Elsevier

Energy Policy

Volume 35, Issue 1, January 2007, Pages 156-177
Energy Policy

Asymmetric error correction models for the oil–gasoline price relationship

https://doi.org/10.1016/j.enpol.2005.10.016Get rights and content

Abstract

The existing literature on price asymmetries does not systematically investigate the sensitivity of the empirical results to the choice of a particular econometric specification. This paper fills this gap by providing a detailed comparison of the three most popular models designed to describe asymmetric price behavior, namely asymmetric ECM, autoregressive threshold ECM and ECM with threshold cointegration. Each model is estimated on a common monthly data set for the gasoline markets of France, Germany, Italy, Spain and UK over the period 1985–2003. All models are able to capture the temporal delay in the reaction of retail prices to changes in spot gasoline and crude oil prices, as well as some evidence of asymmetric behavior. However, the type of market and the number of countries which are characterized by asymmetric oil–gasoline price relations vary across models. The asymmetric ECM prescribes that long-run price asymmetries are most likely to be found in the second stage of the transmission chain. Conversely, the ECM with threshold cointegration suggests that long-run price asymmetries vary across countries and markets. Short-run price asymmetries are captured by the asymmetric ECM specification and the TAR-ECM. The latter model suggests that all European countries are likely to be affected by asymmetries at the distribution stage, while the results obtained with the asymmetric ECM are mixed.

Introduction

The transmission of positive and negative changes in the price of oil to the price of gasoline is very relevant for both consumers, who tend to be very sensitive to the money they pay for the fuel consumed by their cars, and researchers, who are often requested to provide plausible explanations of the observed temporal behavior of the oil–gasoline price relationship.

The notion that gasoline prices react quickly to oil price increases and slowly to oil price reductions is largely accepted among consumers. The levels recently hit by oil and gasoline prices, the present uncertainty in supply and reserve availability, and growing world energy demand have contributed to reinvigorate the interest in the asymmetric transmission of changes in the price of oil to the price of gasoline. According to the latest Oil Market Report issued by the International Energy Agency, crude oil prices strengthened since mid May 2005 up to the end of August 2005. During the same days, the price of gasoline has risen even more sharply, supporting the notion that input price increases are immediately transmitted to output prices. WTI crude oil daily posted price was quoted below 44US$ per barrel ($/bbl) in mid May 2005, it was above 58$/bbl in late July 2005, and it recorded quotations above 66$/bbl in late August 2005 (i.e. +14% in 1 month). IPE Brent crude oil daily closing price was between 45$/bbl and 50$/bbl in mid May 2005, and it jumped to more than 65$/bbl in late August (that is, +8% between July and August). Conversely, NYMEX unleaded gasoline daily price was below 1.50US&dollar per gallon ($/gal) in mid May 2005, it recorded 1.75$/gal in late July 2005 and soared to 2.50$/gal in late August 2005 (i.e.+43% in 30 days). At the end of the first decade of October 2005 WTI and Brent prices were around 60$/bbl, while unleaded gasoline price was back to the end-of-July level of 1.75$/gal. The scenario depicted above rises at least one major question: when oil prices fall, are gasoline prices likely to decrease immediately, or will they respond with some delay?

The literature looking for empirical evidence in support of asymmetries in the transmission mechanism is wide. This literature employs a variety of reduced-form dynamic regression models relating the price of gasoline to the price of oil. Findings vary across countries, time periods, frequency of the data, markets, models, tax regimes and petroleum fiscal systems. This explains the reason why there is no clear-cut evidence in the empirical literature that prices rise faster than they fall.

The aim of this paper is to address the following question: to what extent does the empirical evidence on price asymmetries depend on the specific model used to analyze the relationship between gasoline and oil prices? This question is particularly relevant, since the existing literature does not systematically investigate the sensitivity of the empirical results to the choice of a particular econometric specification. Actually, one of the few attempts to explain the variability of the empirical findings on price asymmetries goes back to Shin (1994), who nevertheless argues that the contradictory results are mainly due to the lack of homogeneity in the data, rather than to different models.

The present paper fills this gap by providing a detailed comparison of the three most popular models designed to describe asymmetric price behavior, namely asymmetric error correction model (henceforth asymmetric ECM), autoregressive threshold ECM and ECM with threshold cointegration. In order to reduce the proportion of variability in the results due to different countries, periods of time, data frequencies and markets, each model is estimated on a common monthly data set which describes the retail and wholesale gasoline markets of France, Germany, Italy, Spain and UK over the period 1985–2003. The empirical results obtained from the different econometric specifications are compared, the predictions of each model are interpreted from a policy perspective, and each model is evaluated in terms of its ability to capture specific types of asymmetric price behavior.

The plan of the paper is as follows. An exhaustive review of the econometric literature on price asymmetries in the gasoline market is offered in Section 2. Section 3 describes the data and the econometric models used in the empirical analysis. The results are presented and discussed in Section 4. Section 5 provides some concluding remarks.

Section snippets

Overview of the literature

Numerous attempts have been made to analyze the relationship between the price of crude oil and the price of gasoline (or other petroleum products). Studies typically differ in one or more of the following aspects: the country under scrutiny; the time frequency and period of the data used; the stage of the transmission mechanism, i.e. either retail or wholesale, or both; the dynamic model employed in the empirical investigation; whether the price data are gross or net of taxes.

The problem of a

Data and econometric models

In this paper, the transmission of changes in upstream prices to downstream prices is investigated at different stages of the process of price formation. We consider the price of crude oil (CR) together with the gasoline spot price (SP), the before-tax gasoline retail price (NR) and the exchange rate between the US dollar and individual national currencies (ER) for five European countries, namely France, Germany, Italy, Spain and UK.2

Empirical results and discussion

We estimate the asymmetric error correction models described in Section 3 to describe the gasoline-price relation in France, Germany, Italy, Spain and UK over the period 1985–2003. Following the majority of the empirical literature, our study uses the net-of-taxes gasoline prices. Given the different fiscal systems which characterized the countries under scrutiny, this choice will ease the comparison of the empirical findings between countries.

In order to gain a deeper understanding of the

Conclusion

Contrasting evidence about price asymmetries in the oil-product price relationship has been found in the applied econometric literature. Different data, together with different econometric models, have been employed in different studies. One of the major causes of the very large volatility in the empirical findings is the heterogeneity of the econometric approaches used in the empirical applications. Thus, a thorough assessment of the impact of different econometric approaches on the results

Acknowledgments

The authors wish to thank Umberto Cherubini, Marzio Galeotti, Alessandro Lanza, Anil Markandya, Micheal McAleer, Ryozo Miura and Kazuhiko Ohashi for insightful discussion, and seminar participants at the Fondazione Eni Enrico Mattei, the Graduate School of International Corporate Strategy, Hitotsubashi University, Tokyo and the University of Milan-Bicocca for useful comments and suggestions.

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