فصلنامه پژوهش های اقتصادی ایران
پیاپی 47 (تابستان 1390)

During the past decades, it has been indicated that more knowledge leads inexorably to greater economic growth.This paper will study the role of the knowledge based economy components on economic growth in Iran and some selected countries during 1996-2007.The main hypothesis is that: ICT as a major factor has dominant effect in promoting economic growth. Comparison to education, the role of ICT is found to be greater than education in selected countries.Our findings based on panel data during 1996-2007 indicate that Innovation and ICT both have positive and significant affects on economic growth.

This paper examines the relationship between the volatility of WTI prices and the open interest volumes (OIV) in NYMEX using a VAR model for the period 1986-2010. The results from the estimated model imply the existence of a causal relationship from OIV to the price volatility of WTI. Based on the results obtained from VECM, the existence of a causal relationship between the level of WTI prices and OIV is not confirmed. This can be justified on the basis that traders’ expectations would primarily affect variations in the futures prices. Since the increase in crude oil price volatilities usually indicates an upward shift in the uncertainties of price forecasts, our results show that the volume of open interest can be regarded as a key factor in the analysis of price behavior in the global oil market.

This paper studies four ARCH type models including ARCH, GARCH, EGARCH and TGARCH at Value at Risk (VaR) estimation. The four models were applied to daily Tehran stock market data to assess each model in estimating one day Value at Risk at various confidence intervals. Our findings suggest that for the daily return of Tehran Stock market, which exhibit fat-tailed and leptokurtic features, the VaR estimates generated by the GARCH-T models have good accuracy at high confidence levels.

Total factor productivity is an index to represent optimal use of production factors, and the degree of achievement of predetermined goals. In this study efficiency and productivity of research sector and total production (education and research) of 31 large state universities has been investigated, in order to improve the competitiveness and productivity. With the use of data envelopment analysis the efficiency and productivity changes of universities were measured, and also productivity growth of total and research productivity with separate components has been investigated. The results indicate that universities are technically inefficient. For example in research scope during 5 year, 7 universities are efficient, while 23 universities are inefficient. In total efficiency (research and educational) scope, 19 universities are efficient, while 12 university are inefficient. In order to avoid having randomized result in one year or to compare the first year with the last period, the geometrical mean of 5 years of study have been used. The findings of this study indicates that, Tehran university, Shiraz university, Kurdistan university, Ardebil university, Kermanshah university, Lorestan university and Hamedan university have the highest rang of efficiency among the others and also 13 university were lower than average. Consequently the study suggests that there are no significant improvements in research productivity and TFP in these years, which is due to the low improvement in technological efficiency. Moreover improvement of efficiency and productivity in universities requires strategic planning and productivity management cycle improvement.

Reforming Iran’s tax system is one of the most important issues due to the role of government’s expenditures and uncertainty in oil income. Therefore the modern value-added tax system is recognized as an approach by which tax transparency and tax structure reform can be enabled. However, increase in prices is an impact of applying this system. In this paper we have taken the advantage of symmetric product-by-product input-output table with basic prices to study the impacts of implementing value-added tax systems. With the help of IO-SAM software, this is the first time to set the Make and Use matrix on price basis of the year 1378. This table is the only table that can be used in analyzing price impacts caused by value-added tax system. The results illustrate; a 3-percent value added tax rate leads to increase in level of prices for about 1.5 percent, without consideration of any tax exemption. After exempting subject products of article 12 of value-added tax law, this index reaches 0.8 percent. Moreover, our examinations identify a 2.99 housing service price impact as the highest among the other 119 products’ in the economy. This rather high impact is generally rooted in its being not interchangeable in the as well as its overweighting demand.

Long memory in asset returns and volatilities is a new research area, both in theoretical and empirical modeling of high frequent financial time series. The most popular techniques of time series modeling with long memory is the ARFIMA-FIGARCH, but this fractionality in the integration of time series modeling has not been extended to the Multivariate GARCH models yet. The present paper aims to extend the BEKK’s MGARCH models to take into account the presence of long memory in daily financial time series. Although the proposed procedure is highly non-linear in the fractionality parameters with a serious computational burden, it estimates all the parameters of mean and variance equations in a nonlinear framework and finds a unique solution, by numerical optimization procedures. In the empirical part of the paper a multivariate FIGARCH is used to check the transmission of volatility among the automobile industry, machinery leasing and equipment indices in the Tehran Stock Exchange. The results confirm the existence of short memory in both conditional means and conditional variances, and moreover the magnitude of estimated d parameter is remarkably different from those of resulted from GPH and single ARFIMA-FIGARCH. Empirical findings of the MFIGARCH specification were compared with those of BEKK, and the comparison shows that MFIGARCH estimations are consistent with theoretical considerations. Moreover, our findings confirm the presence of lead and lag effects and information flow between the returns and volatilities of automobile industries and machinery leasing stock prices, and a multilateral information transmission from machinery leasing’s stock towards the Auto industry and machinery parts manufacturing share prices is observed.

Studies in applied econometrics and related disciplines are widely using time series techniques. Sound application of these techniques requires the satisfaction of their underlying assumptions. One of these techniques is ARDL Model. There are a number of examples in the published works in Iranian economic studies which suffers from misconceptions leading to biased and inconsistent estimates of parameters. For example, without assuring the exogeniety of the other RHS variables of the model, estimates are biased and inconsistent. Although fitting an ARDL model to exogenous and/or predetermined RHS I(0) and/or I(1) variables may seem appropriate, however, to continue the path leading to the extraction cointegration vectors, would be a misleading strategy. The aim of this paper is to highlight these misconceptions in the application of ARDL technique. To this end, after a theoretical survey of the concept, a dynamic simultaneous equation model (DSEM) of macroeconomic equations is introduced and simulated. The simulated series are used to estimate various versions of the model including VAR, ARDL, DSEM, VECM. Then the correct and incorrect application of ARDL model is specified by using two scenarios.

In this paper we are going to model stocks and derivatives markets by means of recent research work that can be used in Iran and explain some of the market shortages. For this, first we use Markov process properties and economic regimes phenomena for modeling underling asset price (stocks) by dynamic switching model regim. We then, using an American option on this asset we obtain a dynamic and new model. On the other hand, by considering the oil convenience yield of underling asset we extend a dynamic model with stochastic volatility for underlying asset for pricing futures of that asset and by some environmental changes to oil underlying asset, we will try to model the oil field-derivatives. Since in this paper we tried to introduce new models for financial markets and these models have not been used in Iran till now, we run them on some developed countries data by advanced numerical methods and MATLAB codes. Because global markets have an important effect on pricing financial quantities, it is necessary for top managers to consider these effects.