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  Public-Private Partnerships (PPP) models using the capacities of private sector have provided a background to supply public services and infrastructures in different ways. Transportation sector as a fundamental sector of economic development in Iran needs public-private participation models. For this purpose a theoretical literature of public-private partnerships has been reviewed and then the barriers to the development of such partnerships in transportation sector of Iran economic, infrastructure, legal and social areas were investigated. Finally with AHP, TOPSIS and SAW methods of Multi Criteria Decision Making (MCDM)the barriers were prioritized and their relative importance was analyzed. The results of three methods indicate that factor of financial markets limitations and availability of financing is the main barrier to the development of public-private partnerships. Although there is a little different among the results of TOPSIS in rating some final factors compared to other two methods, by calculating rank correlation coefficient (Spearman) the null hypothesis(the lack of correlation between the results) was rejected and with 99.75 percent probability all of the result are similar. Ranking results of barriers to the development of public-private partner ships in this study can be taken into consideration in policymaking and determining the requirement to use these models in the fields of transportation and other infrastructural areas.

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  D’Alessandro’s (2010) model investigates the impact of total government spending on private consumption but according to Barro’s (1981) suggestion, the impact of two groups of government spending on private consumption can be studied separately. The fist group produces utility affecting services for household and the second group is as an input in the private production process. So in the present article, we use d’Alessandro’s (2010) framework -after some changes in household utility function and the production function- for estimating the separate effects of two groups of government spending on private consumption.

  In the next step, the data for Iran (1959-2007) is considered and the estimation results show that the first group of government spending for household consumption in short run is Edgeworth complement and in long run is Edgeworth independent. While government spending in case of the second group has a positive relationship with household consumption both in long run and short run. Thus, this paper proposes particular attention to changes in the composition of government spending in favor of government consumption spending as an input (second group) rather than expenses affecting the utility of households.

 

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  The aim of this study is to calculate the marginal private and social costs of two thermal power plants in Isfahan region for a particular day in January 2010. For this purpose a nonlinear planning model with linear constraints has been used. The objective function (social cost) which is a twofold objective function is calculated by the summation of variable costs and external costs of power plants in the above mentioned region.

  The results of minimizing the objective function of private cost and also minimizing objective function of social cost indicate a significant difference between marginal social cost and marginal private cost. This difference is considered as marginal external cost in peak hours of electricity consumption and has had an obvious increase to the off-peak hours of electricity consumption in the region of the study. Taking into account the social costs of electricity generation, green power generation technologies can compete with thermal power plants.

 

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The concept of “Innovation” has changed considerably in recent years. According to new theories, the innovation emerges in a system of interrelated elements and determinants during which the idea changes to a commercialized output or process. The literature on the innovation has concentrated mainly on various aspects of innovation chain separately. In this paper we tried to investigate the general effects of the whole elements of the innovation chain simultaneously. These elements are: R&D expenditures, physical capital formation, human capital and patent filling (residence and non-residence). We utilized multivariable time-series methods including cointegration and vector error correction model (VECM) to assess the long-run effects of innovation elements on total factor productivity in Iran. Results show that excluding the human capital variable, other elements of innovation chain have positive effects on TFP among them, residence and non-residence patent filling having the normalized long-run coefficients of 0.58 and 0.48 respectively, are the most important factors affecting TFP in Iran.

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The shares of state-owned or public companies are supplied in privatization plan. If the financial market be clear and efficient, it is expected that discovered price of supplied shares be efficient too. However, there is no guarantee for the fulfillment of this condition. Specially, implementation of those policies that, for example, a shock to exchange rate or the price of inputs (such as fuel), can affect market efficiency to discover efficient price of shares. In this study, the factors that cause the deviation of the actual share price have been identified, at first. After that a computable system has been designed by implementation error corrector filters. The input of this system is biased variable and corrected variable is the output. In this study, comparing previous studies, is generalized. So computable designed model can evaluates a wide range of factors. This system has been used to calculate the share of Tehran Regional Electricity Company. The outcomes show that the value of its shares is change from a negative amount (based on bias variables) to 2445 billion Rials (after passing based variable from correction filters). This difference, in addition of information asymmetry, maybe causes, in special in energy and electricity sectors, some opportunities to rent.

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Cigarette and tobacco products in the VAT Law is considered as one of the particular goods and in order to contorlingit’s consumption by price tools, higher tax rates than the standard rate will be levied on it. In this paper, forecasting of revenues of this tax using an approach based on the estimating of tax base has been considered. Thus the first stage, tax base (consumption expenditure) is forecasted for the period 2012 to 2015 and then tax related years by applying the tax rates, will be calculated. In this regard, Because of concerns that policy makers have access to accurate predictions of tax revenues, Supervised neural networks Method to prediction and back-propagation algorithm to train is used. The results indicate that the average annual growth of revenue from value added tax on Cigarette consumption will have 20 percent during the forecasting years.