Table 8 Summary of the literature review
From: How do supply or demand shocks affect the US oil market?
Author | Country | Data span | Methodology | Results |
|---|---|---|---|---|
Bacon (1991) | UK | 15 June 1982–19 January 1990 | The modelling of asymmetric partial adjustment | When prices of crude oil rise, this causes an increment of gasoline prices (or other refined products) in a faster way. Conversely, the drop in crude oil prices does not provoke a faster response to gasoline prices |
Borenstein et al. (1997) | USA | March 1986–December 1992 | Cointegration | When crude oil prices fluctuate, i.e., increase or decrease, the response of the gasoline prices is asymmetric |
Girma and Paulson (1999) | USA | April 1984–December 1994 | Cointegration | Cointegration between WTI and unleaded gasoline and heating oil prices |
Gjolberg and Johnsen (1999) | USA | January 1992–August 1998 | ECM | All refined products, possibly excluding heavy fuel oil, prices are co-integrated with the crude price. Having estimated two simple error correction models, we find that the current product–crude margin deviations from a long-run equilibrium may contain significant information about the future changes in product prices and margins |
Adrangi et al. (2001) | USA | VAR model and a bivariate GARCH model | Movements in crude oil prices cause shifts in the price of the refined product used, i.e., the Los Angeles diesel. This can also happen in the opposite direction due to demand inferences | |
Bachmeier and Griffin (2003) | USA | February 1985–November 1998 | Asymmetric ECM | No evidence a pass-through response from crude oil prices to gasoline prices |
Hammoudeh et al. (2003) | USA | Cointegration, Vector ECM, ARCH/GARCH | They suggest a bidirectional causal relationship between daily crude oil and gasoline prices. He also evidences a unidirectional causality from crude oil price to heating oil | |
Grasso and Manera (2007) | France, Germany, Italy, Spain and the UK | 1985–2003 | Symmetric ECM, threshold ECM, and ECM with threshold cointegration | The type of stages and the number of countries which are characterized by asymmetric oil–gasoline price relations vary across models |
Asche et al. (2003) | USA | January 1992–November 2000 | Cointegration | In the long-run, changes in crude oil prices feed through to these refined product prices, while the reverse is not true. Given that the crude oil price seems to determine these prices, this also provides an example of supply driven market integration |
Kaufmann and Laskowski (2005) | USA | January 1986–December 2002 | ECM | An asymmetric relation between crude oil and motor gasoline is explained by refinery utilization rates and inventory behavior. Additionally, the asymmetric relation between crude oil and heating oil maybe is produced by contractual arrangements between retailers and consumers. Indeed, these results would suggest that price asymmetries might be caused by efficient markets |
Honarvar (2009) | USA | September 1981–December 2007 | Crouching ECM | The behaviour of the forms depends on the fluctuations of the crude oil price, being conditioned by the origin of the shocks, i.e., if there is a shock in the crude oil price, it could be due to market conditions. In contrast, if the shock occurs in the refined product price, the origin may be induced by “efficiency or consumers’ incentives”, i.e., the demand side |
Kaufmann et al. (2009) | USA | 25 February 1994–15 September 2006 | VECM | They show that shifts in prices of refined products do not affect crude oil prices. Hence, changes in the demand for a given refined product have effects on the product mix of refined products and thus, for the demand for crude oil, arising a situation in which excess demand may result in rising prices |
Kilian (2010) | USA | October 1973–October 2008 | Structural VAR model and VAR model | The VAR model also ignores the possibility of asymmetries in the transmission of oil price increases to retail gasoline prices |
Douglas (2010) | USA | August 1990–May 2008 | Threshold autoregressive model for the error-correction term | He evidences that retail gasoline prices exhibit asymmetric price adjustment |
Venditti (2013) | Germany, France, Italy and Spain and the USA | January 1999–September 2009 | Cointegration and Impulse-Response Functions asymmetry tests | Evidences on the rockets and feathers issue by using weekly data on gasoline and gasoil prices for the U.S., the euro area, by using nonlinear impulse response functions and forecast accuracy tests and displaying evidence of asymmetries in the U.S |
Karali and Ramirez (2014) | USA | January 14, 1994–February 4, 2011 | GARCH model | They obtain the presence of asymmetric effects in crude oil following major political, financial, and natural events. Furthermore, seasonality and day-of-the-week effects in the crude oil and heating oil markets are encountered |
Atil et al. (2014) | USA | January 1997–September 2012 | NARDL model | They evidence that a shock in the crude oil price transfers in a non-linear manner to gasoline and natural gas prices and shows that energy products prices dynamics possess a complex relationship |
Han et al. (2015) | USA | 3 October 2005–30 June 2014 | VAR and ECM, Granger causality, Markov model and Impulse-Response Functions | They find bidirectional causality between crude oil and gasoline prices when facing a supply shock. They show that the interaction between crude oil price and gasoline price possess long-live |
Bremmer and Kesselring (2016) | USA | 1/1/2008–12/31/2009 | ECM Granger causality test | When the data set is partitioned into three subsets, regression results and their impulse response functions provide evidence in favor of “rockets and feathers” asymmetric pricing behavior during periods of generally rising crude oil prices. However, there is also evidence that during periods of generally falling oil prices “balloons and rocks” asymmetric pricing behavior prevails |
Kpodar and Abdallah (2017) | 162 countries | January 2000–December 2014 | VAR model and Impulse-Response Functions | Their results point out that positive shocks on crude oil prices possess a larger impact than negative shocks on gasoline prices response |
Baumeister et al. (2018) | USA | January 1992–September 2012 | Verleger’s decomposition and mean-squared prediction error (MSPE) | They explored the predictive content of product spreads for the WTI spot price of crude oil, showing that many approaches favored by practitioners do not work well in practice, and they derived alternative forecasting models that do. Although their analysis focused on forecasting the real price of oil, they note that our approach can be easily adapted to forecasting the nominal price of oil. These findings support the conclusion that there is valuable predictive information in product spot price spreads |
Martinez et al. (2018) | USA | 14 June 2006–16 February 2017 | Wavelet local multiple correlation | They find that the wavelet correlations are strong throughout the period studied and show a strong decline in correlation values from 2013 to 2015 (due to the overproduction of tight oil in the U.S. and a slowdown in global demand for oil) when seven commodities (crude oil -WTI- and six refined products -conventional gasoline, RBOB regular gasoline, heating oil, Ultra-Low-Sulphur diesel fuel, kerosene and propane-) are analyzed |
Bilgin and Ellwander (2019) | OECD countries | 988Q1–2017Q3 | Structural VAR | They show that despite the parsimony of the identifying assumptions, the information on global fuel consumption helps to provide comparatively sharp insights on elasticities and other quantitative features of the global oil market |
Martin-Moreno et al. (2019a) | Germany, France, Italy and the UK | January 2005–November 2013 | Markov-switching model and TAR-ECM | In general, the results show evidence of an asymmetric response of gasoline and diesel prices to changes in the price of crude oil, both in the short-run and with respect to the adjustment towards long-run equilibrium. These price asymmetries fall in line with the “rockets and feathers” hypothesis |
Martin-Moreno et al. (2019b) | Spain | January 2009–December 2017 | Markov-switching model and TAR-ECM | For small changes in international oil prices there is neither price asymmetry nor rockets and feathers behavior in the retail markets. However, price asymmetries in line with rockets and feathers behavior in retail gasoline and gasoil markets are present when these changes exceed a certain threshold |
Kyritsis and Andersson (2019) | USA | 2 January 1997–29 December 2017 | Granger and Quantile causality | They show a bidirectional causal relationship between heating and crude oil price returns and between natural gas and crude oil price returns, respectively. It is worth noting that they interpret causality as a predictability way instead of studying structural economic relations |
Gosinska et al. (2020) | European countries | January 2000–July 2016 | Threshold CVAR | It is shown that between the European and domestic wholesale markets fuel prices adjust symmetrically and asymmetrically between the domestic wholesale market and the retail market. This finding confirms that the most probable cause of asymmetric price adjustments (especially in new EU member states) is the behaviour of petrol stations and not of oil companies |
Olayungbo and Ojeyinka (2021) | Nigeria | 1973Q1–2020Q2 | Hidden cointegration and ECM | They find that positive and negative components of both the crude oil and petroleum prices move together in the long run. The result suggests evidence of long-run asymmetry in Nigeria. The empirical findings from both the long-run and short-run results show that petroleum prices in Nigeria respond asymmetrically to changes in crude oil prices. Specifically, the outcomes from the study reveal that positive changes (increase) in crude oil prices produce a larger and stronger effect on petroleum prices than the effect of negative changes (decrease) in crude oil prices indicating evidence of an asymmetric relationship between the two prices in Nigeria. Thus, the findings confirm the existence of the rocket and feather hypothesis in the retail energy market in Nigeria |
Bakhat et al. (2022) | Bulgaria (BG), Cyprus (CY), Germany (DE), France (FR), Greece (GR), Italy (IT), Poland (PL), Romania (RO), Spain (SP), the United Kingdom (UK) and the United States of America (US) | 2009–2020 | NARDL model | The results show that both asymmetries, in terms of speed and magnitude, exist for many of the analyzed markets, demonstrating the importance of not only accounting for the impact but also for the mean lag of the response |
Ederington et al. (2021) | USA | 24 June 1988–26 April 2019 | Granger causality | They cannot evidence Granger causality from product prices to oil prices is found for the full sample period nor the period up to the end of 2005, but evidence that gasoline prices Granger-caused oil prices is found for post-2005. Similar results are found for an extended model that also includes potentially endogenous real market variables related to supply and demand in the oil, heating oil and gasoline markets |
Vides et al. (2021) | USA | 16 June 2006–29 January 2021 | FCVAR model | They evidence that the order of integration of the crack spread displays a long memory process. Finally, by attending to the coefficient adjustments, supply-driven market integration is given. Additionally, the Verleger hypothesis is rejected for all refined products, corroborated by the component share |