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Housing Affordability Index×Urban Scaling Laws×
AlanUrban StudiesUrban Studies
AileProcess / pipelineRegression model
Köken yılı20062007
KökenHousing-economics tradition (ratio measures); Michael E. Stone (residual-income approach)Luís Bettencourt & Geoffrey West
TürIndex/ratio comparing housing cost to household incomePower-law regression of urban indicators against population size
Seminal kaynakStone, M. E. (2006). What is housing affordability? The case for the residual income approach. Housing Policy Debate, 17(1), 151–184. DOI ↗Bettencourt, L. M. A., Lobo, J., Helbing, D., Kühnert, C., & West, G. B. (2007). Growth, innovation, scaling, and the pace of life in cities. Proceedings of the National Academy of Sciences, 104(17), 7301–7306. DOI ↗
Diğer adlarMedian Multiple, Housing Cost Burden Ratio, Residual Income Affordability, NAR Housing Affordability IndexUrban Scaling, Settlement Scaling Theory, Power-Law Urban Scaling, Superlinear and Sublinear Urban Scaling
İlişkili44
ÖzetA housing affordability index summarises how the cost of housing in a city or market relates to what households can pay, condensing prices, rents and incomes into a single interpretable number. The simplest forms are ratios — the median house price divided by median income, or housing outlays as a share of income — while the residual-income approach championed by Michael Stone instead asks what is left for everything else after housing is paid. Together these measures let analysts compare affordability across places and over time, flag cost-burdened populations, and track housing stress as markets shift.Urban scaling laws describe how the aggregate properties of cities — wealth, innovation, infrastructure, crime — change systematically with population size, following power laws rather than growing in simple proportion. Building on the 2007 work of Luís Bettencourt, Geoffrey West and colleagues, the framework shows that socioeconomic outputs typically scale superlinearly (a doubling of population more than doubles GDP and patents) while infrastructure scales sublinearly (larger cities need proportionally fewer roads and cables per person), with a single exponent β capturing the regularity across an entire urban system.
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