فصلنامه تحقیقات مدلسازی اقتصادی
سال پنجم شماره 20 (تابستان 1394)

This paper aims at estimating Geometric Brownian Motion (GBM) Model، based on two central parameters in this model (volatility and drift)، and forecasting Henry Hub natural gas daily spot prices (07/01/1997-20/03/2012). Researches reveal that two mentioned parameters estimation can be satisfied with different approaches and in various time scales. Therefore، two approaches of backward looking and forward looking have been used in different time scales and sub-periods. Results show that the volatility and drift values are highly dependent on the time scale and backward results are lower than the forward ones. Moreover، along with increasing the number of random runs of the model although the fluctuating range decreases، the predicted line slope is very close to the actual line. Ultimately، the performance evaluation criteria yields that forward method، clearly in 2009، has the best performance. The sub-periods of 2001-2004 in backward and forward methods have the next best performances، respectively. These sub-periods can be used as a basis for calculating the central parameters of the model. In addition، the results suggest that relying on data used in the most recent period is not sufficiently accurate. Also، it is observed that sub-periods or time scales with higher volatility show better performance evaluation criteria، therefore they can be applied in price forecasting with GBM model.

Cigarette and tobacco products in the VAT Law is considered as one of the particular goods and in order to contorlingit’s consumption by price tools، higher tax rates than the standard rate will be levied on it. In this paper، forecasting of revenues of this tax using an approach based on the estimating of tax base has been considered. Thus the first stage، tax base (consumption expenditure) is forecasted for the period 2012 to 2015 and then tax related years by applying the tax rates، will be calculated. In this regard، Because of concerns that policy makers have access to accurate predictions of tax revenues، Supervised neural networks Method to prediction and back-propagation algorithm to train is used. The results indicate that the average annual growth of revenue from value added tax on Cigarette consumption will have 20 percent during the forecasting years.

As one of the important energy forms، natural gas consumption has an upward trend in recent years. Therefore management and planning for provision of it requires prediction of the future consumption. But many of prediction procedures are inherently stochastic therefore it is important to have better knowledge about the robustness of prediction procedures. This paper compares robustness of two prediction procedures; Artificial Neural Networks as a nonlinear and ARIMA as a linear model. using resampling method to predict the monthly consumption of natural gas in the household sector. Data spans from 2001-4 to 2012-3، to train the networks، we used genetic algorithms and Particle Swarming Optimization then results were compared using 10-fold method. According to the results، the particle swarm optimization (PSO) outperforms the genetic algorithm. Then we used data from 2001-4 to 2010-3، with resampling by 2000 to predict the natural gas consumption for the 2001 -4 to 2012-3 and to form critical values. Results show that prediction by a mixed method using ANN and PSO is more robust than ARIMA method.

This study considers the subject of social capital measurement and its problems. Because of the social capital is the qualitative subject، therefore its measurement have special problems، and there is no the same approach in this matter. These problems are in both of international and national level. For the reason، there are different methods to measure social capital. These methods have caused their results to be different and sometimes conflict. These differences are very high، such that the correlation between these indexes is sometime zero، negative and positive.

Financial institution as a non-bank financial institutions، institutions that are active in mediating funds in financial markets. Services are in many ways similar to the services provided by banks. Because the relationship between the development of non-bank financial institutions and Iranian gross domestic production (GDP) seem important. In this context، the main objective of this study was to investigate the effect of non-bank financial institutions in the areas of facilities of GDP contracts with other variables such as per capita GDP and employment effects on the labor force for the period 1999Q1-2013Q4. To estimate the Generalized Method of Moments (GMM) is used to model estimation results indicate a significant positive impact on the development of non-bank financial institutions and facilities with regard to Islamic contracts. The per capita income and employment variables have a significant positive impact on GDP respectively.

Fiscal decentralization that is considered a transfer of responsibilities that associated with accountability to sub – national governments، increases efficiency and providing better access to public goods in the Economy. According to the five-year development plans of Iran creating and allocating structure for provincial budgeting، fiscal decentralization generally is moving in the costs of its Provinces in order to give more responsibility to the provincial development projects. The aim of this study is an investigation of effect for partial fiscal decentralization on regional economic growth of Iran. Fiscal decentralization index is proportion of provincial''s capital assets to government''s capital assets، So this researches the effects of decentralization on economic growth in the framework of Solow''s growth model. That the results based on data from 30 provinces between 2000 and 2007 on the panel data estimation، shows partial fiscal decentralization which has a non-linear relationship with the growth (convex shape) and partial fiscal decentralization Indicts the Optimal degree in growth of regional economy in Iran.

The main purpose of the present study is to evaluate the relationship between the oil price shocks and the indexes of the Stock Exchange Market of Tehran. The present study is conducted by using from the data obtained from the common working days between world oil market and the Stock Exchange Market of Tehran between 8 December 2008 and 19 Mars 2014. In the present study the nested test، Johansen''s co-integration test، vector error correction model and Engle- Granger method have been used in order to represent the long run relationship between the variables. The empirical findings of this paper indicate that there is a significant and positive long-run equilibrium between the OPEC oil price and six indices of capital market (total stock index، industry index، the price index of 50 companies، top 50 indices، return and price index، Index of 30 large companies). Also there is no significant long run equilibrium relationship between the OPEC oil prices and three indexes namely first market، second market and free float indexes.