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Making a place for space: Using spatial econometrics to model neighborhood effects


Zangger, Christoph (2019). Making a place for space: Using spatial econometrics to model neighborhood effects. Journal of Urban Affairs:1-26.

Abstract

Researchers interested in neighborhood effects face many methodological challenges, including, among others, the unobserved selection into neighborhoods that might be associated with the outcome under study, the identification of endogenous effects, or the dependence of results on a neighborhood’s spatial scale. However, another issue has received little attention. Though theoretical explanations commonly stress the interdependence of individual actions in neighborhoods and the spatial diffusion processes between neighbors, the quantitative methods used to evaluate these approaches usually do not directly model such spillover and multiplier effects from one observation to another. Instead, they control for the resulting spatial correlation; for example, by means of multilevel models. Using spatial weights matrices that reflect the extent to which individual neighbors mutually influence each other, this article demonstrates how spatial econometrics are a means for the simultaneous modeling of different mechanisms of neighborhood effects. It further demonstrates how spatial Durbin models reproduce results from multilevel and instrumental variable models without the need to rely on aggregated characteristics of predefined neighborhoods.

Abstract

Researchers interested in neighborhood effects face many methodological challenges, including, among others, the unobserved selection into neighborhoods that might be associated with the outcome under study, the identification of endogenous effects, or the dependence of results on a neighborhood’s spatial scale. However, another issue has received little attention. Though theoretical explanations commonly stress the interdependence of individual actions in neighborhoods and the spatial diffusion processes between neighbors, the quantitative methods used to evaluate these approaches usually do not directly model such spillover and multiplier effects from one observation to another. Instead, they control for the resulting spatial correlation; for example, by means of multilevel models. Using spatial weights matrices that reflect the extent to which individual neighbors mutually influence each other, this article demonstrates how spatial econometrics are a means for the simultaneous modeling of different mechanisms of neighborhood effects. It further demonstrates how spatial Durbin models reproduce results from multilevel and instrumental variable models without the need to rely on aggregated characteristics of predefined neighborhoods.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:06 Faculty of Arts > Institute of Sociology
Dewey Decimal Classification:300 Social sciences, sociology & anthropology
Scopus Subject Areas:Social Sciences & Humanities > Sociology and Political Science
Social Sciences & Humanities > Urban Studies
Uncontrolled Keywords:Sociology and Political Science, Urban Studies
Language:English
Date:17 May 2019
Deposited On:11 Nov 2019 08:00
Last Modified:29 Jul 2020 11:28
Publisher:Wiley-Blackwell Publishing, Inc.
ISSN:0735-2166
OA Status:Closed
Publisher DOI:https://doi.org/10.1080/07352166.2019.1584530
Official URL:https://doi.org/10.1080/07352166.2019.1584530

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