Real Oil Price Research Articles

Oil Price Uncertainty and Consumer Sentiment in Advanced Economies

How does oil price uncertainty affect consumer sentiment in advanced economies? Is the response of consumer sentiment to exogenous positive and negative oil price shocks symmetric or asymmetric? Motivated to answer these questions, this paper provides a comprehensive examination of the effects of real oil price shocks on consumer sentiment in the G7 economies in the context of two classes of empirical models. With the application of a bivariate structural GARCH-in-Mean VAR model we find that (in general) oil price uncertainty has a negative and statistically significant effect on consumer sentiment in the G7 countries. Moreover, using a test of symmetry, we find that the relationship between oil prices and consumer sentiment is in general asymmetric. JEL Classification: C32, D12, Q43, O57

Do Supply Chain Pressures Affect Consumer Prices in Major Economies? New Evidence from Time-Varying Causality Analysis

This study explores the dynamic causality between the consumer price index and supply chain pressure index in two large economies. Despite extensive research into the role of supply chains at the firm level, literature on their impact on time-varying inflation and macroeconomic stability is scarce. Using data from the United States and the European Union from January 2000 to December 2021, we employ novel time-varying causality techniques to examine the evolving relationships among inflation, supply chains, real gross domestic product, interest rates, and oil prices. Our findings show that supply chains have a significant dynamic relationship with consumer prices, particularly during economic crises like the 2008 global financial crisis and the COVID-19 pandemic. Robustness tests including impulse response functions and the autoregressive distributed lag model confirm this causality. These results are critical for policymakers, emphasizing the importance of supply chains in controlling inflation and achieving global economic resilience and stability.

Revisiting the Nexus Between Oil Prices and Economic Activity for Asian Economies Using MIDAS

The objective of this paper is to re-examine the causal relationship between oil prices and economic activity for five Asian economies. We apply the unrestricted MIDAS (U-MIDAS) model using monthly data for real oil prices and quarterly data for real GDP for the period from 1998Q1 to 2019Q4. The causal nexus between oil prices and economic activity is also studied by means of wavelet analysis to investigate whether the relationship between the variables changes over different time scales. The key empirical results under the MIDAS approach show that there is a clear significant causal link from oil prices to economic activity, which is not as clearly found under the standard VAR approach. In addition, our results using impulse response functions suggest that the five Asian economies respond, in general, positively in economic activity to an oil price shock at shorter time horizons (less than two years), while the positive responses switch to mostly negative ones at longer time horizons (from two to four years). Our results, in general, support that the (theoretically) expected negative causal nexus between oil price fluctuations and economic activity for oil importers is dominant over longer time horizons for our dataset. An exception to this pattern is China, which has a dissimilar country profile in terms of its oil market and production structure from the profiles of the other Asian economies in the study. JEL Classification: C32, E32, O53, Q43

Volatility Transmission between Oil Price and Exchange Rate

This article presents a study on the transmission of oil price volatility to the exchange rates of 14 countries (net oil exporters and importers) during the period from 02/01/2000 to 31/11/2022. The aim is to compare the effect of oil price fluctuations on exchange rate volatility based on the country's nature. Using ARCH, GARCH, and GARCH-BEKK models, our results reveal that the real effective exchange rate is significantly linked to fluctuations in the real oil price for both categories of countries: oil importers and exporters. These findings have important implications for monetary, fiscal, inflationary, and trade policies for these countries.

The economic and fiscal transition costs of global climate mitigation in fossil fuel export dependent economies

Global decarbonization has large implications for trade and financial flows, and with few economies likely to be more affected than those relying heavily on exporting fossil fuels. This study first identifies 40 highly fossil fuel dependent economies and then, through several empirical strategies, examines the potential implications for oil rents, public finances and economic growth from global decarbonization. First, it is estimated that as a group, countries would lose more than 60 percent of oil rents alone, or between (present value adjusted) US$12–14 trillion, for the period 2023–2040 under a global ‘net-zero 2050’ versus a ‘business as usual’ scenario, - a loss equivalent in size to between 120 and 142 percent of GDP. Second, local projections model estimates suggest that there are large and persistent adverse growth and fiscal impacts associated with global decarbonization in emerging market and developing economy oil exporters. Here, a 10 percentage point (pp) decrease in (real) oil price inflation is associated with a decline of 1.58 percent in (real) GDP four periods after the shock; a decrease in annual government revenue (as a percentage of GDP) by between 0.6 and 0.8 pp and; an addition of about 0.5 pp to government debt per year. Finally, the study discusses relative vulnerabilities, and the domestic and international policy options needed to mitigate transition cost. Aside from a handful of primarily high-income countries, most countries have little or no savings to help them cushion an inevitable steep fall in demand for their main export and source of revenue, and more than one third of countries are characterized by either low or medium levels of human development. Whereas several countries are relatively well positioned to successfully mitigate the transition cost provided urgently prioritized domestic reforms, a substantial subgroup of countries will need international assistance to avoid potentially large negative socio-economic consequences.

The Impact of Indonesian Crude Oil Demand Prices on the Indonesian Biodiesel Industry

Biodiesel is one of Indonesia's potential export commodities as there is a production surplus that occurs every year from 2006 to 2020. The study used the 2SLS method with a validation and simultaneous equation model. Data processing using SAS/ETS version 9.4. The purpose of this study is to analyze the impact of Indonesia's crude oil demand price on Indonesia's biodiesel industry. The findings indicate that the demand for Indonesian biodiesel is positively impacted by a rise in the global real price of crude oil by 0.11%. This increase is due to both the biodiesel industry's and the local market's need for Indonesian palm oil. The local price of Indonesian biodiesel would rise by 0.49% due to the increase in demand for the fuel. The amount of biodiesel produced in Indonesia will increase by 0.87%, this increase in production is due to increasing domestic demand for Indonesian palm oil, and the volume of biodiesel exported to destination countries will increase by 0.01%. Exports of palm oil may be more impacted by the policy of raising the actual world price of crude oil. This implies that the program may potentially result in a rise in raw material exports. On the other hand, the biodiesel industry and other industries also see a spike in palm oil as a result of the strategy of raising the real world price of crude oil.

Assessing the baseline model of WTI oil and stock returns under financial volatility and spillover effects

Do financial volatility shocks matter for WTI oil and stock markets? They should since world economic activity responds to volatility. To investigate this question, we revisit two empirical frameworks widely used in the literature. Our baseline involves the standard identification of oil shocks in structural vector autoregressions (SVAR) with (world) oil supply, demand, and real oil prices. We then propose a global vector autoregressive (GVAR) model integrating 14 major world economies. We introduce the volatility measure (VIX), various stock markets, and compare two oil demand proxies: real economic activity (REA) based on commodity prices and world industrial production (WIP). The results of the impulse response analysis do not indicate major differences across models. However, when measuring the share of oil price variance explained by shocks to VIX (or to U.S. high-bond corporate yield) SVAR overestimates the influence of VIX. We find (world) demand shocks explain a larger part of the variance of oil and stock markets compared to supply shocks. In SVAR, new information coming from a one standard deviation shock to VIX is incorporated negatively and instantaneously on real oil prices: −1.6 for REA and −1.4 for WIP. In GVAR these are reduced slightly to −1.2 from VIX and to −0.6 if coming from corporate bond yield shocks. Our study highlights the sensitivity of econometric results to distinct approaches: one that identifies shocks and another that captures spillover effects.

The Impact of Oil Prices on the Import of Capital Goods in Azerbaijan

The article studies theoretical and practical aspects of the oil prices impact on the import of capital goods in an oil-exporting country. Based on the two-step Engel-Granger procedure for cointegration analysis, the relationship between the real volume of imported capital goods per capita and the real price of Azeri light oil is examined. It has been determined that the real volume of imported capital goods per capita is highly dependent on the oil price, and the volatility of the oil price also affects the volatility of imports of capital goods. This also shows that investment activity in the country depends on oil prices. Therefore, it is necessary to spend oil revenues, regardless of oil prices, depending on the economic development goals and to pursue policies to transform oil revenues into stable growth factors.

International Linkages of Inflation‐Output Dynamics: Fresh GVAR Evidence from Pakistan and Its Trading Partners

The key purpose of this study is to explore the relationship between inflation and output dynamics in a global macroeconomic framework by utilising time‐series data from Pakistan and thirty‐two trading partners which account for around 95 per cent of foreign trade of Pakistan, over the period 1979Q2–2016Q4. By featuring the GVAR approach, this paper empirically examined the international linkages to account for cross‐country inflationary spillovers. The findings show that both foreign and global variables jointly and significantly matter for the inflation‐output relationship in developing economies, in general and, in particular, in the economy of Pakistan. The findings from general impulse response functions (GIRF) reveal that shocks to the US real output, oil prices and food prices are transmitted and settled quickly, and put forward a significant impact on real GDP and inflation in Pakistan and its trading partner economies. Inflation in Pakistan is driven more strongly by the global changes in oil and food prices than GDP. For monetary policy formulation, the central bank should take into account developments in inflation‐output dynamics of Pakistan's major trading partners.

Identifying oil price shocks with global, developed, and emerging latent real economy activity factors

SummaryThis paper proposes an identification strategy for international oil price shocks while accounting for the heterogeneous sources of oil demand from global, developed, and emerging economies. Unlike existing works, we isolate global oil demand shocks, associated with a global real economic activity factor, from oil demand shocks originating specifically from developed and emerging economies, associated with real economic activity factors within these two groups of economies. The paper uses a structural factor‐augmented vector autoregression (FAVAR) model with latent global and specific factors to model crude oil demand and supply. To identify the shocks, we extract real economic activity factors from a large panel of emerging and developed economies' real activity variables using a two‐level factor model. The paper shows how structural shocks can be identified by solving equations that arise from economically meaningful zero restrictions on the impact matrix of the reduced‐form FAVAR model innovations. The empirical application shows that identifying the international oil demand shocks based on the global and specific latent factors is essential to appropriately quantify their heterogeneous impacts on these factors, the crude oil production, and the real oil price.

Energy price shocks and current account balances: Evidence from emerging market and developing economies

This paper investigates the effects of real energy price shocks on current account balances of 45 emerging market and developing economies. The investigation is based on country-specific structural vector autoregression models, where alternative specifications and identification schemes are considered for robustness purposes. The empirical results suggest that 1 % of a positive real oil price shock results in up to 0.11 (0.08) percentage points of a cumulative improvement (deterioration) in current account balances of oil exporters (importers) after five years, whereas 1 % of a positive real natural gas price shock results in up to 0.06 (0.04) percentage points of a cumulative improvement (deterioration) in current account balances of natural gas exporters (importers) after five years. Real coal price shocks result in higher current account balances of oil exporters and natural gas exporters, suggesting substitution of coal with oil and natural gas in such cases. When contributions of alternative real energy prices to the variance of current account balances are compared, real oil price shocks dominate those of real natural gas and real coal prices. The empirical results investigating the effects of oil demand versus oil supply shocks on current account balances suggest that oil demand shocks (rather than oil supply shocks) result in similar reactions of current account balances to real oil price shocks, supporting the view that the effects of oil demand shocks are different from those of oil supply shocks. The results are robust to the consideration of country-specific changes in real GDP and real effective exchange rates.

Oil price dynamics in times of uncertainty: Revisiting the role of demand and supply shocks

Drivers of real oil prices have been explored extensively in the literature with little consensus. Using a new identification scheme based on forecast error variance, we identify oil-specific demand, demand, and oil supply shocks that maximize the sum of forecast error variance of three variables explained by their respective shocks. The estimation, with the sample period until 2007, suggests that the three identified shocks have similar effects as in the early literature, with oil-specific demand shocks playing a prominent role. However, in the post-crisis period supply shocks have emerged as a source of short-run increases in oil prices, and demand shocks do not have a long-run effect on prices, unlike in the pre-crisis period. By further including risk in the model, we show that the importance of supply shock in driving oil prices in the short run is not driven by global risk. These estimates overwhelmingly suggest zero short-run supply elasticity - a matter of debate in the recent literature. Aside from oil-specific demand shocks, six episodes (including COVID-19) and a time-varying VAR with stochastic volatility identified based on forecast error variance suggest that other shocks, in particular supply shocks, have also played a significant role in driving oil prices in different episodes which cannot be ignored while evaluating the oil price dynamics.

Asymmetric influence of oil demand and supply shocks on meat commodities

We analyze how different types of oil shocks impact the prices of six meat commodities: beef, lamb, pork, poultry, fish, and shrimp. Proceeding in two stages, we first decompose variations in the real oil price into oil supply, aggregate demand, and oil-specific demand shocks using a recursive structural vector autoregression. Then, we examine the asymmetries in the effects of these three types of shocks on meat prices using nonlinear autoregressive distributed lag models. There are three main findings. First, oil supply shocks and oil-specific demand shocks affected meat prices in the short and long run—aggregate demand shocks were largely irrelevant. Second, asymmetries in the effects of oil price shocks were present mainly in the long run; there was limited evidence of these asymmetries in the short run. Third, the effects of the three types of shocks differed between the six meat prices. These findings suggest that the conventional approach to analyzing the response of agricultural prices to oil price shocks will neglect the heterogeneity in these responses to various categories of oil price shocks. While studying the effects of a composite of oil price shocks on agricultural prices is informative, exploring the impacts of various categories of oil price shocks will be more insightful, presenting a more nuanced view of the associations between oil and agricultural prices.

Revisiting the connectedness between oil prices and uncertainty indicators in BRICS countries

The paper revisited the connectedness between oil prices (ROILP), economic policy uncertainty (EPU), and geopolitical risks (GPR) in the BRICS countries using data from January 1997 to October 2022. The study applied the spillover index, a rolling window based on the generalized VAR framework, and a wavelet coherence approach to investigate the passthrough, multiple regime changes, co-movements, and lead-lag status between the series. The study found that oil prices were a significant transmitter of shocks to other variables in the system among countries, with Brazil having the highest spillover index (11.7%) followed by South Africa (10.5%), India (10.2%), China (9.5%), and Russia (9.2%). The rolling spillover from GPR to ROILP suggested that GPR had a varying spillover effect on real oil prices in the BRICS economies, with Russia and India experiencing relatively stronger effects compared to the other countries. The spillover from EPU to ROILP showed that Brazil and China recorded significant increases in spillover effects, both respectively reached peaks of 54% and 61% suggesting their vulnerability to EPU and its impact on real oil prices during economic stress. The wavelet coherence largely revealed mixed directions of co-movement and heterogeneity between ROILP and EPU (GPR) across countries, indicating that the relationship between the variables was not consistent, varied over time and scale. Different from previous studies, the analysis focused on the direction of the spillover between oil prices and uncertainty measures, then estimated the numerical amount of the spillover to discover the variable that gave more shock than it received. While the wavelet coherence identified variations in coherence, across the time and frequency domain, the adoption of the rolling-window technique enabled the capture of the influence of arbitrary multiple regime changes in the spillover. The findings had some policy implications.

Crude oil price forecasting: An ensemble‐driven long short‐term memory model based on CEEMDAN decomposition and ALS‐PSO optimization

AbstractAs the lifeline of various industries, crude oil is frequently considered a pillar of economic development. The accurate and reliable prediction of crude oil price can provide investors and decision makers with valuable guidance for formulating their strategies. However, the complexity of the crude oil market and the volatility of oil prices pose significant challenges to forecasting crude oil price. To achieve higher prediction accuracy, this paper proposes a new model in which a new modal component reconstruction rule based on sample entropy (SE) is innovatively proposed and includes an improved particle swarm optimization model to avoid getting trapped in a local optimal solution. Two real crude oil price series are selected for experimentation, and the results demonstrate that the proposed model exhibits superior performance in predicting crude oil price. The developed model outperforms the compared models in terms of mean absolute error, root‐mean‐square error, mean absolute percentage error, and coefficient of determination. This result indicates that Complete Ensemble Empirical Mode Decomposition with Adaptive Noise exhibits better decomposition performance. SE can effectively reduce error accumulation, and particle swarm optimization with an adaptive learning strategy (ALS‐PSO) achieves better optimization results for a long short‐term memory network compared with PSO only. Therefore, the proposed model is an effective crude oil price prediction tool that can be applied in practice for investment and policy‐making.

Identifying money and inflation expectation shocks to real oil prices

The paper extends the well-known three-variable SVAR model that explains real oil prices based on supply and demand shocks to the oil market. We identify significant monetary sources of shocks to real oil prices through a money supply shock and an inflation expectations shock. Results indicate robust significance of these two monetary shocks under a variety of time periods, using an alternate aggregate demand variable, and adding a fourth fundamental variable based on oil inventories. We also use alternative money aggregates for the money supply. Given their significance, we derive a historical variance decomposition of real oil price changes by each shock's contribution. We find a significant displacement of oil supply and demand factors by monetary factors that we match up to historical US monetary policy regimes. During major oil price episodes when monetary shocks dominate, the US money supply and inflation expectation shocks largely explain oil price increases above fundamentals. We interpret this in terms of the US monetary policy during crisis periods and find a common component of that policy linked to oil price episodes. Results imply that US monetary policy led to unintended consequences in energy markets. The results could facilitate improvements in international energy policy, US monetary policy, and global economic stability.

Forecasts of the real price of oil revisited: Do they beat the random walk?

In macroeconomic forecasting, the real price of oil is traditionally computed as the monthly average price of oil deflated by the price index. Consequently, the no-change forecast used to benchmark forecasts of the real price of crude oil is a monthly average price. We demonstrate that an alternative no-change forecast which reflects the random walk forecast from daily oil prices – the end-of-month price – is significantly more accurate in predicting the real price of oil up to one year ahead. We find that at the one-step-ahead prediction, all existing forecasts that outperform the monthly average no-change forecast perform worse than the end-of-month no-change forecast. The results call into question the usefulness of existing forecasting approaches for the real price of crude oil relative to naive forecasts.

Hydrocarbon price spillover to banking performance in Eurozone

AbstractThe current study investigates the impact of real oil price shocks on the Eurozone banking sector from February 2009 to February 2022, using the Structural Vector Autoregressive method to distinguish the reaction between Eurozone bank indices and three structural indicators in the oil market shocks. The shocks include global oil demand, supply shock, and specific oil market shocks. Our findings show that the banking sector in the Eurozone responds positively toward an oil‐specific demand shock (oil price) in the short run, but it responds negatively in the medium and long run that lasts for a long time. The banking sector, on the contrary, does not react to supply shocks, which provide a significant policy implication for regulators and policymakers.

실질유가와 실질실효환율의 불확실성이 한국 신재생에너지 산업의 품목별 실질수출에 미치는 비대칭적 영향

This study analyzes the asymmetric long and short-run effects of real oil price (ROP) and real effective exchange rate (REER) uncertainties on real exports (RX) by items in the Korean new renewable energy (NRE) industry. In this study, the heterogeneous impact on the export size of uncertainty variables from January 2000 to December 2022 are examined using the nonlinear autoregressive distributed lag (NARDL) and quantile regressions (QR) methods. The estimation results of the NARDL model showed that the energy storage system (ESS) was most affected by uncertainty variables in both the short- and long-run, followed by fuel cells, oceans, smart meters, and solar and wind power. Meanwhile, the results of the NARDL asymmetry analysis showed that uncertainty variables in both the short- and long-run had the greatest asymmetric effect on fuel cells and smart meters. Additionally, the QR empirical results according to the RX size show that increasing the ROP, decreasing the REER, and increasing the REER volatility have a significant impact on the small RX size. However, decreasing the ROP and REER have a significant impact on the large RX size. Policy authorities should apply trade and exchange rate policies in an optimal combination to reduce the impact of ROP volatility on the RX in the NRE sector while considering REER volatility. Additionally, exporters in the NRE industry should seek to improve quality competitiveness through high-tech development and hedge strategies using internal and external management techniques to minimize the impact of price volatility on the RX of NRE Industry.

The impact of oil price shocks on the agricultural commodity prices

AbstractIn this study, we empirically examine the effects of oil‐related shocks on the prices of nine agricultural commodities for the period 1974:01–2022:02. We decompose real oil prices into three independent parts: oil supply shocks; global demand shocks; demand shocks that are specific to the crude oil market applying a symmetric VAR model. Then, we assess the effects of these three shocks on the prices of nine major agricultural commodities individually. Based on our findings, we reveal that the responses of agricultural commodity prices to an oil price change depend significantly on the timing and the driver of the underlying oil price change.