Iranian Journal of Economic Research
Year:2010 | Volume:13 | Issue:41|Papers Count:7

The purpose of this research is to measure cost and profit efficiency for the Iran's commercial and public banks. We also determine time variant efficiency factors for period 1381-1384 (2001-2004). To measure the efficiency, we use stochastic frontier analysis (SFA) and error component model following Battese and Coelli (1992) using the Maximum Likelihood method and a panel data. Labor, physical capital, and financial capital are considered as inputs, and loans, bonds and other earning assets as outputs. The results show that most of the private banks are more efficient in profit efficiency than public banks, while most of the public banks are more efficient than private banks in cost efficiency. The cost efficiency has decreased but the profit efficiency has increased for the period under consideration. Profit efficiency is not positively correlated with cost efficiency, suggesting the possibility that cost and revenue inefficiencies may be negatively correlated. Cost efficiency ranges from 46.88 percent (Bank Saderat) to 91.58 percent (Bank Tejarat) with an average of 68.8 percent, and profit efficiency from 61.16 percent (Bank Melli) to 94.85 percent (Bank Sepah) with an average of 85.3 percent. Average and variance of profit efficiency is more than those of cost efficiency, implying profit efficiency is influenced by more variables.

DEA models that calculate the efficiency index with respect to inputs and outputs are commonly used in recent years. Although flexibility is one of the key characteristics of DEA models, specially where data is abundant, they overestimate the efficiency in small samples. Furthermore, they do not take into account managers' relative preferences about inputs or outputs. In this study, the managers' preferences are derived from a survey completed by bank experts. Then analytical Hierarchy process (AHP) is used to the weight the outputs and inconsistency of expert views.Finally, the expert matrix is derived from consistent expert views by the weighted geometrical average. Results show that 85 percent of branches have the efficiency lower than 50 percent with 41 percent of branches having the efficiency lower than 25 percent.

Using Conventional methods of Chenery-Watanabe and Rasmussen in inter industry linkages hae three limitations: Supply and demand sectors cannot be distinguished, distinction between balanced and unbalanced growth strategies are not clear and the measurement of inter industry linkages mainly depends on the size of sectoral intermediate demands. In this paper, we introduce an eigenvector method to overcome those limitations. We use the 22 aggregated sectors of the 1380 (2000) survey-based Input-Output table. The overall results show high correlation coefficients between the conventional methods. Furthermore,, we find that the eigenvector method is able to better identify those sectors which remains in the production process and therefore the key sectors.

Productivity improvement is one of the important factors in economic growth.. This paper attempts to study the impact of human capital on Total Factor Productivity in the industrial sector of East Azarbaijan Province in Iran during the period 1374-1385 (1994-2005). To probe the impact of human capital on Total Factor Productivity, the Data Envelopment Analysis (DEA) technique the Malmquist Index have been applied. The results indicate that the management efficiency, as an index of human capital, affects the TFP to almost the same extent as other factors.

Electricity demand is growing very fast in Iran and it is important to forecast its future demand and its monthly variation accurately.Artificial Neural Network (ANN) is a powerful tool for nonlinear models for forecasting and it was used to estimate monthly electricity demand in this study. In this paper, we compared the Non-linear ANN model with ARIMA linear model to estimate monthly electricity demand for a priod of 3 years. Using MSE, RMSE, NMSE, MHE, MAPE and R2 indicatorss, our results show that ANN forecasting model is superior to ARIMA in terms of less error coefficient and high explanatory ability.

This paper investigates the sustainability of fiscal process in Iran. For fiscal process to be sustainable, government's intertemporal budget constraint should be satisfied.In this paper, we have assessed sustainability condition for period 1964-2007, using cointegration tests. The model is based on Bohn (1998) and the Barro's tax smoothing model (1986). This model is modified for an oil-producing country, noticing that oil income has comprised a large part of government income in Iran.Results show that fiscal process is not sustainable in Iran. The sustainability of the fiscal process is also compared in two periods, before and after the revolution.The estimated coefficients of the model indicate that the fiscal sustainability condition has become worse after the revolution