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Measuring the Spatial Dimension of Regional Inequality: An Approach Based on the Gini Correlation Measure

Author

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  • Domenica Panzera

    (“G. d’Annunzio” University of Chieti-Pescara)

  • Paolo Postiglione

    (“G. d’Annunzio” University of Chieti-Pescara)

Abstract

Traditional inequality measures fail to capture the geographical distribution of income. The failure to consider such distribution implies that, holding income constant, different spatial patterns provide the same inequality measure. This property is referred to as anonymity and presents an interesting question about the relationship between inequality and space. Particularly, spatial dependence could play an important role in shaping the geographical distribution of income and could be usefully incorporated into inequality measures. Following this idea, this paper introduces a new measure that facilitates the assessment of the relative contribution of spatial patterns to overall inequality. The proposed index is based on the Gini correlation measure and accounts for both inequality and spatial autocorrelation. Unlike most of the spatially based income inequality measures proposed in the literature, our index introduces regional importance weighting in the analysis, thereby differentiating the regional contributions to overall inequality. Starting with the proposed measure, a spatial decomposition of the Gini index of inequality for weighted data is also derived. This decomposition permits the identification of the actual extent of regional disparities and the understanding of the interdependences among regional economies. The proposed measure is illustrated by an empirical analysis focused on Italian provinces.

Suggested Citation

  • Domenica Panzera & Paolo Postiglione, 2020. "Measuring the Spatial Dimension of Regional Inequality: An Approach Based on the Gini Correlation Measure," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 148(2), pages 379-394, April.
    • Handle: RePEc:spr:soinre:v:148:y:2020:i:2:d:10.1007_s11205-019-02208-7
    DOI: 10.1007/s11205-019-02208-7
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    Cited by:

    1. Domenica Panzera & Alfredo Cartone & Paolo Postiglione, 2022. "New evidence on measuring the geographical concentration of economic activities," Papers in Regional Science, Wiley Blackwell, vol. 101(1), pages 59-79, February.
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    4. Pritam Ghosh & Asraful Alam & Nilanjana Ghosal & Debodatta Saha, 2021. "A Geospatial Analysis of Temporary Housing Inequality among Socially Marginalized and Privileged Groups in India," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(3), pages 798-819, June.
    5. Alfredo Cartone & Domenica Panzera & Paolo Postiglione, 2022. "Regional economic disparities, spatial dependence and proximity structures," Regional Science Policy & Practice, Wiley Blackwell, vol. 14(5), pages 1034-1050, October.
    6. Alfredo Cartone & Domenica Panzera, 2021. "Deprivation at local level: Practical problems and policy implications for the province of Milan," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(1), pages 43-61, February.
    7. Umut Türk & John Östh, 2023. "Introducing a spatially explicit Gini measure for spatial segregation," Journal of Geographical Systems, Springer, vol. 25(4), pages 469-488, October.
    8. Benassi Federico & Mucciardi Massimo & Pirrotta Giovanni, 2023. "Looking for a New Approach to Measuring the Spatial Concentration of the Human Population," Journal of Official Statistics, Sciendo, vol. 39(3), pages 285-324, September.
    9. Fathim Rashna Kallingal & Mohammed Firoz C, 2022. "Developing a methodological framework for capturing regional disparities in social development," Regional Science Policy & Practice, Wiley Blackwell, vol. 14(5), pages 1085-1112, October.

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    More about this item

    Keywords

    Inequality measure; Spatial patterns; Spatial autocorrelation; Inequality decomposition;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • R1 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)

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