This paper discusses the effects of industrial agglomeration on electrical energy consumption from a spatial perspective by highlighting multiple agglomeration types. It is argued that different types of industry agglomeration may exert differentiated effects on energy consumption and their possible spatial interactions. With city sector panel data of China's 285 prefecture-level cities for the period 2003-2013, we adopted the Spatial Durbin Model (SDM) with fixed effects to examine the spatial effects of industrial agglomeration types on energy consumption. The model found that all types of industrial agglomeration play significant and different roles in explaining overall local energy consumption. Second, geographical proximity, diversity, and related variety show the spatial spillover effects on surrounding areas. Third, the spatial energy effects of industrial agglomeration across regions are evidently heterogeneous. Diversity and one of its sub-forms-related variety maintains consumption-saving effects in regions with the initial or intermediate stage of an industry life cycle, while unrelated variety changes over different phases. The results suggest that policymakers scientifically discriminate regional features and guide the agglomerated types of industries in order to balance economic growth with energy conservation.

Air pollution is a major environmental urban issue, particularly in fast-growing cities in developing countries. Reducing air pollution is thus a challenge while evaluating the economic value of air quality is crucial for environmental policies made. However, few studies accurately estimate this value as they neglect the possible endogeneity issues, as well as the dynamic and heterogeneous effects of air pollution. Under the hedonic framework, we therefore assess the economic effect of fine particulate matter (PM_2.5) on housing prices in Beijing, China. We construct a panel based on resale apartment transactions matched with average quarterly PM_2.5 data between 2013 and 2019. To reduce the risk of an estimation bias, we apply an instrumental variable (IV) approach. Our results show that PM_2.5 is negatively associated with housing prices. Households were willing to pay an extra 0.0852% per housing unit price for an average quarterly reduction in PM_2.5 of 1 µg/m³. Furthermore, we argue that high-income dwellers tend to pay more for clean air. The negative effects of PM_2.5 across regions are significant and different. Compared with that in the basic year 2013, the negative effect increases in the first 3 years and then decreases in the last 3 years. Our findings enhance our comprehension of the economic impact of air quality and make a valuable contribution to the nuanced understanding of willingness to pay for air quality, which is beneficial in assessing and optimizing environmental regulations.

The ripple effect of housing price movements between cities has been extensively investigated, but there are relatively few studies on this topic within a metropolitan context, especially at the submarket level. This paper describes the use of ripple effect theory to examine the diffusion process and convergence of intra-urban housing prices at the submarket level in Shanghai, an emerging global city in China. The analysis is based on directed acyclic graphs, local indicators of spatial association time-paths, and a recently developed convergence test. The empirical results of grouping analysis identify 25 submarkets in Shanghai, and the diffusion of housing prices between these submarkets is found to be caused by both geographical and economic proximities. There is also a complex recursive process of price spillovers from high- to low-priced submarkets, and vice versa, which contributes to the spiraling local housing prices. Housing prices diverge across all submarkets, and the whole market can be divided into three convergence clubs. Finally, these convergence clubs have a circular structure with a degree of continuity. This study broadens our knowledge of the price interrelationship among housing submarkets at the intra-urban level. These findings have profound implications for urban planners, policy makers, and local residents.