Economics at your fingertips  

Quantifying Retail Agglomeration using Diverse Spatial Data

Duccio Piovani, Vassilis Zachariadis and Michael Batty

Papers from

Abstract: Newly available data on the spatial distribution of retail activities in cities makes it possible to build models formalized at the level of the single retailer. Current models tackle consumer location choices at an aggregate level and the opportunity new data offers for modeling at the retail unit level lacks a theoretical framework. The model we present here helps to address these issues. It is a particular case of the Cross-Nested Logit model, based on random utility theory built with the idea of quantifying the role of floor space and agglomeration in retail location choice. We test this model on the city of London: the results are consistent with a super linear scaling of a retailer's attractiveness with its floor space, and with an agglomeration effect approximated as the total retail floorspace within a $325m$ radius from each shop.

Date: 2016-12
New Economics Papers: this item is included in nep-dcm, nep-geo, nep-upt and nep-ure
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link) Latest version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Access Statistics for this paper

More papers in Papers from
Bibliographic data for series maintained by arXiv administrators ().

Page updated 2020-07-03
Handle: RePEc:arx:papers:1612.06441