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Multilevel Modelling with Spatial Effects

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  • Corrado, L.
  • Fingleton, B.

Abstract

In multilevel modelling, interest in modeling the nested structure of hierarchical data has been accompanied by increasing attention to different forms of spatial interactions across different levels of the hierarchy. Neglecting such interactions is likely to create problems of inference, which typically assumes independence. In this paper we review approaches to multilevel modelling with spatial effects, and attempt to connect the two literatures, discussing the advantages and limitations of various approaches.

Suggested Citation

  • Corrado, L. & Fingleton, B., 2011. "Multilevel Modelling with Spatial Effects," SIRE Discussion Papers 2011-13, Scottish Institute for Research in Economics (SIRE).
  • Handle: RePEc:edn:sirdps:255
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    File URL: http://hdl.handle.net/10943/255
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    References listed on IDEAS

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    Cited by:

    1. Luisa Corrado & Bernard Fingleton, 2012. "Where Is The Economics In Spatial Econometrics?," Journal of Regional Science, Wiley Blackwell, vol. 52(2), pages 210-239, May.
    2. Ye, Qianting & Liang, Huajie & Lin, Kuan-Pin & Long, Zhihe, 2019. "Hierarchically spatial autoregressive and moving average error model," Economic Modelling, Elsevier, vol. 76(C), pages 14-30.
    3. Darko, Francis Addeah & Ricker-Gilbert, Jacob & Shively, Gerald & Florax, Raymond & Kilic, Talip, 2014. "Where and why is Fertilizer (Un)Profitable in sub-Saharan Africa? A Spatial Econometric Analysis of Fertilizer Use in Malawi," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170651, Agricultural and Applied Economics Association.
    4. Susana Katherine Chacón Espejo & Dusan Paredes Araya, 2013. "Spatial Income Inequality in Chile and the Rol of Spatial Labor Sorting," Documentos de Trabajo en Economia y Ciencia Regional 46, Universidad Catolica del Norte, Chile, Department of Economics, revised Apr 2013.
    5. Gerald L. McCallister, 2016. "Beyond Dyads: Regional Democratic Strength’s Influence on Dyadic Conflict," International Interactions, Taylor & Francis Journals, vol. 42(2), pages 295-321, March.
    6. Baltagi, Badi H. & Fingleton, Bernard & Pirotte, Alain, 2014. "Spatial lag models with nested random effects: An instrumental variable procedure with an application to English house prices," Journal of Urban Economics, Elsevier, vol. 80(C), pages 76-86.
    7. Susana Katherine Chacón Espejo & Dusan Paredes Araya, 2013. "Income Inequality in Chile and the Rol of Spatial Labor Sorting," Documentos de Trabajo en Economia y Ciencia Regional 46, Universidad Catolica del Norte, Chile, Department of Economics, revised Apr 2013.
    8. Webb, Calum & Bywaters, Paul & Scourfield, Jonathan & McCartan, Claire & Bunting, Lisa & Davidson, Gavin & Morris, Kate, 2020. "Untangling child welfare inequalities and the ‘Inverse Intervention Law’ in England," Children and Youth Services Review, Elsevier, vol. 111(C).
    9. Darko, Francis Addeah & Ricker-Gilbert, Jacob & Kilic, Talip & Florax, Raymond & Shively, Gerald, 2016. "Profitability of fertilizer use in SSA: evidence from rural Malawi," 2016 Fifth International Conference, September 23-26, 2016, Addis Ababa, Ethiopia 249269, African Association of Agricultural Economists (AAAE).

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    More about this item

    Keywords

    Multilevel Modelling; Spatial Effects; Fixed Effects; Random Effects; IGLS; FGS2SLS;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • R0 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General

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