Today the quantitative assessment of economic and social impacts of petroleum products supply constraints is one of the main policy issues in Iran. This issue arises from the fact that importing gasoline, gasoil and liquefied petroleum gas (LPG) is restricted by international sanctions. In this paper, we showed that a demand driven Social Accounting Matrix (SAM) is not a suitable tool for answering the above question. So, a modified SAM, known as mixed supply driven SAM is suggested. For this purpose the energy SAM of 2006 is used.

  The overall results reveal that: 1) Petroleum products supply constraints have the most impacts on crude oil and natural gas, retail and wholesale, chemical and agricultural sectors.2) Operating surplus has the most reduction among the other production factors. Results also showed that the fall of urban income as a consequence of supply constraints is more than rural labor either relatively or absolutely.

Abstract

 Forecasting of crude oil price plays a crucial role in optimization of production, marketing and market strategies. Furthermore, it plays a significant role in government’s policies, because the government sets and implements its policies not only according to the current situation but also according to short run and long run predictions of important economic variables like oil price. The main purpose of this study is modeling and forecasting spot oil price of Iran by using GARCH model and A Gravitational Search Algorithm. Performed forecasts of this study are based in static and out-of-sample forecasting and each subseries data is divided in to two parts: data for estimation and data for forecasting. The forecast horizon is next leading period and its length is one month. In this study the selected models for forecasting spot oil of Iran are GARCH(2,1) and a Cobb Douglas function which is functional of prices of 5 days ago. Finally, the performances of these models are compared. For comparison of these models MSE, RMSE, MAE, and MAPE criteria are used and the results indicate that except in MAPE criterion, the mentioned criteria are smaller for GARCH model in comparison to GSA algorithm.