Identification of Spatial Spillovers: Do's and Don'ts

Nicolas Debarsy () and Julie Le Gallo ()
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Nicolas Debarsy: LEM - Lille économie management - UMR 9221 - UA - Université d'Artois - UCL - Université catholique de Lille - Université de Lille - CNRS - Centre National de la Recherche Scientifique
Julie Le Gallo: CESAER - Centre d'économie et de sociologie rurales appliquées à l'agriculture et aux espaces ruraux - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - Institut Agro Dijon - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement

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Abstract: The notion of spatial spillovers has been widely used in applied spatial econometrics. In this paper, we consider how they can be identified in both structural and causal reduced‐form models. First, discussing the various threats to identification in structural models, we point out that the typical estimation framework proposed in the applied spatial econometric literature boils down to considering spatial spillovers as a side‐effect of a data‐driven chosen specification. We also discuss the limits of blindly relying on interaction matrices purely based on geography to identify the source and content of spillovers. Then, we present reduced forms impact evaluation models for spatial data and show that the current spatial versions of usual impact evaluation models are not fully satisfactory when considering the identification issue. Finally, we propose a set of recommendations for applied articles aimed at identifying spatial spillovers.

Keywords: Spatial spillovers; Spatial interactions; Causal inference; Interference; Structural and reduced form identification (search for similar items in EconPapers)
Date: 2025-03-11
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Published in Journal of Economic Surveys, 2025, pp.1-44. ⟨10.1111/joes.12692⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-04992582

DOI: 10.1111/joes.12692

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