Journal of Economic Research
Year:2009 | Volume:44 | Issue:86|Papers Count:12

Energy as an important production factor has significant effects on economic growth. Identifying the relationship between energy and economic growth can help to improve governmental energy policies. Applying ARDL and ECM methods, this paper examines the longrun and shortrun causality relationships between (1) energy consumption and economic growth and (2) energy consumption and employment in various economic sectors of Iranian economy for the period 1971-2003. The results show that there is a longrun and shortrun unidirectional causality relationship from energy consumption to economic growth, a shortrun unidirectional causality relationship from economic growth to natural gas consumption, a unidirectional causality relationship from energy consumption to value added in industrial sector and shortrun and longrun unidirectional causality relationship from electricity consumption to value added in agricultural sector.

According to the literature, economic liberalization is an important factor affecting the Intra industry Trade (IIT). Present paper is trying to examine the positive effect of economic liberalization on Iran's IIT as well as to review the effectiveness of important components of economic liberalization including privatization, trade liberalization, exchange rate liberalization and financial liberalization on IIT, based on theoretical models. For the empirical study, we have estimated IIT type at 6-digit HS classification system during time period 1992-2005 by using trade types index. Then, we have used two group models (IIT and types of IIT) for examining this hypothesis. Overall, although it seems that there is no deterministic theoretical relationship between important components of economic liberalization and IIT, yet economic liberalization has positive effect on IIT, based on experimental evidences.

Regarding to important role of interest rate in adjusting and performing economic policies, in particular monetary policies, in recent decades too many efforts has been done for adjusting this variable as one of the most important key economic indicators. Due to the noticeable impact of interest rate to solve or generate economic problems in some societies, reducing it to its optimal level is in the first line of agenda as an important issue. In this study, according to Chicago School principles, we determine the most effective economic variables on interest rate. Then we use Bayesian Causal Map (BCM) to analyze the suitable ways of reducing interest rate in Iran over the period of 1976 to 2006. We concluded that interest rate tends to be depress through reducing inflation rate, reducing expected rate of inflation, controlling money stock, controlling credits and reducing budget deficit. Furthemore, the results of study confirm the Chicago School ideas about importance of money and direct and powerful impact of it on real economic variables in Iran and according to beliefs of this school, in process of reducing interest rate, money stock and inflation rate are the most important economic variables in Iran.

Do government expenditures often yield the expected improvement in social outcomes? This paper asserts that the good governance indicators can explain differences in attainment to a good health and education outcomes in OIC countries.This paper analyses the linkage between three concepts; "Good Governance", "Public Spending" and "Social Outcomes" For this propose, we measure the governance level by "corruption" and "quality of bureaucracy". Public spending becomes more effective in health and education sectors in countries with good governance; also, public spending has less impact on health and education outcomes in poorly governed countries.By using OIC countries data in period 1991-2005, we found that public health and education spending has a stronger negative effect on child mortality and stronger positive effect in raising primary education attainment in countries, which have good governance.

In economic theory, we are always faced with the the tradeoff between equity and efficiency. in this article, we try to analyze this relation according to the changes in the pharmaceutical system of Iran between 1376 and 1385. In this approach, changes in the process of allocating subsidies to medicine in healthcare sector in iran between 1976 and 1985 have been studied, according to changes in efficiencies in pharmaceutical industry and distributional justice (distributional equality) in health care system. Concerning the distributional justice (distributional equality) , the data for the medicine expenditure of the households has been used and the growth of the share of this expenditures has been calculated between 1376 and 1385. Concerning the efficiency issue in the pharmaceutical industry, Herfindal Index has been caculated according to share of of pharmaceutical firm's sale in the market and it is found that total production and sale of the firms has increased between 1376 and 1385. This evidence shows that the degree of competition has increased which would lead to more efficiency in the pharmaceutical industry. As conclusion we found that although efficiency has increased in the pharmaceutical industry, the distributional justice (equity) has not deterirated in these years.

In this paper we investigate the long memory of Tehran Securities Price Index and fit ARFIMA model using 970 daily data since 1382/1/6 until 1386/4/17. Furthermore, we compare the forecasting performance of ARFIMA and ARIMA models. The results show that the series is a long memory one and therefore it can become stationary by fractional differencing. We obtaine the fractional differencing parameter d=0.4767.Having done the fractional differencing and determination of the number of lags of autoregressive and moving average components, the model is specified as ARFlMA (2, 0.4767, 18). We estimate the parameters of the model using 900 in-sample data and use this estimates for forecasting 70 out-sample data. Comparing forecasting performance of two models illustrate that forecasting performance of ARFIMA model is better than ARIMA model.

This paper estimates demand functions for wireless and wire line phone, using Almost Ideal Demand System (AIDS) and attempts to test the hypothesis of substitutability between wireless and wire line in Iran. The results indicate that the number of mobile subscribers has been growing more than the number of wireline subscribers over studied period. This maybe because of lower price of mobile access in recent years. This process may lead to complete substitubility of mobile services in the future.The price elasticities of fixed and mobile services show the sensivity of subscribers, specially for the mobile services. The results show that price and service regulations are needed, since market forces aren't sufficient to hold prices in check.This fact may arise from factors such as; government supply of services, insufficient competition and inerease in the price of wireless services compane to wireline services.

Risk prediction plays an increasing role in financial risk management.This study aims to investigate existence of asymmetry and long memory volatility in Tehran Stock Exchange Index daily data over period of 1998-2006.1467 daily index returns are used for volatility modeling via GARCH (Long & short Memory) processes for both normal and t-student innovations. The specification and forecasting performance of competing volatility models are compared by standard criteria. Considering the evidence of long memory, ARFIMA models are developed for conditional mean and both long and short memory models are used for conditional variance. We find that long memory models (particularly with normal distribution of innovations) perform more accurately. Also empirical results indicate that GARCH models have confidential performance with t-student innovation. In sample and out-of-sample Value at Risk calculation resulted by FIGARCH models are more accurate than those of generated by traditional GARCH, particularly in 2.5% critical region.

This paper describes two data analysis techniques adopted in a Decision Support System (DSS), Decline Curve Estimation and Artificial Neural Network (ANN) approaches, which aid users in predicting oil production of a field. The system generates different predictions, according to scenario, chosen for prediction. These two approaches show that to explain production of a field, ANN method shows better fit to historical data, compared with regression method used for decline curve estimation. But to predict production of the same field these two show completely different for casts, which alarms us to be careful in using a particular method for predictions. In the case of modeling a mathematical relation for production of a field, researchers should apply different approaches and compare the result to reach to a better conclusion about the production rate.

This paper reviews the relationship between inflation rate and minimum wage in Iran's economy over the 1969-2005. According to the economic literature, there is a narrow relationship between inflation rate and minimum wage. Some economists believe in increased inflation due to minimum wage. The other group of economists considers the increased inflation as a cause for increasing minimum wage. The study results do confirm the existence of causal relationship from inflation rate to minimum wage.