridge University Press, vol. 10(3), pages 276-297, July.
    • Handle: RePEc:cup:polals:v:10:y:2002:i:03:p:276-297_01
    as

    Download full text from publisher

    File URL: https://www.cambridge.org/core/product/identifier/S104719870001007X/type/journal_article
    File Function: link to article abstract page
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Russell Weaver, 2015. "The Racial Context of Convenience Voting Cutbacks," SAGE Open, , vol. 5(3), pages 21582440155, August.
    2. Lim, Johan & Lee, Kiseop & Yu, Donghyeon & Liu, Haiyan & Sherman, Michael, 2012. "Parameter estimation in the spatial auto-logistic model with working independent subblocks," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 4421-4432.
    3. Judge, George G. & Miller, Douglas J. & Cho, Wendy K., 2003. "An Information Theoretic Approach to Ecological Estimation and Inference," CUDARE Working Papers 25065, University of California, Berkeley, Department of Agricultural and Resource Economics.
    4. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    5. Lim, Johan & Wang, Xinlei & Sherman, Michael, 2007. "An adjustment for edge effects using an augmented neighborhood model in the spatial auto-logistic model," Computational Statistics & Data Analysis, Elsevier, vol. 51(8), pages 3679-3688, May.
    6. Cem Ertur & Julie Le Gallo & Catherine Baumont, 2006. "The European Regional Convergence Process, 1980-1995: Do Spatial Regimes and Spatial Dependence Matter?," International Regional Science Review, , vol. 29(1), pages 3-34, January.
    7. Breandán Ó'hUallacháin, 2008. "Regional growth transition clubs in the United States," Papers in Regional Science, Wiley Blackwell, vol. 87(1), pages 33-53, March.
    8. Sergio J. Rey & Luc Anselin & David C. Folch & Daniel Arribas-Bel & Myrna L. Sastré Gutiérrez & Lindsey Interlante, 2011. "Measuring Spatial Dynamics in Metropolitan Areas," Economic Development Quarterly, , vol. 25(1), pages 54-64, February.
    9. Anselin, Luc, 2002. "Under the hood : Issues in the specification and interpretation of spatial regression models," Agricultural Economics, Blackwell, vol. 27(3), pages 247-267, November.
    10. Cem Ertur & Julie Le Gallo, 2008. "Regional Growth and Convergence: Heterogenous reaction versus interaction in spatial econometric approaches," Working Papers hal-00463274, HAL.
    11. Baodong Liu, 2007. "EI Extended Model and the Fear of Ecological Fallacy," Sociological Methods & Research, , vol. 36(1), pages 3-25, August.
    12. John S. L. McCombie & Mark Roberts, 2007. "Returns To Scale And Regional Growth: The Static-Dynamic Verdoorn Law Paradox Revisited," Journal of Regional Science, Wiley Blackwell, vol. 47(2), pages 179-208, May.
    13. Ding, Wangwang & Du, Juntao & Kazancoglu, Yigit & Mangla, Sachin Kumar & Song, Malin, 2023. "Financial development and the energy net-zero transformation potential," Energy Economics, Elsevier, vol. 125(C).
    14. Katherine J. Curtis, 2012. "Book Review: Spatial Regression Models," Sociological Methods & Research, , vol. 41(4), pages 671-674, November.
    15. Fan Yin & Yongsheng Qian & Junwei Zeng & Xu Wei, 2024. "The Spatial Spillover Effects of Transportation Infrastructure on Regional Economic Growth—An Empirical Study at the Provincial Level in China," Sustainability, MDPI, vol. 16(19), pages 1-23, October.
    16. Longhi, Simonetta & Nijkamp, Peter, 2006. "Forecasting regional labor market developments under spatial heterogeneity and spatial correlation," Serie Research Memoranda 0015, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    17. repec:asg:wpaper:1028 is not listed on IDEAS
    18. Helms, Andrew C., 2012. "Keeping up with the Joneses: Neighborhood effects in housing renovation," Regional Science and Urban Economics, Elsevier, vol. 42(1-2), pages 303-313.
    19. Simonetta Longhi & Peter Nijkamp, 2005. "Forecasting Regional Labour Market Developments Under Spatial Heterogeneity and Spatial Autocorrelation," Tinbergen Institute Discussion Papers 05-041/3, Tinbergen Institute.
    20. Zachary Elkins & Beth Simmons, 2005. "On Waves, Clusters, and Diffusion: A Conceptual Framework," The ANNALS of the American Academy of Political and Social Science, , vol. 598(1), pages 33-51, March.
    21. Simonetta Longhi & Peter Nijkamp, 2007. "Forecasting Regional Labor Market Developments under Spatial Autocorrelation," International Regional Science Review, , vol. 30(2), pages 100-119, April.
    22. Dayton M. Lambert & Wan Xu & Raymond J. G. M. Florax, 2014. "Partial Adjustment Analysis of Income and Jobs, and Growth Regimes in the Appalachian Region with Smooth Transition Spatial Process Models," International Regional Science Review, , vol. 37(3), pages 328-364, July.

    More about this item

    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:cup:polals:v:10:y:2002:i:03:p:276-297_01. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Kirk Stebbing (email available below). General contact details of provider: https://www.cambridge.org/pan .

    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.