The need for public housing is increasingly emphasized worldwide, making it necessary to analyze the relationship between public housing location and local characteristics within a city. This study aimed to identify these relationships from a literature review and then empirically analyze them. Two statistical models (gamma and inverse Gaussian) were compared to find the most suitable model for analyzing public housing location. The analysis revealed three main results. First, hierarchical regression analysis confirmed that the model adopting the population’s socioeconomic characteristics, access to infrastructure, and environmental characteristics had the best explanatory power. Second, Korean cities have different characteristics to other countries in the relationship between public housing location and a city’s local characteristics. Finally, the gamma model was the most appropriate of the two statistical models. The findings are expected to help further clarify the future role and contribution of public housing. The results could encourage developing countries to reduce their initial project burdens and social costs by choosing the right location.