Website: https: //manual. warondisease. org/knowledge/appendix/optimal-budget-generator-spec. html Abstract: 20-40% of public goods funding is misallocated relative to outcome-maximizing benchmarks, representing trillions annually in foregone welfare gains. Budget processes respond to lobbying intensity and historical precedent rather than causal evidence of effectiveness. The Optimal Budget Generator (OBG) applies causal inference, diminishing returns modeling, and cost-effectiveness analysis to determine optimal public goods funding levels that maximize two welfare metrics: real after-tax median income growth and median healthy life years. For each spending category, OBG estimates an Optimal Spending Level (OSL) identifying where marginal returns equal opportunity cost. The Budget Impact Score (BIS) measures confidence in each OSL estimate based on study quality, statistical precision, and temporal recency of the underlying causal evidence. The result is a gap analysis showing which categories are over- or underfunded relative to evidence-based benchmarks, enabling systematic reallocation from low-return to high-return public investments. At system scale, the model's Optimal Governance Trajectory reaches 56. 7x (95% CI: 19. 3x-304x) the Earth baseline after 20 years, raises average income to \1. 16 million (95% CI: \395, 118-\6. 22 million) versus \20, 483 on the status-quo path, reaches \10. 7 quadrillion (95% CI: \3. 64 quadrillion-\57. 2 quadrillion) in total output, and recovers roughly \101 trillion (95% CI: \83. 3 trillion-\191 trillion) /year in suppressed value (The Political Dysfunction Tax (https: //political-dysfunction-tax. warondisease. org) ). Summary: The Optimal Budget Generator (OBG) uses causal inference, diminishing returns modeling, and cost-effectiveness evidence to determine optimal public goods funding levels that maximize two welfare metrics: real after-tax median income growth and median healthy life years. For each spending category, OBG estimates an Optimal Spending Level (OSL) and produces a gap analysis showing where current government budgets are over- or underfunded relative to evidence-based benchmarks. The Budget Impact Score (BIS) measures confidence in each recommendation based on the quality of causal evidence.
Mike P. Sinn (Thu,) studied this question.