Home prices have surged in major Chinese cities, leading to concerns of asset price bubbles and housing affordability. The policy of home purchase restrictions (HPR) has been one of China’s harshest housing market interventions to squeeze out speculative demand and dampen the soaring home prices. Beijing was the first city to implement the HPR. Employing the regression discontinuity design technique, we find that Beijing’s HPR policy triggered a 17–24 % decrease in resale price, a drop in the price-to-rent ratio of about a quarter of its mean value, and a deep (1/2 to 3/4) reduction in the transaction volume of the for-sale market, with no significant change in the rent or the transaction volume of rental units. In submarkets where housing supply was less elastic, the effects of the HPR were larger in price and smaller in quantity, suggesting that wealthy buyers likely benefited more from the HPR. The scope of the analysis does not allow conclusions regarding the persistence or longevity of these effects.

China urbanization is associated with both increases in per capita income and greenhouse gas emissions. This article uses micro data to rank 74 major Chinese cities with respect to their household carbon footprint. We find that the ‘greenest’ cities based on this criterion are Huaian and Suqian while the ‘dirtiest’ cities are Daqing and Mudanjiang. Even in the dirtiest city (Daqing), a standardized household produces only one-fifth of the emissions produced in America’s greenest city (San Diego). We find that the average January temperature is strongly negatively correlated with a city’s household carbon footprint, which suggests that current regional economic development policies that bolster the growth of China’s northeastern cities are likely to increase residential carbon emissions. We use our city-specific income elasticity estimates to predict the growth of carbon emissions in China’s cities.

Urban traffic is embedded in and fundamentally shaped by the spatial pattern of urban land use, such as city size, density, extent of polycentricity, and the relationship between employment and residential locations. Previous evidence, mainly from European and American cities, suggests that the duration of commute trips increases with city size and the spatial separation between jobs and housing. On the other hand, the influences of density and polycentricity are less clear. Using data from 164 cities in China, this study empirically analyzes the relationship between city average commute duration and multiple dimensions of urban spatial structure. Controlling for economic, demographic, and infrastructure characteristics, we find that commute duration correlates positively with city size and jobs–housing separation but negatively with density and polycentricity. As one of the earliest studies on commute cost in the rapidly urbanizing and motorizing Chinese cities, this study can help Chinese decision makers improve urban economic and environmental efficiency through spatial planning and policy making. Specifically, compact, mixed-use, and polycentric spatial development may ease the burden of commute, and thus substitute for unnecessary infrastructure investment and energy consumption during a period of rapid urban expansion in China.

Climate action at the local level represents an important and unique complement to global and national-level policies. This study provides one of the first systematic analyses of local climate actions in the State of California by comparing cities’ adoption of alternative policies and statistical modeling of local choices of climate actions. The pattern of adopting different climate actions incrementally suggests that cities prefer certain actions than others. Coastal location, instead of the usual predictors of local mitigation actions, is found to affect cities’ adaptation actions. Whether a city is more likely to keep its commitment to mitigate climate change depends on the nature of the commitment.