Abstract
The paper focuses on the issue of the modifiable areal unit problem (MAUP), which is frequently discussed within spatial econometrics. This issue concerns the changeability of the characteristics of the analysed phenomena under the impact of the change in the composition of territorial units. The article indicates four conditions which need to be fulfilled if the correctness of spatial analyses is to be maintained. Also, the paper introduces the concept of the quasi composition of regions (QCR). It was defined as a set of particular compositions of territorial units for subsequent aggregation scales. Particular compositions of territorial units are selected in a way that allows a correct analysis within the undertaken research problem to be conducted. The chief asset of the paper is the proposal to redefine the concept of the modifiable areal unit problem. Both the scale problem and the aggregation problem were linked to the accepted quasi composition of regions. The redefinition of the concept is vital for the research conducted since analysing phenomena based on compositions of territorial units which are excluded from the quasi composition of regions leads to the formulation of incorrect conclusions. Within the undertaken research problem there exists only one particular composition of territorial units which allows the identification and description of the dependence for analysed phenomena. Within the considered modifiable areal unit problem two potential problems were defined and they can occur while making spatial analyses. The first is the final areal interpretation problem (FAIP) that occurs when the characteristics of phenomena or the dependence are designated for too large region. The other issue is the aggregation scale interpretation problem (ASIP). It occurs when a quasi composition of regions is enlarged by an aggregation scale where the correctness of the results of the undertaken research problem is not preserved. In both cases it is possible to reach a situation where the obtained characteristics will be deprived of the cognitive value.
Highlights
The paper focuses on the modifiable areal unit problem (MAUP) in spatial analyses conducted
The research thesis formulated in the paper has the following wording: ‘how to obtain correct results within analyses made for spatial data?’ The answer to the question will enable us to provide a comprehensive study of the issue of the modifiable areal unit problem that has already been mentioned in numerous works Gehlke and Biehl (1934), Yule and Kendall (1950), Robinson (1950), Blalock (1964), Openshaw and Taylor (1979), Openshaw (1984a, 1984b), Reynolds (1988), Fotheringharn and Wong (1991), Holt, Steel, and Tranmer (1996), Tranmer and Steel (2001), Arbia (2006), Manley, Flowerdew, and Steel (2006), Suchecki(ed.) (2010), Flowerdew (2011) and Pietrzak (2014a, 2014b)
Spatial analyses of Poland, or of the European Union, carried out by various researchers, are usually based on irregular regions corresponding to the NUTS classification which results from data availability1
Summary
The paper focuses on the modifiable areal unit problem (MAUP) in spatial analyses conducted. Spatial analyses of Poland, or of the European Union, carried out by various researchers, are usually based on irregular regions corresponding to the NUTS classification which results from data availability. Spatial analyses of Poland, or of the European Union, carried out by various researchers, are usually based on irregular regions corresponding to the NUTS classification which results from data availability1 Due to this fact, the considerations made in the present paper will be limited to irregular regions. As regards condition 2, the choice of the aggregation scale for spatial data is made and basing on it conclusions will be drawn from the analysis conducted. Economic phenomena are analysed basing on spatial data related to a selected aggregation scale (e.g., a province, NUTS 2). The choice of the measures or of the model for describing the phenomena of the formulated research problem is significant
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