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Credit Rating of Real Bank Customers Based on Logistic Regression and MPLE Logistic Methods and Neural Network
Seyed Ahmad Ameli, , ,
Volume 16, Issue 59 (5-2025)
Abstract
By designing an efficient loan management system, banks can increase efficiency and reduce the probability of non-repayment of principal and sub-loans. In this paper, the efficiency of logistic regression models, artificial neural network, was examined to predict the credit risk of real customers or in other words, applicants for microloans, which include a large group of customers in the country's banking system. Given the imbalance of the number of data, the optimal threshold was calculated using two sensitivity and detection curves, and the credit risk of each model was extracted from this method. In logistic regression, the compensated maximum likelihood method was used to estimate the coefficients considering the small number of bad customers instead of the maximum likelihood method. Finally, the accuracy and precision of each model was examined with multiple criteria. Using the Rock curve, the resolution of the models was examined, where the neural network model had the best resolution. Then, by comparing the MSE, RMSE and MAE errors, the efficiency of the methods was compared, and the performance of MPLE logistics and neural network is almost the same. Finally, considering the bank's goal in three scenarios of minimum credit risk, identifying good customers and separating customers, neural network, MPLE logistics, and in the third scenario, neural network and MPLE logistics simultaneously have been selected as the best models.
 
Economic Policy Uncertainty and Inflation in Iran with Wavelet Machine Learning Approach and Wavelet Quantile Causality
Ali Moridian, Hassan Heidari, Seyed Mehdi Hosseini, Heshmatollah Asgari,
Volume 16, Issue 60 (9-2026)
Abstract
Objective: This study examines the effects of economic policy uncertainty, exchange rate, and oil price on inflation in Iran during the period 2008 to 2023. The main objective is to identify the short-term, medium-term, and long-term nature of these effects and analyze inflation dynamics using modern wavelet and machine learning methods.
Materials and Methods: Regularized least squares regression with wavelet kernel (WKRLS) and nonparametric wavelet quantile causality (WNQC) are used to analyze nonlinear and scale-dependent relationships between variables. The data include inflation index, economic policy uncertainty (EPU), unofficial exchange rate, and oil price on a monthly basis. The generalized wavelet quantile Dickey-Fuller test (Wavelet-QADF) is also used to examine the stationarity of time series.
Results: The results show that key variables of the Iranian economy are stationary in most quantiles and time scales. According to WKRLS estimates, the effect of economic policy uncertainty on inflation is weak in the short run, decreasing but still significant in the medium run, and increasing non-linearly and acceleratingly in the long run. The exchange rate has the greatest impact on inflation, especially in the short run due to the Iranian economy’s heavy dependence on imports. Oil prices also have a significant impact on inflation and its volatility in the long run. WNQC findings show that economic policy uncertainty and exchange rate uncertainty have a stronger effect in the low and middle quantiles of inflation, while oil prices mainly amplify inflation fluctuations in the long run.
Conclusion: The findings emphasize the importance of stable economic policies, reducing dependence on oil revenues, and controlling exchange rate fluctuations for managing inflation in Iran. Also, combining wavelet and machine learning methods allows for a more comprehensive analysis of inflation dynamics in different conditions.
 
Assessing the Impact of Internet Access Satisfaction on Subjective Well-being Using a Discrete Choice Approach
Dr Akram Akbari, Dr Parviz Mohamadzadeh, Mr Hussein Ali Sheeaa,
Volume 16, Issue 60 (9-2026)
Abstract
Extended Abstract
Introduction
Subjective well-being has become an increasingly important concept in welfare economics, happiness economics, and social policy analysis. Unlike objective welfare indicators such as income, employment, consumption, or access to public services, subjective well-being reflects how individuals evaluate and experience their own lives. In societies undergoing economic, institutional, and generational transitions, individuals’ assessment of their living conditions relative to their parents can provide a meaningful indicator of perceived progress or decline. Iraq represents an important context for such an analysis because the country has experienced economic uncertainty, institutional challenges, demographic pressures, and rapid digital transformation. In this setting, internet use may influence individuals’ perceived well-being by expanding access to information, learning opportunities, social networks, public services, and economic prospects. However, the relationship between internet use and subjective well-being is unlikely to be direct, linear, or uniform across all individuals.

Background and Innovation
The literature suggests that the welfare effects of internet use depend not only on access but also on the intensity, quality, and purpose of use. Internet use may improve well-being by reducing information costs, facilitating communication, supporting learning, and creating new opportunities. At the same time, it may generate adverse effects through social comparison, misinformation, excessive use, or passive consumption of digital content. Therefore, recent studies emphasize the importance of human capital and digital capability in shaping the welfare consequences of internet use. The main contribution of this study is threefold. First, it focuses on intergenerational relative subjective well-being, rather than conventional life satisfaction. Second, it distinguishes active internet use from mere access or satisfaction with access. Third, it examines whether education moderates the association between internet use and relative subjective well-being.

Aim and Method
The main objective of this study is to examine the relationship between active internet use and intergenerational relative subjective well-being in Iraq, with particular emphasis on the moderating role of education. The dependent variable is an ordinal measure of respondents’ evaluation of their current living conditions compared with their parents’ generation. It takes three ordered categories: worse than parents, the same as parents, and better than parents. The empirical analysis uses micro-level data from the eighth wave of the Arab Barometer survey for Iraq. Given the ordinal nature of the dependent variable and the survey design of the data, the baseline specification is estimated using a survey-weighted ordered logit model. The model controls for age, age squared, gender, household size, urban residence, employment status, household income adequacy, evaluation of current economic conditions, expectations about future economic conditions, trust in government, and governorate fixed effects. To assess the robustness of the results, alternative specifications including ordered probit, different measures of internet use, marginal effects, and post-estimation diagnostics are also employed.

Findings
The results indicate that the direct association between internet use and intergenerational relative subjective well-being is not uniform across the population. In the baseline models, internet use alone does not show a strong and stable direct relationship with higher relative subjective well-being after controlling for individual, economic, institutional, and regional characteristics. However, the interaction between active internet use and higher education provides evidence of heterogeneous effects. Among individuals with higher education, active internet use is associated with a higher probability of reporting a “better than parents” status and a lower probability of reporting a “worse than parents” status. This finding suggests that education may enhance individuals’ ability to transform digital access and internet use into meaningful opportunities.
The results also show that household income adequacy, household size, evaluation of current economic conditions, expectations about future economic conditions, trust in government, age, and age squared are important correlates of intergenerational relative subjective well-being. Governorate fixed effects are jointly significant, indicating that regional differences within Iraq play an important role in explaining variations in perceived intergenerational well-being. The robustness checks further suggest that the relationship between digital engagement and subjective well-being should not be interpreted as a simple universal effect. Rather, the welfare implications of internet use depend on individuals’ human capital and their capacity to use digital resources effectively.
Overall, the findings imply that digital policy should move beyond expanding physical internet access alone. Policies aimed at improving subjective well-being through digital transformation should also promote digital literacy, purposeful internet use, skill formation, and the integration of educational and digital development strategies. In particular, strengthening human capital may allow individuals to benefit more effectively from online information, learning resources, communication networks, and economic opportunities.
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