Initial Results from an Agent-Based Simulation of Housing in Urban Beirut

Conference paper (2018)

Authors

Stefano Picascia Manchester Metropolitan University, University of Siena
Ali Termos American University of Beirut
N. Yorke-Smith Algorithmics - EEMCS
Research Group
Algorithmics (EEMCS) (TU Delft)
Copyright: © 2018 Stefano Picascia, Ali Termos, N. Yorke-Smith
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Published Date

01-07-2018

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Software Technology

Research Group

Algorithmics

Abstract

The motivation for this extended abstract is to develop an agentbased model (ABM) to capture the existence of migrant and refugee flows, and to explore their effects on urban dynamics. We leverage an extant agent-based model founded on the rent-gap theory, as a lens to study the effect of sizeable refugee migration upon a capital city in West Asia. In order to calibrate and validate the simulation model, we construct indices for housing prices and other factors. Results from the model show the impact of migration shock on the housing market, and identify the relative efficacy of housing intervention policies. Our work progresses towards a tool for policy makers asking what-if questions about the urban environment in the context of migration.

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