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Moonshot Projects

Dynamic Medicare

Medicare accounts for 15 percent of the federal budget. While currently almost equal in size to all nondefense discretionary spending, Medicare spending is projected to grow substantially over time as additional baby boomers retire. The Medicare program currently faces large present value shortfalls, unless additional general revenue transfers are made over time, payroll taxes are increased, or benefits are reduced. Unlike Social Security, which accounts for almost a quarter of the federal budget, the modeling of Medicare is still in its infancy, especially as Medicare finances relate to the economy. Medicare presents multiple unique modeling challenges. This project aims to fill this important void and allow PWBM consider even large fundamental reforms to Medicare, including movements from its predominantly fee-for-service model.

Aggregate OLG

Government projections typically incorporate a risk of a recession as a simple “haircut” to expected GDP growth over the next decade. However, this approach creates considerable false precision and estimation error. Actual GDP is not smooth and deficit spending is very nonlinear relative to GDP due to countercyclical policies at the macroeconomic level (e.g., tax cuts and new spending programs) and the microeconomic level (e.g., unemployment insurance and welfare programs). For example, the debt held by the public doubled in size between 2008 and 2012 due to the Great Recession. While our current OLG model allows for idiosyncratic shocks at the household level (microeconomics uncertainty), GDP and factor prices are deterministic (deterministic macroeconomics). Allowing for macroeconomics uncertainty involves solving a very high dimensional problem, the type of problems that are typically futuristic in nature and currently the subject of quantum computing. Using various approximation methods with controllable error bounds, we are currently developing a next generation overlapping-generations model with macroeconomics uncertainty in addition to microeconomics uncertainty. It will allow PWBM to develop more accurate ranges for projections and to provide much deeper analysis of programs like unemployment insurance that have both a macroeconomics and a microeconomics component.