Journal of Economic Research
Year:2010 | Volume:45 | Issue:92|Papers Count:11

Nowadays, credit risk is recognized as one of the most important bankruptcy factors of banks and financial institutions. In order to manage and control this risk, design of credit rating models is undeniable necessity. Credit rating is used to identify the probability of credit default and on the other side classify the customers into two groups: good and bad accounts.  Until now, various statistical methods, including discriminant analysis, logistic regression and neural networks have been developed for credit rating. Meanwhile, neural networks due to the high flexibility and precision, in recent years have been considered more. This study presents a credit rating model using adaptive neuro-fuzzy inference system to predict financial performance of bank customers. In this model, debt ratio, operational ratio, and return on equity have been selected as input variables, and on the other side the probability of default has been considered as output variable. After training and testing the model based on data from Keshavarzi bank over 2001-2006, the model predicts the credit status of customers with Accuracy of 69.36%.

In this article, the effectiveness of eight different technical indexes including simple moving average, weighted moving average, exponential moving average, relative strength, commodity channel, stochastic, money flow and demand are examined by comparison between indexes returns with buy and hold returns. The results shows the return of Buy and Hold strategy is more than technical indexes in the year 2004 and is less than that in the years 2004 and 2006. This matter can be referred to the change in the market situations. The result of the repeated measures test indicates that there is no significant differences between the average returns of technical indexes and buy and hold strategy during studding years. Finally we show the coefficients of variation of some technical indexes used in this paper are lower and coefficients of variation of some other indexes are greater than coefficient of variation of buy and hold strategy.

Value added is a criterion for evaluating the performance of economic units. Statistics related to various economic indicators of industrial workshops located in Iranian provinces with their value added are annually obtained by Statistical Centre of Iran via “Industrial Workshops Survey” program. This study is going to find the most important factors affecting the value added of the workshops, by using one of the newest methods for variable selection, called SCAD penalty function.The results show that from 1997 to 2006, the amount of labour education, type of workshops management, audit fee, research and propaganda cost, and land value are of the highest important for producing value added of the industrial workshops.

We have studied the relation between bank deposit rates and house prices in Iran. For that, we have run some VAR models, using the following variables: real deposit rates (including 1 and 5 years deposit rates), money supply (including the high powered money and the liquidity), GDP, housing services index, and number of licenses for new houses. Our results show that a reduction in the deposit rates reduces its attraction and increases demand for housing as an alternative asset to stock wealth. In other word, we find that there is a negative relation between bank deposit rates and house prices.

This paper is analysing the role of economic reforms on the labour market in Iranian industry in economic reform period (1990-2005), and in turn, it is comparing it with closed economic period (1979-1989). In order to do the above comparative analysis, the manufacturing industry has been categorized based on Hecksher-Ohlin and Gause methodology. Accordingly, we have some industrial groups, including, export oriented, import competitor, non-trade, oil industries (in 3 and 4 ISIC, rev levels). The result shows that: open economic policies has increased the real wage, but has not declined the inequality between skilled and non-skilled labours. The growth rate of productivity of trade industries, the real production and the value added of those industries have increased considerably during 1990-2005 period. Employment elasticities and the share of women in industrial employment have also enhanced in that period.

In this paper, The Behavior of saving and consumption has been considered in Ramsey – Cass- Koopmans model’s framework. Our purpose was investigation of dynamics of these variables and analysis of their response to other parameter and variable variations. So, we made Lagrangian function subject to some restrictions and Euler equations and other steady state path equations. And then, We have calculated time path of endogenous variables (k,c) by Shooting Algorithm. Also, we made time series of saving and consumption by simulation method. And the comparison of this simulated data with actual data, by MAPE and other criteria shows that the generated data from neoclassical growth model explains more than 85 percent of actual data. As a next step, we have investigated the effects of other exogenous variables on simulated saving data. Our findings shows that, with adjusted assumption, TFP fluctuations will be able made significant variations in saving.

Energy policy making in the third millennium is summarized in three areas. The first area: moving toward the use of renewable, clean and environment compatible energy, the second area: restructuring in the energy sector, to make it competitive, & finally, the third area is: increasing efficiency in energy consumption. Power industry as a growing sub-section of energy sector, especially in recent decades, constitutes about one-third of the world’s economy and energy. As in many other countries the power industry in Iran needs to go through some evolution in its policy making & should pay special attention to at least, two areas of the three areas mentioned above. Although the present study is on the two areas of restructuring & increasing efficiency in power industry, it has strong emphasis on demand side management, through economical methods of load management. To this end, using self –rationing method, the feasibility study of subscribed capacity market between factories will be studied. The research methodology in this study is descriptive and it is based on causal method performed cross sectional in 2006. To gather information a questionnaire was prepared and sent out to cement plants. Results of the research suggest that plants with higher electricity opportunity costs have more willingness to pay (WTP) for subscribed capacity. Self- rationing, through subscribed capacity market can, on the one hand reduce capacity costs of cement plants, and on the other hand, provide some of the needed load for other customers, or even other cement plants. This will result in the reduction of investment costs in providing new capacity during peak period. It will also increase efficiency, one of the goals of load management. This market would eliminate the inefficiency of Woo's model, by removing too much load relief from the system.

This paper identifies characteristics of business cycles in Iran, applying Hodrick-Prescott (HP) and Band-Pass (BP) filters. Using seasonal and anual data for 1970-2003, it is found that oil income is the key driving factor of business cycles in the Iranian economy. Furthermore, it is indicated that Iran's economy has experienced seven business cycles during this period, in which the economic boom and recession were observed in 17 and 15 years, respectively. The average years of boom exceeds that of recessions, while the range of fluctuations has been higher in recessions. Considering the impact of business cycles on the economy, the above results should be taken note of in macroeconomic policy making process in Iran.

Cycles fluctuations in housing investment and national economy, variation in consumers and producers behavior, deviation in allocation of economic resources, the aggravation of capital transfer in asset market, the variation of income distribution pattern and imbalance in resource and expenses are the consequences of fluctuations in housing prices. These consequences and its control and recognition have been an important subject on economics policy in recent decades. Macroeconomic and monetary policy variables have significantly affect on housing prices. In this paper we analyze the effect of monetary policy on housing prices bubble and we use panel data method with annual data from (1991-2004) for 18 countries. We use price-to-rent ratio approach to calculate house price bubble. Our results indicate that monetary policy and asset price variables are effective variable on housing bubble. Monetary policy variables have the most important effect on housing price and bubble formation in Iran and countries that have high price-to-rent ratio.

In this research, potential effects of oil and monetary policy shocks on economic growth of Iran are examined and share of each of them on economic growth are calculated during 1974-2006 period and potential mutual effects of those shocks by using the Vector Auto Regressive (VAR) model are analysed.Results of this research show that oil shocks significantly affected the economic growth in Iran. However, in spite of oil shocks affected on the liquidity of money that led to expansionary monetary policy, monetary shocks did not have any effect on growth.Strong relationship between oil shocks & GDP growth in Iran indicates that the economy of Iran is heavily depending on oil revenues. On the other hand, the monetary shock which is due to increase in oil revenues, does not have strong effects on GDP growth because of delay in effectiveness of monetary action and also due to implementation of contractionary monetary policy to control inflation rate that has ended up with a weak effects on GDP growth.