فصلنامه مدلسازی اقتصادی
سال نهم شماره 3 (پیاپی 31، پاییز 1394)

In this research, main issue is to find the indicators and provinces that inefficient and even efficient provinces can use them as references to achieve the boundaries desired in decent works. So, an analytical-descriptive methodology is used at the presence of all provinces in 3rd and 4th development plan during 2000-2007. The results pattern-finding in provinces have represented that the provinces such as Hormozgan, Tehran and Gilan are the most important ones. Also, in terms of the indicators all over the country, the results have shown a high sensitivity in the provinces regarding to the indices of relief committee members and underemployment. The consequence of this sensitivity in decision making bodies of the country is to use these indices to achieve optimum efficiency.

The banks and non-banking financial institutions have facilitated trading and commercial activities and increased the markets, and economic growth and prosperity by organizing and directing the payments. In this study, firstly, the researchers have explained the channels by which banking and non-banking financial institutions affect economic growth, and secondly, paid attention to the ways of affecting the explanatory variables on economic growth in Iran. At the end, by using the traditional model of King and Levine Generalized Method of Moments (GMM), the effects of non-banking financial institutions supervised by Central Bank of IRI and Commercial and specialized banks are studied during 1999:Q1 - 2013:Q4. The empirical results of this study have indicated that all explanatory variables used have significantly positive effect on economic growth. Also, the experimental results have shown that banking financial institutions have a greater and significant effect on economic growth compared to non-banking financial institutions.

This study intends to investigate the effect of air pollution on public health expenditures and to identify the most important factors affecting the relationship between air pollution and public health expenditures. The scope of the study is the developing countries during 1995-2011. For this purpose, a dynamic panel and Generalized Method of Moments are used. The empirical results indicate that there is a robust and significant relationship between air pollution, per capita income, urbanization, government size, aging dependency and public health expenditure and unemployment have a negative but significant effect on public health expenditures. Also, per capita income, urbanization and education have significant effect on the relationship between air pollution and public health expenditures. That is, the effects of air pollution on health expenditures in the countries with higher per capita income, higher urbanization rates and lower education levels are significantly higher than other countries.

The main purpose of this paper is to evaluate the structure of banking structure in Iran and assess the monopoly power factor based on Bresnahan and Lau approach. In this paper, the market situation of monetary in Iran consisted 18 active banks are studied during 2007–2011. By the use of Bresnahan's market power model, it is found that there is no deposit market for pre-said banks in Iranian banking industry. The coefficients estimated by the research model have represented that the hypothesis of perfect competition without any withholding rates and deposit rates can be rejected for the entire market.

Exchange market pressure (EMP) is an important index for evaluating the changes of exchange rate and foreign exchange reserves simultaneously. In this paper, exchange market pressure is calculated based on Weymark approach during 1989: Q1- 2012:Q4. The method applied for estimating EMP is Co-integration technique by using Johansen-Juselius (JJ) technique. The results have represented that, during the period, there is a pressure on exchange rate and about 44% of exchange market pressure is attracted by foreign exchange and remaining 56% absorbed by the changes in exchange rate.

In this paper, the factors affecting house prices have been studied in Tehran during 1991-2007. After combining the parameters and variables, land prices, construction costs, interest rates, per capita residential buildings completed, money supply and the returns in alternative markets are considered as theoretical determinants of housing prices, in which their effects should be tested and measured. Besides these factors, a component of unobserved or implicit trend including technical performance, preferences and non-economic factors is considered in the model. In order to estimate the model, a structural time series is used. This model has the capability to specify the regression equation of state - space and Kalman filter algorithm and the maximum likelihood method to estimate unknown parameters. The results have reflected the negative impact of real interest rates, returns on alternative assets such as gold, foreign exchange, equities, per capita residential buildings completed and the positive impact of construction costs. But, M2 is weak and insignificant. Strong relationship between land prices and housing prices identified seem to bo a simultaneous movement of two variable rather than a causal relationship.

The purpose of this study is to investigate the development and collapse of price bubbles of housing market in Tehran by the data of housing rents, land price during 1995:Q1-2014:Q1. Based on the critiques to the common methods of evaluating the price bubbles and the possibility of happening more than one bubble in the time period under consideration, in this study, Generalized Supremum Augmented Dickey–Fuller is used. By this method, it is possible to determine the development and collapse periods of price bubble in addition to test multiple bubbles,. The results represent that in the period under review, the ratio of price - rent as an indicator of return on assets, has no rational price bubbles. However, by the abruptly and explosively changing in defining the price, there will be a price bubble in housing during 3 periods including 2001:Q1- 2002:Q1, 2004:Q1- 2004:Q2, 2006:Q2- 2007:Q2 and 2006:Q2-2007:Q2 and so in land real prices during 3 periods including 2000:Q2-2001:Q2, 2006:Q2-2007:Q2 and 2012: Q1-2013:Q2.