Mathematical Modeling of VAT Systems to Assess Their Impact on Business Operations and Consumer Spending

Abstract

This study employs mathematical modeling to analyze the impact of Value-Added Tax (VAT) systems on business operations and consumer spending from 2020 to 2024. The research objectives include assessing VAT policies' effects on business costs and profitability, evaluating how VAT rate changes influence consumer spending patterns, and providing evidence-based recommendations for optimizing VAT policies. Utilizing regression analysis (R² = 0.78, p < 0.01), correlation analysis (r = -0.65, p < 0.01), and chi-square tests (χ² = 23.42, p < 0.001), the study confirms that VAT compliance costs significantly impact business profitability, while higher VAT rates reduce consumer spending. Statistical analysis also highlights that small businesses bear a disproportionately higher VAT compliance burden, reinforcing the need for policy interventions. The study concludes that while VAT remains a stable revenue source, its economic impact varies-high rates deter spending, yet strong enforcement improves revenue collection (r = 0.72). Recommendations include implementing digital tax compliance solutions, introducing progressive VAT rates, strengthening enforcement, harmonizing VAT regulations, and leveraging predictive tax models to enhance policy efficiency.