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Value Added Tax (VAT) as a method of tax charging with creating a new tax base broad has been interest of many countries. Also Value Added Tax in our country in order to reform the structure of tax and increasing government revenues was approved by the House after a relatively long time and in the second quarter of year 1387 was carried out. Given that this law as an experiment and for five year was carried out study of effects of this tax on macroeconomic variables is of particular importance. In this study has tried to use the analytical relationships Input-Output and production of technical coefficient matrix constant assumption of fixed economic conditions and economic variables and limiting assumptions of this study to the price effects resulting from applying VAT on cost of whole different departments to deal with the country's economy. By using of model price of input - output and applying tax rates issue of Article 12 on exemption for goods and services and ultimately applying export exemption issue of Article 13 on value added tax the price effects of each section of economy is calculated and with and with considering of share of each section from the whole output the price effects is calculated. Results show that implementation of VAT has had very low price effects.

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The subject of microeconomics is the behavior of firms, individuals and government. According to production theory, rational behavior of the firms, leads to profit maximization. So, one of the most important rational questions in production theory, is the determination of a suitable location of the firm. In the last two decades, several theories have been proposed to analyze the factors affecting the location of economic activities. These theories emphasize on many factors that can be summarized in two categories: factors affecting supply and demand. The aim of this article is to determine and analyze factors affecting the location of electronics industry in Iran. In this regard, 25 factors were identified. Whoever, this number of explanatory variables decreases the number of degree of freedom in a Logit and/or Probit model dramatically. So, the principal component analysis was used to decrease the number of LHS variables. Results show that the industrial development and the creation and maintenance of facilities have important effects on the location of electronics industry in different provinces of Iran. Also due to high proportion of the value to the weight of the final products or the high mobility and tradability of electronics industry products, local and surrounding area‘s income have negative impacts on the industry location.

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One of the most important aspects of vulnerability of the Iran economy can be observed in depreciation of real exchange rate during the oil booms. This phenomenon is called "Dutch disease". In other words when a country starts exporting natural resources, the ensuing capital inflows lead to an increase in demand. The real exchange rate (RER) typically appreciates due to “spending effect” as the price of domestic nontradables increases relative to the price of tradables. The main objective of this paper is to examine the cyclical patterns of the house price and macroeconomic variables in Iran. Using Hodrick and Prescot filtering method, the cross-correlation analysis is first presented to identify the long-run behavior of the variables. Then based on the vector autoregressive (VAR) model, we investigate the interaction between housing price cycles and cyclical component of real oil revenue, real exchange rate, real GDP, money supply and interest rate. The results show that positive oil shocks, leads to an increase in housing price cycles.

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  This research aims to analyze the effects of industrial agglomeration on regional economic growth in the Iranian provinces. For this aim, this study is divided into theoretical and applied sectors.

  In the theoretical point of view, the research has proposed a simple theoretical framework to study the impacts of industrial agglomeration on regional economic growth. In applied sector, we have specified econometrics models and estimated them by using a system of simultaneous equations using Panel Data for 28 provinces of Iran over the period 2000-2006.

  Results show that regional economic growth is positively affected by industrial agglomeration and regional knowledge level and negatively affected by human capital mobility cost and per capita income. Results also show that regional economic growth, transportation cost, household expenditure and human capital mobility cost have positive effects on industrial agglomeration in the Iranian provinces.

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Generally,some booms in housing prices are followed by busts. One common phenomenon relating these changes is that the house price cycle is generally believed to the product of the short-run deviations from the long-run upward trends. The long-term cyclical fluctuation in Iran’s housing market was periodically occurred about every 6 years.
 Furthermore, Movements in house prices have significant impact on household welfare, financial stability and business cycles. Being able to forecast housing price booms is therefore of central importance for central banks, financial supervision authorities as well as for other economic agents. However, forecasting house prices using only a single or a few selected variables at a time intuitively appears efficient because only a single variable almost contain all of the pertinent investigative information about the past behavior of the variable. In this study, wavelet decomposition has been used to extract the cyclical components of house price, and then using the cyclical components and neural network methodwe start to forecast the booms in housing prices in 2013.