Journal of Money & Economy
Volume:8 Issue: 4, Fall 2013

In this paper, we investigate whether incorporating common factors of CPI sub-aggregates into forecasting models increases the accuracy of forecasts of inflation. We extract factors by both static and dynamic factor models and then embed them in ARMA and VAR models. Using quarterly data of Iran’s CPI and its sub-aggregates, the models are estimated over 1990:2 to 2008:2 and out of sample forecasts are produced for 2008:3 to 2012:1. The results show that in most cases the performance of the models containing common factors of CPI sub-aggregates is better than the Autoregressive, as one of the benchmark models. But, only for the horizon of two-step ahead, the performance of the factor models are significantly better than that of benchmark. Also, the FAVAR performs better than the other factor models in forecasting inflation.

This paper proposes a fully micro-founded framework that incorporates optimizing banks into a DSGE model, and evaluates the role of banks and financial shocks in the Iranian business cycles. We consider banks that offer different banking services and interact in an interbank market. Loans are produced using interbank borrowing and deposits. Banks have monopoly power, but cannot set nominal deposit and prime lending rates. The model also includes financial and unconventional monetary policy shocks. The main findings are: (1) Capturing the key features of the economy of Iran; (2) bank behavior substantially affects credit supply conditions and the transmission of different shocks; (3) financial shocks have significant effects on the Iranian business cycle fluctuations.

The impact of financial leverage on firm investment is one of the most important issues in corporate finance. Debt overhang reduces the incentives of shareholder–management coalition in controlling the firm to invest in positive net-present-value investment opportunities. On the other hand, firms without debt in their financial structure face with a new problem known as over-investment. This study uses regression analysis to survey the effects of financial leverage on investment decisions of TSE1 firms between years 2001-2010. The results show that in contrary to previous findings in literature, when using total liabilities to total assets as the measure of leverage, there is no relationship between the two parameters and by using long term debt to total assets, we see a positive impact.

Data Envelopment Analysis (DEA) is a widely used non-parametric method for ranking by Decision-Making Units (DMU). Despite the fact that DEA method does not require numerous preconditions, the necessity of the DMUs to be homogeneous is one of the most important rules in applying this technique. Moreover, in real world problems, due to the nature of DMUs, the need for ranking the grouped data has gained significant importance. Credit rating of the financial facility applicants is considered by the banks and financial institutions as one of the most important management issues and significant budget is allocated to develop and imply an effective rating system. Since the applicant organizations operate in different businesses and industries, and simultaneous rating of these companies using the DEA method leads to violation of homogeneity rule, thus, application of this powerful tool is restricted. The purpose of this paper is to resolve this key weakness in such a way that makes it possible to simultaneously consider the heterogeneous companies. The results of the proposed method have shown an enhanced capability for rating the decision-making units.

In this study، we use Stochastic Frontier analysis approach to estimate cost efficiency، economies of scale، and technological progress among Iranian banks from 1999 to 2012. The results show that there is a marked difference in cost efficiency before and after the recent financial sanctions against Iranian banking industry. Moreover، the results indicate that specialized government-owned banks are less efficient than commercial government owned banks and non-government owned banks after the imposed financial sanctions. Furthermore، we could not find a logical relationship between cost efficiency and Iranian banks’ size. Cost reductions attributed to technological progress and economies of scale were greater prior to recent financial sanctions.

This paper investigates the role of economic freedom in banking stability by using a panel data set for the period 1998-2013 in 43 selected countries. We turn our investigation to the effects of economic freedom on banking stability. The effects of economic freedom on financial stability are estimated. This paper calculates the z-score measure for banking stability. The findings from this study seem to suggest that overall economic freedom has positive impacts on the banking stability in the selected countries. The positive sign of the coefficient indicates that higher (lower) freedom on the activities that banks can undertake increases (reduces) banks’ stability, which is consistent with the view that less regulatory control allows banks to engage in various activities enabling banks to exploit economies of scale and make income from non-traditional sources. Furthermore, higher freedom on entrepreneurs helps to start businesses and job creation and consequently, increases intermediation performance which increases banks’ stability.