Journal of Money and Economy

The recent housing market experience has led many to concern that the developments in the housing sector are not just a passive reflection of macroeconomic activities but instead might be one of the driving forces of them. In this context, it is crucial to understand the nature of the economy by considering the housing market and build a suitable monetary policy. In this paper, using Bayesian methods, we develop and estimate a DSGE model for Iran from 1988q1 to 2017q4, which explicitly models the housing in the banks’ portfolio to study the macroeconomic effects of monetary authority’s reaction to the housing price inflation. Our findings indicate that this reaction amplifies all the implications of the structural shocks.

The stock market is influenced by other parallel markets and macroeconomic variables; such variables have impacts on the behavior of financial market players. Accordingly, this study first examines the existence of herding behavior among investors in the Tehran Stock Exchange (TSE). It then investigates the effects of exogenous economic variables on this industry-level behavior in the Tehran Stock Exchange (TSE) throughout 2008- 2018. For this purpose, 12 different industries were studied, and the results of nonlinear regression analysis showed the existence of herding behavior in all selected industries in the bearish market. However, this is not true for the bullish market. The findings also indicate that the effects of exogenous variables are not the same in different industries.

This study was designed to explain the Blockchain acceptance indices in Iran's financial markets aimed at identifying different angles for the implementation of Blockchains. The Blockchain acceptance indices were extracted in 4 levels, 12 variables, and 53 indices of related research literature in the field of e-commerce and mobile banking. To validate the research indicators, the Fuzzy Delphi technique was used to refine the indices in addition to the documentary study. The survey was conducted in three stages and the results of each stage were refined. Based on data analysis, 39 indicators were confirmed. The results of this study can provide useful insights for researchers and policymakers of Iran’s financial markets to understand the prerequisites and effects of the Blockchain implementation on financial markets, and thereby, they would be able to change business models to take advantage of Blockchain capabilities in the infrastructure of Iran’s financial markets by considering different aspects.

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.

With advanced information and communication technology, the organizations’ business model has undergone fundamental changes. These changes are also observed in the banking industry. This research aims at explaining the Iranian electronic banking business model and recognizing its challenges in the transformation to digital banking, which is considered as the research innovation. In terms of method, the present research is a qualitative study and in terms of goal, it is primary research. In this research, grounded theory has been used as a systematic method for the investigation of complex multilateral issues. The population includes the expert managers of the banking industry who have mastery over macro policies of banking and electronic payment in Iran. Regarding the research method, all the interviews were recorded and converted to text. The coding and classification process was done based on three stages of open coding, axial coding, and selective coding. The outputs of these three stages were provided in the form of codes, concepts, and categories. During and after data collection, the data were reviewed for several times, the key points were specified, and the related codes were counted. Finally, 761 codes, 26 concepts, and 14 categories related to the research topic were identified based on which, the conceptual business model of Iranian electronic banking was developed. Based on the conceptual model of the research, seven challenges for digital banking transformation were identified.

The soundness and efficiency of banks is one of the important subjects that neglecting it can have adverse consequences for every country's economy. For economies depending on the money market, such as the Iran economy, this subject is more critical. Therefore, in this study, using panel data related to 16 Iranian banks for the annual period of 2010-2017, the economic efficiency was determined using a translog cost function and stochastic frontier analysis method then, by estimating the model of panel vector autoregression model and Granger causality test, the causal relationships between efficiency and information asymmetry in terms of adverse selection ( the ratio of loans to assets and the ratio of loans to deposits) and moral hazard ( the ratio of non-performing loans), were investigated, both of which are caused due to the information asymmetry. The estimations confirm the unilateral causal relationship of adverse selection and moral hazard with banking system efficiency. And, on the contrary, they claim that low efficiency of the banking system increases the adverse selection and moral hazard is not confirmed. Besides, the results of other estimates based on the panel model with random effects indicate a negative and significant impact of moral hazard and adverse selection on efficiency.