Oil Prices Research Articles

The asymmetric and dynamic effects of oil price shocks and geopolitical risks on carbon prices in China

The asymmetric and dynamic effects of oil price shocks and geopolitical risks on carbon prices in China

Unveiling the impact of oil price shocks on global sukuk markets: a focus on quantile coherence and time-frequency connectedness

Unveiling the impact of oil price shocks on global sukuk markets: a focus on quantile coherence and time-frequency connectedness

Predictive Powers of Carbon Emissions and Oil Price on Stock and Foreign Exchange (FX) Markets Using Multivariate Recurrent Neural Networks (RNN) Model

The predictive power of environmental factors such as CO2 levels and Brent oil price was evaluated on the stock market (S&P 500) and foreign exchange (FX) rates for market currency pairs (EUR/USD) and emerging market currency pairs (MXN/USD) with recurrent neural networks (RNN). The S&P 500 is a collection of well-established companies in the United States representing the macroeconomic health of the nation and the global economy. The FX market is a global decentralized over-the-counter (OTC) market used to determine the spot price of currency pairs. A highly leveraged market usually trades within a specific price range. Since stocks and FX pairs are highly correlated to macroeconomic factors, it was hypothesized that environmental factors such as CO2 levels and oil prices also have predictive power due to their close causal relationship with anthropological economic activities. To verify the predictive power, an RNN model was built, and a bi-directional neural network with an internal state was used to process data sequences. The performance of RNN was quantified by measuring the residual prediction from the true value. Although the study at its current state might need further statistical rigor, it concluded that environmental factors increased the predictive power for the S&P 500 while decreasing it for the DM FX pair and the EM FX pair showed mixed results.

Impact of External Shocks on Peru's Economic Growth, 2000-2021

Objective: To analyze the impact of China's GDP growth and an international oil price shock (external shocks) on Peru's growth rate, terms of trade, private investment, exports and unemployment for the period analyzed. Originality/Value: This study contributes to the literature on the dependence of a small economy on external factors, verifying through an econometric analysis the implications of an external shock that will be relevant for economic policy decision makers, academia and globalized economic culture. The relevance and value of this research are evidenced by quantifying the impacts of a large economy like China on variables such as terms of trade, private investment and Peru's GDP growth rate. Method: It is quantitative and exploratory with 4 variables, China's GDP growth rate, terms of trade, private investment and Peru's GDP growth rate; It is exploratory because it will give us an overview or knowledge of the behavior of China's GDP growth rate, terms of trade and private investment and their impact on Peru's growth rate from 2000 to 2021. The variables explained are: China's GDP growth rate (tCreChin), terms of trade (tInt), private investment (inv Priva). Explanatory variable: Peru's GDP growth rate (tCrePerú). The design is non-experimental of a correlational type, the population includes data from the 04 variables for the years 2000-2021, each with 22 observations that were extracted from the 21 years analyzed, extracted from institutional secondary sources BCRP and World Bank (WB). Subsequently, tests will be carried out to verify correlation, stationarity and heteroscedasticity in the variables and the estimation of the model parameters for several alternatives or possible combinations of factors. In each case, the “t” test, the “F” test will be performed and the coefficient of determination R2 will be calculated, to determine the best fit. And finally, the best model will be selected for forecasting purposes. Results: The response of GDP to a shock of the GDP variable of China has a positive impact from period 1-3, on the other hand the IT variable has a positive impact from period 1. Another relevant aspect achieved is that in 10 years, 51% of the variability of Peru's economic growth depends on the variability of China's growth, 2.20% of the variability of Peru's economic growth depends on the variability of the IT variance and 1.48% of the variability of Peru's economic growth depends on the variability of private investment. Discussion: Our results find similarity with studies by Guevara and Yamaca (2021) and Chávez (2020) et.al., since an external shock is positive and explains a high percentage of historical variability. A shock to China's GDP growth has a greater effect on Peru's GDP growth; and financial shocks reduce domestic GDP growth. On the other hand, Peruvian monetary policy is synchronized with the behavior of the American FED to mitigate the adverse effects of external factors. In our study we use a VAR demonstrating the influence of China's economic growth, the terms of trade, Peruvian GDP and private investment. Finally, the findings indicate that the impacts of external shocks on economic growth are more long-term than short-term, and also reveal the existence of fragility in the international economy that can be opportunities on the side of raw material prices.

Unveiling an asymmetric relationship between global crude oil and local food prices in an oil-importing economy

AbstractRecent swift comovements of local food and global crude oil prices have attracted the attention of policymakers and researchers. To evaluate this relationship, many studies have used time series models to explore global crude oil and local food prices. However, robust research based on advanced nonlinear time series models that incorporate control variables for their formation is lacking. In this paper, nonlinear techniques are applied to assess the asymmetric nexus between Brent oil prices and local retail food prices in Slovakia. To estimate this value, we extend the single-threshold NARDL approach to the MTNARDL model. The nominal exchange rate and industrial production index are used as the control variables. Compared with conventional NARDL models, the MTNARDL model provides a more detailed representation of global oil‒local food price linkages and detects the asymmetric effect of global oil prices on food prices from both long- and short-term perspectives. Interestingly, with respect to long- and short-term food price volatility, changes in response to oil price fluctuations are greatest under a regime with rather a small number of positive and moderate changes.

The Eectricity Crisis and the Feasibility of Nuclear Energy in Egypt

The power outage crisis is increasing in Egypt, negatively affecting many other sectors such as industry, agriculture, and trade. In light of the lack of sufficient capacity to meet the growing needs of consumers, which has led to regular power shortages and power outages. While Egypt needs additional energy, the production of gas and oil needed to generate thermal energy decreased in 2014, and Egypt moved from an exporter of natural gas to a net importer. In addition to this, the volume of subsidies allocated to energy increased, the rise in global prices for oil and natural gas, and the need for huge investments to create Power generation plants, development of transportation networks, and distribution of electrical energy, which led to pressure on the general budget. A continuous and reliable supply of electricity is needed for Egypt's social and economic development. Accordingly, the government encouraged the development of new energy, invited the private sector to participate in energy generation, and a number of government reforms were made in order to enhance competition in the energy market, which required the need to study the possibility of providing it using nuclear energy. Its stations have a high load capacity, operate almost at full capacity all the time, are characterized by the stability of the electrical network and energy independence, and avoid the risks of fuel price shocks, and the costs of generating electricity from them decrease with increasing production. The importance of this research lies in highlighting the challenges facing the structure of the electricity sector in Egypt, and studying the advantages enjoyed by nuclear energy as the most important renewable energy sources in the world. Its importance also lies in comparing nuclear energy with other energy sources, and trying to benefit Egypt from obtaining this energy for use. In economic development projects, rationalizing tariffs and supporting their access to the poor. <i>This research is divided into</i>:<i>The first topic</i>: The electricity generation crisis in Egypt and a development vision for the contribution of nuclear energy to its solution, <i>The second topic</i>: trends in development planning for establishing nuclear plants in Egypt. The electricity generation crisis in Egypt and a development vision for the contribution of nuclear energy to its solution.

Can oil prices affect economic uncertainty and financial stress? Quantile-based evidence from France and Germany

Can oil prices affect economic uncertainty and financial stress? Quantile-based evidence from France and Germany

Combining the effects of industrialization and oil prices on CO2 emissions: What role do renewable energy, urbanization and financial crisis play?

AbstractTransitioning to a low‐carbon economy is essential for sustainable development; however, there remains a significant gap in understanding the moderating role of oil prices within the industrialization‐CO2 emissions relationship. This study is the first to investigate how industrialization interacts with oil prices to affect CO2 emissions across 30 African countries from 2000 to 2021, focusing on country‐specific heterogeneity. The results of Driscoll‐Kraay and IV‐GMM techniques suggest that industrialization drives CO2 emissions, while oil prices mitigate CO2 emissions in Africa. The results also show that economic growth (GDP) and urbanization stimulate CO2 emissions, while renewable energy and financial crises reduce it. The study's key findings report that oil prices moderate industrialization to reduce CO2 emissions in Africa. The heterogeneity analysis reveals that industrialization reduces CO2 emissions in top, upper‐middle and low‐industrialized countries. Oil prices reduce CO2 emissions in upper‐middle and low‐industrialized countries, while this relationship is insignificant in top industrialized countries. The findings also indicate that oil prices moderate industrialization to reduce CO2 emissions in upper‐middle industrialized countries, not top and low industrialization groups. Finally, findings from quantile regression suggest that the effects of oil price and industrialization on CO2 emissions are heterogeneous. Policymakers should promote green industries, invest in renewable energy infrastructure, and implement regulations that adhere to environmental standards.

Causality relationships between climate policy uncertainty, renewable energy stocks, and oil prices: a mixed-frequency causality analysis

This paper investigates the predictive relationships among climate policy uncertainty (CPU), oil prices, and renewable energy (RE) stock market returns, particularly highlighting the challenges posed by the varying data frequencies of these variables. The study utilizes a comprehensive dataset comprising monthly CPU, daily oil prices, and RE stock returns, sourced globally. By applying a mixed-frequency causality test (MFCT), the analysis reveals significant predictability across different time horizons, particularly highlighting the strong influence of oil prices on RE stock returns over short-term horizons, while CPU demonstrates a more pronounced effect over medium to long-term horizons. In contrast, the application of the classical Granger causality test on low-frequency (monthly) data indicates an insignificant relationship between CPU and RE stocks, suggesting that traditional models may overlook important predictive dynamics. The analysis was conducted using Matlab code, and the findings provide valuable insights for policymakers in designing effective climate policies and for investors in optimizing portfolio strategies and hedging against risks.

How volatility in the oil market and uncertainty shocks affect Saudi economy: a frequency approach

In this study, spectral Granger causality analysis is employed to investigate the spectral dynamics of uncertainty transmission and its impact on economic growth and financial development in Saudi Arabia from 1993 to 2020. We examine the relationships between crude oil volatility, geopolitical risk, global economic uncertainty, financial development (measured by market capitalisation, MCGDP, Financial Institutions Access Index, FIAIX) and economic growth. The empirical results show that negative shocks in crude oil volatility have a significant impact on financial development as measured by the MCGDP, with capital flight and reduced domestic investment playing key roles, despite the effective contribution of increased government spending to mitigate these effects. In this study, spectral Granger causality analysis is employed to investigate the spectral dynamics of uncertainty transmission and its impact on economic growth and financial development in Saudi Arabia from 1993 to 2020. We examine the relationships between crude oil volatility, geopolitical risk, global economic uncertainty, financial development (measured by market capitalisation, MCGDP, Financial Institutions Access Index, FIAIX) and economic growth. The empirical results show that negative shocks in crude oil volatility have a significant impact on financial development as measured by MCGDP, with capital flight and lower domestic investment playing a key role, despite the effective contribution of increased government spending in mitigating these effects. However, looking at the FIAIX, crude oil volatility has a different impact, with positive shocks having no significant impact on financial development. In contrast, negative shocks show long-term causal effects, which emphasises the vulnerability of the banking sector to oil price fluctuations. Geopolitical risk has a significant long-term impact on the MCGDP due to uncertainty shocks caused by regional and global geopolitical measures. For geopolitical risk, the results are mixed with a significant causality of negative shocks on the FIAIX over certain frequencies, emphasising the sensitivity of the banking sector to geopolitical tensions. In contrast, the world economic uncertainty has only a limited direct impact on the FIAIX, indicating the resilience of the Saudi financial sector to fluctuations in global uncertainty. In terms of economic growth, positive shocks have a greater impact than negative shocks due to the volatility of crude oil. However, shocks resulting from geopolitical risks, whether positive or negative, have little effect on economic growth. The industrial production index, a measure of the resilience of the Saudi economy, indicates that it is susceptible to positive shocks from fluctuations in oil prices over a range of time periods. Our study’s findings can assist Saudi Arabia’s authorities in fortifying the country’s financial and economic resilience against the spread of uncertainty. For strong financial development and sustainable economic growth, these uncertainty elements must be well monitored.

Economic reforms and consumption trends: A deep dive into Saudi Arabia’s economic evolution

This study examines the aggregate consumption function of Saudi Arabia from 2000 to 2022, focusing on identifying key determinants of household consumption and evaluating the impacts of disposable income, household wealth, government expenditure, interest rates, and oil revenues. the research uses advanced econometric methods, including the autoregressive distributed lag (ARDL) model and Johansen cointegration test, to analyze the relationships among these variables. the findings reveal that disposable income, household wealth, and government expenditure significantly and positively influence consumption, whereas interest rates show a negative correlation. oil revenues also play a critical role, reflecting the country’s economic reliance on oil. the study highlights the necessity for economic diversification to reduce the impact of oil price volatility on household income and consumption stability. The results offer crucial insights for policymakers, emphasizing the need for strategies that enhance household income and wealth, maintain robust public sector spending, and effectively manage interest rates. these findings also support the importance of consistent and predictable income sources for sustaining consumption. additionally, this study suggests directions for future research, including developing sophisticated forecasting models to predict consumption trends and exploring other influencing factors such as demographic shifts and technological progress.

Extreme comovements and downside/upside risk spillovers between oil prices and exchange rates

Abstract This paper examines the dependence structure and risk spillovers between oil prices and exchange rates in both oil-exporting and oil-importing countries. Using a flexible dependence switching copula model, we analyze both positive and negative dependence and transitions between the dependence regimes. Additionally, we investigate the directional risk spillovers between oil and currency markets in both their downsides and upsides. Based on empirical data from 1999 to 2024 for major oil-exporting and oil-importing countries, we find that oil price-currency dependence is predominantly positive for oil-exporting countries, with infrequent transitions, but mainly negative for oil-importing countries, with frequent transitions between the two dependence regimes. These transitions often occur around crisis or war times. Furthermore, we observe that during downturns in the oil market, tail dependence between oil prices and currencies becomes more pronounced than during upturns. Our results indicate the presence of risk spillovers between oil and currency markets, with the downside spillover effects outweighing the upside ones. Moreover, we find that risk spillover is stronger from oil markets to currency markets than the reverse direction. These insights substantially enrich the existing literature and would offer valuable implications for effective risk management strategies and policymaking.

Asymmetric relationship between crude oil price and remittance inflows in a small island economy: Evidence from non-linear ARDL approach

Sri Lanka's economy heavily depends on remittance inflows to finance its import of essential and intermediate goods. A decline in remittances could severely limit the country's import capacity, affecting overall economic growth and development. This study investigates the impact of crude oil prices on Sri Lankan remittance inflows from 1980 to 2020, while accounting for per capita GDP, financial development, and exchange rates as additional explanatory variables. Employing a nonlinear autoregressive distributed lag (NARDL) model, the analysis reveals significant asymmetric effects of oil price shocks on remittance inflows. In the short run, positive oil price shocks lead to increased remittance inflows, whereas negative shocks reduce them. However, in the long run, both positive and negative oil price shocks have an adverse impact on remittance inflows. Furthermore, changes in per capita GDP, financial development, and exchange rates also play a crucial role in influencing remittance inflows. The findings highlight Sri Lanka's vulnerability to global oil market fluctuations and suggest policy measures to mitigate these risks. Key recommendations include diversifying labor export markets, enhancing financial infrastructure, and reducing dependence on remittance inflows to sustain import capacity and promote long-term economic resilience.

Unwrapping the Intricate Interplay Between Energy Dependency and Macroeconomic Volatility in OECD Countries

While research has explored the connection between oil prices and macroeconomic performance, there is limited understanding of the interaction between overseas energy imports dependency and macroeconomic fluctuations. This work addresses the foregoing study using the augmented mean group (AMG) econometrics technique on panel data of 29 OECD net energy‐importing countries from 2001 to 2021. The long‐run finding unearthed that energy dependency intensifies macroeconomic instability, confirming that relying on overseas energy imports will hamper the smooth functioning of domestic economic machinery in the form of energy supply interruption. Besides energy dependency, this study uses government consumption spending, regulatory quality, and globalisation as control variables in macroeconomic instability function. The long‐run outcomes further depict that government consumption spending and globalisation aggravate macroeconomic instability while regulatory quality reduces it. These findings are further checked by applying the pooled mean group‐autoregressive distributed lag (PMG‐ARDL) method. In conclusion, this study provides policy implications to prioritise domestically produced energy use and diversify energy sources by increasing the share of clean energy in the total energy mix.

Geopolitical Risk and Food Price Inflation: A GVAR Analysis of BRICS and the G7

ABSTRACT We investigate the influence of geopolitical risk on domestic food prices in 12 economies (BRICS and the G7) using a global vector autoregressive (GVAR) approach from 2003M1 to 2022M9. The results show that geopolitical risk shocks cause increases in international prices (oil, agricultural, and general commodity prices). We found that these shocks also provoke fluctuations in domestic food prices. The variance decomposition indicated that international prices and geopolitical risk contribute to the formation of domestic food prices. Finally, the estimates suggest relevant differences between the formation of domestic food prices in BRICS and G7 countries.

Interconnectedness of financial markets in crises in the case of the enlarged BRICS

The article presents a study of the connectivity and integration of sovereign bond and stock markets in 10 BRICS+ countries in the context of crisis instabilities in 2019−2024. Financial markets are becoming more integrated, and an increasing share of public investments are carried out across borders, which increases not only the opportunities for participants, but also the risks of a new crisis. The work used data on central bank rates of the considered countries, yield indices of 10-year government bonds, gold and Brent oil prices. The methods include the analysis of exchange rate dynamics, connectivity estimates based on the multivariate concordance coefficient and two-factor Friedman rank variance analysis, VAR models, Granger predictability and cointegration. The objective of this study is to analyze the interrelationship and cointegration between the sovereign bond and equity markets of selected BRICS+ countries during crisis periods. Our findings indicate that market interrelationship intensifies during crises, which in turn amplifies volatility. Additionally, we observed that none of the economies within the BRICS+ group can be classified as fully integrated or entirely isolated markets. The disruption of the interrelationship in the sovereign bond markets of the group is primarily reflected in the inconsistency of dynamic changes between Russia, China, and India. During the global shock of 2019–2020, the crisis spread from China, followed by Indonesia, and later to the other countries of the group. The financial and debt markets of the sampled countries were able to quickly cope with the severe shocks of the COVID-2019 period. The 2022–2024 crisis, which lasted significantly longer, began in Russia before spreading to countries across Asia and Africa. By 2024, Russia’s sovereign bond yields showed a marked decline. The increased market volatility following 2022 disrupted the integration and interrelationship of the stock and debt markets within the BRICS+ countries.

Talk green, act brown: Transition risks and drilling investments of U.S. upstream oil and gas firms

AbstractThis paper explores the relationship between upstream oil and gas firms' proactiveness in addressing climate change transition risks and their drilling investments. We propose that due to limited capabilities to transition to renewable energy, these firms may strategically display proactiveness to greenwash their intentions to increase drilling activities. Leveraging a unique dataset comprising manually collected information on upstream firms' drilling investments, we find empirical evidence supporting our hypotheses. Specifically, firms showing greater proactiveness toward transition risk during earnings calls paradoxically increase their drilling investments. Additionally, high oil prices negatively moderate this relationship by creating a lucrative environment that benefits stakeholders, such as shareholders and investors, and simultaneously alleviates internal resource constraints, thereby reducing the need for greenwashing. This study contributes to the literature by illustrating how firms, under significant societal pressure but lacking transition capabilities, employ greenwashing tactics to obscure their investment activities.

The role of corruption in the oil price–growth relationship: Insights from oil-rich economies

The role of corruption in the oil price–growth relationship: Insights from oil-rich economies

Probabilistic oil price forecasting with a variational mode decomposition-gated recurrent unit model incorporating pinball loss

Prediction methods have garnered significant attention in intelligent decision-making. Most existing approaches to predicting crude oil prices prioritize accuracy and stability while providing precise prediction intervals (PIs) that can offer valuable insights. Thus far, we introduce a novel hybrid model to forecast future crude oil prices. Our approach leverages the variational mode decomposition (VMD) to simplify the complexity of the original time series, yielding a set of subseries. These subseries are then modeled using a deep neural network architecture called a gated recurrent unit (GRU). To address the prediction uncertainty, we employed the pinball loss function rather than the mean square error (MSE) to guide the proposed VMD-GRU. This adaptation extends the traditional GRU-based point forecasting to probabilistic forecasting by estimating quantiles. We evaluated our proposed model on a well-established crude oil price series by conducting both single- and multi-step-ahead forecasting analyses. Our findings underscore the efficacy of the combined model, demonstrating its superior predictive performance compared to benchmark models.

Asymmetric Effect of Oil Prices on Kazakhstan’s Stock Market Index and Exchange Rate

In this study, the asymmetric effect of oil prices in Kazakhstan on the exchange rate (USD/KZT) and Kazakhstan stock market index (KASE) returns was analyzed using the non-linear ARDL cointegration (NARDL) method with monthly data for the period January 2010-February 2024. As a result of the findings of the study, both positive and negative changes in oil prices statistically affect stock returns and exchange rates in the long term. The estimated long-term positive (0.115982) and negative (0.111234) coefficients of oil prices on KASE returns were found to be statistically significant at the 5% significance level. Thus, in the examined period, the KASE variable gave different reactions to positive or negative shocks in the oil price. In the model where the exchange rate is the dependent variable, the estimated long-term positive (-0.093875) and negative (-0.092918) coefficients of oil prices were found to be statistically significant at the 95% reliability level.