Abstract
AbstractThis paper analyzes the relationship between informal housing and labor informality at the intraurban level, considering these two phenomena' simultaneity and spatial dimensions. Our analysis focuses on the context of a city in a developing country, Medellín (Colombia), characterized by significant housing precariousness and low employment quality, where space seems to play an essential role in understanding this relationship. Using data from 176 analytical regions in Medellín for 2017, we estimate a series of spatial simultaneous equation models that consider the potential cross-equation correlations in the error terms. The results show that these two types of urban informality are highly persistent in space, with noticeable spatial clusters observed in the peripheral and marginalized areas of the city. Additionally, the estimated econometric models reveal that precarious working conditions are key to explaining the spatial choice of housing and its characteristics, and vice versa. These findings emphasize the need for place-based policies that specifically target disadvantaged areas and help improve residents' working and housing conditions to address urban informality.
Publisher
Springer Science and Business Media LLC
Reference81 articles.
1. Abramo, P. (2009). Social innovation, reciprocity and the monetarization of territory in informal settlements in Latin American cities. Social innovation and territorial development. In D. MacCallum, S. V. Haddock, & F. Moulaert (Eds.), Social innovation and territorial development (1st ed., pp. 115–130). Routledge.
2. Aliu, I., Akoteyon, I., & Soladoye, O. (2021). Living on the margins: Socio-spatial characterization of residential and water deprivations in Lagos informal settlements, Nigeria. Habitat International, 107, 102293.
3. Alves, G. (2018). Determinants of slum formation: the role of local politics and policies. Working paper, No 2018/06. CAF.
4. Alves, G. (2021). Slum growth in Brazilian cities. Journal of Urban Economics, 122, 103327.
5. Amrhein, C., & Flowerdew, R. (1992). The effect of data aggregation on a Poisson regression model of Canadian migration. Environment and Planning A, 24(10), 1381–1391.