The topology of favela street networks and its relationship with surrounding real estate value: A spatial and complex networks analysis

This study investigates whether the internal topology of slum street networks is associated with rental price variation in surrounding formal housing markets. Using spatial econometric models and robustness checks across alternative spatial specifications, we find that network characteristics such as circuity, node density, and the prevalence of dead-ends are associated with nearby rental prices. These relationships remain stable across model specifications, although their magnitude decreases as spatial interaction scales increase. A complementary machine learning analysis is consistent with these findings, suggesting that orientation entropy of informal settlements is also an important predictor of rental prices. Overall, the results suggest that the surrounding urban morphology of slums may constitute a relevant structural dimension associated with housing market and should be considered in urban planning interventions.