Empirical Analysis of Global Oil Price Determinants at the Disaggregated Level Over the Last Two Decades

Yoshino, Naoyuki; Alekhina, Victoriia

doi:10.2139/ssrn.3541511

Cited by 3 publications

(2 citation statements)

References 17 publications

(23 reference statements)

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“…Researchers (Yoshino and Alekhina, 2019) conclude that the largest oil consumers in the last 20 years have a greater influence on the cost of oil than exporting countries, and the strengthening of the US dollar had a negative impact on oil quotes. In other words, the last two decades are characterized by the fact that demand in the oil market has a greater impact on price dynamics than supply.…”

Section: Theoretical Aspects Of the Studymentioning

confidence: 99%

The Impact of Covid-19 on Pricing in the Global Oil Market

Chuvakhina

Yarygina

Ustinova

et al. 2022

IJEEP

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This article is devoted to analysing current factors affecting prices in the global oil market for the period from December 2019 to July 2022. The study focuses on the processes taking place in the economy of the United States and the eurozone countries, which led to an increase in inflation in response to the economic crisis caused by COVID-19 and their impact on current oil prices. It analyses the traditional and non-traditional measures of the US and Eurozone monetary policies designed to stimulate business activity and bring their economies out of recession. It is observed that the actions of financial regulators contributed to the growth of inflation rates, especially in the energy sector. The paper emphasizes the growing crisis in the United States and the eurozone countries, which in the future may lead to a decrease in the consumption of energy resources, including crude oil and petroleum products, which will negatively affect the stability of the global oil market. The influence of factors of the growth of US dollar inflation and measures aimed at regulating the physical volume of oil production in the framework of OPEC+ deals, which affect pricing in the world oil market, is compared using the correlation analysis. As a result of the study, it is concluded that during the analysed period there is a shift of factors affecting pricing in the world oil market from monetary to supply-demand factors in the commodity market. The current inflationary pressure of the US dollar and the euro, combined with a reduction in oil supplies to the world market due to the restrictions imposed, makes it difficult to predict oil prices and leads to an increase in the volatility of oil quotes.

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Section: Theoretical Aspects Of the Studymentioning

confidence: 99%

The Impact of Covid-19 on Pricing in the Global Oil Market

Chuvakhina

Yarygina

Ustinova

et al. 2022

IJEEP

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“…[45]. There are several detailed review papers about crude oil price determinants [13,[46][47][48][49][50][51][52][53][54].…”

Section: Data Used In the Studymentioning

confidence: 99%

Forecasting the Crude Oil Spot Price with Bayesian Symbolic Regression

Drachal

2022

Energies

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In this study, the crude oil spot price is forecast using Bayesian symbolic regression (BSR). In particular, the initial parameters specification of BSR is analysed. Contrary to the conventional approach to symbolic regression, which is based on genetic programming methods, BSR applies Bayesian algorithms to evolve the set of expressions (functions). This econometric method is able to deal with variable uncertainty (feature selection) issues in oil price forecasting. Secondly, this research seems to be the first application of BSR to oil price forecasting. Monthly data between January 1986 and April 2021 are analysed. As well as BSR, several other methods (also able to deal with variable uncertainty) are used as benchmark models, such as LASSO and ridge regressions, dynamic model averaging, and Bayesian model averaging. The more common ARIMA and naïve methods are also used, together with several time-varying parameter regressions. As a result, this research not only presents a novel and original application of the BSR method but also provides a concise and uniform comparison of the application of several popular forecasting methods for the crude oil spot price. Robustness checks are also performed to strengthen the obtained conclusions. It is found that the suitable selection of functions and operators for BSR initialization is an important, but not trivial, task. Unfortunately, BSR does not result in forecasts that are statistically significantly more accurate than the benchmark models. However, BSR is computationally faster than the genetic programming-based symbolic regression.

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An Empirical Analysis of Supply and Demand Factors Influencing Global Oil Prices: A Panel Data Approach

Tomić,

Stevandić

2024

SIJ

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This study examines the factors that impact global oil prices, focusing on the relationship between supply and demand in international markets. The authors used an econometric panel methodology to identify the primary factors influencing global oil prices, using Brent crude oil prices as the dependent variable. The study also considered alternative measures, such as Dubai and West Texas Intermediate (WTI) prices, as well as a composite global price index derived from the average of WTI, Dubai, and Brent prices, to ensure the robustness of the findings. The study found that key factors influencing global oil prices remained consistent across different dependent variables introduced into the model. The research emphasizes the critical role of supply and demand dynamics as the main drivers shaping global oil prices. On the supply side, variables such as oil reserves, international oil trade, and the number of active oil rigs were considered. The results indicated that an increase in active oil rigs is associated with increased oil prices, while an increase in international oil trade leads to price reductions. When oil prices rise, active oil rigs often increase, but with a specific time lag. This rig increase can further drive up oil prices, particularly when the market expects continued price growth or when investments in new rigs are financed by anticipated higher revenues from oil sales. Increased international trade in oil leads to a more excellent supply of oil in the global market, which drives down global oil prices. Although oil reserves showed a positive coefficient, they were marginally significant, suggesting a potential upward pressure on prices when reserves increase. This positive relationship between oil reserves and prices may reflect market perceptions of future supply constraints, where increased reserves signal potential future scarcity rather than immediate availability, thereby exerting upward pressure on prices due to speculative behavior and strategic stockpiling. On the demand side, industrial growth was a critical factor that significantly drove oil prices higher. At the same time, renewable energy consumption had a statistically significant adverse impact, reducing global oil demand and lowering oil prices. The study also examined the impact of major global events, including the COVID-19 pandemic and the effects of the Global Financial Crisis. It revealed that the COVID-19 pandemic had a statistically significant negative impact on oil prices due to worldwide lockdowns and economic slowdowns. However, the Global Financial Crisis did not exhibit statistical significance in the model using WTI prices, though it still negatively affected all models. The study employed various panel data regression techniques, including pooled, fixed effects (FE), and random effects (RE) models. Diagnostic tests for heteroskedasticity and autocorrelation were conducted, leading to the application of Robust Hausman tests that identified the fixed effects model as the most appropriate for this analysis. Moreover, the study used Driscoll-Kraay standard errors to correct for heteroskedasticity, autocorrelation, and cross-sectional dependence, which reinforced the fixed-effects model's validity. The key findings highlighted the importance of supply and demand as pivotal factors influencing global oil prices.

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Empirical Analysis of Global Oil Price Determinants at the Disaggregated Level Over the Last Two Decades

Cited by 3 publications

References 17 publications

The Impact of Covid-19 on Pricing in the Global Oil Market

The Impact of Covid-19 on Pricing in the Global Oil Market

Forecasting the Crude Oil Spot Price with Bayesian Symbolic Regression

An Empirical Analysis of Supply and Demand Factors Influencing Global Oil Prices: A Panel Data Approach

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