Abstract
Most cities exhibit a rise in socio-economic heterogeneity and cultural diversity. Is there a common future perspective for a balanced development of liveable cities? Adopted at Habitat III in Quito, the New Urban Agenda envisages future cities as inclusive places for sustainable development. However, if people’s conceptions of liveability are very diverse or even contradictory, the Agenda is nothing more than a pipe dream. At the same time, inequality is on the rise, both globally and locally, and cities are no exceptions to this. In view of this, this study examines to what extent perceptions of city liveability vary across different socio-economic groups. Due to the focus on gender, age and economic status in the Agenda, this study compares individual views on liveability across these three social strata, with a focus on cities in Europe. It also looks at how these cities differentiate themselves to meet the multi-faceted demands of the inhabitants. The empirical part of the study uses multivariate techniques (e.g. Shapley values, multidimensional scaling analysis) to extract information on liveability perceptions in many cities in Europe. Our study provides a unique insight into what domains are most closely related to urban well-being. It also identifies, at the domain level, relevant interventions that could build more liveable and sustainable cities in Europe and elsewhere. Our findings suggest that, relative to other public amenities, improvement in qualities of the natural environment (e.g. air quality, green spaces) can be a key to enhance urban liveability in Europe.
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Notes
- 1.
By robustness, it means that the Shapley values are more stable across different models (e.g. OLS) and model specifications.
- 2.
Based on our data, results from models using log-likelihood tend to distribute Shapley values equally to all independent variables. In a robustness check in which satisfaction is treated as a continuous variable, the obtained Shapley values are close to those using pseudo-R2 of a probit regression estimation.
- 3.
The list is by no means exhaustive. However, as will be explained in the methodology section, Shapley decomposition is a permutation-based analysis which is computationally expensive. This limits the possibilities of expanding the set of attributes.
- 4.
To enumerate, they are (1) ABC vs BC, (2) ACB vs CB, (3) AB vs B, (4) AC vs C, (5) A vs (BC), and (6) A vs (CB). Although the order of the variables does not produce a material difference in the calculation of the R2 in cases (1) and (2), and in cases (5) and (6), Shapley decomposition is a permutation-based method, and we need to take them into consideration in the calculation. We use the Stata Module Shapley2 by Wendelspiess Chávez Juárez (2015) to perform our analysis.
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Wong, PH., Celbiş, M.G., Kourtit, K., Nijkamp, P. (2023). Same Bed, Different Dreams? Socio-Economic Strata and Differences in Liveability Perception in European Cities. In: Fusco Girard, L., Kourtit, K., Nijkamp, P. (eds) The Future of Liveable Cities. Footprints of Regional Science(). Springer, Cham. https://doi.org/10.1007/978-3-031-37466-1_14
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