Premium
Dynamic relationship analysis of us gasoline and crude oil prices
Author(s) -
Liu LonMu
Publication year - 1991
Publication title -
journal of forecasting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.543
H-Index - 59
eISSN - 1099-131X
pISSN - 0277-6693
DOI - 10.1002/for.3980100506
Subject(s) - outlier , econometrics , gasoline , crude oil , autoregressive integrated moving average , brent crude , lag , time series , autocorrelation , stock (firearms) , economics , statistics , computer science , volatility (finance) , mathematics , engineering , petroleum engineering , computer network , mechanical engineering , waste management
Abstract This paper studies the dynamic relationships between US gasoline prices, crude oil prices, and the stock of gasoline. Using monthly data between January 1973 and December 1987, we find that the US gasoline price is mainly influenced by the price of crude oil. The stock of gasoline has little or no influence on the price of gasoline during the period before the second energy crisis, and seems to have some influence during the period after. We also find that the dynamic relationship between the prices of gasoline and crude oil changes over time, shifting from a longer lag response to a shorter lag response. Box‐Jenkins ARIMA and transfer function models are employed in this study. These models are estimated using estimation procedure with and without outlier adjustment. For model estimation with outlier adjustment, an iterative procedure for the joint estimation of model parameters and outlier effects is employed. The forecasting performance of these models is carefully examined. For the purpose of illustration, we also analyze these time series using classical white‐noise regression models. The results show the importance of using appropriate time‐series methods in modeling and forecasting when the data are serially correlated. This paper also demonstrates the problems of time‐series modeling when outliers are present.