Modelling the green knowledge production function with large panel data econometrics

Niccolò Murtas ()
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Niccolò Murtas: University of Ferrara

No 725, SEEDS Working Papers from SEEDS, Sustainability Environmental Economics and Dynamics Studies

Abstract: This study estimates an aggregate green knowledge production function (GKPF) for 19 OECD countries from 1981 to 2012, using panel-data econometric methods to address spatial spillovers and unobserved heterogeneity. Both Cobb-Douglas and translog functional forms are evaluated with multiple estimators, including standard fixed and random effects models, pooled and mean group common correlated effects (CCE) estimators, and random-trend models to account for shared upward trends among variables. The regression analysis examines the relationship between green patenting and key determinants such as R&D expenditure, human capital, and environmental policy indicators. The results consistently show a robust positive effect of domestic R&D, whereas the impacts of other factors exhibit greater variability. Methodologically, the findings highlight the sensitivity of coefficient estimates to unobserved heterogeneity and the choice of functional form.

Keywords: Green innovation; knowledge production function; panel data; spatial spillovers (search for similar items in EconPapers)
Pages: 50 pages
Date: 2025-07, Revised 2025-07
New Economics Papers: this item is included in nep-sbm and nep-tid
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http://www.sustainability-seeds.org/papers/RePec/srt/wpaper/0725.pdf Revised version, 2025 (application/pdf)

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