Tax Evasion and the Dynamics of Income Disclosure Schemes
This thesis explores the persistent issue of black money in India through the lens of the Income Disclosure Scheme (IDS), with a focus on behavioural responses and strategic enforcement. Traditional IDS frameworks, which rely on fixed penalty structures, often fail to induce voluntary compliance from tax evaders. This work reformulates the IDS penalty parameter as an endogenous function of audit probability and penalty rate both of which are modelled to depend on the degree of evasion, enforcement resources, and macroeconomic constraints. By incorporating elements of game theory and behavioural economics, the paper captures the nuanced decision making processes of taxpayers who weigh the benefits of evasion against the risks of detection and disclosure.
The analysis identifies key equilibrium strategies under different policy configurations and demonstrates how a dynamic, responsive penalty system one that escalates with greater under reporting can lead to more effective disclosure outcomes. It also emphasizes the importance of risk-based auditing and behaviourally informed policy design to counter procrastination and over optimism among tax evaders. The findings offer actionable insights for future IDS implementations, advocating for calibrated deterrence, efficient resource allocation, and credible enforcement as pillars of successful tax reform. Ultimately, the thesis contributes a robust theoretical foundation for designing IDS schemes that are both economically sound and behaviourally realistic.