Abstract
The analysis of socio-economic data often implies the combination of data bases originating from different administrative sources so that data have been collected on several separate partitions of the zone of interest into administrative units. It is therefore necessary to reallocate the data from the source spatial units to the target spatial units. We propose a review of the literature on statistical methods of spatial reallocation rules (spatial interpolation). Indeed one can distinguish several types of reallocation depending on whether the initial data and the final output are areal data or point data. We concentrate here on the areal-to-areal change of support case when initial and final data have an areal support with a particular attention to disaggregation for continuous data. There are three main types of such techniques: proportional weighting schemes also called dasymetric methods, smoothing techniques and regression based interpolation.
Keywords
areal interpolation; spatial disaggregation; pycnophylactic property; change of support; polygon overlay problem;
JEL codes
- C21: Cross-Sectional Models • Spatial Models • Treatment Effect Models • Quantile Regressions
- C31: Cross-Sectional Models • Spatial Models • Treatment Effect Models • Quantile Regressions • Social Interaction Models
- C53: Forecasting and Prediction Methods • Simulation Methods
Replaced by
Van Huyen Do, Christine Thomas-Agnan, and Anne Vanhems, “Spatial reallocation of areal data - another look at basic methods”, Revue d'Économie Régionale et Urbaine, May 2015, pp. 27–58.
Reference
Van Huyen Do, Christine Thomas-Agnan, and Anne Vanhems, “Spatial reallocation of areal data - a review : Réaffectation spatiale de données surfaciques - revue bibliographique”, March 2013, revised March 2014.
See also
Published in
March 2013, revised March 2014