spatial econometrics

The objective of this study was to predict the impact of income tax accounting standards on the financial performance of listed companies in selected countries including Iran, Turkey, Iraq, and Gulf Council member states using a combined approach of artificial intelligence and spatial econometrics over the period 1990 to 2023. In this study, various artificial intelligence methods such as artificial neural networks, support vector machines, deep learning, decision trees, random forests, and genetic algorithms were used in combination with spatial modeling. The results show that income tax accounting standards have a significant impact on the financial performance of companies, and the combination of artificial intelligence methods with spatial modeling significantly increases the prediction accuracy. Among the different methods, deep learning combined with spatial modeling showed the best performance. These results highlight the importance of considering spatial dependencies in financial and accounting analyses in the study region, and can be valuable for policy makers, corporate managers, and investors.

This study examines the relationship between earnings management and financial performance of banks listed on the stock exchanges in Iran and Iraq, focusing on the role of internal controls. This study utilizes the statistical population of 44 banks from Iraq and 22 banks from Iran during 2010-2023 using the combined methods of deep learning, machine learning and spatial metrics. Deep neural networks identified different patterns in the two countries and deep learning algorithms determined the relative importance of the variables. Earnings management showed a significant positive relationship with financial performance (spatial coefficient: 0.5953, Z-statistic: 61.87). Income per employee (coefficient: 0.3218, Z-statistic: 33.57) and sustainable investment return (coefficient: 0.2871, Z-statistic: 29.91) also had a positive impact on financial performance. Operating expense margin, ratio of non-performing loans to total loans, and general and administrative expenses negatively affected financial performance. Internal controls played a mediating role, strengthening the relationship between Earnings management and performance (coefficient: 0.4127, Z-statistic: 43.08). Earnings Management has a significant role in the financial performance of banks and internal controls strengthen this relationship. It is suggested that the monetary authorities of both countries establish stricter rules for financial reporting, set minimum standards for manpower productivity, and require banks to implement advanced control systems. These findings suggest that bank regulators in both countries should adopt stricter accounting rules, set minimum standards for employee productivity, and mandate the implementation of advanced control systems. For bank managers, the results highlight the importance of focusing on earnings management strategies, improving staff productivity and enhancing internal control mechanisms in order to improve financial performance.

Generally, knowledge spillovers result in the creation of new knowledge, increased competitive advantages, and economic cooperation. Since the investigation of spillover flows among countries is considered to be highly important, in this study, knowledge spillovers and its resulting externalities were considered among a number of selected European countries during 1995 to 2011 using spatial econometric analysis. The results indicated an indirect effect and positive feedback caused by changing human development index, research and development expenditure, and knowledge-bearing imports, which confirmed the existence of spillovers and adsorption capacity in this region.