IDEAS home Printed from https://ideas.repec.org/p/red/sed019/943.html
   My bibliography  Save this paper

Gray Zones: Slums and Urban Structure in Developing Countries

Author

Listed:
  • Tiago Cavalcanti

    (University of Cambridge)

  • Daniel da Mata

    (Sao Paulo School of Economics)

  • Marcelo dos Santos

    (Insper)

Abstract

Slums are prevalent in many developing country cities and are a critical feature of their landscape. Slums are characterized by the lack of well defined property rights and by precarious public infrastructure, such as access to improved water and sanitation. However, they allow poor households to live in the city close to where they work and enjoy agglomeration externalities. We investigate how slums are formed and how different urban related policies affect the structure of a city. We build a dynamic spatial environment in which agents are heterogenous in their labor productivity and they endogenously choose where and the type of housing mode (formal or informal) they live. We fit the model such that key macro and micro level moments of the city of Sao Paulo in Brazil are matched. We then implement counterfactual exercises to assess the role of urban land use and transportation policies on the city landscape and welfare of their citizens. We show that some policies can have non-trivial effects. For instance, a fall in transportation costs rises the overall efficiency of the city, which attracts more households to the city. Immigration from rural households increases house prices and lead to a substantial rise in slums on the border of the city. We also show that given the land use in a city, slums can be persistent over time even when the city adopts urban policies to foster formal housing.

Suggested Citation

  • Tiago Cavalcanti & Daniel da Mata & Marcelo dos Santos, 2019. "Gray Zones: Slums and Urban Structure in Developing Countries," 2019 Meeting Papers 943, Society for Economic Dynamics.
  • Handle: RePEc:red:sed019:943
    as

    Download full text from publisher

    File URL: https://red-files-public.s3.amazonaws.com/meetpapers/2019/paper_943.pdf
    Download Restriction: no
    ---><---

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:red:sed019:943. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Christian Zimmermann (email available below). General contact details of provider: https://edirc.repec.org/data/sedddea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.