Gasoline price predictability: insights from consumer vehicle‐buying assessments

2021 ◽  
Author(s):  
Hamid Baghestani
Keyword(s):  
Author(s):  
Jeremy Mattson

This study estimates the effects of gas prices on bus ridership for different types of transit systems. Because the price of gas can have a delayed effect on the demand for transit, a dynamic polynomial distributed lag model is utilized which measures short- and longer-run effects. The model is first applied to aggregate data for cities of different sizes and then to three specific small urban and rural transit systems in the Upper Great Plains. The results show that bus ridership is fairly inelastic with respect to gasoline price. Most of the estimated elasticities are in the range of 0.08 to 0.22, with two estimates being as high as 0.5.


2018 ◽  
Vol 10 (12) ◽  
pp. 43
Author(s):  
Feng Xu ◽  
Mohamad Sepehri ◽  
Jian Hua ◽  
Sergey Ivanov ◽  
Julius N. Anyu

Accurate prediction of gasoline price is important for the automobile makers to adjust designs and productions as well as marketing plans of their products. It is also necessary for government agencies to set effective inflation monitoring and environmental protection policies. To predict future levels of the gasoline price, due to difficulties of obtaining accurate estimates of influential external factors, data driven time-series forecasting models thus become more suitable given the convenience and practicability they are providing. In this paper, five popular time-series forecasting models, i.e., ARIMA-GARCH, exponential smoothing, grey system, neural network, and support vector machines models, are applied to predict gasoline prices in China. Comparing the performances of these models, it is noted that for this specific time series, a parsimonious ARIMA model performs the best in predicting the gasoline prices for a short time horizon, while for the medium length and long run the SVR and FNN models outperforms others respectively.  


Energy Policy ◽  
2014 ◽  
Vol 73 ◽  
pp. 225-233 ◽  
Author(s):  
Michael L. Polemis ◽  
Panagiotis N. Fotis
Keyword(s):  

2003 ◽  
Vol 85 (3) ◽  
pp. 772-776 ◽  
Author(s):  
Lance J. Bachmeier ◽  
James M. Griffin
Keyword(s):  

2018 ◽  
Vol 57 (4) ◽  
pp. 1171-1200
Author(s):  
Jonathan E. Ogbuabor ◽  
Anthony Orji ◽  
Gladys C. Aneke ◽  
Manasseh O. Charles

2021 ◽  
pp. 1532673X2110434
Author(s):  
Sung Eun Kim ◽  
Joonseok Yang

Gasoline prices are often a heated topic during presidential election campaigns in the United States. Yet, presidents have limited control over gasoline prices. Do voters reward or punish the president for changes in gasoline prices? Why might voters blame the president for an outcome beyond direct presidential control? This study addresses these questions by testing the effects of gasoline prices on pocketbook retrospection by voters. To capture the personal economic burden of gasoline prices, we rely on average driving times to work, given the inelastic nature of gasoline consumption for commuting. The results provide evidence for pocketbook voting: constituencies with longer average driving times to work are more likely to hold the president accountable for gasoline price increases. These findings have broader implications regarding electoral accountability and rationality in voting.


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