A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
A spatiotemporal analysis of public pharmaceutical expenditure
Abstract A regression model for per capita public pharmaceutical expenditure, based on aggregate data from fifty Spanish provinces, observed annually for the period 1996–2002 is analyzed. The necessity of simultaneously controlling for dynamic patterns and spatial autocorrelation is demonstrated. As the aim of the present and related studies of small-area variation is to control for spatial association rather than to formulate it as an explicit part of a model, the traditional application of parametric spatial autocorrelation or spatial autoregression specifications seems unnecessarily restrictive and superfluous. The present study analyzes the effects of spatial association using a non-parametric spatial filtering approach. The importance of adjusting for spatial association is confirmed, but it is further shown that the parametric and the non-parametric approaches may lead to substantially different conclusions regarding explanation of pharmaceutical expenditure variations. Thus, the need for further evidence on the implications of spatial association—and the recognition that this is more than just spatial autocorrelation and/or spatial autoregression—when analyzing complex large area behavior using small area data is demonstrated.
A spatiotemporal analysis of public pharmaceutical expenditure
Abstract A regression model for per capita public pharmaceutical expenditure, based on aggregate data from fifty Spanish provinces, observed annually for the period 1996–2002 is analyzed. The necessity of simultaneously controlling for dynamic patterns and spatial autocorrelation is demonstrated. As the aim of the present and related studies of small-area variation is to control for spatial association rather than to formulate it as an explicit part of a model, the traditional application of parametric spatial autocorrelation or spatial autoregression specifications seems unnecessarily restrictive and superfluous. The present study analyzes the effects of spatial association using a non-parametric spatial filtering approach. The importance of adjusting for spatial association is confirmed, but it is further shown that the parametric and the non-parametric approaches may lead to substantially different conclusions regarding explanation of pharmaceutical expenditure variations. Thus, the need for further evidence on the implications of spatial association—and the recognition that this is more than just spatial autocorrelation and/or spatial autoregression—when analyzing complex large area behavior using small area data is demonstrated.
A spatiotemporal analysis of public pharmaceutical expenditure
Lauridsen, Jorgen (author) / Bech, Mickael (author) / López, Fernando (author) / Sánchez, Mariluz Maté (author)
2008
Article (Journal)
Electronic Resource
English
BKL:
83.64$jRegionalwirtschaft
/
74.12
Stadtgeographie, Siedlungsgeographie
/
38.00$jGeowissenschaften: Allgemeines
/
38.00
Geowissenschaften: Allgemeines
/
83.64
Regionalwirtschaft
/
74.12$jStadtgeographie$jSiedlungsgeographie
RVK:
ELIB39
/
ELIB18
/
ELIB45
Local classification FBW:
oek 4450
A spatiotemporal analysis of public pharmaceutical expenditure
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