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What values of Moran’s I and Theil index decomposition really mean under different conditions: on the issue of interpretation

Author

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  • Vojtěch Nosek

    (Charles University in Prague)

  • Pavlína Netrdová

    (Charles University in Prague)

Abstract

In recent decades, improved methodological apparatuses and increased data availability have enhanced data analyses in social sciences. Moreover, complex analyses using sophisticated methods take just a matter of seconds nowadays thanks to highly powerful software. However, such methods are often poorly understood from a methodological point of view despite the fact that knowledge of their specific properties is crucial to accurately interpreting the results. In this paper we study methods of spatial aspects of variability and examine a specific property of such methods to demonstrate how it can affect the final interpretation. By modelling data in a regular 100 by 100 grid as well as empirical examples from Czechia based on data from the 2011 Czech census, this paper presents possible interpretation-biases and recommendations for how to avoid them. We use the example of spatial autocorrelation (measured by Moran’s I) and variability decomposition (measured by the Theil index); two basic methods which enable us to measure variability in regions and in space.

Suggested Citation

  • Vojtěch Nosek & Pavlína Netrdová, 2017. "What values of Moran’s I and Theil index decomposition really mean under different conditions: on the issue of interpretation," Letters in Spatial and Resource Sciences, Springer, vol. 10(2), pages 149-159, July.
    • Handle: RePEc:spr:lsprsc:v:10:y:2017:i:2:d:10.1007_s12076-016-0178-2
    DOI: 10.1007/s12076-016-0178-2
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    References listed on IDEAS

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    1. Sergio Rey & Richard Smith, 2013. "A spatial decomposition of the Gini coefficient," Letters in Spatial and Resource Sciences, Springer, vol. 6(2), pages 55-70, July.
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    7. Takahiro Akita, 2000. "Decomposing Regional Income Inequality Using Two-Stage Nested Theil Decomposition Method," Working Papers EMS_2000_02, Research Institute, International University of Japan.
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    Cited by:

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    More about this item

    Keywords

    Regional variability; Spatial autocorrelation; Interpretation; Theil index; Moran’s I;
    All these keywords.

    JEL classification:

    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General

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