Investigating the impact of water, energy, and greenhouse gas uncertainty on investment returns: Application of fuzzy regression (Iran case study)

Articles in Press

Document Type : Original Article

Authors

1 Assistant Professor, Economics Department, Faculty of Economics and Management, University of Sistan and Baluchestan, Sistan and Baluchestan, Iran.

2 Ph.D of Econometrics, Faculty of Economics. Allameh Tabatabai University, Tehran, Iran

3 Faculty Member of Economics, Allameh Tabataba'i University, Tehran, Iran

Abstract

This study employs a fuzzy logic-based approach to estimate the impact of uncertainty in key sustainability-related sectors—namely water, energy, waste, greenhouse gas (GHG) emissions, and debt-to-capital ratio—on return on investment (ROI) over the period from 1993 to 2024. Given the inherently imprecise and dynamic nature of environmental and financial variables, fuzzy logic provides a robust framework to model vagueness and ambiguity in data. The analysis integrates longitudinal data across global markets, incorporating fuzzy sets to represent uncertain input variables and their nonlinear relationships with ROI. Results indicate that increased uncertainty in water and energy usage, as well as higher GHG emissions and waste production, negatively influence ROI, particularly when coupled with elevated debt-to-capital ratios. However, the application of sustainable practices that reduce these uncertainties can lead to more stable and higher investment returns. The findings offer strategic insights for investors and policymakers aiming to balance economic performance with environmental and financial risks. They also highlight the importance of investments needed to meet regulatory requirements, which are the main drivers for organizations at the financial level.

Highlights

  • Defines environmental and financial uncertainty as the lack of complete knowledge regarding the probability distributions of future outcomes; it further highlights how the compounded effect of these uncertainties, along with their temporal evolution, critically shapes long-term investment returns.
  • Demonstrates the advantage of fuzzy logic in capturing vagueness and expert knowledge, compared to traditional deterministic investment models.
  • Informs investors and policymakers on how multi‑sectoral uncertainties—when quantified and modeled robustly—can guide strategic decisions for sustainable and resilient investment planning.

Keywords

References

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International Journal of New Political Economy

Articles in Press, Accepted Manuscript
Available Online from 09 June 2026

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History

  • Receive Date: 30 January 2026
  • Revise Date: 02 June 2026
  • Accept Date: 09 June 2026
  • First Publish Date: 09 June 2026
  • Publish Date: 09 June 2026

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