Document Type : Research Paper
Authors
1 Ph. D. in Economics, Faculty of Economics and Administrative Sciences, Ferdowsi Universuty of Mashhad, Mashhad, Iran
2 Associate Professor of Economics, Faculty of Economics and Administrative Sciences, Ferdowsi Universuty of Mashhad, Mashhad, Iran
Abstract
Uncertainties are an intrinsic element of economic systems, exerting substantial and complex effects on various economic structures. Oil prices, in addition to being a crucial factor in production, are also a key indicator of oil revenues within Iran's economy. This study investigates the impacts of economic policy uncertainty and geopolitical uncertainty, originating globally as well as from China, the United States, and Russia, on Iran’s crude oil prices. The analysis is conducted using the Generalized Additive Model (GAM) with monthly data from 1997 to 2022. The results indicate that economic policy uncertainty at the global level, as well as that originating from China and Russia, has a significant and nonlinear effect on Iran’s crude oil prices. Similarly, geopolitical uncertainty originating globally, from China, and from Russia has a direct and nonlinear influence. In contrast, geopolitical uncertainty from the United States shows a linear and inve
rse relationship with Iran’s crude oil prices. Moreover, the study explores the effects of concurrent uncertainties from the same source, revealing that simultaneous uncertainties originating globally, from Russia, and from the United States, have substantial and nonlinear impacts on Iran’s crude oil prices. These findings highlight the importance of employing advanced models capable of accounting for the joint effects and interactions of multiple variables. The insights provided by this research are valuable for stakeholders in oil markets and policymakers involved in managing the complexities of financial and geopolitical dynamics.
Introduction
Numerous studies have demonstrated that economic uncertainties, by creating unstable expectations, significantly impact key macroeconomic variables including exchange rates (Balli et al., 2016; Bartsch, 2019; Chen et al., 2020), employment (Caggiano et al., 2017), investment (Barro et al., 2017), exports (Borio et al., 2022; Jia et al., 2020), cryptocurrency markets (Fassina et al., 2021), and inflation (Binder, 2017). Since these variables are directly and indirectly connected to energy markets and oil prices, uncertainties consequently affect these markets as well (Jiantiella & Vataja, 2018; Pham & Nguyen, 2022; Wen et al., 2022). Among various uncertainty indices, geopolitical uncertainty and economic policy uncertainty have gained particular research attention due to their greater applicability. Oil, as a strategic commodity and the "lifeblood of industry" (Zhang, 2011), influences both macroeconomic stability and global financial markets (Apergis & Miller, 2009; Hu et al., 2016; Kilian & Park, 2009; Sadorsky, 2009), with its political nature making it susceptible to geopolitical tensions and policy changes (Bloomberg et al., 2009; Su et al., 2021). Given Iran's 5.5% share in global oil trade, this study examines the impact of geopolitical and economic policy uncertainties originating from global, Russian, Chinese, and US sources on Iranian oil prices, extending existing literature in three dimensions: (1) measuring these uncertainty effects, (2) examining linear/nonlinear relationships through econometric methods, and (3) analyzing pairwise interactions between uncertainty indicators from common sources.
Methodology and Data
This study employs Generalized Additive Models (GAM) to analyze nonlinear relationships between variables (Wood, 2006). The key advantage of GAM lies in its ability to automatically identify relationship patterns (via spline smoothing functions) without requiring linearity assumptions (Wood et al., 2015). The model utilizes cubic splines (Hastie & Tibshirani, 1987) and tensor products (Wood, 2006) to estimate both univariate and multivariate smoothing functions, incorporating roughness penalties (Wood & Augustin, 2002) to prevent overfitting. Monthly data (1997-2022) includes Iranian oil prices (OPEC) alongside economic policy uncertainty (EPU: Baker et al., 2016) and geopolitical risk (GPR: Caldara & Iacoviello, 2022) indices from four regions (global, China, Russia, US). The final model evaluates both individual and interactive effects of these indicators on oil prices through a combination of linear (S) and nonlinear (f) smoothing functions.
Findings and Conclusion
The investigation reveals no consistent pattern in the relationship between uncertainties and oil prices, with divergent results across studies. While three primary factors - supply changes, demand fluctuations, and future expectations - fundamentally influence oil prices, the study emphasizes that uncertainties primarily affect prices indirectly through altering financial market participants' sentiment. For instance, simultaneous increases in both geopolitical and economic policy uncertainties from US sources drive up Iranian oil prices, whereas the same uncertainties from Russian sources lead to price declines. These variations underscore how investor sentiment toward uncertainty origins plays a pivotal role in price volatility. Notably, some uncertainties don't directly affect supply/demand but induce price fluctuations through systematic biases in financial decision-making. These findings align with behavioral economics principles, suggesting traditional models may inadequately explain such dynamics.
The study offers three key recommendations:
Adopt Generalized Additive Models (GAM) for analyzing multiple uncertainties' simultaneous effects on oil prices, particularly leveraging their capability to identify nonlinear and interactive relationships.
Alert oil market participants that concurrent rises in US-sourced geopolitical and policy uncertainties may signal imminent price surges.
Monitor price drop risks when either US-sourced policy or geopolitical uncertainty increases independently, as this may trigger sudden declines in Iranian oil prices.
These findings highlight the critical importance of incorporating market sentiment and uncertainty origins in economic analyses, demonstrating that policymakers and market participants should complement fundamental analysis with attention to investors' systematic behavioral biases.
Acknowledgments
The authors of the article are grateful to all those who contributed to the preparation and improvement of the quality of the article with their valuable comments.
Keywords: Uncertainty of Economic Policy, Geopolitical Uncertainty,
Keywords
- Uncertainty of Economic Policy
- Geopolitical Uncertainty
- Iranian Crude Oil Price
- Generalized Additive Model (Gam)
Main Subjects
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