A latent class model of residential choice behaviour and ethnic segregation preferences

Ibraimovic, Tatjana; Hess, Stephane

doi:10.1080/02673037.2017.1373749

Cited by 13 publications

(6 citation statements)

References 44 publications

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“…Similarly, using descriptions of dierent types of neighbourhood businesses in the choice experiment might not be the best way to measure people's response to the social and ethnic composition of housing alternatives' surroundings. At the same time, alternative measures such as the information about the share of migrant populations (e.g., Ibraimovic and Hess, 2018) might induce social desirability bias. Likewise, people usually do not judge neighbourhoods by means of such statistical information but rather based on daily experiences with people and the infrastructure they encounter in the local context.…”

Section: Discussionmentioning

confidence: 99%

“…With the former, however, it is not possible to fully disentangle people's preferences from unobserved characteristics, tastes, opportunities, and limitations that are associated both with their observed choice and the predictors used in the model. Meanwhile, only few studies have tried to study residential preferences directly by means of survey experiments (e.g., Bruch and Mare, 2006;Ibraimovic and Hess, 2018). This is surprising given that these methods bear the advantage of causally revealing the factors that shape the formation of people's preferences (Train, 2009).…”

Section: Introductionmentioning

confidence: 99%

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Choosing the right place? An experimental examination of ethnic preferences in housing decisions

Zangger¹

2019

Preprint

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Residential preferences are often treated as exogenous causes of social and ethnic segregation. In this paper, this assumption is challenged. Instead, this contribution proposes and evaluates how residential preferences are shaped by the conditions of one's neighbourhood. This approach acknowledges the mutual dependence of experienced neighbourhood and housing conditions, residential preferences, and segregation patterns. Doing so, an alternative explanation for the often documented ethnic preferences in housing decisions is elaborated and tested by applying multilevel generalized linear latent and mixed logit models to unique, geocoded data from a choice experiment. Results indicate that people differ in their evaluation of the social and ethnic composition of housing alternatives' residential surroundings. Moreover, these heterogeneous evaluations are largely independent of respondents' own ethnic background. Instead, the observed taste heterogeneity varies over respondents' bespoke neighbourhoods. However, the evaluation of the social and ethnic composition of the housing alternatives does not vary over larger administrative neighbourhoods. This result highlights the importance of proximate, small-scale geographic processes in shaping people's residential preferences.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Choosing the right place? An experimental examination of ethnic preferences in housing decisions

Zangger¹

2019

Preprint

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“…For example, the study of Guo and Bhat (2007), in the USA, found that families would rather reside in areas with a high proportion of other families with similar household structure and size as their own. Relatedly, it is well established that new immigrants tend to gravitate towards established migrant groups from a similar ethnic background (Ibraimovic and Hess, 2018; Moallemi and Melser, 2020).…”

Section: Datamentioning

confidence: 99%

Examining the spatial and non-spatial linkages between suburban housing markets

Moallemi

Melser

Silva

et al. 2021

IJHMA

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Purpose The purpose of this paper is on developing and implementing a model which provides a fuller and more comprehensive reflection of the interaction of house prices at the suburb level. Design/methodology/approach The authors examine how changes in housing prices evolve across space within the suburban context. In doing so, the authors developed a model which allows for suburbs to be connected both because of their geographic proximity but also by non-spatial factors, such as similarities in socioeconomic or demographic characteristics. This approach is applied to modelling home price dynamics in Melbourne, Australia, from 2007 to 2018. Findings The authors found that including both spatial and non-spatial linkages between suburbs provides a better representation of the data. It also provides new insights into the way spatial shocks are transmitted around the city and how suburban housing markets are clustered. Originality/value The authors have generalized the widely used SAR model and advocated building a spatial weights matrix that allows for both geographic and socioeconomic linkages between suburbs within the HOSAR framework. As the authors outlined, such a model can be easily estimated using maximum likelihood. The benefits of such a model are that it yields an improved fit to the data and more accurate spatial spill-over estimates.

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“…Latent class models have been used to account for heterogeneity in residential location choice (Ettema, 2010;Glumac et al, 2014;Ibraimovic and Hess, 2017;Liao et al, 2014;Lu et al, 2014;Smith and Olaru, 2013;Tu et al, 2016;Walker and Li, 2007), allowing for a better characterization of behavior. Latent class models applied to the problem of location choice for residential supply are not reported in the literature, to the extent of our knowledge.…”

Section: Housing Submarkets and Location Choice Modelsmentioning

confidence: 99%

Subdividing the sprawl: Endogenous segmentation of housing submarkets in expansion areas of Santiago, Chile

Cox

Hurtubia

2020

Environment and Planning B: Urban Analytics and City Science

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Urban sprawl is a phenomenon observed in most cities around the globe and especially in Latin America, where it is associated to socioeconomic segregation. In the case of Chile, sprawl has been generally based on large real estate projects. Developers target their projects to different types of consumers, which translates into submarkets with a broad range of housing-unit’s characteristics, but also different location strategies. This heterogeneity has been analyzed and measured in the literature, but quantitative studies have used exogenous or sequential methods to identify submarkets, leading to potential bias in the segmentation. In this paper, we propose an econometric model to measure location drivers for different types of real estate projects that fills this gap. The modeling framework is based on discrete-choice and latent-class models, allowing us to simultaneously identify market segmentations, and their particular location choice preferences, without the need of arbitrary or ex-ante definitions of submarkets. The model is applied to the city of Santiago, Chile. The results reveal two clearly different approaches taken by developers to produce housing, with one submarket of “exclusive” and more sprawling projects, and another submarket of “massive” and more density driven projects. Location strategies are very different between submarkets, reproducing the socio-spatial segregation already observed in the consolidated city.

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A latent class model of residential choice behaviour and ethnic segregation preferences

Cited by 13 publications

References 44 publications

Choosing the right place? An experimental examination of ethnic preferences in housing decisions

Choosing the right place? An experimental examination of ethnic preferences in housing decisions

Examining the spatial and non-spatial linkages between suburban housing markets

Subdividing the sprawl: Endogenous segmentation of housing submarkets in expansion areas of Santiago, Chile

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