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Green innovations and patents in OECD countries

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Green innovations and patents in OECD countries. / Heshmati, Almas; Tsionas, Mike.
In: Journal of Cleaner Production, Vol. 418, 138092, 15.09.2023.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Heshmati, A & Tsionas, M 2023, 'Green innovations and patents in OECD countries', Journal of Cleaner Production, vol. 418, 138092. https://doi.org/10.1016/j.jclepro.2023.138092

APA

Heshmati, A., & Tsionas, M. (2023). Green innovations and patents in OECD countries. Journal of Cleaner Production, 418, Article 138092. https://doi.org/10.1016/j.jclepro.2023.138092

Vancouver

Heshmati A, Tsionas M. Green innovations and patents in OECD countries. Journal of Cleaner Production. 2023 Sept 15;418:138092. Epub 2023 Jul 26. doi: 10.1016/j.jclepro.2023.138092

Author

Heshmati, Almas ; Tsionas, Mike. / Green innovations and patents in OECD countries. In: Journal of Cleaner Production. 2023 ; Vol. 418.

Bibtex

@article{73ece9027bf840adb8c251488011401c,
title = "Green innovations and patents in OECD countries",
abstract = "Green transition is important for the economics of the OECD countries and their transition to cleaner production. This paper estimates a knowledge production function consisting of a system of innovation inputs, innovation outputs, and productivity with feedback effect from productivity on innovation investments. The model accounts for productivity shock, endogeneity of inputs, and their simultaneity and interdependence. Productivity shock is a latent unobserved component that is specified in terms of observable factors. The model is estimated using Bayesian methods organized around Marco Chain Sequential Monte Carlo iteration techniques also known as Particle Filtering. For the empirical part, the paper uses balanced panel data covering 27 OECD countries' green innovation and patents activities observed during the period 1990–2018. Our empirical results show evidence of significant heterogeneity in productivity and its relationship with its identified determinants. The paper also discusses the implications of these results for OECD countries{\textquoteright} green growth strategies.",
keywords = "Industrial and Manufacturing Engineering, Strategy and Management, General Environmental Science, Renewable Energy, Sustainability and the Environment, Building and Construction",
author = "Almas Heshmati and Mike Tsionas",
year = "2023",
month = sep,
day = "15",
doi = "10.1016/j.jclepro.2023.138092",
language = "English",
volume = "418",
journal = "Journal of Cleaner Production",
issn = "0959-6526",
publisher = "Elsevier Ltd",

}

RIS

TY - JOUR

T1 - Green innovations and patents in OECD countries

AU - Heshmati, Almas

AU - Tsionas, Mike

PY - 2023/9/15

Y1 - 2023/9/15

N2 - Green transition is important for the economics of the OECD countries and their transition to cleaner production. This paper estimates a knowledge production function consisting of a system of innovation inputs, innovation outputs, and productivity with feedback effect from productivity on innovation investments. The model accounts for productivity shock, endogeneity of inputs, and their simultaneity and interdependence. Productivity shock is a latent unobserved component that is specified in terms of observable factors. The model is estimated using Bayesian methods organized around Marco Chain Sequential Monte Carlo iteration techniques also known as Particle Filtering. For the empirical part, the paper uses balanced panel data covering 27 OECD countries' green innovation and patents activities observed during the period 1990–2018. Our empirical results show evidence of significant heterogeneity in productivity and its relationship with its identified determinants. The paper also discusses the implications of these results for OECD countries’ green growth strategies.

AB - Green transition is important for the economics of the OECD countries and their transition to cleaner production. This paper estimates a knowledge production function consisting of a system of innovation inputs, innovation outputs, and productivity with feedback effect from productivity on innovation investments. The model accounts for productivity shock, endogeneity of inputs, and their simultaneity and interdependence. Productivity shock is a latent unobserved component that is specified in terms of observable factors. The model is estimated using Bayesian methods organized around Marco Chain Sequential Monte Carlo iteration techniques also known as Particle Filtering. For the empirical part, the paper uses balanced panel data covering 27 OECD countries' green innovation and patents activities observed during the period 1990–2018. Our empirical results show evidence of significant heterogeneity in productivity and its relationship with its identified determinants. The paper also discusses the implications of these results for OECD countries’ green growth strategies.

KW - Industrial and Manufacturing Engineering

KW - Strategy and Management

KW - General Environmental Science

KW - Renewable Energy, Sustainability and the Environment

KW - Building and Construction

U2 - 10.1016/j.jclepro.2023.138092

DO - 10.1016/j.jclepro.2023.138092

M3 - Journal article

VL - 418

JO - Journal of Cleaner Production

JF - Journal of Cleaner Production

SN - 0959-6526

M1 - 138092

ER -