تابع مرزی تصادفی

An inefficient firm causes a waste of resources by using a non-optimal combination of capital and labor and especially energy. Measuring inefficiency and identifying the factors that cause it is vital in achieving the firm's potential production and, as a result, the sustainability of economic growth and increasing the economic well-being of the society. Meanwhile, choosing the right model to measure inefficiency is always one of the basic challenges among researchers in this field. This study attempts to provide an overview of the concept of efficiency and its types and different measurement models with an emphasis on the Frontier Analysis. Considering the large volume of theoretical and experimental studies in inefficiency, our review aims to provide a proper understanding of their strengths and weaknesses by investigating the evolution of the models demonstrated in the literature, and thus helps the researcher to create a clear framework for analysis and choosing the appropriate model. Furthermore, this study offers suggestions to measure inefficiency as accurately as possible from the theoretical and technical viewpoints, which have been understudied in the literature.

Considering the emphasis of the Vision Plan and especially the Fourth Development Plan on economic efficiency and return, as well as the announcement of the policies of Article 44 of the Constitution in 2005 based on the transfer of state-owned companies to the private sector and the implementation of “Justice Shares“ plan during this program, this article has been prepared with the aim of analyzing the relation between relative efficiency and equity returns for firms active in the Tehran Stock Exchange. Although the stochastic frontier analysis is an already established method for measuring firm efficiency in production economics, it has just recently begun to be employed in the field of finance. And it can be applied in the equity pricing. The findings of this analysis show that once the other factors and parameters affecting the rate of return were successfully controlled, firm efficiency would obtain a significant explanatory power for average equity returns in cross-sectional analysis of data. Moreover, the findings of this study show that the relative significance of efficiency on returns depends on firm size. The paper uses the firm-level panel vector autoregressive (P VAR) approach to examine the dynamic relation between firm efficiency and stock return. The findings show that the relation between the two is significant, and in line with theoretical studies.

The purpose of this paper is to measure the technical efficiency of the manufacturing sector in Iran's provinces during the development plans after the revolution. This analysis focuses on the comparison of provinces in terms of manufacturing performance and the determinants of technical efficiency. The model used to measure that efficiency is based on the stochastic frontier approach (SFA) devised by Battese and Coelli (1995).
The results show that the efficiency levels in the manufacturing sector are low. Even in the third development plan, as the best case, the average efficiency level was 0.401, which is very low. Although the average technical efficiency has been low, some provinces have had a considerable performance in this regard. The highest and the lowest technical efficiency levels ever recorded are 0.652 and 0.202 belonging to Khouzestan and Sistan Balouchestan provinces respectively.
Among the effective factors impacting efficiency, government ownership of industrial units and energy intensity are found to have negative impacts while enterprise size (i.e. the average value added of an industrial unit) has a positive impact on efficiency. The research also shows that provinces such as Kerman and Hormozgan, have had the highest average efficiency as compared to mega-industrial provinces.
All in all, the most important policy which can be recommended based on this research is that, given the low efficiency level in the huge industrial sector, an increase in the efficiency can be attainable through economic management empowerment in public industrial enterprises and optimum allocation of production factors in the sector.

Banks as economic firms try to provide banking services in low cost. The efficiency of banking system and its convergence among the Iranian banks is a top priority for planners and decision-makers. In this research, the data of 9 Iranian banks (6 commercial and 3 specialized) during 2001-2012 period are utilized according to intermediate approach and Stochastic Frontier Analysis (SFA) within a translog cost function and Model I of Battese and Colli (1992). The results show that average efficiency for commercial and specialized banks has been 78.95% and 87.58%, respectively, which imply that the average efficiency of specialized banks is more than that of commercial banks. In addition, the convergence process has been studied as a result of economic growth models. The speed of efficiency convergence has been estimated by -571% in absolute model, and -576% in conditional model, respectively. The average efficiency growth is decreasing and the efficiency adjustment speed is convergent.

Energy is the main scares factor of production. So paying attention to energy efficiency is necessary in achieving higher growth rates. The aim of this research is to investigate energy consumption efficiency of Iran’s provinces because of their climate differences. We estimate a Cobb-Douglas stochastic frontier production function (based on theoretical and empirical grounds) with provincial data of 1385-1390 to compare energy efficiencies of similar climate provinces. Our findings show that although the provincial inefficiency is rising through time but its effect on provincial production is trivial. The comparison of energy efficiencies between similar climate provinces show that in mountainous climate area, Chaharmahal Bakhtiari province in semi-hot climate area, Hormozgan province, in hot climate southern Khorasan province and in wet climate Gilan province, are more energy efficient provinces. Also we find that average technical efficiency and average energy efficiency of 30 provinces during our time period are 90% and 2% respectfully, which means that although the total technical efficiency of country is high but the energy efficiency is low.

This paper examines empirically the depth of financial development in the IRAN banking industry and it's comprision with MENA banking system during 1995 -2008 by applying Panel Data method. The study measures the cost efficiency of these banks using the stochastic frontier approach (SFA). The result shows that banks in MENA area, on average, could save 20 percent of their total costs if they were operating efficiently. We use a two- stage regression method to investigate the impact of depth of financial development on bank efficiency. The findings show that, the depth of financial development of the banking industry has increased the efficiency of banking system during the period of study.

The main purpose of this research is to measure technical efficiency of Iranian manufacturing sector by Stochastic Frontier Approach (SFA). For this porpoise، the performance of 130 different industrial groups، at The International Standard Industrial Classification (ISIC) was analyzed and discussed during 1996-2007. The results of the study showed that average technical efficiencies of different manufacturing groups were 0. 55. The largest score in efficiency was found for copper metals Manufacturing and refined petroleum products Manufacturing with 0. 83 and 0. 78، and the lowes scores in efficiency was registed for brick production manufacturing and grain mill products Manufacturing with 0. 21 and 0. 23، respectively. Average of technical efficiency is laid in range of 0. 50 to 0/60. In addition، the output inefficiencies are directly related to energy intensity and inversely to the size of firms، while government ownership does not affect the level of inefficiency.

The purpose of this study is to estimate economic efficiency of electricity distribution companies in Iran and to find out its determinants using Stochastic Frontier Approach. To this end panel data of 41 companies for the period 2003-2006 was collected and economic efficiency has been estimated using Battese and Coelli’s error comonent (1992) and inefficiency effects (1995) models. The findings of the research showed that the average economic efficiency of electricity distribution companies in Iran during the studied period are 1.74 and 1.65 according to Battese and Coelli’s first and second models, respectively. Among the determinants of economic efficiency of these companies, the ratio of bank employees qualified with university education and working years have most influence on efficiency. Ghom and Gilan companies are ranked the highest and lowest level of economic efficiency in the studied period, respectively.

The purpose of this paper is to measure technical efficiency of the manufacturing sector in Iran's provinces during the period 1991-2004 This analysis focuses on regional comparisons of manufacturing performance and the determinants of technical efficiency among the provinces. The approach used to measure efficiency is stochastic frontier model from battese and coelli (1995) to explore the determinants of the technical efficiency. The summery results show the efficiency levels in the manufacturing are low. The average annual efficiency level for the manufactories of provinces is 0.374 and the average annual growth in technical efficiency is 1.1 percent over the period 1991-2004. Although the average level of the technical efficiency has been low, some provinces have enjoyed a substantial performance in this regard. The highest technical efficiency level recorded is of Khozestan province with 0.76 and the lowest is in Sistan Balouchestan province with 0.199. Surveying effective factors impacting in efficiency, two factors of government ownership of industrial units and energy intensity have negative (positive) impact and enterprise size (average value added of a industrial unit) has the positive (negative) impact on efficiency (inefficiency). The research also shows that provinces such as Boushehr and Hormozgan, have higher efficiency in average comparing mega-industrial provinces and have been experiencing higher industrial efficiency rate in the last years of the studied period. All in all, the most important policy recommendation which can be presented based on the research is that given the low efficiency level in huge industrial sector, efficiency increase can be attainable through economic management empowerment of public industrial enterprises and optimum allocation of production factors in the sector.

Using Battese and Coelli (1992) Error Component Frontier Model, the cost function of four electricity distribution companies in Khorasan Province is estimated by maximum likelihood method for the period 1372-1381. The results indicate that load factor and customer density are negatively whereas number of distributed electricity is positively correlated with costs of the companies. In addition, based on estimated coefficients of cost model, there is diseconomies of scale in the electricity distribution companies. Estimated average efficiency cost is 3.98 which denotes high inefficiency in cost allocation of the companies.

The main objective in this paper is twofold: measuring technical efficiency and indicating its determinant factors for the Iranian insurance companies. We utilize stochastic frontier function and two alternative models: the “error component frontier”model proposed by Battes and Coelli (1992) and”technical inefficiency effect” model proposed by Battes and Coelli(1995). the parameters of both models are estimated by maximum likelihood method. Earned premium and investment income selected as outputs of insurance industry. Panel data of Iran, Asia, Alborz and Dana –the four insurance companies-over 10 years,(1922-2001); used to measure their technical efficiencies. The findings of this paper show that technical efficiency is equal to 79.30% in error component model and 81.71% in technical inefficiency model from earned premium point of view and 58.51% in error component model and 59.64% in technical inefficiency model from investment income point of view. Further results indicated that technical efficiency has direct relation with respect ratio of the number of branches located in Tehran, total assets, ratio of life insurance premium, ratio of non- life insurance premium and inverse relation with respect to ratio of employees qualified with bachelor’s degree.