Monetary & Financial Economics

Abstract This paper investigates the dynamic relationship between financial development and sectoral composition in emerging economies. Utilizing a panel ARDL model on a dataset of 45 emerging markets over the period 1995–2023, the study uncovers a robust empirical pattern: financial development is significantly associated with structural transformation, characterized by a declining share of agriculture and a corresponding increase in the share of industry—particularly services. The results also indicate the presence of bidirectional causality between financial development and the industrial and service sectors, suggesting a mutually reinforcing dynamic in the structural transformation process. However, the paper critically evaluates this general finding within the specific institutional context of Iran. It argues that under a state-dominated, bank-based financial system marked by financial repression and directed credit policies, the classical link between finance and structural change becomes distorted. The findings reveal that in such a setting, financial expansion does not necessarily lead to efficient resource allocation or support productive transformation and may even exacerbate structural rigidities. The paper concludes that for countries like Iran, quantitative financial expansion is insufficient. Rather, qualitative financial development—anchored in deep institutional and policy reforms—is a prerequisite for fostering a healthy and sustainable structural transition.

Abstract Today, the significant impacts of blockchain technology on several industries, including the financial sector, cannot be ignored. However, its potential to increase security, speed, and transparency in the financial reports of Iraqi banks has not yet been examined. Therefore, the aim of the present study is to investigate the impact of blockchain technology on the security, speed, and transparency of financial reports in banks listed on the Iraqi Stock Exchange with data from the last six months of 2023 and the first three months of 2024. Descriptive statistical methods and inferential statistics (multivariate regression and structural equation model) were used for analysis. 384 people from among accountants, independent auditors, managers, and others in banks listed on the Iraqi Stock Exchange was considered as a sample. The results of the hypothesis test showed that at the 99% confidence level, the level of familiarity with blockchain technology was a factor in increasing the security and quality of information in banks' financial reports. Thus, the level of use of blockchain technology had a positive and significant impact on the security, speed, and transparency of financial reports of Iraqi listed banks. Since the present study was examined in an emerging market such as Iraq, it can provide useful information in this field for readers in Iraq and other similar countries.

Abstract The necessity of need to reduce dependence on foreign currency income from oil and move towards providing a significant part of the required currency through non-oil exports is felt more. In this regard, paying attention to the mining sector due to its rich and underground reservoirs is a suitable solution to solve this problem. However, the further development of the mining sector in order to achieve economic goals is affected by economic sanctions. Undoubtedly, examining the manner and mechanism of impact of shocks caused by economic sanctions on the country's mining sector can help the officials and economic planners of the country to better face and reduce their negative economic consequences, including reduction in production and added value, reduction in employment, reduction in investment, etc., in the mining sector. Therefore, in this study, for the first time, the effects of shocks caused by economic sanctions (1. the shock of the increase in the exchange rate, 2. the shock of the decrease in the import of raw materials, capital and intermediate goods, 3. the shock of the decrease in crude oil export income and 4. The shock of non-oil export reduction) on foreign trade of Iran's mining sector. For this purpose, the required data was collected from the social accounting matrix and the Recursive Dynamic Computable Equilibrium (RDCGE) model was used to analyze the data. The results showed that among the shocks caused by economic sanctions, in order: the shock caused by the increase in the exchange rate, the shock caused by the decrease in the import of raw materials, capital and intermediate goods, the shock caused by the decrease in crude oil export income and the shock caused by the reduction of non-oil exports have the greatest impact on trade balance of Iran's mining sector.

Abstract The aim of the current research is to modeling of financial distress prediction using XGBoost ensemble learning algorithm in listed companies on Tehran Stock Exchange. The statistical population of the present research is the listed companies to the Tehran Stock Exchange during the period 2012 to 2023 and the screening sampling method, in this regard, 1800 firm-year (150 firms for 12 years), observations collected from the annual financial reports of the case have been tested. In this research, independent variables according to the theoretical foundations and empirical background of internal and external research include 52 variables in two categories of accounting variables (profitability indicators, obligations fulfillment indicators, activity indicators, cash flow indicators and growth sustainability indicators) and Non-accounting variables (cash flow composition indices, corporate governance indices, macroeconomic indices, management ability index, audit index and competitiveness index) were determined. In order to identify the important variables for developing the model, the average comparison test of two sample was used, and according to the results, 40 variables out of 52 variables were selected as the final variables for developing the model. The results show that the overall accuracy of XGBoost ensemble learning algorithm and logit regression is 97.8% and 92.1%, respectively, which indicates that compared to logit regression, XGBoost algorithm performs better in predicting companies with Has financial distress. In other words, the results show the efficiency of XGBoost algorithm compared to logit regression. Therefore, the XGBoost algorithm provides the most efficient model for predicting financial distress in listed companies on the Tehran Stock Exchange.

Abstract This paper examines the effects of exchange rate policies and liquidity creation on key macroeconomic variables in Iran. Using quarterly data from 1991 to 2023, we employ a Dynamic Stochastic General Equilibrium (DSGE) model to analyze the transmission mechanisms of these shocks. The Iranian economy has long grappled with the interdependence of exchange rate and monetary policies, presenting significant challenges for policymakers. A substantial portion of government budget expenditures is financed through oil export revenues and withdrawals from the Foreign Exchange Reserve Account. This dynamic compels the Central Bank to purchase foreign currency, consequently expanding the monetary base. Given this linkage, monetary authorities must carefully assess the impact of oil revenue fluctuations when formulating policies to ensure economic stability. Our study specifically investigates: The exchange rate policy channel (transmitted through exchange rate adjustments). The monetary policy channel (transmitted through liquidity creation). Key findings reveal that: Exchange rate shocks have a more pronounced inflationary effect compared to liquidity creation shocks. These shocks also lead to reductions in both consumption and income, underscoring their contractionary impact on the economy. These results highlight the critical role of exchange rate management in Iran’s macroeconomic stability and suggest that policymakers should prioritize mitigating exchange rate volatility to curb inflation and support economic growth.

Abstract The Bitcoin market, characterized by its high volatility, consistently attracts the attention of investors and researchers. However, two primary challenges persist within this market: assessing its efficiency and identifying periods of price bubbles. These bubbles can lead to erroneous financial decisions. Despite extensive research, ambiguities surrounding non-random behavior and the formation of price bubbles in Bitcoin remain. This study investigates the efficiency of the Bitcoin market and identifies potential bubbles using the DS LPPLS (Discrete Singularity Log-Periodic Power Law Singularity) model, alongside confidence and sentiment indices. Daily closing prices of Bitcoin from the beginning of 2025 to the end of 2024 were utilized for this analysis. Through the examination of price charts and relevant indicators, it was determined that the Bitcoin market generally does not exhibit weak-form efficiency, and its behavior does not fully align with a purely random walk model. The confidence and sentiment indices, which reflect investor emotions towards the market, experienced significant fluctuations and showed a high correlation with price changes. Sudden and simultaneous increases in positive sentiment indicators and price suggest the formation of price bubbles during certain periods. The findings of this research indicate that the DS LPPLS model, in conjunction with confidence and sentiment indices, serves as a robust tool for analyzing Bitcoin market behavior and detecting price bubbles. Nevertheless, for more precise results, further in-depth investigation into factors influencing the market and the application of more complex models are warranted.

Abstract Aim and Introduction:
The precautionary demand for money is usually influenced by uncertain factors and changes in cash flows, and is dependent on assets with high liquidity. This study aims to identify the role of qarz al-hasanah (interest-free loans) in the precautionary demand for money using the Canian and Tarka model.
Methodology:
The specified equations were estimated using quarterly time series data from the years 1377 to 1402 using the ARDL method, and the coefficient obtained from the ECM estimation is used to identify long-term relationships.
Findings:
The results show that the expansion of the capital market has a greater impact on the allocation of money demand than on liquidity preferences, and gold strengthens the precautionary demand for money during periods of economic instability, especially when monetary policies face challenges in dealing with crises. Furthermore, inflation significantly affects adaptive behaviors and changes in money demand, and qarz al-hasanah plays a key role in enhancing liquidity and managing short-term financial gaps. Additionally, a long-term relationship exists between the qarz al-hasanah variable, as an independent variable, and the precautionary demand for money.
Discussion and Conclusion:
The precautionary demand for money is influenced by several factors, including capital markets, loans, inflation, and asset preferences. The expansion of the capital market has a greater impact on the allocation of money demand than on liquidity preferences. Gold, as an asset, strengthens the precautionary demand for money during periods of economic instability and challenges the effectiveness of monetary policy. Inflation affects adaptive behaviors, and currency also creates an immediate precautionary response in money demand. Qarz al-hasanah is confirmed in smoothing liquidity cycles and managing both short-term and long-term money demand, and i t effectively contributes to increasing liquidity and filling short-term financial gaps.

Abstract The main objective of this research is to validate and fit the comprehensive risk management development model. This research is applied in terms of purpose and descriptive-analytical in terms of data collection method based on the structural modeling approach. To understand the relationship between the structures of the extracted model from the context-based approach, a phenomenographic strategy was used. The data collection tool was a researcher-made questionnaire, and for this purpose, data were collected from 87 experts in the field of investment who were selected using the convenience sampling method. The research data were analyzed using Smart-PLS software. The results of the research indicate that the majority of the paths are confirmed, such that the path of causal conditions through the phases of risk management planning, risk identification, implementation of qualitative risk analysis, implementation of quantitative risk analysis, risk response planning, and risk control has a significant relationship with the category of comprehensive risk management. Also, the path of the underlying conditions has a significant relationship with the comprehensive risk management strategies, and finally, the path of the strategies has a significant relationship with the consequences of implementing the comprehensive risk management model.

Abstract Empirical identification of the role of the life cycle in the fluctuation of stock returns according to economic conditions will improve the performance of investors and will improve the accuracy of company managers' forecasts. Based on this, in this research, the relationship between the stages of the company's life cycle and the fluctuation of stock returns according to the variables of macroeconomic conditions was investigated in the form of two hypotheses. The research is applied in terms of purpose and using the post-event approach, and based on the method, it is of the descriptive-correlation type. The statistical population of companies admitted to the Tehran Stock Exchange and the sample number was 157 companies during the years 1397 to 1401. To test the hypotheses, multivariate regressions were used in the Eviews13 software environment. The results of the research show that the volatility of stock returns in the maturity stage is less than the recession stage and in the growth stage it is more than the recession stage. If the exchange rate is taken into account, the volatility of stock returns in the stages of emergence, maturity, growth and decline is lower than in the recession stage. If the inflation rate is taken into account, the volatility of stock returns in the stages of emergence, maturity and growth is higher than in the stage of recession, and in the stage of decline it is not different from the stage of stagnation. If the bank interest rate is considered, the volatility of stock returns in the stages of emergence, maturity and growth is higher than in the stage of recession, and in the stage of decline, it is not different from the stage of recession. And finally, if the GDP is considered, the fluctuation of stock returns in the stages of emergence, maturity, growth and decline is not significantly different from the recession stage.

Abstract The aim of the present study is to investigate the effect of investment in fixed assets on the speed of cash holding adjustment. The present study is applied and from the methodological perspective, the correlation is of a causal (post-event) type. The statistical population of the study is all companies listed on the Tehran Stock Exchange, and using the criterion-based screening sampling method, 144 companies were selected as the research sample and were studied over a 10-year period between 2014 and 2023. The results of the research hypothesis test showed that the speed of cash holding adjustment among the sample companies is about 77 percent. Companies cover the gap between actual and optimal cash holdings on average at the same speed annually. Also, investment in fixed assets affects the speed of cash holding adjustment and reduces the speed of adjustment. In fact, given the ability to collateralize fixed assets, companies with higher fixed asset investments move towards optimal cash holdings at a slower rate and do not need to hold as much cash. Based on the results, it can be stated that companies that allocate a higher share of their investment to fixed assets have a lower need to hold large amounts of cash to manage liquidity risk or potential investment opportunities due to the ability to use these assets as collateral for financing. As a result, these companies move towards optimal cash holdings at a slower rate, because fixed assets play an alternative or complementary role in managing financial risk and securing resources and reduce the immediate pressure to quickly adjust cash reserves.

Abstract Abstract
Introduction: Selecting an appropriate computerized accounting information system (CAIS) is a pivotal strategic decision that directly influences financial transparency, decision quality, and operational efficiency in today’s digital business environment. Despite a growing array of CAIS solutions, Iranian firms lack a systematic, evidence based framework to guide their choice under rapidly evolving technology and regulatory landscapes.
Theoretical Framework: Drawing on DeLone & McLean’s Information Systems Success Model and Davis’s Technology Acceptance Model (TAM), this study conceptualizes CAIS selection as a multi criteria decision problem, encompassing two broad dimensions—software capabilities and vendor attributes. Prior research highlights the critical roles of technological infrastructure, service quality, and user support in driving successful system adoption.
Methodology: A purposive snowball sample of ten CAIS experts (each with ≥10 years’ relevant experience) was assembled. We constructed a three level AHP hierarchy containing nine criteria and 35 subcriteria identified from the literature. Pairwise comparisons were conducted via Expert Choice 11, ensuring all consistency ratios (CR) remained below 0.10.
Results & Discussion:
• Top ranked criteria: Technology infrastructure (weight = 0.293), Maintenance & Upgrades (0.198), and Training & Documentation (0.175).
• Quantitative ranking model: Based on the final AHP weights, we developed a scoring model that systematically combines the nine criteria into a single CAIS suitability index, enabling organizations to numerically compare alternatives.
• Key technology subcriteria: Web based architecture & e commerce support (0.323), Flexibility for future needs (0.171), and Data interoperability (0.169). These findings underscore the necessity of cloud readiness, API integration, and seamless data exchange to enable advanced analytics and real time reporting.
• Service oriented dimensions: Technical support responsiveness (0.406) and comprehensive user documentation (0.462) highlight the indispensable roles of vendor support and end user empowerment in achieving rapid, risk mitigated CAIS deployment.
Conclusions & Suggestions:
Organizations should prioritize CAIS solutions with robust web centric and cloud capabilities, backed by formalized upgrade and support agreements. Continuous, blended training programs (self learning modules, user guides, and instructor led workshops) are essential to maximize user adoption and minimize operational errors. Future research is encouraged to:
1. Undertake large scale, non Delphi survey studies across diverse industries to validate and generalize AHP derived weightings;
2. Employ Fuzzy AHP or integrate AHP with DEA to capture environmental uncertainty and criterion interdependencies;

Abstract Given the numerous challenges facing the Iranian economy, globalization and financial development are considered as two key factors in the country's economic growth process. This study examines the effects of globalization and financial development on Iran's economic growth. The main objective of this research is to create an analytical framework and model to calculate total factor productivity (TFP) and examine the effects of these two variables on Iran's gross domestic product (GDP). The data used were collected from 2000 to 2023 and include key variables such as physical capital, financial development, globalization index, government spending, and inflation rate. Advanced econometric methods such as the ARDL model and static and cointegration tests were used to analyze the data, which allows for a detailed examination of the long-term and short-term relationships between the variables. The results of the research show that globalization and financial development have a positive and significant effect on Iran's economic growth and can act as the main drivers in this process. In contrast, government spending and inflation rate have negative effects on economic growth, and these results indicate the need for optimal management of government spending and control of inflation rate to maintain economic stability. These findings can help policymakers and economic decision-makers in designing effective and efficient strategies and lead to improvement of the country's economic situation.

Abstract The purpose of this study is to investigate the effect of comparability of financial information and earnings management and smoothing on the level of shareholder loyalty. The present study is applied and methodologically it is a causal (post-event) correlation.The statistical population of the study was all companies listed in the Tehran Stock Exchange and using the systematic elimination sampling method, 163 companies were selected as the research sample and were studied in a 10-year period between 2014 and 2023. Three levels of loyalty for investors‌(total, majority, and minority) were considered to measure the dependent variable. Three hypotheses were proposed for the present study, and the results showed that at the level of total shareholder loyalty, earnings management does not affect the loyalty‌ of the company's shareholders. Gaining shareholder loyalty has the opposite effect. Earnings smoothing does not affect the loyalty of the company's shareholders‌. Disclosure of high-comparability information has a direct effect on gaining the loyalty of the company's shareholders. Earnings management has an inverse effect on gaining the loyalty of the company'‌s shareholders.

Abstract The aim of this article was to investigate the effect of economic policy uncertainty on the performance of the insurance industry in Iran. For this purpose, data from the period 1370-1402 were used based on the frequency of annual data and the autocorrelation method with nonlinear distribution lags. The results of this study indicated a significant and asymmetric effect of economic policy uncertainty on the performance of the insurance industry in the two sectors of life and non-life insurance. Based on data analysis, positive and negative uncertainty shocks have different effects on premiums received. In the life insurance sector, the impact coefficients of positive shocks are reported to be 0.22 and negative shocks are -0.15, and in the non-life insurance sector, they are 0.28 and -0.19. These results indicate that increased uncertainty in economic policies leads to growth in demand and, consequently, an increase in premiums received, while a decrease in uncertainty is associated with a decrease in insurance demand. This asymmetric relationship means that the intensity of the impact of positive shocks (increased uncertainty) on premiums received is greater than that of negative shocks (decreased uncertainty). This asymmetry is more pronounced in the non-life insurance sector than in the life insurance sector due to the coverage of more diverse and shorter-term risks and higher sensitivity to economic fluctuations.