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Interactive R&D spillovers: an estimation strategy based on forecasting-driven model selection

Author

Listed:
  • Georgios Gioldasis

    (UniFE - Università degli Studi di Ferrara = University of Ferrara)

  • Antonio Musolesi

    (UniFE - Università degli Studi di Ferrara = University of Ferrara)

  • Michel Simioni

    (UMR MoISA - Montpellier Interdisciplinary center on Sustainable Agri-food systems (Social and nutritional sciences) - Cirad - Centre de Coopération Internationale en Recherche Agronomique pour le Développement - IRD - Institut de Recherche pour le Développement - CIHEAM-IAMM - Centre International de Hautes Etudes Agronomiques Méditerranéennes - Institut Agronomique Méditerranéen de Montpellier - CIHEAM - Centre International de Hautes Études Agronomiques Méditerranéennes - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - Institut Agro Montpellier - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement)

Abstract

This paper proposes an estimation strategy that exploits recent non-parametric panel data methods that allow for a multifactor error structure and extends a recently proposed datadriven model-selection procedure, which has its roots in cross validation and aims to test whether two competing approximate models are equivalent in terms of their expected true error. We extend this procedure to a large panel data framework by using moving block bootstrap resampling techniques in order to preserve cross-sectional dependence in the bootstrapped samples. Such an estimation strategy is illustrated by revisiting an analysis of international technology diffusion. Model selection procedures clearly conclude in the superiority of a fully non-parametric (non-additive) specification over parametric and even semi-parametric (additive) specifications. This work also refines previous results by showing threshold effects, non-linearities, and interactions that are obscured in parametric specifications and which have relevant implications for policy.

Suggested Citation

  • Georgios Gioldasis & Antonio Musolesi & Michel Simioni, 2023. "Interactive R&D spillovers: an estimation strategy based on forecasting-driven model selection," Post-Print hal-03476599, HAL.
    • Handle: RePEc:hal:journl:hal-03476599
    DOI: 10.1016/j.ijforecast.2021.09.009
    Note: View the original document on HAL open archive server: https://hal.inrae.fr/hal-03476599
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    Citations

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    Cited by:

    1. Musolesi, Antonio & Prete, Giada Andrea & Simioni, Michel, 2022. "Is infrastructure capital really productive? Non-parametric modeling and data-driven model selection in a cross-sectionally dependent panel framework," TSE Working Papers 22-1335, Toulouse School of Economics (TSE).
    2. Antonio Musolesi & Giada Andrea Prete & Michel Simioni, 2022. "Is infrastructure capital really productive? Non-parametric modeling and data-driven model selection in a cross-sectionally dependent panel framework," SEEDS Working Papers 0522, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised Mar 2022.

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