Long-Term Profitability Prediction under Taxation Changes: Efficiency Analysis of Companies Using DEA Model

Abstract

This research focuses on predicting the long-term profitability of companies in the context of tax regulation changes using the Data Envelopment Analysis (DEA) model. The study adopts an applied approach and employs a descriptive-analytical methodology. To collect the necessary data, financial information from companies listed on the Tehran Stock Exchange was analyzed over a five-year period, spanning from 2016 to 2021. The research aims to assess how changes in tax regulations influence both the profitability and efficiency of companies. By utilizing the DEA model, this study provides a quantitative evaluation of the impact of tax adjustments on corporate financial performance. The findings reveal that tax changes have a significant effect on long-term profitability, with the potential to either improve or diminish a company's financial efficiency and overall profitability. Furthermore, the DEA model has demonstrated its ability to accurately forecast corporate profitability under various tax scenarios. This predictive power makes the model a valuable tool for financial analysts, policymakers, and corporate managers. By leveraging DEA-based insights, decision-makers can better navigate tax policy adjustments, optimize financial strategies, and enhance overall corporate performance.