جستجوی مقالات مرتبط با کلیدواژه "industrial" در نشریات گروه "اقتصاد"

The purpose of the article is to investigate the effect of exchange rate fluctuations on the growth of different sectors of Iran's economy through import and export channels using the Garch model and simultaneous equations during the period of 2018-1988in Iran.The results showed that exchange rate fluctuations have the greatest impact on industry and mining sectors. With the increase in exchange rate fluctuations, the added value of the industry and mining sector decreased by 0.0349% and the added value of the agricultural sector decreased by 0.008%. Regarding the added value of the service sector, since this sector has little dependence on imports, it is not significantly affected by exchange rate fluctuations. With the increase in exchange rate fluctuations, the rate of economic growth in the whole economy and in these sectors decreases, which is due to the dependence of the Iranian economy and the industrial and agricultural sectors on the import of raw materials and inputs. Finally, based on the results, in order to reduce the economy's dependence on imports and its impact on exchange rate fluctuations, it is suggested to use the import substitution strategy in the country's development plans.

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.

The aim of present study is to identify the convergence of productivity in the provinces of Iran from 2007 and 2010. In order to evaluate, the researcher used the absolute and conditional beta convergence. With respect to the importance of the neighborhood effect in the study, the spatial economy method is used. The result shows that the absolute beta convergence has been approved and this coefficient has the numerical value 0.12.Thiscoefficientisstatistically significant. The conditional convergence coefficient is equal to 0.24, and the coefficient is statistically significant at the 1% level. The control variables in the conditional convergence included industrial diversification, industrial evenness, access to interstate road infrastructure, human capital. Industrial diversification and level of education have negative effect, and industrial evenness positive and access to the road infrastructure have positive effect on productivity convergence. Based on the results of the study it can be suggested that policy- makers and economic planners take more attention to the evenness industry based on the potential of each region.

The main reason of this study is investigation in effect of the number of large industrial segments on Gini coefficient from 1974 to 2012. To this end, linear and nonlinear models are estimated. The results show that nonlinear model has more explanatory power than linear model. We defined three threshold include up, middle and down threshold, with regard to acceptance of nonlinear model. The results also show that variation in the number of industrial segment of last period has the most effect on current Gini coefficient in low threshold and is reduced with moving toward up threshold. The results also show that variation in the number of industrial segment of last period has the most effect on current Gini coefficient in low threshold and is reduced with moving toward up threshold.

The investigation of the relationship between water pollution and its determinants is one of the important issues in environmental economics and has been studied empirically in recent years. Moreover, in most empirical studies the nexus between industrial and agricultural development and water pollution has not been considered. So, to address this lacuna, the main objective of this paper is to examine the effects of industrial and agricultural development on water pollution emission in the Iranian economy over the period of 1975 to 2014 in short-run and long-run. For this purpose, the empirical econometric model has been estimated by T-Y and DOLS approaches for these sectors during the period of study. The results of this paper show that the EKC curve is confirmed in Iran and industrial value added and population density in urban areas have positive and significant effects on water pollution. Moreover, the value added of agricultural sector has negative and significant effect on water pollution.

The effort of this paper is to use 21 indicators related to the subject of the industries with 4 digit codes of ISIC(Third edition) which its information obtained from the Iran center of statistic’s during the period of (1379-1384), this article tries to rank those information by numerical taxonomy, factor analysis and structural change methods. This article also studies the structural changes with 2 digit codes of ISIC. The obtained results from indicators of fundamental analysis show that there is tendency and bias to produce industrial applications such as ungrouping equipments and machinery motor vehicle trailer and mini trailer production other transportation vehicles, fundamental metals, metallic fabric productions, chemical productions and produce the coke and the oil productions is considered during the mentioned period.