Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/244350 
Year of Publication: 
2019
Series/Report no.: 
Working Papers on Innovation and Space No. 05.19
Publisher: 
Philipps-University Marburg, Department of Geography, Marburg
Abstract: 
There is growing evidence that personality traits are spatially clustered across geographic regions and that regionally aggregated personality scores are related to political, economic, social, and health outcomes. However, much of the evidence comes from research that has relied on methods that are ill-suited for working with spatial data. Consequently, the validity and generalizability of that work is unclear. The present work addresses two main challenges of working with spatial data (i.e., Modifiable Aerial Unit Problem and spatial dependencies) and evaluates data-analytic techniques designed to tackle those challenges. Using analytic techniques designed for spatial data, we offer a practical guideline for working with spatial data in psychological research. Specifically, we investigate the robustness of regional personality differences and their correlates within the U.S. (Study 1: N = 3,387,303) and Germany (Study 2: N = 110,029). To account for the Modifiable Aerial Unit Problem, we apply a mapping approach that visualizes distributional patterns without aggregating to a higher level and examine the correlates of regional personality scores across multiple levels of spatial aggregation. To account for spatial dependencies, we examine the correlates of regional personality scores using spatial econometric models. Overall, our results suggest that regional personality differences are robust and can be reliably studied across countries and spatial levels. At the same time, the 4 results also show that ignoring the methodological challenges of spatial data can have serious consequences for research concerned with regional personality differences.
Subjects: 
Geographical Psychology
Personality
Spatial Analysis
Document Type: 
Working Paper

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