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Measuring Intra-Urban Inequality with Structural Equation Modeling: A Theory-Grounded Indicator

Author

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  • Matheus Pereira Libório

    (Department of Administration, Pontifical Catholic University of Minas Gerais, Belo Horizonte, MG 30535-012, Brazil)

  • Oseias da Silva Martinuci

    (Department of Geography, Maringá State University, Maringá, PR 87000-000, Brazil)

  • Sandro Laudares

    (Department of Geography, Pontifical Catholic University of Minas Gerais, Belo Horizonte, MG 30535-012, Brazil)

  • Renata de Mello Lyrio

    (School of Information Science, Federal University of Minas Gerais, Belo Horizonte, MG 31270-901, Brazil)

  • Alexei Manso Correa Machado

    (Department of Computer Science, Pontifical Catholic University of Minas Gerais, Belo Horizonte, MG 30535-901, Brazil
    Department of Anatomy and Imaging, Federal University of Minas Gerais, Belo Horizonte, MG 30130-100, Brazil)

  • Patrícia Bernardes

    (Department of Administration, Pontifical Catholic University of Minas Gerais, Belo Horizonte, MG 30535-012, Brazil)

  • Petr Ekel

    (Department of Electrical Engineering, Pontifical Catholic University of Minas Gerais, Belo Horizonte, MG 30535-012, Brazil
    Department of Electrical Engineering, Federal University of Minas Gerais, Belo Horizonte, MG 31270-901, Brazil)

Abstract

Composite indicators are almost always determined by methods that aggregate a reasonable number of manifest variables that can be weighted—or not—as new synthesis variables. A problem arises when these aggregations and weightings do not capture the possible effects that the various underlying dimensions of the phenomenon have on each other, and consequently distort the assessment of intra-urban inequality. In this paper, we explore the direct and indirect effects that the different underlying dimensions of intra-urban inequality have on indicators that represent this phenomenon. Structural equation modeling was used to build a composite indicator that captures the direct and indirect effects of the underlying dimensions of intra-urban inequality. From this modeling that combines confirmatory factor analysis with a system of simultaneous equations, the intra-urban inequality of the urban conurbation of Maringá–Sarandi–Paiçandu, Brazil was measured. The model comprises first- and second-order structures. The first-order structure is composed of non-observed variables that represent three underlying dimensions of intra-urban inequality. The second-order structure is the intra-urban inequality composite indicator that synthesizes the non-observed variables of the first-order structure. The model aims at demonstrating how to perform a theorized measurement of urban inequality so that it makes it possible to identify which dimensions most influence the others, as well as which dimensions are more relevant to this purpose.

Suggested Citation

  • Matheus Pereira Libório & Oseias da Silva Martinuci & Sandro Laudares & Renata de Mello Lyrio & Alexei Manso Correa Machado & Patrícia Bernardes & Petr Ekel, 2020. "Measuring Intra-Urban Inequality with Structural Equation Modeling: A Theory-Grounded Indicator," Sustainability, MDPI, vol. 12(20), pages 1-18, October.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:20:p:8610-:d:430528
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    1. Huibo Pan & Lili Yao & Chenhe Zhang & Yuchi Zhang & Yuying Gao, 2024. "Research on Financial Poverty Alleviation Aid for Increasing the Incomes of Low-Income Chinese Farmers," Sustainability, MDPI, vol. 16(3), pages 1-24, January.
    2. Patrícia Bernardes & Petr Iakovlevitch Ekel & Sérgio Fernando Loureiro Rezende & Joel Gomes Pereira Júnior & Angélica Cidália Gouveia Santos & Maurício Andrade Rodrigues Costa & Rafael Lopes Carvalhai, 2022. "Cost of doing business index in Latin America," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(4), pages 2233-2252, August.
    3. Alexei Manso Correa Machado & Petr Iakovlevitch Ekel & Matheus Pereira Libório, 2023. "Goal-based participatory weighting scheme: balancing objectivity and subjectivity in the construction of composite indicators," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(5), pages 4387-4407, October.
    4. Matheus Pereira Libório & Petr Yakovlevitch Ekel & Oseias da Silva Martinuci & Letícia Ribeiro Figueiredo & Renato Moreira Hadad & Renata de Mello Lyrio & Patrícia Bernardes, 2022. "Fuzzy set based intra-urban inequality indicator," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(2), pages 667-687, April.

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