Competition law is a newcomer to the legal system recently. A sound understanding of competition policy can provide us with sufficient bases to apply a fundamental and normative view of the issues of competition law. The difference in supervision and regulation determines how the market functions and in order to understand this difference one must understand competition policy. Competition policy may be based on governmental support for national production and industry or on a non-interventional and regulatory posture. Moreover, supervision, based on the principle of non-intervention in the market mechanism, is rooted in liberal ideas; however, regulation, whether as a rule or an exception, is based on the assertion that the market has been ineffective in attaining its goals. Therefore, the government will resort to interventions to regulate inefficiencies.  This paper aims to analyze Supervisory Authority in Implementing Competitive Policy by employing the description method. In this article the author tries to first delineate competition policy, its related requirements and imposed deviations to the market. Then, by defining the supervisory entity and clarifying its distinction from the regulatory institutions, the author considers the characteristics of an appropriate supervisory entity conducting a comparative study of this issue in Iran and the U.S.A. This form of Competition policy because of its applicable experiences which have been well described by recent scholarship is considered suitable for the native system.

The aim of this study is Decomposition of the changes in energy consumption with emphasizing the Structural changes in Iran during 2001-2011 using Input-Output Structural Decomposition Analysis (I_O SDA). Structural changes in this study represent the changes in structure of intermediate input in sectors and also changes in structure of final demand categories. Structural changes in intermediate inputs decomposed into intermediate input substitution in sectors and changes in direct backward linkages. Structural changes in final demand represent the changes of the share of each sector in total final demand categories. The results showed that energy coefficients helped to reduce energy use and final demand changes and technological changes (Structural changes in intermediate inputs) caused to increase of energy use. The final demand had the main contribution on increase of energy use (44186. 26 BGJ). Among the final demand components, increase in level of investment and household’ s consumption was the main drivers of energy use increment.

In this paper is tried to analyze emission Decomposition of CO2 to three effects include Leontief Structure (DCstr), Final Demand Effect (DC fdm) and Emission Intensity Effect (DC int) by using of Structural Decomposition Analysis (SDA). Then, we compare three such SDA methods analytically and empirically through decomposing changes in Iran’s CO2 emissions. SDA’s method is consisted of Lasppeyres and Divisa family. this paper is used of 1986-1991 and 2001-2006 tables for estimating SDA methods. this study is also used RAS method for gaining inside-sector exchanges matrix, to assimilate 2001-2006 tables. The results show that three above effects in-group participate increasing emission (in both comparison of 1986-1991 and 2001-2006). Whereas the sub-categories results for three methods (MRCI, LMDI-I and LMDIII) are close to each other in 1986-1991. But above results are not true for 2001-2006.

The purpose of the current research was to investigate the obstacles to the implementation of school-based management in Iran's educational system based on the interpretive Structural modeling approach. The research method was a modeling study. The statistical population of the research was specifically the academic staff members of the university, 25 of whom were purposefully selected from the desired cases. The data collection tool was a researcher-made self-interactive questionnaire. In order to measure and evaluate the validity of the questionnaire, the criterion of content validity was used. The content validity of the questionnaire was 0.96. The data Analysis was done with interpretive Structural modeling method. The results of the research showed that 9 factors play a role as barriers to school-oriented management. Also, the results showed that financial obstacles (the cost of school-oriented management), socio-cultural obstacles and political obstacles (political focus on schools by the central government) as key independent variables have high influence power and low dependence. Also, the results showed that the lack of belief in the professional competence of school administrators, the lack of infrastructure facilities, the emphasis of upper management on the supervision and control of schools, and the lack of cooperation of local communities with school-based management as the linking variables with the greatest power of influence and the greatest power of dependence. and the centralism in the education system of the country and the lack of legal powers to school managers and staff as dependent variables have high dependency power and low influence power.

Technological change is one of the most important sources of the output growth not only on the supply side but also on the demand side of the economy. Because technological change in each economic sector causes input substitution among production inputs and this can influence growth of output in other sectors through the backward linkages. In the present study, the impact of technological changes of economic sectors on the production growth of four agricultural subsectors, from demand perspective, has been analyzed over 1986-2001 periods. To this end, Structural Decomposition Analysis methodology has been utilized using input-output tables of the years 1986, 1991, and 2001. Following this approach and as a first step, output growth has been decomposed into three main components including, changes in final demand, import substitution, and technological change. Technological change effect has further been decomposed into individual coefficients and technological change effects in each economic sector on the growth of output in agricultural subsectors were calculated. Results indicate that growth of agricultural products is highly influenced by technological change in food industries which has been relatively livestock and poultry using and the other agricultural products saving. This result emphasizes the necessity of developing food industries for processing cropping, horticulture and fisheries products together with the development of livestock and poultry processing industry.