Relative performance of statistical and fuzzy regression models in estimation of gasoline demand in Iran

Gasoline is the most important energy product in the passenger transportation sector in Iran. Gasoline demand survey has a high priority in Iran because of its ever-increasing consumption. The most important challenges for this purpose are uncertainties resulting from structural failure of economy, changing of policies and lack of accurate data. This research aims to specify the variables explaining the gasoline demand in Iran and to estimate gasoline demand by using the statistical and fuzzy regression models over the period 1981-2007. Finally, the models were compared using standard criteria. The results indicate that both methods have enough accuracy for estimating and forecasting gasoline demand. In addition, there is a significant relationship between gasoline price, car per capita and trend as explanatory variables of gasoline demand per capita.

Abstract licence: CC BY-NC

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