Spatial Planning
Urban Modelling
Data Analytics
Digital Cities

WORKING PAPERS

Ling Li and Li Wan (2021)

This paper studies the spatial impact of COVID-19 pandemic through the lens of intra-city population and house rent changes in Beijing, China. Drawing on multiple geospatial data sets, we find that the pandemic has flattened the housing bid-rent curve in Beijing, which corroborates existing literature mainly based on cities in developed countries. Through regression analysis and spatial equilibrium modelling, we identify key mechanisms of the flattened bid-rent curve and the accompanying decentralisation of residents. First, workplace population change, particularly in central Beijing, seems to be the main factor contributing to the resident population and house rent changes. Second, we find no significant evidence on the spatial impact from remote working, as the share of remote working in Beijing appears low after about one year recovery. This finding contrasts to existing studies where remote working has been perceived as the main driver for urban spatial structure change in a developed country context. Third, through a novel method for quantifying locational preference changes, it is found that the observed decentralisation trend in Beijing, ceteris paribus, may also be associated with increased (decreased) preference for living in suburban (central) locations. However, the preference change for central locations is marginal, hence providing an early rebuttal of the ‘demise of centres’ proposition.

Li Wan, Tianyuan Wang, and Helen X. H. Bao (2021)

The rapid urbanisation in Chinese cities features a distinctive land finance model, where land market, local economy, government revenue, and urban development are intertwined. Quantifying the interdependence between land market and other parts of the social, economic, and political systems has been a challenging undertaking, and the task is further complicated by the great cross-city heterogeneity in natural endowment and local socio-economic conditions. Few existing studies succeeded in capturing both the complexity of the system and the nuance of cross-city variations at the same time. We propose a novel structural equation modelling (SEM) method, integrated with the latent class analysis (LCA), to address this challenge. The LCA is used to identify distinct city groups based on two purposely constructed land-use efficiency measurements. The categorical latent classes of cities are then incorporated in a series of structural equation models, capturing the non-linear heterogeneity across cities. Based on data for 272 prefecture-level Chinese cities between 2012 and 2017, we found quantified evidence on both the direct channel (i.e., one-off revenue from land conveyance fee) and indirect channel (e.g., sustainable tax revenue from the business and employment growth enabled by land development) through which land supply drives urban development. The study also quantifies the significant gap among Chinese cities in terms of land-use efficiency. Our findings highlight the importance of developing and implementing reliable land-use efficiency measurements, the need to shift policy focus from one-off income to long-term sustainable revenue, and the potential of lower-tier cities in the next stage of urbanisation in China.

Jerry Chen and Li Wan (2022)

Mental health in the UK had deteriorated compared with pre-pandemic trends. The impact of COVID-19 on the subjective wellbeing of working populations with distinct lifestyles is not yet studied. Methods: Combining time use surveys collected pre- and during COVID-19, latent class analysis was used to identify distinct lifestyles based on aggregated daily activity patterns and reported working modes. We provide qualitative pen portraits alongside pre-versus-during pandemic comparisons of intraday time use and wellbeing patterns. Lifestyle heterogeneity in wellbeing was quantified in relation to aggregated activity types. Results: COVID-19 impact on wellbeing varied significantly between usual working hours (6am-6pm) and rest of the day. The decline in wellbeing outside of usual working hours was significant and consistent across lifestyles. During usual working hours, the direction of impact varied in line with working modes: wellbeing of homeworkers decreased, remained relatively stable for commuters, and increased for certain hybrid workers. Magnitude of impact correlates strongly with lifestyle: those working long and dispersed hours are more sensitive, whereas non-work dominated lifestyles are more resilient. Conclusion: The direction and magnitude of impact from COVID-19 were not uniformly manifested across activity types, time of day, and latent lifestyles. Blurring work-life boundaries and general anxiety about the pandemic may be key determinants of the decline outside of usual working hours. During usual working hours, strong yet complex correlations between wellbeing and time-use changes suggested that policies aiming to enhance wellbeing of workers need to consider not only spatial flexibility but also provide wider support for temporal flexibility.