Wednesday, September 20, 2017

Public transport and school location impacts on educational inequalities in Sao Paulo

In 2016, I had the opportunity to attend a session at the AAG conference where Ana Moreno-Monroy presented a very interesting paper analyzing inequalities in school accessibility by public transport  in Sao Paulo. The paper is coming out in the Journal of Transport Geography and it's coauthored by Robin Lovelace and Fred Ramos, such a great team. I should also note that a big chunk of the data analysis was conducted in R using stplanr, a library for transport planning developed by Robin and Richard Ellison and which is a major contribution to the field.


Moreno-Monroy, A. I., Lovelace, R., & Ramos, F. R. (2017). Public transport and school location impacts on educational inequalities: Insights from São Paulo. Journal of Transport Geography.

Abstract:
In many large Latin American urban areas such as the São Paulo Metropolitan Region (SPMR), growing social and economic inequalities are embedded through high spatial inequality in the provision of state schools and affordable public transport to these schools. This paper sheds light on the transport-education inequality nexus with reference to school accessibility by public transport in the SPMR. To assess school accessibility, we develop an accessibility index which combines information on the spatial distribution of adolescents, the location of existing schools, and the public transport provision serving the school catchment area into a single measure. The index is used to measure school accessibility locally across 633 areas within the SPMR. We use the index to simulate the impact of a policy aiming at increasing the centralisation of public secondary education provision, and find that it negatively affects public transport accessibility for students with the lowest levels of accessibility. These results illustrate how existing inequalities can be amplified by variable accessibility to schools across income groups and geographical space. The research suggests that educational inequality impacts of school agglomeration policies should be considered before centralisation takes place.


Figure 2. Visual representation of the 12,697 OD pairs routed through the Google Distance Matrix API on an interactive map in RStudio, an open source data analysis platform.


credit: Moreno-Monroy et al 2017

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