Aldieri L., Brahmi M., Cheng X., Vinci C.P. (2021). Knowledge spillovers and technical efficiency for cleaner production: an economic analysis from agriculture innovation. Journal of Cleaner Production, 20/10/2021, vol. 320, p. 1-7.
https://doi.org/10.1016/j.jclepro.2021.128830
https://doi.org/10.1016/j.jclepro.2021.128830
Titre : | Knowledge spillovers and technical efficiency for cleaner production: an economic analysis from agriculture innovation (2021) |
Auteurs : | L. Aldieri ; M. Brahmi ; X. Cheng ; C.P. Vinci |
Type de document : | Article |
Dans : | Journal of Cleaner Production (vol. 320, October 2021) |
Article en page(s) : | p. 1-7 |
Langues : | Anglais |
Langues du résumé : | Anglais |
Catégories : |
Catégories principales 06 - AGRICULTURE. FORÊTS. PÊCHES ; 6.4 - Production Agricole. Système de ProductionThésaurus IAMM SYSTEME DE PRODUCTION ; AGRICULTURE ; INNOVATION ; EFFICACITE ; CHANGEMENT CLIMATIQUE ; EUROPE ; ETATS UNIS |
Résumé : | The objective of the analysis is to investigate the production efficiency in the USA and Europe through the channel of knowledge spillovers from technological innovation in the agricultural sector. Since the empirical evidence concerning the climate change effects on the production efficiency is yet weak, the paper further contributes to the literature attempting to bridge this gap. To this end, the non-parametric Data Envelopment Analysis (DEA) empirical methodology and Tobit regression are developed on the basis of a sector-based panel data set over the time period of 2002-2017. In particular, the empirical results evidenced a negative effect of land use spillovers on efficiency indicator for American firms and a positive effect for European ones. The study findings are innovative and invaluable to generate policy implications for the investigated country governments particularly in terms of developing industrial strategy instruments in the agricultural field: Government is supposed to establish the special funds to encourage the firms to expand innovation activities in their own production process and the investment of R&D is expected to increase, which can further improve the productivity and reduce the reliability of knowledge spillovers. Finally, it is important that the results are scalable, and the model could be extended also to developing countries. |
Cote : | Réservé lecteur CIHEAM |
URL / DOI : | https://doi.org/10.1016/j.jclepro.2021.128830 |