Journal of Economic Modelling
Year:2010 | Volume:3 | Issue:4 (10)|Papers Count:11

The aim of this paper is to evaluate the asymmetric effects of oil shocks on output in IRAN during 1959-2007. To do this, we are going to study three effects of oil income shocks on output by the help of LSE approach in the context of output function. The data collected represents that the effects of oil shocks on output are asymmetric in both short-term and long-run. In short- term, positive oil shocks effects are greater than negative ones. But, in long-term, negative shocks are greater. The effects of positive oil shocks on output will be decreased over the time and then, in the case of negative shocks, these effects will be stronger.

The aim of this research is to consider the effect of the monetary policy on the production and inflation through the bank credit channel (Loan Channels) during 1989-2008 in Iran. So, the effect of monetary policy will be considered through the bank loan channel by Vector Error Correction model (VEC). In general, the results show that the more the amount of money by developing bank debts to the central bank, only the production level will be expanded in short-term and even it has negative effect in long-term. But, the general level of prices will be increased in short and long-term.So, the use of this policy tools affecting the level of the production is not suitable. But, it can contribute as an anti-inflationary policy.

The aim of this paper is to recognize the effective elements on the level of companies’ investment. So, under the effect of 7 selected variables like cash flow, Tobin ratio, growth rate of income, divided payments, announced payments, liabilities changes and paid-in capital, the level of companies' investment is to be researched. By using the data of 100 companies as a sample and applying Regression OLS from 2002 to 2008, we will continue the research. The results represent that factors like cash flow, Tobin q ratio, dividened payments, announcements and liabilities changes affect the investment level. But, the growth rate and paid-in capital have no effect on the level of investment.

Transportation sector is an important part of a production and consumption cycle. The expansion of transportation leads to increase the activities of the labor and capital and creates positive externalities for other economic sectors. Therefore, it has an important role in the process of economic growth. This paper investigates the effect of government investment in the transportation sector on economic growth during 1973-2009 in Iran. For this purpose, an Auto Regressive Distributed Lag (ARDL) model will be developed. Our findings show that, in short-term., investing in transportation has a significant positive effect on GDP. In long-run, GDP elasticity to public investment in transportation is a significant positive value equal to 0.08. Then, by positive effects mentioned above, we recommend more and more governmental investment in this sector.

In this paper, a new hybrid method is presented based on fuzzy neural network for estimating the fuzzy coefficients or parameters of fuzzy supply and demanding the labor function with fuzzy inputs. Here, the neural network is considered as a part of a large field called neural computing or soft computing. Moreover, in order to find the approximate parameters, a simple algorithm is proposed from the cost function of the fuzzy neural network. Finally, we illustrate the approach by the help of some numerical examples.

This study focuses on the structure and performance of automobile industry during1998-2007 in Iran. According to the results of the analysis, the indices between two top enterprises are fluctuated  between 77/93-99/21 based on Concentration Index, between 3625-4953 as per Herfindhal-Hireshman Index, and between 0/415-0/488 based on the Entropy Index. From the calculated indices figures, it can be proved that the concentration level is very high in the market. Moreover, social cost or welfare loss of monopoly in the same market is measured by the use of Cowling & Muller Methods in 2007. Due to the analysis, firstly, the functional cost of sedan automobile has been estimated in the format of collating one sample data by separating 5 major institutes and the manufacturer of vehicle including: Iran khodro, Saipa, Pars khodro, Bahman Group, Moratab in time intervals from 2000 to 2007. Result indicates welfare loss, due to monopoly, was 26% of the product sale in this market in 2007 representing a high amount of concentration.

In this research we are going to develop a model for evaluating the credit risk and credit ranking through customers in Parsian Bank by the help of Logit and Probit Regression and GMDH neural network methods. This model will be based on the qualitative and financial data of a random sample of 400 customers receiving credit facilities.After analyzing the credit files of each customers, we identified 11 explanatory variables including qualitative and financial aspects as follows: type of security, type of the workplace owner ship, cooperation background, capital, current ratio, quick ratio, the ratio of current asset to total assets, total asset turn over, turnover, current capital turnover, dept ratio and stock holder equity ratio that have significant impact on credit risk. Findings of the study corroborate the economic and financial theories of effective factors influencing credit risk and indicate that neural network model produce more efficient and precise results than the other popular economic models like Logit and Probit. Also, money explanatory variables such as the type of collateral and dept ratio have the most effects and the cooperation background, current ratio, stock holder equity have a usual effect and the rest variables are less effective.

This research tries to study the price changes of OPEC oil on the trade balance of the Iran economy. To do this, with the help of a 6-varible sample, we are going to pay attention to the experimental study of short-run and long-run relationship between so-called variables during 1967-2006 using an ARDL model. The results achieved represent that OPEC oil price change will affect the trade Balance negatively.