Estimation of asymmetric responses of U.S. retail fuel prices to changes in input prices based on a linear exponential adjustment cost approach

Karol Szomolányi (), Martin Lukacik () and Adriana Lukacikova ()
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Martin Lukacik: University of Economics in Bratislava
Adriana Lukacikova: University of Economics in Bratislava

Central European Journal of Operations Research, 2022, vol. 30, issue 2, No 16, 757-779

Abstract: Abstract Numerous studies have indicated that retail fuel prices respond more quickly when crude oil prices rise than when they fall. We suggest that the fuel price making process is discretionary with nonlinear price adjustment costs. Then the theories do not assume linear cointegration relation between input and output prices. This paper analyzes the asymmetric reactions of retail gasoline and diesel prices to changes in input prices in the U.S.A. by use of empirical approach based on the linear exponential adjustment costs formulation. This allows us to measure average weekly price biases caused by asymmetries. The orthogonality conditions implied by the rational expectation hypothesis make the generalized method of moments a natural candidate to estimate the reaction function. In order to ensure the robustness of our results, other estimators are used for estimation in some cases. The econometric analysis indicates that the reaction functions of several retail fuel prices (diesel and gasoline, regional, state and city prices) are correlated and, therefore, it is appropriate to estimate them using the system estimators. The following results arise from our study: retail fuel prices react asymmetrically to changes in crude oil spot prices at an overall level, as well as at the level of regions and the given states and cities; retail fuel prices react asymmetrically to changes in American port spot fuel prices; this study does not confirm the asymmetric relationship between spot crude oil prices and port spot fuel prices.

Keywords: Asymmetric price responses; Fuel prices; Linear exponential adjustment cost function; Generalized method of moments (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s10100-021-00783-0

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