نشریه مدلسازی اقتصاد سنجی
سال پنجم شماره 2 (پیاپی 17، بهار 1399)

Given the fact that sugar producing industries are one of the most water consuming food industries of our country, the absence of complete purification of the industry’s sewage and sewage disposal with high BOD index impose lots of environmentel costs to the society. Hence, economic assessment of these industries, without taking environmentel costs, can be very misleading. To include such costs, this paper uses a Stochastic Nonparametric Envelopment of Data (StoNED) to evaluate the marginal cost of controlling the BOD index of wastewater produced by the sugar industry in the year 2017. The results show sugar industry in our country is environmentally inefficient on average about 6.5 percent. In addition, the average shadow price per kilogram caused by BOD of manufacturing plants is about 612.6 thousand Rials. Obtained shadow prices can be used to plan proper pollution controlling tools; they also are used for more accurate evaluation of economic planning of sewage treatment.

The correlation between market movements and returns is an important issue in risk management and investment portfolio strategies. Investors who try to diversify their assets in regional markets pay special attention to communications between financial markets. In this study, we have tried to study the contagion of risk tail from the financial sector to other economic sectors and the specific characteristics of each industry that affect this phenomenon. For this purpose, we introduce a new index for risk tail contagion from financial market to industries or in other words, conditional coexcee dance (CCX) in the TSE.  We investigate risk tail contagion between the market and industry, using 26 TSE industries data for the period 2011 to 2017 by estimating the Poisson's regression. The results show that the risk tail contagion is lower among industries that have a higher relative value index and higher investment. Contagion also occurs more for industries that use external debt.

Futures are used as the most important risk hedge tools to reduce the risk of the crude oil market. The optimal hedging risk strategy is determined by calculating the optimal hedging risk ratio. It is important to determine the relationship between the time series of spot prices and futures in calculating the optimal hedging risk ratio. Therefore, in this paper, the OLS, ECM, DCC GARCH and GARCH models based on Copula are used to calculate and evaluate the optimal hedge ratio of spot market hedging risk to the futures market over the period 2018-2013. The results show that the DCC-GARCH model has the highest optimal hedging risk ratio at 0.805. Considering the percentage of variance reduction, it can be concluded that the dynamic strategies of DCC and copula to models Static hedging risk is more efficient. Also, the time-varying, t-student, gamble, and normal capsules show better performance than the DCC model. Also, among the functions mentioned above, the copula t student function has the best performance.

one of the methods for developing foreign trade in each country is the precise understanding of the commercial economic potential of major partners and ways of improving the volume and composition of foreign trade, including exports and imports. on this basis, in this study to examine the commercial potential between iran and member states of the D8 (eight islamic countries developing) during the 1992 - 2016 model of gravity model, the dynamic spatial method (sgmm) is chosen as the most appropriate method of estimation. the results show that the gross domestic product coefficient (gdp) and trade partner countries are positive and therefore, the gross domestic product as a measure of the economic size of countries has a direct impact on their bilateral trade. The geographic distance coefficient was seen as a measure of negative transportation costs, which indicates that the greater the distance between the capital of countries, the degree of bilateral trade is reduced. the coefficient of the SAARC and ASEAN is positive and significant, which indicates that Iran's membership in these countries increases the trade potential of this country. Also, the spatial Rho coefficient has been negative, implying a negative spatial dependence between the D8 countries. The results of the trade potential estimation show that the total trade potential of Iran with D8 has been 2398.47977 billion dollars the period under review, of which only 1400 billion dollars has been realized.

The main purpose of this study is to investigate the effect of intra-industry trade on inflation for Iran during the period 1992-2017. Although in the framework of traditional trade theories, the effect of foreign trade on inflation is generally considered negative, studies over the topic based on new trade theories (NTT) are little and with no definite results. However, intra-industry trade seems to be able to moderate inflation through several ways, such as economies of scale and product differentiation. The results of estimate a smooth transition regression for Iran show that intra-industry trade in the form of a three-regime structure has a negative and significant negative effect on inflation. This finding is consistent with the Krugman models. Also, the results of the present study show that the effect of intra-industry trade on inflation rate has been non-linear and its presence accompanied with other factors has moderated the inflation. Based on the results, the policy recommendation of this research is to reform the structure of foreign trade in favor of intra-industry trade trade in such a way that while developing foreign trade based on comparative and competitive advantages, it is possible to adjust the inflation rate.

In this study, the effect of global economic policy uncertainty on stock, gold and foreign exchange market volatility in Iran is examined. Therefore, using the monthly data of Tehran Stock Exchange price index, gold coin price and exchange rate for the period from April 2002 to March 2017, correlation of the mentioned variables with global economic policy uncertainty in Iran has been investigated by the dynamic conditional correlation-GARCH model (DCC-GARCH). The research results show that fluctuations in global economic policy have a significant effect on stock, gold coin and exchange rate market fluctuations. This index generally has a positive effect on the fluctuations of gold coin price (except during 2004-2007), and has both positive and negative effect on stock and exchange market fluctuations. Thus, the global economic uncertainty index is useful in predicting market volatility and can improve stock price, gold price and exchange rate forecasts.