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

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  • Nicolas Debarsy

    (LEM - Lille économie management - UMR 9221 - UA - Université d'Artois - UCL - Université catholique de Lille - ULCO - Université du Littoral Côte d'Opale - 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)

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.

Suggested Citation

  • Nicolas Debarsy & Julie Le Gallo, 2025. "Identification of Spatial Spillovers: Do's and Don'ts," Post-Print hal-05107904, HAL.
    • Handle: RePEc:hal:journl:hal-05107904
    DOI: 10.1111/joes.12692
    Note: View the original document on HAL open archive server: https://hal.science/hal-05107904v1
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