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  1. Abstract

    This study investigated how urban cultural and economic tolerance affects urban innovative capacities based on China's prefecture‐level cities. Several tolerance indices, including ratios of migrants, rental housing, gay people, and private economies were introduced and the cities’ tolerance scores were measured using factor analysis. The results show that cities with higher cultural and economical tolerant scores were agglomerated in three metropolitan areas in China's southeastern coastal region. The spatial regression model demonstrates that urban cultural and economic tolerance increases urban innovation output and promotes innovation capacities. We also introduced the crime rate as an instrumental variable and found that the effect of tolerance on innovation remains robust. Our study suggests it is important for the Chinese government to establish an open and tolerant environment to attract migrants, creative artists, and entrepreneurs to foster urban vitality and improve urban innovative capacities.

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  2. In this paper we move away from a static view of neighbourhood inequality and investigate the dynamics of neighbourhood economic status, which ties together spatial income inequality at different moments in time. Using census data from three decades (1980–2010) in 294 metropolitan statistical areas, we use a statistical decomposition method to unpack the aggregate spatiotemporal income dynamic into its contributing components: stability, growth and polarisation, providing a new look at the economic fortunes of diverse neighbourhoods. We examine the relative strength of each component in driving the overall pattern, in addition to whether, how, and why these forces wax and wane across space and over time. Our results show that over the long run, growth is a dominant form of change across all metros, but there is a very clear decline in its prominence over time. Further, we find a growing positive relationship between the components of dispersion and growth, in a reversal of prior trends. Looking across metro areas, we find temporal heterogeneity has been driven by different socioeconomic factors over time (such as sectoral growth in certain decades), and that these relationships vary enormously with geography and time. Together these findings suggest a high level of temporal heterogeneity in neighbourhood income dynamics, a phenomenon which remains largely unexplored in the current literature. There is no universal law governing the changing economic status of neighbourhoods in the US over the last 40 years, and our work demonstrates the importance of considering shifting dynamics over multiple spatial and temporal scales. 
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    Shanghai has experienced a rapid process of urbanization and urban expansion, which increases travel costs and limits job accessibility for the economically disadvantaged population. This paper investigates the jobs-housing imbalance problem in Shanghai at the subdistrict-level (census-level) and reaches the following conclusions. First, the jobs-housing imbalance shows a ring pattern and is evident mainly in the suburban areas and periphery of the Shanghai metropolitan area because job opportunities are highly concentrated while residential areas are sprawling. Second, structural factors such as high housing prices and sprawling development significantly contribute to the jobs-housing imbalance. Third, regional planning policies such as development zones contribute to jobs-housing imbalance due to the specialized industrial structure and limited availability of housing. However, geographically weighted regression reveals the development zones in the traditional Pudong district are exceptional insofar as government policy has created spatial heterogeneity there. In addition, the multilevel model used in this study suggests regions with jobs-housing imbalance usually have well-connected streets, and this represents the local government’s efforts to reduce excessive commuting times created by jobs-housing imbalance. 
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