Optimal Decision and Enforcement Procedures for Social Policy: The Tax - Benefit System

The design of social welfare programs is vitally important and rife with challenges. As governments tighten their budgets, welfare policies are frequently called into question. How can costs and disincentives be limited without disadvantaging those genuinely in need? In a perfect world, governments would always be able to identify which individuals are in need of some form of benefits. In reality, the state makes mistakes: some needy individuals may be incorrectly denied benefits, while some non-needy individuals may be incorrectly awarded benefits. Such mistakes introduce inequities into society since those who ought to be treated identically by the welfare system are not. The question is then how these errors, and the extent to which they are made, affect the optimal design of welfare programs.
With his PhD research, Sean Slack is working to provide some insights into these questions. Sean’s work is based on theoretical modelling of an economy where there is a well-defined needy group in society, whereas the government can only imperfectly identify this group. His results show that the accuracy of the government’s test in awarding benefits and, further, how well the conditions placed on applicants are enforced, are influential in determining the optimal design of welfare programs. Research like Sean’s could be used to inform the welfare reforms currently taking place in many countries, to ensure that inappropriate benefit claims are not honored, nor are people in need unjustly refused.