Cost Efficiency of the Syrian Banking Sector: Using Parametric and Non-Parametric Analysis

This study aims at measuring the cost performance efficiency of Syrian banking sector during the period 2006-2010. The selected period has been going through a lot of reforms to build an effective, efficient, competitive, and stable banking system. The study employs both parametric Stochastic Frontier Analysis (SFA), and non-parametric Data Envelopment Analysis (DEA). These methods are used to evaluate the cost efficiency of Syrian banks. The study utilizes a one stage SFA model that includes input, outputs and the environmental variables (ownership structure, size, deregulation, market structure, and capital ratio) of cost efficiency measurements. Moreover, the traditional DEA model has been used with the aim of comparing the results of the SFA model. The results of SFA analysis indicate that the cost efficiency of Syrian banks is estimated to be, on average, 58.8%, while the DEA model results shows an average of 69.5%, the results also show that private banks are more efficient than state-owned banks using both SFA and DEA analysis. The study also found that large banks are more efficient than smaller banks.

Measuring the efficiency of container terminals using Data Envelopment Analysis

Container terminals are different in the degree of service for container ships, which increased recently and especially in the Mediterranean, also differ in use of the amount of inputs required for operational process, which create the problem of declining technical efficiency of container terminals Mediterranean. Therefore, the researcher measured the efficiency (12) a major container terminal in the Mediterranean in 2010, using the Data Envelopment Analysis (DEA). Where the inputs: Number of quay cranes, and space of terminal, and the output was the annual throughput of containers. The practical results showed that the rate of technical efficiency – (CRS) was 49%, while the rate of technical efficiency – (VRS) 69.3%. Tangier container terminal achieved the best level of technical and scale efficiency, While Mersin, Algeciras, and Tartous achieved the technical efficiency only, while remaining terminals did not achieve any efficiency, Therefore advisable to reconsider in their used inputs to improve their efficiency.

Analyzing Financial Statements Using Window Data Envelopment Analysis

Internal and external data users are interested in financial data analysis, because of their need to obtain financial information about the company and to know the strength of its financial position. Although ratio analysis is always considered as one of the best financial statements analysis methods, but its interpretation is often difficult and controversial. Where each group of ratios can only show a single financial dimension, thus it may be difficult, when analyzing financial statements, tointe grate the results of different groups of financial analyses. So, an approach namely Data Envelopment Analysis, which is used in this research with Window approach by using variable returns of scale model, known as BCC related to researches Banker, Charnes and Coopers. In order to study the efficiency of the 19 subcompany of the General Establishment for food industries during the period 2008-2010. And also to study the direction of performance changes, in order to determine the best and the worst company through the company's efficiency using Super-Efficiency model. The study results showed that the number of efficient companies are six, and the number of inefficient companies are 13. Also showed that the Boken Water Company got the highest efficiency, and the company conserves Hasaka got less efficiency. All companies have less efficiency during the study period.