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.
Nonparametric estimation of international R&D spillovers
Antonio Musolesi
Secondo
;
2018
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.| File | Dimensione | Formato | |
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