Can U.S. EIA Retail Gasoline Price Forecasts Be Improved Upon

Assessment of the relationship between oil prices and US oil stocks

This article examines how the shale oil revolution has shaped the evolution of U.S. crude oil and gasoline prices. It puts the increased production of shale oil into historical perspective, highlights uncertainties about future shale oil production, and cautions against the view that the United States will become the next Saudi Arabia. It then reviews how the ban on U.S. crude oil exports, capacity constraints in refining and transporting crude oil, and the regional fragmentation of the global market for crude oil after 2010 have affected U.S. oil and gasoline prices. In particular, the article discusses the reasons for the persistent wedge between U.S. and global crude oil prices in recent years, explains why domestic oil trading at a discount has not lowered U.S. gasoline prices, and discusses the role of shale oil in causing the 2014 oil price decline. Finally, the article explores the implications of the shale oil revolution for the U.S. economy and explains why increased shale oil production is unlikely to create a boom in oil-intensive U.S. manufacturing industries.

The world annual biofuel production has exceeded 100 billion litres in 2009. The development of the biofuel production is partly influenced by the government support programs and partly by the development of oil prices. The main purpose of this paper is to analyze the statistical relationship between ethanol, gasoline and crude oil prices. We aim to check the correlation among these variables and to analyze the strength and direction of a possible linear relationship among the variables. We are interested in analyzing how each variable is related to another, so we evaluate the inter-relationship among the variables in the Vector Autoregression (VAR) and the Impulse Response Function (IRF). In order to achieve our goal, we first collected weekly data for each variable from January, 2000 to October, 2009. The results provide evidence of the cointegration relationship between oil and gasoline prices, but no cointegration between ethanol, gasoline and ethanol, oil prices. As a result, we used a VAR model on first differences. After running the Impulse Response Function, we found out that the impact of the oil price shock on the other variables is considerable larger than vice versa. The largest impact of oil price shock was observed on the price of gasoline.  

When oil prices increase, we are likely to see gas prices increase instantaneously. When oil prices decrease, there tend to be time lags associated with lower gas prices. (Bacon 1991) illustrates this response as rockets and feathers: gasoline prices shooting up like rockets in responses to positive oil price shocks and floating down like feathers in response to negative shocks This article investigates the rocket and feathers hypothesis between gas stations in the Cleveland Ohio area. This analysis shows that it takes roughly 4.5 weeks for the price shock to be absorbed by retail gasoline prices. The asymmetry appears to increase as time from the initial shock passes, as initially expected.

Gasoline markets in 1996 and 1997 provided several spectacular examples of petroleum market dynamics. The first occurred in spring 1996, when tight markets, following a long winter of high demand, resulted in rising crude oil prices just when gasoline prices exhibit their normal spring rise ahead of the summer driving season. Rising crude oil prices again pushed gasoline prices up at the end of 1996, but a warm winter and growing supplies weakened world crude oil markets, pushing down crude oil and gasoline prices during spring 1997. The 1996 and 1997 spring markets provided good examples of how crude oil prices can move gasoline prices both up and down, regardless of the state of the gasoline market in the United States. Both of these spring events were covered in prior Energy Information Administration (EIA) reports. As the summer of 1997 was coming to a close, consumers experienced yet another surge in gasoline prices. Unlike the previous increase in spring 1996, crude oil was not a factor. The late summer 1997 price increase was brought about by the supply/demand fundamentals in the gasoline markets, rather than the crude oil markets. The nature of the summer 1997 gasoline price increase raised questions regarding production and imports. Given very strong demand in July and August, the seemingly limited supply response required examination. In addition, the price increase that occurred on the West Coast during late summer exhibited behavior different than the increase east of the Rocky Mountains. Thus, the Petroleum Administration for Defense District (PADD) 5 region needed additional analysis (Appendix A). This report is a study of this late summer gasoline market and some of the important issues surrounding that event.

Gasoline and crude oil price movements have been the focus of many studies in the last decade. We use the asymmetric error correction model (ERM) to examine the hypothesis of asymmetric pricing for both regular and premium gasoline markets at the US national level and in the four states with the highest gasoline consumption. Using weekly crude oil and retail gasoline prices from June 2000 to February 2023, the results show an asymmetric response in the gasoline market for all four states and at the national level. However, the adjustment speed tends to differ for the types of gasoline and across states. The implications of these results for policy and welfare are discussed in this study.

Grounded in the Granger causality test, vector autoregression (VAR) model, and BEKK-GARCH model, our current study aims to examine the effect of mean and volatility spillover between the United States (US) economic policy uncertainty (EPU) and West Texas Intermediate (WTI) crude oil price. Using the US EPU monthly index and WTI spot price data from 1996 to 2019, we revealed that there is a one-way Granger causality link between the US EPU and spot price of WTI crude oil. The VAR model not only illustrated that there is a mean spillover effect between WTI oil price and US EPU, but they will also be affected by its memory, as well as the other’s past. At the same time, it also pointed out that this correlation has positive and negative directions. The BEKK-GARCH model test yielded similar conclusions to the VAR model and, importantly, proved a two-way volatility spillover effect between the US EPU and WTI spot price fluctuations. In conclusion, US economic policy has a substantial influence on the variation of global crude oil prices, as an essential strategic reserve resource and will also influence the government’s economic policy formulation. Understanding the association between WTI crude oil price and policy uncertainty not only helps investors to manage assets allocations and mitigate losses but also guides US policymakers to adjust the energy structure for economic sustainability.

According to many studies, the transmission of oil prices to retail fuel prices is asymmetric. Fuel prices react faster if oil prices rise and more slowly if oil prices fall. We use the simple and dynamic asymmetry models, error correction models, threshold autoregressive cointegration, and an approach based on the adjustment cost function in the linear-exponential form to verify the hypothesis of asymmetric reactions of gasoline and diesel prices in Croatia. The analysis uses a weekly time series of Croatian fuel prices obtained from the European Commission Weekly Oil Bulletin and BRENT oil prices from the US Energy Information Administration. Different standard econometric procedures lead to different results. Nevertheless, the approach based on the linear-exponential lost function confirmed the price asymmetries in the Croatian market.

Asymmetric pass-through of oil prices to gasoline prices with interval time series modelling

The paper features an examination of the link between the behaviour of oil prices and DowJones Index in a nonlinear autoregressive distributed lag NARDL framework. The attraction of NARDL is that it represents the simplest method available of modelling combined short- and long-run asymmetries. The bounds testing framework adopted means that it can be applied to stationary and non-stationary time series vectors, or combinations of both. The data comprise a monthly West Texas Intermediate (WTI) crude oil series from FRED, commencing in January 2000 and terminating in February 2019, and a corresponding monthly DOW JONES index adjusted-price series obtained from Yahoo Finance. Both series are adjusted for monthly USA CPI values to create real series. The results of the analysis suggest that movements in the lagged real levels of monthly WTI crude oil prices have very significant effects on the behaviour of the DOW JONES Index. They also suggest that negative movements have larger impacts than positive movements in WTI prices, and that long-term multiplier effects take about 9 to 12 months to take effect.

This paper examined the relationship between oil prices (international oil price and domestic oil price) and stock market price in Nigeria for the period spanning 1985:1 to 2010:4. The study utilised the Johansen's multivariate cointegration test and the vector error correction model (VECM). The Johansen's test showed that the variables are cointegrated, and the cointegration equation revealed that oil prices have significant relationship with stock market price in the long run. The VECM estimate only revealed a unidirectional causality from stock market price to international oil price in the long run. A unidirectional causality was also observed from domestic oil price to stock market price in the long run. The study recommended that policymakers, financial analyst and shareholders should into cognizance changes in international oil price and domestic oil price in their financial decisions given the significant impact of oil prices on stock market price in Nigeria.

The supreme thrust of the present analysis is to explore the influences of foreign exchange reserve, exchange rate, and crude oil price on the stock index of the Dhaka stock exchange (DSE) of Bangladesh. Moreover, this study evaluates the identity of any unpremeditated relationship among the variables from the viewpoint of an emerging country like Bangladesh. Through using monthly time-series data, this study tries to discover the evidence of a long-run affiliation among the variables by using Johansen’s Cointegration test and Vector Error Correction Model (VECM). Besides, the Granger Causality technique is introduced to examine the casualty among variables where the empirical results show a causal linkage between the Dhaka stock exchange index, foreign exchange reserve, and exchange rate, moving only in one way from Dhaka stock exchange index to foreign exchange reserve and exchange rate. In contrast, no causal link was identified between Dhaka stock exchange indexes and crude oil prices. Lastly, Impulse Response Function suggests a permanent effect of all selected macroeconomic factors on the Dhaka stock exchange index in the long run and Variance Decomposition Analysis settles that, the reform in Dhaka stock exchange index can be caused by the innovation in foreign exchange reserve, exchange rate, and crude oil price.

Management It seems only the proverbial blink of an eye since the principal determinants of the price of crude oil on world markets were the tax-paid cost of the Burgan field in Kuwait and the producing allocations decided by the Texas Railroad Commission. Crude oil was in such abundant supply 50 years ago that British Petroleum, then half-owner of the Kuwait concession, and the world's largest oil producer by far, sold more than half a million BOPD of its share of production to its partner, Gulf Oil, at the overlift price, one-eighth way between the accounting cost of production (then about USD 0.80/bbl) and the posted price of USD 1.75. Gulf Oil turned around and resold most of its Kuwait overlift oil at a larger profit, and nobody seemed to care. The world was awash in oil. On the domestic front, supply was so abundant that Texas oil wells were permitted to pump for only 97 days in 1958. Suffice it to say that we no longer exist in a world of oversupply. West Texas Intermediate (WTI) futures on Nymex briefly crossed the USD 100/bbl threshold in late 2007. Alberta has become the new Kuwait, and the Texas Railroad Commission figuratively relocated from Austin to Vienna and became OPEC. Like the Seven Sisters before them, OPEC has attempted to control the price of oil on world markets, with Saudi Arabia shouldering the role of market regulator. While the majors showed impressive solidarity in their dealings with foreign governments, the supply fundamentals were not in their favor. The nationalization of IPC's holdings in Iraq, for example, was precipitated by the refusal of the majors to develop new Iraqi oil fields when there was already too much oil on the market. So what has happened to trigger the more than seventy-fold increase in the price of oil since the 1960s, when the arm's-length price of Kuwait crude was around USD 1.35/bbl, and what lessons may we glean from this history as we peer intently into the crystal ball of price predictions? The Lessons of History As Winston Churchill famously remarked, "Those that fail to learn from history are doomed to repeat it." Three principal forces have been at play over the past 50 years, and we would be remiss in ignoring them.Population and economic growth, which powered world consumption of refined products to grow from 21.3 to 84.4 million BOPD between 1960 and 2006.Cumulative oil production since 1960, which, notwithstanding published recoverable-reserves estimates to the contrary, exceeded reserves additions.The remarkable adaptability of consumers to higher prices, abetted by frequently undisciplined or short-sighted government policies that encourage inefficient use of transportation fuels.

Objective – The aim of this paper is to examine the relationship between the CPI, the brent crude oil price, and the PPI for final manufactured goods as well as the Rand/Dollar exchange rate during the past year. The study used South Africa as a proxy for developed countries. The objective is, therefore, to evaluate the effects of the increase in commodity prices on inflation and other macroeconomic variables. Methodology –The study utilised a quantitative methodological approach through the assessment of an econometric model that employed monthly data from January 2017 to May 2022. The paper utilized variables such as CPI, brent crude oil prices, PPI for final manufactured goods as well as the Rand/Dollar exchange rate. Findings – Short- and long-run relationships were established between the variables using the vector error correction model (VECM) and the Johansen co-integration equation methods. The long-run conclusions showed that high brent crude oil prices, high sunflower oil, a depreciating exchange rate and increasingly high PPI levels will lead to an increase in the CPI (Inflation). The results also indicated that oil prices still influence the basic prices of goods and services since all things need to be transported. Novelty – The results of the study showed that a perpetual international and national macro-economic environment is crucial to prevent inflationary pressures and price shocks, while volatile exchange rates unsteady PPI’s and significantly high oil and commodity prices causes cost-push inflation. Policy certainty and political stability is important to keep inflation stable and economic growth positive, which could lead to a more self-sufficient economy which are is reliant on political instability as an obstacle for positive future economic growth. Type of Paper: Empirical JEL Classification: E31, E37, E60, E63 Keywords: Russian-Ukrainian conflict, economic growth, Brent crude oil prices, PPI, CPI, exchange rates, sunflower oil. Reference to this paper should be made as follows: Neethling, J.R; Wyk, A.S.V. (2022). Analysing the rising oil price shock driven by Russia-Ukrainian tensions - effect on inflationary pressure in South Africa, J. Bus. Econ. Review, 7(3), 178–193. https://doi.org/10.35609/jber.2022.7.3(3)

ABSTRACTCausality patterns are analysed for daily Brent, West Texas Intermediate (WTI), and Argus Sour Crude Index (Argus) oil prices, Argus is the reference price for exports from Saudi Arabia, Kuwait and Iraq. Nonparametric Granger causality testing uncovers bi-directional causal links between Brent and WTI prices at multiple lags. Unidirectional causality from both Brent to Argus and WTI to Argus is also documented. If the current Saudi Arabia attempt to increase market share is successful, variations in Argus prices may start preceding movements in Brent and WTI, also.