"Nowcasting" house prices at high spatiotemporal resolution

Authors: Daniel Arribas-Bel*,
Topics: Urban Geography, Geographic Information Science and Systems, Spatial Analysis & Modeling
Keywords: streamed data, housing, urban dynamics
Session Type: Paper
Day: 4/12/2018
Start / End Time: 1:20 PM / 3:00 PM
Room: Bayside A, Sheraton, 4th Floor
Presentation File: No File Uploaded

A balanced housing market is a central component of a well-functioning economy and has direct connections to socio-economic urban disparities, spanning from poverty to employment access to education and health outcomes. Furthermore, a measurement of the housing market that is detailed in space and time can enable the understanding of socio-economic processes at the heart of disciplines such as Economics, Political Science, Sociology, Geography, or Planning. The main source of evidence on the housing market are house price indices, which are summary measures that track the evolution of the market. This paper proposes a new approach to building housing indices at high spatiotemporal resolution that can be updated as new streamed data are fed into the model. The resulting index provides a unique window to look into a host of urban phenomena, from neighborhood decline, to gentrification, to early warning systems of neighborhood change. The presentation will cover the basics of the index and will illustrate its main principles using UK data on property transactions.

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