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Nonparametric estimation of international R&D spillovers

Author

Listed:
  • Georgios Gioldasis

    () (University of Ferrara)

  • Antonio Musolesi

    () (University of Ferrara)

  • Michel Simioni

    () (Institut National de la Recherche Agronomique (INRA))

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.

Suggested Citation

  • Georgios Gioldasis & Antonio Musolesi & Michel Simioni, 2018. "Nonparametric estimation of international R&D spillovers," SEEDS Working Papers 0318, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised Mar 2018.
  • Handle: RePEc:srt:wpaper:0318
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    File URL: http://www.sustainability-seeds.org/papers/RePec/srt/wpaper/0318.pdf
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    References listed on IDEAS

    as
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