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An exploratory factor analysis model for slum severity index in Mexico City

Author

Listed:
  • Debraj Roy

    (University of Amsterdam, the Netherlands)

  • David Bernal

    (University of Amsterdam, the Netherlands)

  • Michael Lees

    (University of Amsterdam, the Netherlands)

Abstract

Today, over half of the world’s population lives in urban areas and it is projected that, by 2050, two out of three people will live in a city. This increased rural–urban migration, coupled with housing poverty, has led to the growth and formation of informal settlements, commonly known as slums. In Mexico, 25% of the urban population now live in informal settlements with varying degrees of deprivation. Although some informal neighbourhoods have contributed to the upward mobility of the inhabitants, the majority still lack basic services. Mexico City and the conurbation around it form a mega city of 21million people that has been growing in a manner qualified as ‘highly unproductive, (that) deepens inequality, raises pollution levels’ (available at:   https://www.smartcitiesdive.com/ex/sustainablecitiescollective/making-way-urban-reform-mexico/176466/ ) and contains the largest slum in the world: Neza-Chalco-Izta . Urban reforms are now aiming to improve the conditions in these slums and therefore it is very important to have reliable tools to measure the changes that are underway. In this paper, we use exploratory factor analysis to define an index of shelter deprivation in Mexico City, namely the Slum Severity Index (SSI), based on the UN-HABITAT’s definition of slum. We apply this novel approach to the Census survey of Mexico and measure the shelter deprivation levels of households from 1990 to 2010. The analysis highlights high variability in housing conditions within Mexico City. We find that the SSI decreased significantly between 1990 and 2000 as a result of several policy reforms but increased between 2000 and 2010. We also show correlations of the SSI with other social factors such as education, health and fertility. We present a validation of the SSI using Grey Level Co-occurrence Matrix (GLCM) features extracted from Very-High Resolution (VHR) remote-sensed satellite images. Finally, we show that the SSI can present a cardinally meaningful assessment of the extent of deprivation compared with a similar index defined by Connolly (Connolly P (2009) Observing the evolution of irregular settlements: Mexico city’s colonias populares, 1990 to 2005. International Development Planning Review 31: 1–35) that studies shelter deprivation in Mexico.

Suggested Citation

  • Debraj Roy & David Bernal & Michael Lees, 2020. "An exploratory factor analysis model for slum severity index in Mexico City," Urban Studies, Urban Studies Journal Limited, vol. 57(4), pages 789-805, March.
    • Handle: RePEc:sae:urbstu:v:57:y:2020:i:4:p:789-805
    DOI: 10.1177/0042098019869769
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    References listed on IDEAS

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    Cited by:

    1. Heijs, Joost & Cruz-Calderón, Selene Cruz, 2023. "A novel research strategy of measuring housing disadvantages of vulnerable populations for all income levels: the Propensity Score Matching approach," MPRA Paper 117212, University Library of Munich, Germany, revised 04 May 2023.
    2. Paloma Merodio Gómez & Olivia Jimena Juarez Carrillo & Monika Kuffer & Dana R. Thomson & Jose Luis Olarte Quiroz & Elio Villaseñor García & Sabine Vanhuysse & Ángela Abascal & Isaac Oluoch & Michael N, 2021. "Earth Observations and Statistics: Unlocking Sociodemographic Knowledge through the Power of Satellite Images," Sustainability, MDPI, vol. 13(22), pages 1-21, November.
    3. Majid Farooq & Fayma Mushtaq & Gowhar Meraj & Suraj Kumar Singh & Shruti Kanga & Ankita Gupta & Pankaj Kumar & Deepak Singh & Ram Avtar, 2022. "Strategic Slum Upgrading and Redevelopment Action Plan for Jammu City," Resources, MDPI, vol. 11(12), pages 1-29, December.

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