One of the central questions in economics is how to design taxation and social insurance policy. This project pursues a broad program at the intersection of macroeconomics and public economics that will both contribute to the theoretical understanding of how policy should be conducted and provide practical recommendations that can be used by policymakers around the world.
A recently emerged approach, New Dynamic Public Finance (NDPF), provides new methodology and a framework to answer these questions. However, the NDPF approach has delivered mostly theoretical or suggestive numerical predictions rather than implementable policy recommendations. The primary goal of this project is to move NDPF from theory to policy. Results of the project would be directly relevant for the design of capital and labor taxes, Social Security, and disability insurance system.
The main focus of NDPF is the design of policy in dynamic settings, as many taxes such as tax on capital and many social insurance programs such as Social Security are dynamic or intertemporal. The NDPF approach brings two fundamental issues to the forefront of the design of optimal policy in dynamic settings: (1) society desires redistribution or social insurance as agents experience significant adverse shocks during their lifetime, e.g., becoming disabled, and (2) incentives are important because these shocks are private information, e.g., many forms of disability are notoriously difficult to ascertain. This approach has already delivered novel implications for important policy issues that include taxation of capital income and design of disability and social security systems. Specifically, this project achieves two objectives:
1. Derive implementable policy implications in realistic quantitative models. 2. Design policy that accounts for political economy considerations.
Broader Impacts: The first part of the agenda is to study optimal policy using quantitative models that can capture empirically relevant features of the economic environment. Once developed, these models can be used as workhorse models for policy design of taxation and social insurance. The main focus here is quantitative and delivers the determinants and optimal form of capital and labor taxes as well as the form of benefits of optimal social insurance programs such as Social Security. Finally, this project focuses theoretically and quantitatively on a largely unexplored part of the New Dynamic Public Finance - how to optimally design taxes and social insurance over the business cycle.
The second part of the research agenda is intimately linked to the first part, as the design of optimal policies would be irrelevant unless it takes into account the constraints that are faced by politicians implementing such policies. This project analyzes how policies should be designed to account for not only the social insurance versus incentives tradeoff but also the incentives of self-interested politicians. Second, this project studies how to design tax systems that are sustainable, i.e., able to mitigate political incentive problems. Finally, it investigates under which conditions markets can achieve superior allocations than those achieved by centralized governments.
