محمد ولی پور پاشا

This paper seeks to investigate the determinants of banking network profitability in Iran from 2007 to 2012. The results of our study indicate that both bank-specific factors and macroeconomic factors influence banks’ profitability in Iran. Results confirm that bank profitability is significantly influenced by investment to total assets ratio, non-performing loans to total assets ratio, and time deposit to total assets ratio. Among external factors, it turns out that economic growth rate has a significant positive impact on bank profitability. JEL Classifications: C23, G21, M20

The banks’ response to their changes in leverage ratios is examined and evaluated in this paper. This reaction can be interpreted as if the coefficient of total debts to equity (lev1) and total assets to equity (lev2) are positive as anticipated in the banking network of Iran. The paper uses data from 31 Iranian banks’ annual databases during the course of 2006-13 in order to estimate an empirical panel data model of banks’ balance sheet adjustment. We identify the leverage ratio degree to show that both equity and liabilities tend to adjust to move leverage positively without considering the state of the Iranian economy. On the other hand, the index of leverage coefficient conditioned by the state of the economy is negative which replicates that banks tend to experience a negative impact of leverage on the return to equity as a result of cost push due to higher ratio of assets to equity in the bust and inappropriate return on investment. Furthermore, the non-performing loans ratio coefficient is negative and significant which proves that one percent increase in the nonperforming loans has led to a less than one percent decrease in the return on equity ratio as expected, but the total loans to total deposits ratio depicts a negative-significant coefficient which denotes the higher non-performing loans have caused that loans ratio increase will not necessarily give rise to higher returns for the banks. Besides, the leverage ratio (lev2) is positive as expected and banks gain higher returns through higher leverage. However, the leverage measure’s coefficient conditioned by the state of the economy (dummy) is negatively significant owing to cost push from lower return on investment and higher ratio of assets to equity in the bust. JEL Classifications: C23, E32, E44, E51, G21, M20

Development of e-banking has empirically modified the structure and characters of banks’ performance, efficiency, risk and challenges which have also been articulately recognized based on the international best practices. E-banking brazenly accelerates and restructures financial transactions via enhancing technology and expanding the banking services in comparison with conventional banking. Accordingly, online access to the banks’ products, financial statements, payment services and even credit scoring has considerably improved banks-customers relationships in the context of lending and borrowing practice, deposit composition, investment opportunities, trade finance options as well as account management diversification. The impact of recent e-banking developments is statistically evaluated for Iran’s banking network via Dynamic Panel Data approach. The findings highlight that the ratio of ATMs and Electronic Cards transactions to banks' assets negatively-significantly influence the profitability due to higher substitution ratio with the other payment instruments and maintenance cost. The ratio of online branch transactions to the banks' assets negatively-insignificantly affects the profitability owing to the rapid increase in the NPLs and loan/loss expenses which has consequently shrunk Shared Revenues over the past 10 years. SWIFT-branches have positively-significantly enhanced the banks internal-secured cash flow while contemporaneously improves fund efficiency, banks’ services fees, and ultimately profit margin.

Innovations in electronic banking in Iran have led to the development in capacities such as payment instruments and transactions by cards, which are known as electronic payment equipment in the Iranian banking network. Financial supervision is required to be increasingly based on reporting and regulatory processes to efficiently and proactively monitor risk and compliance at banks and financial institutions. Besides, the banking system needs relevant information and instruments on strategy, assessments, and policy decisions in line with the required procedure to enhance transparency. Designing a new criterion in banking innovations by combining the Electronic banking instruments, considering the Electronic banking capacity proper and scaled to the banks’ assets, equity and resources as well as distinguishing the impact of banks’ profitability and capital are attributed as the key contributions in this paper rather than other similar researches. Results indicate that Electronic Banking capacities including the pin-pad, ATM, online branches, card services, and P.O.S volumes have positively and significantly influenced transparency since scales of these innovative capacities have expanded relative to the banks' assets and capital due to their contributions in the velocity and disclosure of data collection and analysis potentials. Results also denote that the state-owned banks in Iran are less transparent than private banks and the size of the bank hurts transparency. The return on equity in the form of bank ownership is multiplied as well as results also indicate that the productivity of equity returns has a positive effect on transparency. The ratio of non-interest income to total income also has a positive impact on transparency. There would be needed to provide transparent information on fee-based services to develop non-interest income. Hence, to improve transparency, the development of fee-based and non-profit-based services are required.

Utilizing finance conceptual framework, this paper applies a Frontier-Volatility analysis to illuminate regulatory policies effects on volatility under Iranian Banking Prudential Framework over the period 2003 to 2015 using the raw database collected, classified and compiled by the Rahavard Novin Co. version 3, Securities and Stock Exchange Organization. Findings portray that volatility is affected by the regulatory policies. Tighter regulatory controls will lead to higher volatility that makes it tough for the central bank to regulate the system for culminating financial stability as well as difficulty of entry for the investors. Regulatory policies’ positive variations will also lead to lower share revenues as well as a decrease in the earning per share (EPS) that will make it volatile and also will heighten the liquidity risk causing volatility as well as lower investment and shared revenues fluctuate the performance. Furthermore, economic growth has been ineffective on volatility in the current period although its effect has been positive and significant in the first lag period. Higher assets circulations cause higher and significant volatility. The debt proportion coefficient is positive and significant as expected that financial institutions gain more through higher leverage leading to higher volatilities in earnings. JEL Classification: C51, C58, G58, F82, G21

Development of E-banking has modified the structure of banking business and banking performance, efficiency, risk and challenges which have also been articulately recognized based on the international best practices. E-banking brazenly expedites and streamlines financial transactions via enhancing technology and expanding the bank services in comparison with conventional banking. Accordingly, online access to the banks’ products, financial statements, payment services and even credit scoring has considerably improved bank-customer relationships in the context of lending and borrowing practice, deposit composition, investment opportunities, trade finance options as well as account management diversification. The impact of recent E-banking developments on banking is statistically tested for the banking network of Iran using Dynamic Panel Data approach. Results indicate that the ratio of ATMs and Electronic Cards to bank assets positively and significantly influence profitability ratios. Meanwhile, the ratio of online branches and Pin Pads to the banks' assets negatively and significantly affects profitability although the transaction volumes have surged for the banks under study. JEL Classification: G21, G23, G32, F34 Keywords: E-Banking, Risks, Banks' Soundness Indicators

This study examines the effect of regulatory policy on efficiency under prudential framework among banks listed in the Iranian Securities and Exchange Organization over the period 2003 to 2015. Arellano-Bond estimation method has been patronized to investigate the effect of regulatory policies on efficiency. Results indicate that regulatory policy indicator indexing reserve requirement on investment deposits has had a positive relationship with the efficiency ratio, Sum of Assets Circulation Ratio (SACR), although it is not meaningful. On the other hand, the legal reserve ratio is positively and meaningfully affecting efficiency in financial institutions. Leverage ratio is negatively and meaningfully affecting the efficiency ratio (SACR) which highlights the point that as the financial institutions heighten their leverage ratio, it will lead to lower sum of asset circulation ratio as the best indicator of efficiency under activity proportions. Higher risk will lead to higher Financial Cost to Net Profit ratio (FCNP) interpreted as lower efficiency in financial institutes. Furthermore, regulatory policy denoted by the legal reserves ratio with one lag interval negatively-significantly influences the financial cost ratio. JEL Classification: C81, E43, E65, G21, G23

Quality Growth Index (QGI) is affected by two sets of combined-structural and social indicators. Structural indicator contributes to achieve the main target of sound-sustainable-competitive output growth. By the way, the sound output growth should enhance social-public services and living standards. Although QGIs are weightedly computed based on different scenarios, the trend of the QGIs and coefficient of variation of the QGIs indicate the robustness of results. The correlation among QGI and social sub-components highlights a positive relationship between QGI and school enrolment, per capita income and public spending on education and health. The result of co-integration model indicates that higher government size and devaluation of local currency have evidently exacerbated QGI. Meanwhile, openness and inflation underscore the positive long-run impact over QGI. Vector error correction equation outlines that about 84 percent of a short-term shock to the co-integrating vector will be absorbed in the first period. In this context, the impulse response of the QGI to the exchange rate and government size shocks are diminishingly and negatively permanent while the response of the QGI to the openness shock is significantly and positively permanent. JEL Classification: O40, O55, I10, I20, I32

Financial statements of nineteen mature banks have been patronized to examine the impact of macroeconomic indicators and bank-specific determinants on the NPLs ratio through Quantile and Panel Data regression approaches. The impact of macroeconomic indicators on credit risk is statistically estimated for banking network via two directions. First, different quantiles are econometrically calculated, assessed and compared during 2007-12. Second, the Panel Data estimation is utilized in the same way to verify the outcomes of quanitle regression and to check the robustness. Results indicate that the impact of real money supply on the banks’ NPLs in 25%, 50%, and 75% of data is positive and significant in line with empirical evidence. The coefficients of the other variables (including the ratio of individual banks’ performing loans to total deposits, individual banks’ performing loans to total loans ratio, as well as GDP would be positively significant as well. The real interest rate has negatively-significantly driven NPLs. The banks’ NPLs are generally exacerbated by the impact of higher real money supply over the long run, real interest rate in the money market and upper return in the assets market mainly because of the negative-inflationary transmission effect. JEL Classifications: C16, C23, E51, G21

The real macroeconomic instability and frequent changes in the monetary and banking regulations with financial contagion to the banks’ financial statements in the banking network of Iran cause intensified instabilities in its financial behaviors. In this paper, using statistical analysis and three-dimensional charts, we have analyzed the behavior of the financial statements of consolidated balance sheets covering the banking network of Iran. The paper also uses a non-linear estimation to calculate the threshold value regarding financial statements such as the nonperforming loan ratio. Results indicate that the banking network financial statements must be restructured due to exogenous shocks. Also, in the recession periods of the year 2011 fourth period and 2012 first period, the recession has reached the banking network with lag and banks have been able to change the return on assets ratio regimes neither in the year 2011 nor in the beginning months of the year 2012. Furthermore, the banks have started a contracting policy in providing loans. As time passes, yields and the performing loans depict the fact that yields on assets as profit indicators are increased unless the interest earning and different periods of time changes are also augmented. Going beyond the critical threshold, generating loans will be likely to drive non-performing loans since these loans are not going to be reimbursed. Banks will have to extend their loans to new loan contracts to consider them as performing which will lead to identification of fake profits in their statements. Key words: Financial Statement restructuring, Nonlinear Estimation, Threshold value JEL Classification: E21, G21, L2

The evidence of the recent years in the banking network of Iran indicates the increasing trend of nonperforming loans each year; thus, the main objective of the current study is to examine the impact of bank specific factors, esp. capital adequacy ratio on the NPLs. Six years dynamic panel data (2007-2012) of 19 banks are applied to scrutinize the relationship between capital adequacy ratio as well as other determinants and the NPLs. Applying correlation and regression analysis shows that the research model which has been utilized is of decent statistical qualification. Results emphasize that banks should control and amend their credit advancement policy with respect to factors influencing the NPLs to have lower non-performing loan ratio and should take into account their risk weighted assets and riskiness of their loan portfolio before they commence lending. In advance of lending to high risky projects and to low quality borrowers, banks should pay attention to the interests of both stakeholders and banks as well as they should consider the riskiness level of their loan portfolio to provide the accurate information relating to their performance because of the probability of high risk project failure which might evidently lead to the growth in NPLs. JEL Classification: C21, G23, G32