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Interactive R&D Spillovers: An estimation strategy based on forecasting-driven model selection

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  • Georgios Gioldasis

    (Università degli Studi di Ferrara)

  • Antonio Musolesi

    (Università degli Studi di Ferrara)

  • Michel Simioni

    (MOISA, INRA, University of Montpellier, Montpellier, France)

Abstract

This paper reconsiders the international technology diffusion model. Because the high degree of uncertainty surrounding the Data Generating Process and the likely presence of nonlinearities and latent common factors, it considers alternative nonparametric panel specifications which extend the Common Correlated Effects approach and then contrasts the out-of-sample performance of them with those of more common parametric models. To do so, we extend a recently proposed data-driven model choice approach, which takes its roots on cross validation and aims at testing whether two competing approximate models are equivalent in terms of their expected true error, to the case of cross-sectionally dependent panels, by exploiting moving block bootstrap resampling methods and assessing forecasting performances of competing models. Our results indicate that the adoption of a fully nonparametric specification provides better performances. This work also refines previous results by showing threshold effects, nonlinearities and interactions, which are obscured in parametric specifications and which have relevant implications for policy.

Suggested Citation

  • Georgios Gioldasis & Antonio Musolesi & Michel Simioni, 2021. "Interactive R&D Spillovers: An estimation strategy based on forecasting-driven model selection," SEEDS Working Papers 0621, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised Jun 2021.
  • Handle: RePEc:srt:wpaper:0621
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    More about this item

    Keywords

    large panels; cross-sectional dependence; factor models; nonparametric regression; spline functions; approximate model; predictive accuracy; international technology diffusion;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • F0 - International Economics - - General
    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights

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