Nonparametric estimation of international R&D spillovers

Georgios Gioldasis (), Antonio Musolesi () and Michel Simioni ()
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Georgios Gioldasis: University of Ferrara
Antonio Musolesi: University of Ferrara
Michel Simioni: Institut National de la Recherche Agronomique (INRA)

No 318, SEEDS Working Papers from SEEDS, Sustainability Environmental Economics and Dynamics Studies

Abstract: In a recent paper, Ertur and Musolesi (Journal of Applied Econometrics 2017; 32: 477-503) employ the Common Correlated Effects (CCE) approach to address the issue of strong cross-sectional dependence while studying international technology diffusion. We carefully revisit this issue by adopting Su and Jin's (Journal of Econometrics 2012; 169: 34-47) method, which extends the 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.

Pages: 15pages
Date: 2018-03, Revised 2018-03
New Economics Papers: this item is included in nep-ecm and nep-eff
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http://www.sustainability-seeds.org/papers/RePec/srt/wpaper/0318.pdf First version, 2018 (application/pdf)
http://www.sustainability-seeds.org/papers/RePec/srt/wpaper/0318.pdf Revised version, 2018 (application/pdf)

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