The Human Development Index does not follow a normal distribution. For skewed distributions, finite mixture models can provide better estimates than fixed-effects models. In this paper, the relationship between compact cities and human development is investigated by employing a finite mixture model using panel data of Chinese prefecture-level cities. In contrast to the majority of the literature, which focuses exclusively on economic density, this article examines the impact of economic and morphological density on the level of human development. The results show that the compact development model has a negative impact on the level of human development and that the intensity of the impact varies for cities with different characteristics.

City shape is an essential reflection of spatial structure, but it has largely been ignored in urban form research. This study employs night-time satellite imagery to depict the scope of urban economic activity to investigate its impact on urban poverty. It is the first study to provide a comprehensive assessment of the mechanisms of city shape on urban poverty by using the fixed-effect estimate methodology for panel data of 285 Chinese cities from 2000 to 2018. The results showed that city compactness has an inverted U-shaped relationship with poverty incidence, which was verified by several robustness tests. Compactness can significantly attract more population into the city, and space costs and commuting costs are important influence channels. Furthermore, there exists heterogeneous nexus between city shape and urban poverty. Compactness has more significant poverty reduction effects in low-attractive cities with low productivity, low wages, and high illiteracy rates.

In comparison to agglomeration economies, the negative externalities of agglomeration have received less attention. Based on the punishment data of illegal loans from Chinese bank branches, this paper focuses on the relationship between density and credit misallocation to enrich the study of the negative externalities of agglomeration. After controlling for city size and a variety of other possible factors, the empirical results suggest that increased density leads to increased credit misallocation, and this result passes a series of robustness tests, including IV estimation. Agglomeration causes credit misallocation primarily through rising house prices, which causes financial institutions to favor housing-related loans. During this process, the government’s reliance on land finance causes higher house prices and, as a result, more severe misallocation. However, agglomeration does not always lead to an increase in credit misallocation. There are also cases where agglomeration does not lead to an increase in credit misallocation, which suggests that we should pay attention to differences in key characteristics between cities when studying the externalities of agglomeration.