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作者

来源

JOURNAL OF URBAN AFFAIRS,Vol.41,Issue8,P.1055-1080

语言

英文

关键字

作者单位

University of Zurich

摘要

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.AcknowledgmentsI thank the editor, the anonymous reviewers, and Sandra Gilgen for their helpful comments and suggestions.Disclosure statementNo potential conflict of interest was reported by the author.Supplementary materialSupplemental data for this article can be accessed here.Additional informationNotes on contributorsChristoph ZanggerChristoph Zangger is a postdoctoral researcher at the Institute of Sociology at the University of Zurich, Switzerland. His research is concerned with the statistical modeling of contextual and compositional effects in various settings such as neighborhoods and schools. He received his PhD from the University of Bern, from which he also received a master’s degree in mathematical statistics.