JOURNAL OF APPLIED ECONOMICS STUDIES IN IRAN
Year:2016 | Volume:5 | Issue:19 |Papers Count:11

This paper examines the robust determinants of public sector size (government) in IRAN in the years 1979-2012 and the uncertainty condition of the model. For this purpose is used the Bayesian Averaging of Classical Estimates (BACE) approach due to favorable characteristics for the assumption of model uncertainty. With estimate 16,000 regression and Bayesian averaging from the coefficients, effective variables were identified. The results show that robust determinants of the public sector size were as follows: lag the government size, population, growth rate of oil revenues, the ratio of population less than 15 and over 65 years to total population, bureaucracy and economic globalization.

Monetary Policy is one of the important instruments of the economic demand management and is much important in policy making decisions. In this direction, determination the rule of monetary policy making and discretion of expansionary and contractionary monetary policies are also important for policy makers and economists. In this study, the monetary conditions index (MCI) over the period 1352-91 and financial conditions index (FCI) over the period 1377-91 calculated using the Principal Component Analysis for Iran's economy. According to the results, the monetary conditions index impact any 3 channel exchange rate, interest rate and credit channel. Also in the calculation of index financial conditions, in addition to the the above channel 3, also has its effect channel Finance. Credit channel has the greatest weight in both financial and monetary conditions index, while the interest rate channel of the lowest weight than the 3 other channels in both the index, implying that credit channel is more important than the other channels in determining the level of output in Iran.

This paper examines impacts of money base and government shocks on economic growth and income inequality of Iranian economy using dynamic stochastic general equilibrium model. The New Keynesian approach was used to design appropriate model and definition the equations. Also, time series data of period 1961 to 2012 was used to calculate the parameters and the simulation the endogenous variables of model with real world. The behavior of the Gini coefficient and economic growth showed that during the selected period the Gini coefficient behavior is counter-cyclical to economic growth. Results based on impulse response functions indicate that money base and government shocks have increased the economic growth via aggregate production. On the other hand, productivity shock has increased economic through non-oil production growth. Oil income shock has increased economic growth through GDP Also, money base and government shocks have worsened household’s income distribution. So, income inequality was increased.

In this paper an attempt is made to study the impact of energy consumption growth on forming regimes of low and high value-added growth of economic sectors of Iran economy by using seasonal data from 1346 to 1392. So, in some models, Markov switching model with the supposition of fixed transition probabilities by value-added growth of economic sectors variable were expanded. According to modeling results, increase in energy consumption growth, leads to increase in value-added growth of economic sectors in Iran economy. In addition in modeling value-added growth of agriculture group and value-added growth of manufacturing and mining group, the positive effect with motion of low value-added growth regime to high value-added growth regime is increased. also in value-added growth of transportation storage and communications group, the positive effect for both regimes are great.

This study was conducted to provide an applicable model for ranking industries based on economic performance. Experts selected indicators include: value added, investing value, production value, exports, employment creation, labor and production productivity. Prioritization of industries is a complex issue, because of the interrelations between these criteria, different dimensions and uncertainty of experts' judgments in determining the importance of the criteria. Also, Human judgments about preferences often vague and exact numbers are not available, then, the use of fuzzy logic in solving such problems is essential. Fuzzy Network Analysis Process (FANP) is a fuzzy multi-criteria decision making model that takes into account the interrelationships between criteria. Therefore, this technique has been used in the determination of the importance of indexes. The data available for various industries in each index, have crisp values, so in the ranking of various industries, the study applied the benefits of ARAS technique. The findings show that the proposed integrated FANP-ARAS technique is able to solve such issue effectively. The data of all manufacturing industries are considered based on the ISIC international classification codes, 2-digit level in the year of 1392 (March 2013 - March 2014) that is presented by the Statistical Center of Iran. The results show that the best industries, based on selected economic indicators in Year 1392 (March 2013 - March 2014), respectively, are as follows: materials and chemical products industry, oil refineries and nuclear fuels and coke industry, and production of basic metals. Other industries are next in rank.

The relationship between the oil as a one of the principal factors in the production and the level of economic activity is a fundamental empirical issue in macroeconomics. Also, on the base of some optimistic new economic growth models, uncertainty of non-renewable proved reserves through positive probability including technology growth and discovering unexpected reserves, is one of the factors which positively affects on the economic growth; therefore, time allocation of non-renewable energy resources to ensure long term economic growth and intergenerational justice is not important. So, to find some evidences about it, in this research we try to find experimentally direct effects of uncertainty of oil proved reserves on macroeconomics of Iran by using annually data from 1980 to 2013 by using Multivariate GARCH-in-mean VAR model. We find that uncertainty in oil proved reserves has not had statistically significant effect on aggregate output in the country in our sample, which time allocation of non-renewable oil proved reserves to ensure long term economic growth and intergenerational justice must be attend. We also find some evidence that the responses to positive and negative shocks are symmetric.

Intermediate import of Iranian industrial sectors almost have 60 percent share of the Iranian imoports which is directly applied in production process. In this paper, with employment of updated social accounting matrix of the year 2011 for Iranian Parliament Research Center, have main question proposed that what are the economic and social impacts of industrial sectors supply constraint on the other economic sectors and production factors and institutions incomes. The results of this study indicate that the most supply constraint occure in manufacture of coke and refined petroleum products which has about 87 thousand billion rials reduction of production in the whole of economy. Also, for all supply industrial constrain sectors instead of manufacture of food and beverages products, operational surplus has the most share of reduction in production factors income. Mixed income after operational surplus have the second rank in reduction of production factors income. Also, according to our expectations, urban households receive more than rural ones and companies income reduction due to supply constrain of industries.

Corruption is defined as abuse of power by governmental and private officials for personal goals. Corruption is affecting by many variables, such as political, economic, cultural, geographical factor and will be influenced on many variables. The main goal of this article, is analyzing of effect of economic activity combination on corruption. In this article, 6 variables corruption, GDP per capita, oil rent, share of industrial value added in GDP and share of services value added in GDP are used. In this article, two models are estimated. First model is Bayesian model that is used for Iran. Second model is panel data model that is used for OPEC countries over the years 1995 to 2010. The conclusion have been obtained shows that oil rent and share of services value added in GDP variables have an positive effect on corruption and as they increase, corruption have been increased. The share of industrial value added in GDP and GDP per capita variables have an adverse effect on corruption and as they increase, corruption have been decreased. Also democracy has no significant effect on corruption.

Many countries are trying to reduce energy consumption and C  emissions by increasing the efficiency and productivity of industries. Therefore studying of environmental efficiency is one of the most common and engaging issues in environment and energy economics. In this paper, we assess the environmental efficiency of Iranian electric power companies by two Data Envelopment Analysis approaches (that is Slack-Based Measures and Directional Distance Functions) in the period of 2004-2014. The results show that Isfahan, Kerman and Gilan electric power companies consist of a high efficiency group, while Sistan and Bluchestan and Kish Electric Power Companies exhibit low efficiency scores. Also, Azerbaijan, Isfahan Khuzestan and Mazandaran electric power companies have been technological regress in recent years. Generally, the overall performance of power industry has been faced with consecutive efficiency decrease and the highest technological regress since liberalization of energy prices in 2010. On the other hand, the Kruskal–Wallis statistic accepts the hypothesis that environmental performance of power industry has been affected by this liberalization.

One of the essential requirements for the banking system is receiving timely payments from applicants because the banks to create their own commitment based on the amount and maturity of their claims. Certainly any disruption repayment facility cause an inability to return depositors, discredit and bankruptcy of banks and institutions, increasing prudential reserves, reducing the facility's capacity to grant loans and ultimately reduce banks and institutions efficiency.Banking system use different ways to ensure timely receipt of claims. One important aspect of this method of obtaining commitment is based on the stipulation. Offering the replacement for delay penalty payment in Iranian banking are necessary because of amount of nonpayment Loan and existing deficiencies in this alternative.The article is going ahead with the use of analytical and descriptive with the experiences of other countries and the questions from Figh Scholars to investigate this hypothesis that the strategy aims to increase the interest rate deals in the beginning of the contract and pay the discount while repayment is timely on contract funds is a good alternative for late penalties on late payments as a stipulation.

This paper examines the impact of financial development and value added on energy consumption in Iran's agriculture and industry sectors , over the period of 1976-2013 by using BAND ARDL, Based on unrestricted error correction model (UECM), (Pesaran, shin and Smith, 2001). In this study was used ratio of credits allocated to agriculture and industry sectors as indicator of financial development. The finding of BAND ARDL are confirming long run relationship among variables and show ,in both sector, financial development and value added growth increase energy consumption. Financial development growth by 1 percent increase energy consumption in industry and agriculture sectors respectively in the 0.05 and 0,025 percent and a 1% increasing in the value added increase energy consumption by as much as 0.31 and 0.62 percent in the aforementioned sectors. Also,the results showed the negative impact of urbanization and liberalization on the energy consumption in agriculture sector and the positive impact of urbanization on the energy consumption in industry sector.