فصلنامه مطالعات اقتصادی کاربردی ایران
پیاپی 34 (تابستان 1399)

In this paper, we examine all the macroeconomic time series which can be considered as potential leading indicators of the state of real activity in Iran, to find the best leading indicators. According to Einian and Barakchian (1393), Non-oil GDP show the fluctuations of real activity in Iran better than other variables. Hence, in our study we consider Non-oil GDP as the target variable and the dating of the business cycles are identified following Einian and Barakchian (1393). 265 macroeconomic variables, obtained from the data sets released by the Central Bank of Iran, are used to construct 1590 potential leading indicators; 6 kinds of transformations are applied to each variable in order to generate 1590 series. These time series are quarterly series which span the period of 1367Q1 to 1387Q2. The number of Missing Points, False Alarm Points, Late Alarm Points, Concordance, and Standard Deviation in forecasting peaks and troughs are used as the main criteria to evaluate the potential leading indicators. The results show that no variable does well in terms of all the criteria; however, there exist 20 variables which performs well in forecasting peaks and troughs and there exist 6 variables which perform well in terms of the standard deviation of the forecasts. Therefore, selecting a set of potential leading indicators to construct a composite leading indicator for non-oil GDP depends entirely on the importance of each criteria for the institutes/researchers who develop the composite leading indicator. We also evaluate the potential leading indicators based on their release lags in the Central Bank's publications. Samaee and Atrianfar (1390) have shown that the national accounts' data have the longest lag (more than 6 months on average), and therefore, we suggest to diminish their role in constructing the composite leading indicator.

The importance of taxes in financing the state budget and exploiting it in the implementation of fiscal policies aimed at redistribution of wealth and income as well as optimal allocation of economic resources among different sectors has revealed more and more the need for identifying the key factors affecting the tax revenues and examining how they affect. In this study, while investigating the factors affecting the direct taxes and their related theoretical basics in the Iranian economy, selecting the important variables affecting the direct taxes of Iranian economy during the period 1972-2018 using dynamic TVP-DMA models was considered. After selecting the important variables affecting the direct taxes through the estimations made by the model, the instantaneous reaction functions or reactions resulting from the changes of these variables and their effects on the growth of the direct taxes in the aforementioned time periods using TVP-FAVAR models were also investigated. The results of this research based on the outputs of TVP-DMA and TVP-DMS models show that in Iranian economy, the variables of “openness degree of economy”, “growth of development budget”, “inflation”, “average tax rate”, and “real income growth” are respectively the most important variables affecting the growth of direct taxes. Examining the effects of these variables on the development of the direct taxes during the study period shows that the openness degree of economy, growth of development budget, average tax rate in the sector of direct taxes, and real income growth have had a positive effect on the growth of direct taxes over many years. The impact of inflation on the growth of the direct taxes in the Iranian economy has been changing over the period, and it has been positive for some years and negative for other periods. Therefore, based on the results of the model, the question of whether the impact of inflation on the growth of direct taxes in the Iranian economy is positive or negative cannot be answered, because the simultaneousness of the inflation and other economic (growth and unemployment rates, etc.) and tax developments (tax breaks, rate changes, etc.) is the main determinant of how this variable affects the growth of direct taxes

In this study, the role of human capital in sustainable development has been analyzed through A simultaneous equations models (economic growth, energy consumption and CO2 emissions) using (GMM) over the period of 1971-2017. In this regard, and with the aim of improving the concept of human capital, average years of schooling and returns to education have been used as human capital index in the model. The results show that human capital in Iran due to the lack of attention to applied educations, the quality of education and mismatch between employment education and their jobs, not only lead to increase in economic growth but also make economic growth slowdown through Disruption of optimal resource allocation and waste of resources. The results also confirm the role of human capital in reducing energy consumption and thereby CO2 emission through the development of energy efficient technologies. The results also show that environmental considerations have not been taken into account in the process of economic growth and energy consumption. Finally, the results show that oil rents in Iran have reduced economic growth and thus اhas been led to the “oil curse phenomenon”.

Today, special attention has been paid to the capabilities of chaos theories and neural networks and the application of these two models in financial markets, especially petroleum products. In this study, daily values ​​of stocks of Iranian petroleum products during December 2007 to June 2016 have been studied. Due to the nonlinear nature of financial data, chaos theory is used to study the chaotic amount of time series. The chaos theory based on Liapanov's exponent and fractal dimension studies the time series caused by nonlinear dynamic systems. In chaos theory, first, using the Lyapanov diagrams and the Poincaré surface of section map and measuring the correlation dimension, the possibility of chaos in time series of daily value of oil products in Iran is investigated. Then, the Lyapunov diagram is plotted using the delay time estimation obtained from the method of the average of mutual information and embedding dimension using the algorithm of the false nearest neighbors. The Lyapunov map and the Poincaré surface of section indicate a chaos in the investigated time series. According to the provocation of chaos in this time series, its nonlinearity was deduced. Therefore, a suitable neural network was designed and the best model was selected to predict the future prices of petroleum products stock with a correlation coefficient of 0.99831 and the error of the training data is 0.0012 and the error of the test data is 0.002 that indicating good accuracy in modeling the price of these industries and can be used to predict its future price.

This article analyses the effect of replacing oil revenue with tax revenue on Iran's institutional quality. For this purpose, good governance index that is derived from the mean of 6 good governance indices, Voice and Accountability, Political stability, Government Effectiveness, Regulatory Quality, Rule of Law and Control of Corruptionwas ,considered as indicators of the institutional governance quality. The Threshold model of Oil revenue effect on the governance quality in Iran, over the period 1996:1-2017:1 estimated by Smooth Transition Regression Model (STR). The inverse U-shaped relationship between the share of oil revenue from GDP and the good governance index  and a direct relationship between the share of tax revenue from GDP and this index are obtained. The Estimated threshold level of oil revenue impact for good governance index was equal to 2.378 percentage. The scenario of a 10% decrease in oil revenue and a 10% increase in tax revenue showed that this replacement resulted in a 11% improvement in the quality of governance in Iran. It is therefore recommended that the reform of the tax structure in Iran be put on the agenda of the government and parliament in order to meet the government's financial needs as well as the state's independence from oil. The government, through its competitiveness and accountability mechanisms, supports the establishment of civil society institutions and enhances the power of citizens to help raise tax revenue.

The present study, by estimating supply and demand functions, investigated the factors affecting Iran’s non-oil exports especially in export of mineral products with an emphasis on export restrictions. The results show that Iran’s non-oil exports have decreased as a result of the international sanctions despite the foreign exchange surge in Iran in 2012. In addition to these sanctions, the structure of Iran’s non-oil export has not undergone any manifest change in terms of the extent of the factor intensity of production, while as far as technology is concerned, the exportation of higher-technology products has been impacted by the sanctions to a greater extent.Using two stages least squares method, non-oil export supply and demand functions in the period from 1987 to 2017 have been estimated. Estimated coefficients show that foreign prices and income of other countries are the most important factors affecting Iran's export demand, and the price and income elasticities in the minerals export sector have been obtained as higher than those of the total non-oil exports. The coefficient of the dummy variable as a determinant of the effect of sanctions is negative and significant for all non-oil exports of Iran while it is positive for the export of mineral products. According to the achievements of the present study, more than two-thirds of Iran's non-oil exports are primary and resource-based products. Iran's non-oil exports are more demand-driven, and factors such as global prices, other countries' incomes, and sanctions are more influential than supply-side factors such as investment or productivity. The results of the model and the analysis of the structure show that the sanctions are ineffective in exporting mineral products.

This paper has investigated the effect of share non-traded goods prices on real exchange rate fluctuations with two economic characteristics, such as openness and price stickiness by using of a DSGE model. The main characteristics of this model with other patterns is that both sectors are considered to be tradeable and non-trade goods. Three scenarios are designed for this purpose. The impact has been investigated a 3% and 5% shock on productivity, a 10% monetary shock, and a combination of a 3% and 10% shock in productivity and money respectively. The results indicate that productivity shocks have led to a decline in real exchange rates due to the relative price fluctuations of non-traded goods. The results of the second scenario indicate that monetary shocks increase the real exchange rate by changing relative price of traded goods. In the third scenario, monetary and productivity shocks have reduced real exchange rates. The results of the scenarios for this model show that changes in the relative price between traded and non-traded goods are the main channel through which productivity shocks are transmitted to the real exchange rate. Therefore the economy’s characteristics have a significant effect on the transmission mechanism and the overall volatility of the real exchange rate in response to both types of shocks. The economy’s characteristics have a significant effect on the transmission mechanism and the overall volatility of the real exchange rate in response to both types of shocks.

Monetary instability and investigating its effects on other macroeconomic indicators is so significant for making economical policies in all countries. An effort has been made in this study to evaluate the monetary instability in Iran’s economy during recession and expansion periods in a dynamic equation system format in Friedman's theory framework about GDP and inflation fluctuations. The period that has been determined for this survey is based on seasonal data from first quarter in 1370 to fourth quarter in 1396. The results show that monetary expansion in both recession and expansion period is more effective in creating inflationary condition than influencing output. Considering the identification of technology structure relevance as an important parameter in the production process which plays an important role in business cycle, a controversial result which is gained shows that technological shock led to increase price level and inflation in Iran’s economy. Finally, it can be expressed that Friedman’s hypothesis can not be confirmed during expansion period in Iran’s economy.

Basically, quantitative specification of sanction effects on economic sectors has undeniable importance to increase the buffering of nations’ economy against their negative effects. On the other hand, majority of estimated models in this field, have carried out through the entering the dummy variables and studying part of economy. Therefore, in this research the effects of economic sanctions was studied on Iran’s productive economic sectors using 4 criteria: 1. Oil export revenues shock, 2. Non-oil export shock, 3. Importing raw materials, capital and intermediate goods shock and 4. Exchange rate shock. For this purpose research data was gathered from Central Bank of Iran during 1988-2017. Also, in order to data analyzing, Structural Vector Auto-Regressive (SVAR) model and Impulse Response Functions (IRF) were applied. Results proved that economic sanctions reduce the value added of considered productive sectors. But effect of studied economic sanction criteria on considered productive sectors were diverse. So that between 4 studied economic sanction criteria respectively: exchange rate shock, Importing raw materials, capital and intermediate goods shock, non-oil export shock and Oil export revenues shock have the most negative effect on value added of considered sectors. In addition, value added of agriculture sector, value added of construction sector and value added of industry and mine sector, exposure with the least effect from the studied economic sanction criteria, respectively.