2013
DOI: 10.1007/s00168-013-0575-z
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Applying economic-based analytical regions: a study of the spatial distribution of employment in Spain

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Cited by 10 publications
(6 citation statements)
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“…Additionally, the so-called Modifiable Areal Unit Problem (MAUP) comes into action. When possible, the use of analytical areas (Rubiera-Moroll on and Viñuela, 2013;Viñuela et al, 2014), internally more homogeneous than provinces, would overcome these drawbacks.…”
Section: Discussionmentioning
confidence: 99%
“…Additionally, the so-called Modifiable Areal Unit Problem (MAUP) comes into action. When possible, the use of analytical areas (Rubiera-Moroll on and Viñuela, 2013;Viñuela et al, 2014), internally more homogeneous than provinces, would overcome these drawbacks.…”
Section: Discussionmentioning
confidence: 99%
“…Regarding Spain, Matea and Mora‐Sanguinetti ( ) show that increasing levels of trade restrictiveness increase commercial density and inflation, but diminish employment. As a result, necessity entrepreneurship is fostered, while opportunity entrepreneurship is stimulated in large cities or villages close to metropolitan areas where there are higher possibilities of being employed (Viñuela et al ., ). Based on this framework we propose the following hypotheses, which seek to address Spain's territorial disparities: H1 .…”
Section: Conceptual Framework and Research Hypothesesmentioning
confidence: 97%
“…Just as the choice of a light intensity (digital number) threshold in the first step proves to be fundamental, picking the commuting (dissimilarity score) threshold is not inconsequential, either. As Duque et al (2007) point out, statistical inference based on regions is strongly affected by aggregation problems, such as the ecological fallacy (Robinson 1950), the modifiable areal unit problem (MAUP) (Openshaw 1977), or spatial aggregation bias (Viñuela et al 2014). These problems are known to have led researchers to wrong conclusions, particularly when the elements grouped within the same region are highly divergent and the distribution of their attributes is asymmetrical.…”
Section: Identifying Functional Territories Using Census Commuting Datamentioning
confidence: 99%
“…This same argument is relevant to explain why our approach needs only an indication of the urban continuum without having to mitigate the blurring problem of the DMSP imagery suggested byAbrahams et al (2016) andSmall et al (2005), which is useful to reduce the spatial over extent of a blooming urban area in a more precise way.10 Nonetheless, we acknowledge that preserving complete municipalities or administrative regions as the basic units to be clustered into larger analytical regions can lead to spatial aggregation bias and to potential scenarios in which results may appear counterintuitive to agglomeration economies(Viñuela et al 2014).…”
mentioning
confidence: 92%