فصلنامه مدلسازی اقتصادی
سال شانزدهم شماره 3 (پیاپی 59، پاییز 1401)

The purpose of the article is to investigate the role of economic and environmental policies on preventing air pollution using the Dynamic Stochastic General Equilibrium (DSGE) model during the period of 1990-2019. Based on the results of the model, the economic policy shock causes a sudden increase in economic growth and consumption and then their decrease; However, the economic policy shock increases air pollution. The shock of environmental policies, firstly, increases consumption and economic growth and then decreases them. Investment also decreases as a result of the shock of environmental policies. Based on the results of variance analysis, the role of economic policies for the country's economic situation and creating air pollution is greater than environmental policies. The role of environmental policies in reducing air pollution is less than the role of economic policies in increasing air pollution. It is suggested that when the government increases its expenditures, it imposes green taxes or carbon emission taxes at a lower rate than the increase in government expenditures so that the economic growth of the country will continue to be maintained along with the reduction of environmental pollution.

The present article aimed to understand the effect of news shocks related to the technology on macroeconomic variables. In this regard, a dynamic stochastic general equilibrium model was used to analyze the reaction of macroeconomic variables in Iran based on seasonal data during 2001-2021. The results indicate that the news shocks increases the productivity of all production factors within one standard deviation. This increase escalates the wage rate as well as the interest rate. Household consumption, production and investment also increase opposing this shock. Due to the increase in production, the working hours will increase and consequently the inflation will decrease. Moreover, the economic prosperity grows due to the increased consumption and production.

After oil revenues, taxes are the second and most important source of government expenditure in Iran's economy. On the other hand, considering the importance of social justice as one of the main goals of the government, the effects of imposing taxes on households are also very important. Therefore, this research, using a calculable general equilibrium model, seeks to investigate the welfare effects of imposing indirect taxes on different income deciles in Iran. For this purpose, two scenarios have been applied and the reactions of households with different income deciles to these scenarios have been investigated. In the first scenario, a uniform tax was imposed on all goods and services at a rate of five percent and in the second scenario, a tax on food at a zero rate, a tax on some luxury goods at a rate of 14 pecent and a tax on other goods at the same rate of 5 percent. EV index was also used to measure welfare. The results of the model show that the imposition of indirect taxes in the first scenario worsens the welfare of low-income households, while the second scenario improves the welfare of poor households and worsens the welfare of rich households. However, in the first scenario, the GDP was higher than in the second scenario. Therefore, it is recommended to choose a tax policy using an integrated tax system, we will see efficiency and economic justice.

This study investigate the Impact of Current Budget Instability and Debt Accumulation on Iran's economic growth using seasonal data during the period 1369:1 to 1397:4 (based on the latest seasonal data published in 1401). Structural Vector Auto Regressive (SVAR) model has been used for this purpose. The results of the impulse response functions show that the instability of the current budget has led to the instability of other research variables along with increasing debt accumulation and decreasing economic growth. According to the results, the debt accumulation variable has a positive effect in the short term and a negative effect in the long term on private sector investment, as well as a significant negative effect on economic growth. The more the current size of the government is reformed, optimized and balanced, the current budget deficit and its financing will be reduced, the design of a favorable policy in this field will be able to eliminate many of the negative effects of the government sector on the national economy. Based on the results, it is suggested that sustainable incomes should be increased in order to improve the operating balance by maintaining tax justice, and the government's current spending policies should be adjusted by maintaining real purchasing power in a way that does not create negative welfare effects.

The purpose of this research is to compare the calibration of options pricing models based on Stochastic Volatility and the Generalized Integral Transformation Technique. For this purpose, the Generalized Integral Transformation Technique based on fixed Volatility and Heston model based on Stochastic Volatility were used for pricing call options. In order to implement the proposed models, This research has used the call option data offered in the Tehran Stock Exchange. The results showed that in the state of In-the-Money and At-the-Money, the Heston-based calibration works better than the Generalized Integral Transformation Technique in all maturity scenarios. In the case of Out-of-the-Money, although the calibration of the Heston model performs poorly in the short-term scenario, but as the time to maturity increases, the calibration of the Heston model has responded better than the Integral Transformation Technique in the mid-term and long-term scenario. Therefore, it is suggested that in order to develop the educational infrastructure and culturalization of options, the Department of New Financial Instruments of Tehran Stock Exchange Company can consider the model presented in this manuscript to calculate the key parameters of option contracts in different scenarios, And in this way, a more accurate valuation of option contracts can be obtained.

The purpose of the research is to predict stock returns using Bayesian averaging and BVAR. The current research is based on the applied research method and MATLAB 2021 and EVIEWS12 have been used to estimate the model. The time period of the research includes the years 2010 to 2019. First, 11 non-fragile variables out of 64 entered variables were identified with the Bayesian averaging model approach. Based on the results of the current ratio; ROE; P/E; oil revenue; The increasing coefficient of money in the whole period has a positive effect and inflation fluctuation variables; debt ratio; fluctuation of GDP growth; unofficial market exchange rate; Interest rate and systematic risk have a negative effect on yield in the whole period. Based on the results of variance analysis, the most explanatory of changes in stock returns is caused by the variable itself (20 percent), followed by interest rate variables (14 percent); Inflation volatility (13 percent) and debt ratio and systematic risk (10 percent) have the highest effect in explaining yield changes.