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

Nicolas Debarsy and Julie Le Gallo

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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: Causal inference; Interference; Spatial interactions; Spatial spillovers; Structural and reduced-form identification (search for similar items in EconPapers)
Date: 2025-12
Note: View the original document on HAL open archive server: https://hal.science/hal-05107904v1
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Published in Journal of Economic Surveys, 2025, 39 (5), pp.2152-2173. ⟨10.1111/joes.12692⟩

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Related works:
Journal Article: Identification of Spatial Spillovers: Do's and Don'ts (2025)
Working Paper: Identification of spatial spillovers: Do’s and don'ts (2024)
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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05107904

DOI: 10.1111/joes.12692

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