Bayesian linear, heteroskedastic, multilevel, and dynamic models for assessing the effects of policy uncertainty, green finance, innovation, and environmental stringency on sustainable economic growth in OECD economies

Authors

• Md Qamruzzaman, United International University
• Abdulrahman Alomair, King Faisal University
• Abdulaziz S. Al Naim, King Faisal University
• Sylvia Kor, Clark University

Document Type

Article

Abstract

This study analyzes how policy uncertainty, green finance, green innovation, and the stringency of environmental policy affect sustainable economic growth in OECD member countries from 1996 to 2023. Given the growing evidence that advanced economies are facing structural lock-ins, a lack of coherent policy credibility, and insufficient financial and innovative capabilities, the current study integrates these factors into a coherent empirical framework that continues to prevent disintegration in the current literature. Using environmentally adjusted multifactor productivity as a proxy for green economic growth, the analysis employs a panel of Bayesian econometric models that include linear, heteroskedastic, multilevel, random-effects, and panel vector autoregressive specifications. The techniques support probabilistic inference, explain cross-country heterogeneity, and learn dynamic mono-dependencies between the variables. Findings continually indicate positive, non-negligible influences of green finance, green innovation, and the stringency of environmental policy on sustainable growth, as well as a large negative effect and higher volatility in growth due to policy uncertainty. These multilevel estimates also reveal substantial cross-country variation, with stronger green financial systems mitigating the negative impact of uncertainty. The support for the examination using Bayesian panel vector autoregressions shows that finance, innovation, and policy stringency Granger-cause advances in sustainable growth. However, uncertainty continues to act as an impediment. The long-run relationships are confirmed through robustness checks using the CS-ARDL, AMG, and CCEMG estimators. These findings emphasize the need for predictable policymaking, expanded green finance, strengthened innovation frameworks, and robust environmental laws to promote long-term growth in developed economies. © The Author(s) 2026.

Publication Title

Discover Sustainability

Publication Date

12-2026

Volume

7

Issue

1

ISSN

2662-9984

DOI

10.1007/s43621-026-03707-7

Keywords

Bayesian econometrics, environmental policy stringency, green finance, green innovation, OECD economies, policy uncertainty, PVAR, sustainable economic growth

Repository Citation

Qamruzzaman, Md; Alomair, Abdulrahman; Al Naim, Abdulaziz S.; and Kor, Sylvia, "Bayesian linear, heteroskedastic, multilevel, and dynamic models for assessing the effects of policy uncertainty, green finance, innovation, and environmental stringency on sustainable economic growth in OECD economies" (2026). Student Publications [Scholarly]. 114.
https://commons.clarku.edu/student_publications/114

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.

Copyright Conditions

Qamruzzaman, M., Alomair, A., Naim, A. S., & Kor, S. (2026). Bayesian linear, heteroskedastic, multilevel, and dynamic models for assessing the efiects of policy uncertainty, green finance, innovation, and environmental stringency on sustainable economic growth in OECD economies. Discover Sustainability.