IRANIAN JOURNAL OF ECONOMIC STUDIES
Year:2013 | Volume:2 | Issue:1|Papers Count:6

This article intends to estimate the optimal value of investment and human capital in R&D sector of Iranian economy using an augmented endogenous growth model. To do so, two issues have been studied. First, an endogenous growth model has been extended to include investment in R&D as an independent variable. In the framework of this model, in order to determine the optimal value of investment and human capital in R&D sector, we derived the optimal path. Second, using the optimal path and Iran’s economic data, the optimal values of human capital and investment in Iran’s RD sector have been estimated. The results show that in order to be in a steady state with 8% economic growth, it’s necessary to allocate 0.7% of total human capital and 8% of national income to R&D sector. However, at present, less than 0.3% of human capital and less than 0.5% of national income is allocated to R&D sector in the Iranian economy.

We have introduced an early warning system for volatility regimes regarding Tehran Stock Exchange using Markov Switching GARCH approach. We have examined whether Tehran Stock Market has calmed down or more specifically, whether the surge in volatility during 2007-2010 global financial crises still affects stock return volatility in Iran. Doing so, we have used a regime switching GARCH model. The data consist of 3067 daily observations of the closing value of the Tehran stock market from 29/09/1997 to 09/09/2010. The results indicate that during the crisis period, Tehran stock exchange was in the high-volatility regime. Smoothed probability plots show that the volatility in 2007-2009 was in high volatility regime but at 2009-2010, Volatility turned to low volatility regime. Also, we have introduced an early warning system for forecasting high volatility in Tehran Stock Exchange.

In recent years, investigating synchronization of business cycles among countries, after increasing integration of global economies, has been attracted more attention of policy makers and researchers. Perhaps an unknown origin of such similarities, as an open question, is the main reason of these interests. So, with regard to the mentioned question, the aim of this paper is to investigate some probably determinants of synchronization among Iran’s main trade partners. Therefore, in the first step, in order to measure business cycles, some parametric and non-parametric techniques are used. Then, applying several criteria, the degree of synchronization is determined. After these two steps, employing IV-GLS and QR estimators, the relationship between business cycles and trade intensity index, as a possible channel of synchronization, has considered. The result shows that an increase in trade intensity index increases business cycle synchronization for all 21 sample countries. Also, this result remained almost unchanged when we divided sample into some subsamples. It is worthy to note that due to the endogeneity of independent variable, the gravity equation and Helpman theorem (1981) are employed. In these equations, some variables such as GDP, common borders and distance had significant effects on trade intensity and hence on business cycles.

Forecasting energy price and consumption is essential in making effective managerial decisions and plans. While there are many sophisticated mathematical methods developed so far to forecast, some nature-based intelligent algorithms with desired characteristics have been developed recently. The main objective of this research is short term forecasting of energy price and consumption in Iranian industrial sector using artificial intelligence including an Adaptive Neuro-Fuzzy Inference System (ANFIS) and an Artificial Neural Networks (ANN). The dataset contains monthly price and consumption of gas oil, petrol, and liquid petroleum gas in the period between March 1996 and March 2010. Based on dataset, energy price and consumption for 2011 and 2012 are forecasted. The results obtained utilizing the two methods show that while both are appropriate tools to forecast price and consumption, most of the time ANFIS has lower error than ANN in terms of the mean squared error criterion.

The aim of this paper is to identify the industrial markets coordinates with the help of Herfindahl–Hirschman concentration index, cost disadvantage ratio (CDR) index and Comanor and Wilson's economies of scale index (MES). The paper also attempts to recognize Iran's monopolistic industries through the Fuzzy TOPSIS method presented by Chen (2000) under triangular fuzzy membership function. Given the findings raised from three market structure components (HHI, CDR and MES) it is confirmed that the most monopolistic industries respectively include: Manufacturers of tobacco products, manufacturers of games and toys, manufacturers of industrial process control equipment and tanning and dressing of leather, manufacturers of luggage, handbags, saddlery and harness, dressing and dyeing of fur. The Entry barrier criterion has also had an essential role in expanding the monopolies in Iranian markets.

The banking sector is one of the important financial intermediaries in an economic system. Improvement in the banking sector can achieve optimal allocation of financial resources. The performance of banks and other financial service providers has direct effect on economic growth. One of the factors that can affect the banks operation is economic freedom. Economic freedom and freedom of private property rights can influence the quality of financial institutions such as banks. Using panel data model, this paper attempts to study the effect of the economic freedom index on the performance of banks in selected developed and developing countries for the period 2001-2011. According to our finding, countries with higher degree of economic freedom index have better financial performance. Moreover, economic freedom indexes have positive effects on bank′s profitability in both groups of countries.