Modelling green knowledge production and environmental policies with semiparametric panel data regression models

Antonio Musolesi (), Davide Golinelli and Massimiliano Mazzanti
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Antonio Musolesi: University of Ferrara and SEEDS
Davide Golinelli: University of Ferrara and SEEDS
Massimiliano Mazzanti: University of Ferrara and SEEDS

Empirical Economics, 2025, vol. 68, issue 1, No 9, 327-352

Abstract: Abstract This paper introduces a novel semiparametric econometric framework for policy evaluation and estimates a green knowledge production function for a large, 30-year panel dataset of high-income countries. Due to the substantial uncertainty in the data-generating process and the potential presence of nonlinearities and latent common factors, the paper explores semiparametric panel specifications that go beyond interactive fixed effects fully parametric models. The findings suggest that (i) the semiparametric additive specification with individual time trends is the preferred model, (ii) threshold effects and nonlinearities are salient features of the data that parametric specifications fail to capture, and (iii) the impact of environmental policy is noteworthy and exhibits clear heterogeneity when modelled as a nonparametric function of specific knowledge inputs. The evidence reveals a significant nonlinear policy inducement effect stemming from R&D investments.

Keywords: Green knowledge generation; Environmental policy; Heterogeneous policy effect; Large panels; Interactive Fixed effects; Spline functions; Model selection (search for similar items in EconPapers)
JEL-codes: C14 C23 O3 Q5 (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s00181-024-02634-8

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