Multilevel Modelling with Spatial Effects
AbstractIn 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.
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Bibliographic InfoPaper provided by Scottish Institute for Research in Economics (SIRE) in its series SIRE Discussion Papers with number 2011-13.
Date of creation: 2011
Date of revision:
Multilevel Modelling; Spatial Effects; Fixed Effects; Random Effects; IGLS; FGS2SLS;
Other versions of this item:
- 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
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-06-05 (All new papers)
- NEP-GEO-2012-06-05 (Economic Geography)
- NEP-URE-2012-06-05 (Urban & Real Estate Economics)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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