Planning Ahead for Better Neighborhoods: Long-Run Evidence from Tanzania

Abstract

Africa's demand for urban housing is soaring, even as it faces a proliferation of slums. In this setting, can modest infrastructure investments in greenfield areas where people subsequently build their own houses facilitate long run neighborhood development? We study "Sites and Services" projects implemented in seven Tanzanian cities during the 1970s and 1980s, and we use a spatial regression discontinuity design to compare greenfield areas that were treated ("de novo") to nearby greenfield areas that were not. We find that by the 2010s, de novo areas developed into neighborhoods with larger and more regularly laid out buildings and better quality housing.

Intergenerational Mobility in Slums: Evidence from a Field Survey in Jakarta

“…Moreover, a related line of research examines urban development and slums. For example, Marx, Stoker, and Suri (2015) focus on ethnic patronage and private investments in slums in Kenya; Henderson, Venables, and Regan (2016) model the dynamic development process of slums in Kenya; Harari and Wong (2018) examine slum upgrading in Indonesia; and Michaels et al (2018) study sites and service programs in slums in Tanzania.…”

Searching for Customers, Finding Pollution

“…Specifically, our 52 sub-counties comprise 179 sampled parishes. Following Ahlfeldt et al (2015), Carozzi and Roth (2020) and Michaels et al (2021), we split parishes in our sample into grid cells of 500m × 500m, drawing grid cells on all selected parishes. 28 Each road, pollution measure and firm are attributed to a cell using their geo-coordinates.…”

“…Guided by the model, we use our data to establish the main empirical results on how the informal nature of production in low-income countries shapes exposure to pollution. To study location choice in practice, we divide the cities in our sample in grid cells of 500 meters × 500 meters following the literature (Ahlfeldt et al 2015, Michaels et al 2021. We then aggregate our key variables of interest -pollution, firm density and road size -at the grid cell level.…”

Pollution in Ugandan Cities: Do Managers Avoid it or Adapt in Place?

“…Specifically, our 52 sub-counties comprise 179 sampled parishes. Following Ahlfeldt et al (2015), Carozzi and Roth (2020) and Michaels et al (2017), we split parishes in our sample into grid cells of 500m × 500m, drawing grid cells on all selected parishes. 27 Each road, pollution measure and firm are attributed to a cell using their geo-coordinates.…”