مطالعات اقتصادی مرتبط با حاملهای انرژی (فسیلی، تجدیدپذیر و برق)
Mohammad Sadegh Adibian; Taghi Ebrahimi Salari; Hadi Esmaeilpour Moghadam
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 ...
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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,
سیاستگذاریهای اقتصادی و مالی در حوزههای فوقالذکر در سطوح ملی، منطقهای و جهانی
Majid Aghaei
Abstract
This study investigates the impact of financial development on renewable energy technology deployment in resource-rich countries with varying levels of financial system maturity. Using panel data from 2000 to 2021, the models were estimated with the Generalized Method of Moments (GMM), while the robustness ...
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This study investigates the impact of financial development on renewable energy technology deployment in resource-rich countries with varying levels of financial system maturity. Using panel data from 2000 to 2021, the models were estimated with the Generalized Method of Moments (GMM), while the robustness of results was validated through Dynamic Ordinary Least Squares (DOLS) and Fully Modified Ordinary Least Squares (FMOLS). The findings indicate that financial development positively affects renewable energy growth in all countries studied. In developed resource-rich countries, particularly those with advanced financial markets, natural resource abundance has facilitated renewable energy development, providing no evidence of the “resource curse.” In contrast, developing resource-rich countries with less developed financial systems show signs of the resource curse. These results highlight the crucial role of financial system development in transforming resource wealth into an opportunity for renewable energy advancement.IntroductionThe sharp rise in energy prices, particularly oil, over the twentieth century has brought about profound challenges and opportunities for the global economy. The heavy reliance on fossil fuels has raised serious concerns regarding energy security and environmental sustainability, prompting countries to seek alternative energy solutions. Among these, the development of renewable energy technologies has emerged as a crucial strategy to mitigate climate change and ensure long-term energy security (Bhattacharya et al., 2017; Charfeddine & Kahia, 2017). In recent years, developed economies have adopted a variety of policy instruments—such as feed-in tariffs and renewable portfolio standards—to accelerate renewable energy deployment (Kim & Park, 2016). However, despite these efforts, the contribution of renewable energy to total energy consumption remains limited, particularly in developing economies. High upfront capital costs and inadequate financial support are frequently cited as major barriers to renewable energy investment. Financial market development plays a pivotal role in mobilizing resources for renewable energy projects by facilitating access to capital and reducing investment risks. Yet, in resource-rich developing countries, the interplay between financial development and renewable energy expansion is complicated by the “resource abundance” phenomenon. While natural resource wealth has the potential to finance large-scale renewable energy investments, empirical evidence indicates that it can also distort economic structures and hinder sustainable development (Nili & Ratad, 2007; Moradbeigi & Law, 2016). Countries such as Iran and the Gulf Cooperation Council (GCC) states, despite abundant oil and gas revenues, have made limited progress in renewable energy adoption.This study aims to explore how financial development influences renewable energy growth in resource-rich economies, considering the dual role of natural resource abundance. By distinguishing between countries with varying levels of financial system development, this research seeks to provide new insights into the mechanisms through which resource wealth and financial markets interact to shape renewable energy transitions.Methods and MaterialDrawing on theoretical foundations and previous studies (e.g., Moradbeigi & Law, 2016; Nili & Rastad, 2007; Kim & Park, 2016), this study employs a dynamic model to investigate the impact of financial development on the deployment of renewable energy technologies, while accounting for the role of natural resource abundance and the level of financial system development across countries. The general model is specified as follows: In this model, represents the installed capacity of renewable energy technologies in country i at time t. The vector includes explanatory variables such as financial development (FD), natural resource rents (NRR), real GDP per capita, population (POP), consumer price index (CPI), and greenhouse gas emissions (GHG). The interaction term FD∗NRR is incorporated to examine the indirect effect of resource abundance on renewable energy development through its influence on financial development.Given the dynamic nature of the model, the estimation is conducted using the Generalized Method of Moments (GMM), as proposed by Arellano and Bond (1991) and further refined by Arellano and Bover (1995) and Blundell and Bond (1998). The sample comprises resource-rich developed and developing countries over the period 2000–2021. Countries are classified into two groups—those with developed and less-developed financial systems—based on the financial development index provided by the International Monetary Fund (IMF). Furthermore, the categorization of developed and developing economies follows the World Bank classification. Only countries with significant natural resource rents are included in the sample (Sachs & Warner, 2001; Moradbeigi & Law, 2016). Results and DiscussionThe empirical findings, based on dynamic panel GMM estimations, reveal significant insights into the relationship between financial development and the deployment of renewable energy technologies (RETs) in resource-rich countries. Diagnostic tests, including the Sargan test for instrument validity and Arellano-Bond serial correlation tests, confirm the robustness and reliability of the model estimations. In resource-rich developed countries, financial development exhibits a strong and positive impact on both annual and cumulative renewable energy capacities, regardless of the maturity level of their financial markets. This highlights the critical role of well-functioning financial systems in mobilizing investments for RETs. Furthermore, the positive and significant coefficients of natural resource rents (NRR) contradict the resource curse hypothesis in these countries, suggesting that revenues from natural resources have been effectively utilized to promote clean energy transitions. The interaction term (FD*NRR) is also significant in countries with highly developed financial systems, indicating that financial development amplifies the positive effect of resource abundance on renewable energy deployment.In contrast, the results for resource-rich developing countries present a more nuanced picture. While financial development positively influences RET expansion in countries with advanced financial markets, its effect is statistically insignificant in those with underdeveloped financial systems. Moreover, the negative and significant coefficient of NRR, alongside the interaction term (FD*NRR), confirms the existence of the resource curse in developing economies with weak financial infrastructures. This suggests that inadequate financial systems hinder the ability of these countries to channel resource rents towards sustainable energy investments. Control variables such as GDP per capita and CPI show consistent positive effects on RET deployment across most models, underscoring the importance of economic development and energy price signals in driving renewable energy adoption. Conversely, greenhouse gas emissions are negatively associated with RETs, supporting the notion that increased fossil fuel dependency hampers clean energy progress.Robustness checks using FMOLS and DOLS estimators corroborate the main GMM results, further strengthening the study’s findings. These results collectively emphasize the pivotal role of financial development in transforming natural resource wealth into a driver for renewable energy growth, particularly in countries with efficient financial systems.ConclusionThis study examined the role of natural resource abundance (resource rents) in shaping the relationship between financial development and renewable energy technology (RET) deployment in resource-rich developed and developing countries, with particular attention to the level of financial market development during the period 2000–2021. The findings reveal that financial development positively influences RET growth in both groups of countries. However, in resource-rich developed countries, this effect is significant regardless of the level of financial market development, whereas in developing countries, the impact of financial development on RET is only significant in those with advanced financial markets. This underscores the critical role of efficient financial systems in mobilizing resources and reducing investment risks in renewable energy projects.Moreover, the positive and significant effect of resource rents in developed countries rejects the “resource curse” hypothesis, highlighting the capacity of advanced financial markets to channel resource revenues toward RET advancement. Conversely, in resource-rich developing countries with underdeveloped financial markets, resource rents negatively affect RET, confirming the existence of the “resource curse.”Based on these results, it is recommended that countries with less developed financial systems strengthen credit markets, support private sector investments, create financial incentives, and enhance institutional frameworks to facilitate renewable energy technology deployment. Additionally, policies aimed at fostering sustainable economic growth, ensuring fair energy pricing, and implementing environmental strategies can play a vital role in reducing dependence on fossil fuels and promoting RET expansion.Acknowledgments The author would like to express their sincere gratitude to the anonymous reviewers for their valuable comments and constructive suggestions, which have significantly improved the quality of this study.Keywords: Renewable Energy Technologies (RET), Financial Development, Natural Resource Rent, GMM Estimator
