Mojtaba Abbasian; Ali Sardar Shahraki; Javad shahraki
Abstract
Energy plays a significant role in today's developing societies. The role of energy demands to make decisions and policy with regard to its production, distribution, and supply. The vital importance of energy, especially fossil fuels, is a factor affecting agricultural production. This factor has a great ...
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Energy plays a significant role in today's developing societies. The role of energy demands to make decisions and policy with regard to its production, distribution, and supply. The vital importance of energy, especially fossil fuels, is a factor affecting agricultural production. This factor has a great influence on the production of agricultural products in Iran. The forecast of the consumption of oil products by the agricultural sector can help managers and planners to adopt sound management practices for their consumption. Presently, artificial neural networks are regarded as a powerful tool for the analysis and modeling of nonlinear relationships. The present study employed GMDH and RBF artificial neural networks to estimate the consumption of oil products by the agricultural sector. The underpinning parameters were selected to include the value added to the fixed price, rural population, agricultural land area, agricultural mechanization (tractor), and the consumption rate of oil products, electricity, price of oil products, and total energy use by the agricultural sector for the period of 1967-2017. The comparison of MSE, MAE, and MAPE for the GMDH and RBF models showed that the GMDH neural network was highly capable of modeling the energy consumption of the agricultural sector.
Amir T. Payandeh Najafabadi; Marjan Qazvini; Reza Ofoghi
Abstract
There are several researches that deal with the behavior of SEs and their relationships with different economical factors. These range from papers dealing with this subject through econometrical procedures to statistical methods known as copula. This article considers the impact of oil and gold price ...
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There are several researches that deal with the behavior of SEs and their relationships with different economical factors. These range from papers dealing with this subject through econometrical procedures to statistical methods known as copula. This article considers the impact of oil and gold price on Tehran Stock Exchange market (TSE). Oil and gold are two factors that are essential for the economy of Iran and their price are determined in the global market. The model used in this study is ARIMA-Copula. We used data from January 1998 to January 2011 as training data to find the appropriate model. The cross validation of model is measured by data from January 2011 to June 2011. We conclude that: (i) there is no significant direct relationship between gold price and the TSE index, but the TSE is indirectly influenced by gold price through other factors such as oil; and (ii) the TSE is not independent of the volatility in oil price and Clayton copula can describe such dependence structure between TSE and the oil price. Based on the property of Clayton copula, which has lower tail dependency, as the oil price drops, stock index falls. This means that decrease in oil price has an adverse effect on Iranian economy.
