Mohsen Mehrara; Mojtaba Mohammdian
Volume 19, Issue 61 , February 2015, , Pages 83-116
Abstract
This paper has tried to apply Bayesian Model Averaging (BMA) and Weighted Average Least Squares (WALS) approaches as methods of averaging in Bayesian econometrics in order to investigate the impact of 18 macroeconomic variables on Gini coefficient in Iran based on annual data from 1976 to 2010. The results ...
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This paper has tried to apply Bayesian Model Averaging (BMA) and Weighted Average Least Squares (WALS) approaches as methods of averaging in Bayesian econometrics in order to investigate the impact of 18 macroeconomic variables on Gini coefficient in Iran based on annual data from 1976 to 2010. The results of two approaches indicate that the growth rate of Gross domestic products is the most important determinant of the Gini coefficient, implying economic growth arising from oil booms leads to more unequal distribution of income. As regards to other variables, the results of BMA estimation indicate that second and third effective variables on Gini coefficient are respectively the ratio of government current expenditure to GDP and the ratio of oil revenue to GDP for which an increase in the ratios engenders inequality. Thus the distribution of oil rents and government expenditure is inconsistent with primary purposes of politicians to ameliorate income distribution. Also the results of WALS estimation rank openness and exchange rate as the most effective variables respectively with positive sign. Therefore economic liberalization moving along with oil revenue during the sample period, has been against the favor of lower income groups. According to aforementioned results, it is necessary to revise economic growth policies to the benefit of low-income groups of people. In addition, renovation of budgeting process and allocation of resources with aim to reduce rent-seeking opportunities and more privileges for low-income groups must be considered by policy makers.
Mohsen Mehrara; Hamid Abrishami; Seyed Mohammad Hadi Sobhanian
Volume 16, Issue 49 , February 2012, , Pages 177-204
Abstract
In this study we have dealt with the non-linear effects of economic growth on the energy consumption growth in countries depending on petroleum revenues (OPEC member countries)as well as the BRIC countries. For this end, the panel data from 1980 to 2006 for both groups of above-mentioned countries was ...
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In this study we have dealt with the non-linear effects of economic growth on the energy consumption growth in countries depending on petroleum revenues (OPEC member countries)as well as the BRIC countries. For this end, the panel data from 1980 to 2006 for both groups of above-mentioned countries was employed and analyzed on the basis of threshold error correction model. The results indicate that in both group of countries, the effects of economic growth are non-linear so that the high economic growth rates (the economic growth rates more than threshold level of 0.01 for OPEC and 0.09 for BRIC) has increased the energy consumption growth with more severity. Of course, the effects of economic growth on the energy consumption growth in BRIC member countries are by far higher. Therefore, although an economic growth rate higher than threshold level may lead to environmental pollution in the OPEC member countries, but these countries should have less anxiety about the detrimental environmental effects of their economic growth compared to the BRIC countries.
Hamid Abrishami; Ali Moeini; Mohsen Mehrara; Mehdi Ahrari; Fatemeh Soleymani Kia
Volume 12, Issue 36 , October 2008, , Pages 58-37
Abstract
In this paper, we use GMDH neural network based on Genetic Algorithm to model and forecast the price of gasoline using two approaches; Deductive Method and Technical Analysis. The results of deductive method indicate that the accuracy of prediction could reach up to 96% and in technical analysis could ...
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In this paper, we use GMDH neural network based on Genetic Algorithm to model and forecast the price of gasoline using two approaches; Deductive Method and Technical Analysis. The results of deductive method indicate that the accuracy of prediction could reach up to 96% and in technical analysis could reach up to 99%. Furthermore the comparison reveals that the GMDH neural networks model consistently outperforms the regression model used in this study.
Mohsen Mehrara; Alireza Abdi
Volume 9, Issue 31 , July 2007, , Pages 1-26
Abstract
This paper studies the impact of Rial's real devaluation and scale variables (domestic and foreign real income) on Iran's trade balance using the Johansen-Juselius and ARDL methods for the period 1338-1383 (1960-2004).
According to co-integration tests results, trade balance variables, ...
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This paper studies the impact of Rial's real devaluation and scale variables (domestic and foreign real income) on Iran's trade balance using the Johansen-Juselius and ARDL methods for the period 1338-1383 (1960-2004).
According to co-integration tests results, trade balance variables, domestic and foreign income, and black market exchange rates are co-integrated indicating a long run equilibrium relationship among them. Moreover, all the long and short run coefficients have expected signs and are stable during the sample period. However, the official exchange rate is not able to explain trade balance fluctuations satisfactorily in this period. The results of co-integration tests reject the null of long run equilibrium relationship among trade balance, scale variables and official exchange rate. The diagnostic tests in the error correction models with official rate imply serious mis specifications as well. The study suggests the need to monitoring the black market rather than official exchange rate.
Mohsen Mehrara; Ghahreman Abdoli
Volume 8, Issue 26 , April 2006, , Pages 25-40
Abstract
This paper uses daily data from the Tehran Stock Market (TSM) to illustrate the nature of stock market volatility in an undeveloped stock market. Although most studies suggest that a negative shock to stock prices will generate more volatility than a positive shock of equal magnitude there is no evidence ...
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This paper uses daily data from the Tehran Stock Market (TSM) to illustrate the nature of stock market volatility in an undeveloped stock market. Although most studies suggest that a negative shock to stock prices will generate more volatility than a positive shock of equal magnitude there is no evidence of symmetric effect in TSM. The EGARCH model passes all the tests and appears to be the most adequate characterization of the underlying data generating process.