Countering Urban Segregation in Brazilian Cities: Policy-Oriented Explorations Using Agent-Based Simulation

Feitosa, Flávia da Fonseca; Le, Quang Bao; Vlek, Paul L. G.; Monteiro, AntÃ ́nio Miguel V; Rosemback, Roberta

doi:10.1068/b38117

Cited by 12 publications

(7 citation statements)

References 7 publications

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“…In contrast to traditional tools, such as equation-based modelling with a set of dynamic equations, or aggregate-level modelling such as system dynamics models, ABM re-creates and predicts the appearance of complex phenomena. Contemporary ABMs capture social constructs such as institutions and norms (Mercuur et al, 2019), and find use in policy exploration (Feitosa et al, 2012). Vinogradov et al (2020) adopt ABM to study Airbnb in Norway.…”

Section: Agent-based Modellingmentioning

confidence: 99%

Agent-based simulation of short-term peer-to-peer rentals: Evidence from the Amsterdam housing market

Overwater

Yorke-Smith

2021

Environment and Planning B: Urban Analytics and City Science

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Gentrification, displacement and social exclusion are hot topics of debate in the city of Amsterdam, the Netherlands. A current phenomena is short-term rentals of private homes. In its peer-to-peer form, this phenomena has grown sharply, facilitated by services such as Airbnb. Its growth has caused controversies among communities in touristic areas of Amsterdam, since it contributes to a changed social fabric, increased housing prices and overall gentrification. In the Netherlands and elsewhere, municipal and national policy makers are interested to regulate short-term rentals. In order to provide insights into qualitative policy effects, we develop a micro-level agent-based simulation. Our spatial model simulates residential migration based on income and house pricing. The underlying economic theory is that of Smith’s rent-gap hypothesis. Our model is among the first agent-based approaches investigating this type of rental market, and the first to model a specific housing market, including social housing, in a geographically accurate way. Simulation analysis shows that the touristic rental market has caused considerable changes in housing prices and population development. We find that more lower income citizens remain in the city centre when regulation of the market is stronger, and that banning the touristic market restrains the overall increase in house prices, compared to the business-as-usual scenario. However, the feasibility of enforcement of regulation, and its libertarian consequences, must be considered.

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Section: Agent-based Modellingmentioning

confidence: 99%

Agent-based simulation of short-term peer-to-peer rentals: Evidence from the Amsterdam housing market

Overwater

Yorke-Smith

2021

Environment and Planning B: Urban Analytics and City Science

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“…Models are instruments for learning from and intervening in the world [44]. This study conceives them as suitable virtual laboratories [37] for investigating the effect of theoretically driven interventions [21,22,37] within highly validated model parameters. This modeling approach recovers the idea of neighborhood mobility as a stem concept for analyzing ERS dynamics, accounting empirically for both its behavioral-structural properties and its dynamic aspects.…”

Section: The Micro-macro-link On Ers Dynamicsmentioning

confidence: 99%

Groups' contribution to shaping ethnic residential segregation: a dynamic approach

Tapia

2021

J Comput Soc Sc

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Some have argued it is possible to infer different groups’ contributions to ethnic residential segregation from their individual neighborhood preferences. From this perspective, natives tend to be more segregation-promoting than non-natives, since they prefer neighborhoods where they are the majority. It remains unclear, however, whether this holds when one evaluates their contributions to segregation within a dynamic perspective. Using register data from Statistics Sweden, I define and model ten different groups’ residential behavior based on their ethnicity and family composition. I thereby simulate the residential mobility of the full population of Stockholm municipality residents from 1998 to 2012. Even though my results at the micro-level are consistent with previous studies, the simulation results show that foreign singles’ mobility patterns are more segregation-promoting than any other groups, since this group shows a greater in-group feedback effect regarding choice of new neighborhoods, an effect that increases their flow from low-to-high segregated neighborhoods progressively. My results suggest that (1) integration initiatives would be more efficient if focused on this particular group and (2) a proper evaluation of micro-behaviors’ implications for macro-patterns of segregation requires a dynamic approach accounting for groups’ heterogeneous behaviors and their main interdependencies on shaping segregation over time.

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“…Such dissimilarities may or may not present spatial patterns. If they do, the geographical system may be said to exhibit spatial segregation, especially if the variables considered correspond to the relative proportions of different population groups (Brown and Chung, 2006;Caridi et al, 2017;Cortese et al, 1976;Cottrell et al, 2017;Cowgill and Cowgill, 1951;Duncan and Duncan, 1955;Farley and Taeuber, 1968;Feitosa et al, 2007Feitosa et al, , 2012Fossett, 2017;James and Taeuber, 1985;Massey and Denton, 1988;Reardon and Firebaugh, 2002;Schwartz and Winship, 1980;White, 1983).…”

Section: From Bespoke Neighbourhoods To Trajectoriesmentioning

confidence: 99%

From urban segregation to spatial structure detection

Randon‐Furling

Olteanu

Lucquiaud

2018

Environment and Planning B: Urban Analytics and City Science

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We develop a "multifocal" approach to reveal spatial dissimilarities in cities, from the most local scale to the metropolitan one. Think for instance of a statistical variable that may be measured at different scales, eg ethnic group proportions, social housing rate, income distribution, or public transportation network density. Then, to any point in the city there corresponds a sequence of values for the variable, as one zooms out around the starting point, all the way up to the whole city -as if with a varifocal camera lens. The sequences thus produced encode in a precise manner spatial dissimilarities: how much they differ from perfectly random sequences is indeed a signature of the underlying spatial structure. We introduce here a mathematical framework that allows to analyze this signature and we provide a number of illustrative examples.

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Countering Urban Segregation in Brazilian Cities: Policy-Oriented Explorations Using Agent-Based Simulation

Cited by 12 publications

References 7 publications

Agent-based simulation of short-term peer-to-peer rentals: Evidence from the Amsterdam housing market

Agent-based simulation of short-term peer-to-peer rentals: Evidence from the Amsterdam housing market

Groups' contribution to shaping ethnic residential segregation: a dynamic approach

From urban segregation to spatial structure detection

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