فصلنامه اقتصاد مقداری
سال ششم شماره 3 (پیاپی 22، پاییز 1388)

Investment in common stocks is one of most beneficent alternatives in capital markets, therefore forecasting of stock price is great significance for shareholders; however the complexity of stock markets. Most studies revealed stock price in Tehran stock exchange has not random walk pattern. Besides, with regard to nonlinear and chaos system in stock market that eclipsed of political, economical and psychological conditions, we can use nonlinear artificial systems such as artificial neural networks (ANN), fuzzy neural networks (FNN) and genetic algorithms (GA’s) for forecasting stock price. Two goals are aimed in this research: 1- Design and present a model for forecasting stock price, using FNN and GA (GFNN). 2- Reduction the forecasting error of GFNN stock price forecasting model, in compare with mere ANN. At first, for examination of mentioned goals, multi layer perceptron (MLP) of ten listing companies in Tehran stock exchange has been designed. Then, after design and implementation of GFNN, the results of two models, have been compared and hypotheses have been investigated by using error evaluating criteria (MSE, R2, NMSE and MAPE). The results of research show, in compare with mere ANN, GFNN has perfect predictions and has higher speed and more strong estimation for stock price forecasting.

Energy is one of the key factors of production. The growth of industrial production is accompanied with increases in the demand for energy. More Efficient use of energy is of great importance for any system of production. This paper entertains a Granger causality test between energy consumption and the value-added of Iranian industries during 1967-2006 by using Toda-Yamamoto method. The results indicate that there is (a) a bi-directional causality relationship Between industries’ industries Value- Added and electricity consumption, (b) and uni-directional causality relationship from industries’value-added to natural gas and other petroleum products. Consequently, it is possible to pursue a reduction policy in petroleum use without any prejudice to industrial production.

Today, economic liberalizations and national and global markets have been quite significant in sustainibility of economic growth. Indeed, financial development relies on an efficient bank system, arising from competitiveness and financial liberalization. This study evaluates effects of financial development, through measuring various indices, on Iran’s economic growth. It also raises questions: what is the effect of financial liberalization on the country growth if the country’s financial system experiences a specific scenario of financial liberalization, like interest rate liberalization and its convergence toward price changes? How does privatization in banking system affect the country’s economic growth? To approach these ends, we use econometric methods (such as ARDL and ECM) and data of Iran’s banking system as well as other macroeconomic variables over 1984-2005. This allows us to explore empirically both short and long-run effects of financial development on the countryُs economic growth. The expected results confirm the significant and positive effects of interest rate convergence and privatization of the banking system on the country’s economic growth, particularly in the long-run.

Electrical industry has strong effect and is dynamic industry because of it,s infrastructural role and it,s relationship to effective factors of economic growth. Increasing efficiency and productivity are significant consideration electrical industry. Electrical production entity (power plants) is important and also most investing entity of electrical industry. Therefore according to importance of power plants, aim of this empirical paper is that to measure thechnical efficiency in year 2008 and productivity during years 2003-2008 for 26 thermal power plants of iran by Data Envelopment Analysis (DEA) method and Malmquist Index. These results explanate the under assumption of constant returns and variable in year 2008, average amount of technical efficiency of power plants was 76.4 and 92.8 respectivity and Scale inefficiency has the maximum impact on the technical inefficiency. On average the productivity growth in all of selected power plants was equal to 1.5 percent during years 2003-2008 and it was the most influential factor in productivity of technological change.

Nowadays, the economists are worrying about inappropriate income distribution and consequently, poverty, rather than wealth. Income distribution is a main element in current societies, and approximately all of the economists express that one of the most important aims and tasks of Governments is income distribution. This research concerns about effects of monetary policies on income distribution in Iran. We analyzed the data by means of vector auto regressive (VAR) model, and the final results show that there are differences between the impacts of monetary policies on income distribution in short-, medium- and long term in Iran. The expansion of money volume as a measure for monetray policy does not immediately result in increasing income inequality, however the intesifying effects of expantionary monetrary policy begins after second period and continues in the next terms.

Iran is one of the oil exporter countries that the major part of its income is revenue of the oil. Trade balance in Iran was fluctuating too much in the past decade. This paper investigates the major sources of changes in the trade balance of Iran with an emphasis on the difference between permanent and transitory disturbances to income. Applying Blanchard-Quah technique, we classified income shocks in two groups, permanent shocks and transitory shocks and we have investigated the impacts of these shocks on the trade balance. The findings support the hypothesis that transitory disturbances to income are the main determinants of changes in the trade balance. These results seem to be fairly consistent with inter-temporal models of trade balance, which demonstrate transitory shocks to income as the main source of variations in the trade balance. These results do not seem to support the idea that productivity shocks alone generate most of the variation in the trade balance.

In most growth theories, economists have been searching ways of faster economic growth to emphasize interrelation sector. In this paper, we have surveyed the interactional relationships among economic sectors (services, agriculture and industry) in period 1980 - 2004. We have used vector autoregressive models (VAR) to estimate their dynamic interrelation effects on each other. The result is that these sectors are complementary in Iran and the growth of each sector relates to other sector's growth. Also, the relationship between agriculture and industry sector is of most importance.