Nonparametric estimation of R&D international spillovers

Georgios Gioldasis, Antonio Musolesi and Michel Simioni ()
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Georgios Gioldasis: Department of Economics and Management - UniFE - Università degli Studi di Ferrara = University of Ferrara
Antonio Musolesi: Department of Economics and Management - UniFE - Università degli Studi di Ferrara = University of Ferrara
Michel Simioni: UMR MOISA - Marchés, Organisations, Institutions et Stratégies d'Acteurs - Cirad - Centre de Coopération Internationale en Recherche Agronomique pour le Développement - INRA - Institut National de la Recherche Agronomique - Montpellier SupAgro - Centre international d'études supérieures en sciences agronomiques - CIHEAM-IAMM - Centre International de Hautes Etudes Agronomiques Méditerranéennes - Institut Agronomique Méditerranéen de Montpellier - CIHEAM - Centre International de Hautes Études Agronomiques Méditerranéennes - Montpellier SupAgro - Institut national d’études supérieures agronomiques de Montpellier

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Abstract: We revisit the issue of international technology diffusion within the framework of large panels with strong cross-sectional dependence by adopting a method which extends the Common Correlated Effects (CCE) approach to nonparametric specifications. Our results indicate that the adoption of a nonparametric approach provides significant benefits in terms of predictive ability. This work also refines previous results by showing threshold effects, nonlinearities and interactions, which are obscured in parametric specifications and which have relevant policy implications.

Keywords: cross-sectional dependence; nonparametric regression; spline functions; large panels; factor models; international technology diffusion (search for similar items in EconPapers)
Date: 2019-06-17
New Economics Papers: this item is included in nep-eff
Note: View the original document on HAL open archive server: https://hal.inrae.fr/hal-02789474v1
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Published in 12. Vietnam Economist Annual Meeting (VEAM 2019), Jun 2019, Dalat, Vietnam. 15 p

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