Policy Wedges and State Space Simulation Models

 

Policy Wedges first gained attention as Climate Stabilization Wedges. However, the application is broader and has been applied to Monetary Policy Wedges and Health Care Policy Wedges. The idea can be applied to any macro-policy agenda using State Space models.

George W. Pasdirtz’s “Policy Wedges” Approach to U.S. Health Care

George W. Pasdirtz’s 2007 paper “Controlling the US health care system with policy wedges” 

proposes a state-space modeling framework to address the long-term growth of the U.S. 

health care sector, which has expanded faster than the economy Springer+1.

Core Methodology

Pasdirtz developed two state-space models:

U.S. economy model (1950–1999)

U.S. health care system model (1950–1999)

The economy model’s output was used as a reference input to control the health care model’s 

growth. This allowed him to simulate a “controlled” scenario where health care growth matched 

economic growthSpringer.

Policy Wedges

A policy wedge refers to a targeted intervention that shifts the growth path of the health care 

system toward the economy’s growth rate. Pasdirtz’s simulations showed that over the late 20th 

century, the U.S. health care system grew faster than GDP, with health care spending as a share 

of GDP rising from 3.4% in 1950 to nearly 14% in 1999 Springer.

To align health care growth with the economy, his model suggested:

13% reduction in capital expenditure
15% reduction in drug prices
32% reduction in physician service prices Springer+1

These wedges represent policy levers—changes in investment, pricing, and service delivery—

that could slow health care growth without eliminating care.

Designing Universal Health Care

Pasdirtz also applied the framework to universal health care design:

Use planning and economic incentives rather than over-engineering benefits

• Avoid centralized, command-and-control approaches
• Balance coverage and cost control through targeted interventions Springer+1

Key Takeaways

Policy wedges are measurable, targeted interventions to slow health care growth.
They can be applied to both cost control and universal coverage design.

The approach combines macroeconomic modeling with policy simulation to test 

counterfactual outcomes.

It offers a data-driven alternative to ad hoc or politically charged reforms.

In short, Pasdirtz’s “policy wedges” framework provides a quantitative, simulation-based 

roadmap for aligning health care growth with economic growth, with practical implications 

for both cost containment and universal coverage policy.