فصلنامه اقتصاد مقداری
سال پانزدهم شماره 3 (پیاپی 58، پاییز 1397)

In this research, the effect of oil price uncertainty on economic growth has been studied using the Generalized Method of Moments (GMM) during the period 1961-2015 in the group of oil exporting countries and oil importers group. Therefore, at first, the uncertainty index due to oil price fluctuations has been estimated using the Exponential Generalized Autoregressive Conditional Heteroskedasticity (EGARCH) model .The research findings show that the uncertainty of the oil price on economic growth is asymmetrical. Also, the results of fitting the dynamic panel model using the GMM method indicate that oil prices uncertainty have a negative effect on economic growth both in the group of oil exporting countries and in the group of oil importing countries. While in both countries, the investment growth rate, Real exchange rate and population growth rate are positively correlated with economic growth.

Increasing investment and achieving higher economic growth rates is the primary goal of the economic systems. Potentially, the natural resources, especially oil, can be very beneficial in economic development and creating resources for investment. But, on the other hand, the impact of natural resources abundance on the investment depends on the specific institutional and political characteristics of each country. Therefore, the present study addresses the interaction of the Governance Index with the abundance of natural resources on the formation of physical capital in the net fuel export countries during the period of 2002-2016 using PMG model. The results of the study show that the interaction of oil revenue with the indicators of the right to comment and accountability, political stability, government effectiveness, rule of law, quality of laws and regulations and control of corruption on the formation of physical capital has a positive and significant effect in long-term and insignificant in the short-term. Also, based on the results of the long-term estimation, gross domestic product per capita (GDP) and degree of economic freedom have a positive and significant effect and the effect of real interest rates on the formation of physical capital is negative and significant. In the short-term, in one hand real interest rate found to be ineffective and on the other hand GDP and degree of economic freedom found to have a positive and significant impact on the capital formation.

This paper is to investigate the role of affecting variables on employment and labor demand in Iran economic sectors. Dynamic labor demand models in the framework of disequilibrium in labor market have been estimated by cointegration approach. Estimating the dynamic model of labor demand shows that among the variables affecting labor demand, production, exports and wage index are the most effective determinants of labor demand in the economic sectors. This is while the investment, despite the policymakers' attention to that, did not meet the expectations that it has strengthened and developed employment. Findings also clarify the different importance of variables effect on labor demand in different sectors. The most effective determinants of labor demand in the industry and mine sector are respectively production, interest rate, exports and wage index. In agricultural sector the highest effect is respectively belonged to wage, production and exports. Production, wage and exports have respectively the greatest effect on labor demand in the services sectors.

Wagner believes that with the increase in per capita incomee of the society, the relative size of the public sector's spending on infrastructure development, including cheap energy will increase. The purpose of this study is to estimate the long-term and short-term effects of economic growth and Information and communication Technology (ICT) on energy (electricity) consumption; using annual time series data in Iran during the period 1971 to 2014. For this purpose, autoregressive distributed lag (ARDL) and the error correction (ECM) methods are used to show the long-term and short-term relationships and further Granger's causality test is used to determine the causality relationship. The results showed that in the long run, economic growth and information and communication technology have stimulated the consumption of electricity in Iran. Multivariate causality test confirms the one-way causal relationship of economic growth and information and communication technology to power consumption. The results also showed that, in the long run, a one percent increase in economic growth and information and communication technology would increase electricity consumption by 0.78% and 0.028%, respectively. The error correction coefficient also shows that in each period 9.7 percent of the imbalance in real per capita consumption is adjusted and approaches its long-term trend. The results affirm the Wagner theory based on the relationship between the growth of per capita income, economic complexity, and the increase in demand for new goods and services, including cheap energy supply by the state.

This paper is aimed to compare stock index forecasting using hybrid models based on Genetic Algorithm (GA) and Harmonic Search (HS) with Artificial Neural Network (ANN). The most relevant technical indicators as inputs and the optimal number of neurons in hidden layer of Artificial Neural Network designated by metaheuristics including Genetic Algorithms and Harmony Search. Daily price index of Tehran Stock Exchange from 21 December 2012 to 21 December 2015 applied to predict and test stock index. The accuracy of forecasting of three models including Regular Artificial Neural Network model, hybrid neural networks based on GA and hybrid neural networks based on HS is evaluated by the prediction error. The results show that the accuracy of prediction in Metaheuristics models such as Genetic Algorithms and Harmony Search in the test period is higher than normal Artificial Neural Network. Also prediction by hybrid neural network model based on harmony Search during the test period compared to hybrid Artificial Neural Network model based on Genetic Algorithm is more accurate.

The purpose of this paper is that using a translog production function and random effect models show that the VAT impact on productivity in Iran. It also uses a model of endogenous growth include households, corporations and governments, the optimal rate of this tax is estimated by calibrating the model for Iran. Because productivity can be divided into three production efficiency, technical efficiency and scale efficiency decomposed (Kambakar and Lowell, 2000) We VAT impact on each of the three sections have reviewed. The results show that increasing the share of VAT positive impact on improving production efficiency, but its impact on technical efficiency and returns to scale is negative.the tax agencies and other firms producing can increase the productivity of their manufacturing process. The results of the estimated model shows that the optimal rate of VAT for the economy by taking 19 percent of the oil revenues and regardless of oil revenues is 21%.