Incentive Alignment Bonds: Making Public Goods Financially and Politically Profitable

Author

Affiliation

Mike P. Sinn

Institute for Accelerated Medicine

Abstract

Government spending correlates with lobbying intensity, not marginal societal value. Programs with benefit-cost ratios exceeding 100:1 (vaccines, e-governance) receive single-digit billions while programs with negative net returns (military beyond deterrence, fossil fuel subsidies) receive hundreds of billions. This paper introduces Incentive Alignment Bonds (IABs), financial instruments that realign politician incentives with net societal value optimization. IABs create a capital pool that rewards politicians (via campaign support and post-office career opportunities) for funding high-NSV programs over low-NSV alternatives. The mechanism requires no legislative change: existing PAC infrastructure, impact bonds, and prediction markets can deploy it today. Analysis of a proposed 1% Treaty redirecting $27.2B/year from military spending to medical research shows expected returns exceeding 100:1 for early investors. The 90:1 capital asymmetry ($454T in household wealth vs. $5T for concentrated interests) means diffuse beneficiaries can outspend incumbent lobbies once coordination problems are solved. IABs solve that coordination problem by turning political change into an investable asset class. A dominant assurance contract mechanism solves the bootstrap coordination problem: investor participation is the strictly dominant strategy regardless of beliefs about other investors’ behavior, closing the end-to-end incentive chain from citizen coordination through treaty passage. At system scale, the model’s Optimal-Governance Path reaches 56.7x the Earth baseline after 20 years, raises average income to $1.16M versus $20.5K on the status-quo path, reaches $10.7 quadrillion in total output, and recovers roughly $101T/year in suppressed value (The Political Dysfunction Tax).

Keywords

mechanism design, public choice, political economy, collective action, social impact bonds, campaign finance, incentive compatibility

The Problem in One Sentence: Politicians are rewarded for funding low-NSV programs (military beyond deterrence: 0.7:1 BCR) and punished for funding high-NSV programs (medical research: 100:1+ BCR) because concentrated interests outlobby diffuse beneficiaries, so government spending is optimized for lobbying intensity rather than marginal societal value.

The Solution: Incentive Alignment Bonds (IABs) flip the incentives by creating a capital pool that rewards politicians (with campaign support and post-office career opportunities) for funding high-NSV programs, making marginal societal value optimization the career-maximizing choice.

49.1 Introduction

49.1.1 The Information-Incentive Disconnect

A central puzzle in political economy is why policies with large positive net social welfare often fail to be adopted. The economic case for many global public goods, including climate mitigation, pandemic preparedness, and clinical trials, is overwhelming, yet governments don’t do them. The conventional diagnosis is wrong: the problem is not lack of information or resources, but wrong incentives.

Rankings of government programs by net societal value already exist and are systematically ignored. The Copenhagen Consensus has published rigorous benefit-cost ratio (BCR) analyses since 2004¹³⁷. Their findings are clear: childhood vaccinations (101:1 BCR), e-government procurement (125:1), and maternal health interventions (87:1) dramatically outperform military spending beyond deterrence requirements (~0.7:1) and fossil fuel subsidies (negative net societal value). GiveWell, Open Philanthropy, the IMF, and numerous academic institutions produce similar analyses.

Yet government spending patterns have not shifted. The U.S. spends $16 on military operations for every $1 on diplomacy and humanitarian aid. Programs with benefit-cost ratios exceeding 100:1 receive single-digit billions while programs with negative net societal value receive hundreds of billions.

Here’s the reality: If a private equity firm allocated capital like the U.S. government, it would invest $100M in ventures that destroy $500M in value while rejecting ventures that return $10B. The firm would be bankrupt within a year. The government simply prints more money and calls it “fiscal policy.”

The marginal value of producing another ranking is zero. We don’t need more information. Politicians already know which programs produce net societal value. We need a mechanism to make existing information consequential in the political utility function (the mathematical representation of what politicians actually care about: reelection, money, status).

This paper argues that politicians maximize reelection probability, post-office career prospects, and status, not aggregate social welfare. The problem is not that decision-makers don’t know which programs produce value. They do know. They don’t care, because caring doesn’t appear in their utility function.

Mancur Olson’s seminal work The Logic of Collective Action¹³⁸ established that groups with concentrated interests (small groups with huge per-person stakes, like weapons manufacturers) systematically outcompete groups with diffuse interests (millions of people with small individual stakes, like citizens who’d benefit from cures) in political competition. Why? A small group facing large per-member stakes will invest more in lobbying than a large group facing small per-member stakes. This holds even when total welfare losses exceed total welfare gains. The beneficiaries of inefficient policies (weapons manufacturers, pharmaceutical incumbents, fossil fuel producers) are concentrated. The beneficiaries of efficient policies (citizens who would benefit from cures, climate stability, reduced existential risk) are diffuse.

The result is a systematic distortion of democratic governance. The U.S. Constitution’s Preamble charges government to “promote the general Welfare,” the welfare of all citizens, not the welfare of any particular faction. Yet Olsonian dynamics ensure that government routinely promotes specific welfare (of concentrated interests who can afford to lobby) at the expense of general welfare (of the diffuse public). This is not corruption in the legal sense; it is the predictable equilibrium (stable outcome where nobody wants to change their behavior) of rational actors operating within existing institutional rules. The problem is not bad actors but bad incentives.

Empirical evidence confirms this pattern. Gilens and Page¹³⁹ analyzed 1,779 policy decisions over two decades. Finding: “economic elites and organized groups representing business interests have substantial independent impacts on U.S. government policy, while mass-based interest groups and average citizens have little or no independent influence.” The correlation between average citizen preferences and policy outcomes was effectively zero. Whether 0% or 100% of citizens supported a policy, its probability of adoption remained unchanged at approximately 30%. By contrast, policies favored by economic elites were adopted at significantly higher rates. Figure 49.1 illustrates this disconnect.

Figure 49.1: What the public wants has zero effect on what policies pass. What rich people want has total effect on what policies pass. You call this democracy.

49.1.2 Key Results

The people who would benefit from good policy have 90 times more money than the people who benefit from bad policy. This is why bad policy keeps winning.

This paper demonstrates that the adoption problem (getting welfare-improving policies passed despite concentrated opposition) is solvable through mechanism design (designing rules so people’s selfish choices create good outcomes):

272% expected first-year ROI on bootstrap capital from lobbying economics (Section 2.2)
$454T vs. $5T capital asymmetry ensures diffuse beneficiaries (citizens who’d benefit from cures) can outspend concentrated opposition (weapons manufacturers) by 90:1 (Section 2.3)
230 benefit-cost ratio of the IAB mechanism itself, even accounting for overhead costs and failure risk (Section 7.3)
Mechanism achieves incentive compatibility (when doing the right thing is also the profitable thing) with realistic parameters in low-opposition domains; requires higher funding in entrenched-opposition domains (Section 3.3)
Complementary mechanisms prevent allocation capture once resources are redirected (Section 6.1)
Bootstrap problem is solvable: ROI potential attracts risk-tolerant capital; capital asymmetry ensures scalability once proof-of-concept succeeds (Section 8.1)
Dominant assurance contract makes investor participation the strictly dominant strategy, closing the end-to-end incentive chain from citizen coordination through treaty passage (Section 8.2)

Scale note. The prize here is not marginal. Under the project’s best-case governance ceiling, the recoverable upside is $101T per year. The 20-year Optimal-Governance Path reaches 56.7x the Earth baseline, raises average income to $1.16M versus $20.5K on the status-quo path, and reaches $10.7 quadrillion in total output. This paper focuses on the adoption mechanism that could make movement toward that ceiling politically profitable; the full derivation lives in The Political Dysfunction Tax⁴⁶.

49.1.3 Reader’s Guide

Non-technical readers can skip Section 3 (formal model); the intuition is provided in Section 2. Economists should focus on Section 3 (explicit functional forms) and Section 7 (welfare accounting). Investors should focus on Section 2.2-2.3 (ROI and capital asymmetry) and Section 8 (bootstrap solution).

A map for three types of readers: people who want to understand, people who want to argue, and people who want to know where their money goes.

This paper introduces Incentive Alignment Bonds (IABs), a mechanism design approach to reversing this dynamic. Rather than attempting to change politicians’ preferences or relying on benevolent decision-makers, IABs restructure the incentive environment so that rational self-interest points toward welfare-improving policies.

49.1.4 Definition

An Incentive Alignment Bond is a financial instrument with three primitive properties:

Investor alignment with public good production: Investors receive returns proportional to verified public-good funding flows achieved (e.g., treaty ratification, appropriations enacted). Returns are keyed to observable funding events, not downstream outcomes, avoiding complex attribution problems. If the policy succeeds, investors profit; if it fails, they do not. This creates a class of actors with concentrated financial interest in policy success.

Money goes to politicians. Politicians do good things. Good things make money. Money goes back to investors. It’s a circle, like a carousel, but for buying democracy.

Politician alignment with public good production: Politicians receive electoral support and career benefits based on their voting record for the target policy class. Supporting the public good becomes the utility-maximizing choice, increasing reelection probability, post-office income, and status.
Funding from lower-value sources: The public good is funded by redirecting resources from government activities with lower social value than the target use. In the strongest case, these are programs that produce measurable net harm. More generally, they are programs that persist due to Olsonian concentrated-benefit/diffuse-cost dynamics rather than comparative merit. This constraint ensures IABs reallocate from less valuable to more valuable uses; they are welfare-improving in expectation under standard utilitarian social welfare assumptions.

The third property is crucial. Many government expenditures persist not because they produce social value, but because their beneficiaries are concentrated while their costs are diffuse. Military spending beyond deterrence requirements. Agricultural subsidies that distort markets. Fossil fuel subsidies that accelerate climate change. These programs survive political competition not on merit but on lobbying intensity. Concentrated interests (weapons manufacturers, incumbent industries) invest heavily in maintaining these programs, while diffuse beneficiaries face collective action problems. IABs redirect these resources to measurable public goods, making the reallocation welfare-improving even before accounting for the public good produced.

The key innovation is that all three alignments reinforce each other. A fraction of redirected funding flows perpetually to (a) investor returns and (b) political incentive mechanisms, while (c) the funding source ensures no beneficial programs are displaced. This makes the instrument self-sustaining: policy success generates the resources that maintain both investor and politician alignment, creating pressure for continuation and expansion.

Unlike Social Impact Bonds (which align service providers with program outcomes), IABs align the actors who control large-scale budget decisions, the politicians, with public-good production. Unlike lobbying (which aligns politicians with narrow interests), IABs align politicians with measurable, welfare-improving outcomes. Unlike campaign contributions (which are ad hoc and candidate-specific), IABs create universal, ex-ante rules tied to objective metrics. And unlike new taxation or deficit spending, IABs fund public goods by displacing harmful or wasteful expenditure.

A natural objection: “How is this not just PACs + voter scorecards + SIBs?” The answer is that existing mechanisms fail to solve the Olsonian problem because they operate in isolation. PACs exist but remain dominated by concentrated interests due to the 90:1 capital asymmetry. Scorecards exist (League of Conservation Voters, NRA ratings) but lack teeth without accompanying financial incentives. SIBs exist but require government to agree upfront, which faces the same collective action problem IABs solve. IABs integrate all three components (investor capital, electoral accountability, post-office incentives) into a single instrument where each component’s effectiveness depends on the others, and where the funding mechanism creates permanent financial incentives for diffuse beneficiaries to overcome collective action barriers. The whole is greater than the sum of its parts because the integrated architecture makes coordinated capital deployment economically rational for millions of individual investors.

49.1.5 Why Reallocation, Not Addition

A natural question: why insist on redirecting resources from harmful programs rather than simply adding new spending on public goods? The answer: real resources (people, factories, scientists) are finite.

Spending more money doesn’t work because there aren’t more doctors. Moving money from bombs to medicine does work because doctors already exist.

When advocates successfully lobby for increased spending on a beneficial program, the political response is rarely a corresponding reduction in harmful programs. Instead, governments usually:

Expand the overall budget through deficit spending or monetary expansion
Increase spending on politically powerful programs in parallel, to maintain coalition support
Dilute the real value of new spending through inflation and competition for fixed resources

The result is that the beneficial program’s nominal budget increases while its real share of resources remains unchanged or even decreases. The concentrated beneficiaries of harmful programs lose nothing; the diffuse beneficiaries of the new program gain less than the headline figures suggest.

Consider the empirical pattern: between 2000 and 2024, U.S. federal spending on both military and healthcare increased much in nominal terms. Neither constituency “lost” to the other. Instead, total federal spending grew from $1.8 trillion to $6.1 trillion, while the national debt expanded from $5.6 trillion to $34 trillion. The real constraint, the finite pool of engineers, scientists, manufacturers, and productive capacity, was diluted across an ever-expanding set of nominal claims. Defense contractors retained their share of real resources; healthcare advocates won nominal victories that competed with inflation and expanding claims elsewhere in the budget.

This is not a failure of advocacy. It is the equilibrium outcome (stable result when everyone optimizes given current rules) of Olsonian dynamics operating under soft budget constraints (when governments can spend without immediate consequences; they just print money or charge it to the credit card of future generations). Concentrated interests protect their programs absolutely. Diffuse interests win nominal victories. The budget grows in nominal terms while each program’s claim on real resources remains contested.

The mechanism is straightforward: when Congress appropriates $10 billion for pragmatic clinical trials without specifying a funding source, the Treasury either borrows or the Federal Reserve accommodates. Total nominal spending increases.

But the supply of trained researchers, laboratory equipment, and institutional capacity does not increase proportionally. The new dollars compete with existing dollars, including those flowing to military, fossil fuel subsidies, and other Olsonian programs, for the same finite resources.

Inflation, both general and sector-specific, erodes the real purchasing power of the nominal increase.

IABs break this dynamic by specifying the funding source as part of the mechanism. The policy does not say “fund pragmatic clinical trials”; it says “redirect 1% of military spending to pragmatic clinical trials.” This forces a real reallocation:

Military budgets face actual cuts in nominal and real terms
Concentrated losers (weapons manufacturers) face real losses, which they will resist
But the IAB political incentive layer ensures politicians who support the reallocation benefit more than those who resist
The finite pool of resources shifts from net-negative to net-positive uses

The third primitive property, funding from harmful sources, is therefore not merely a normative preference or a political strategy. Under the soft budget constraint dynamics described above, it is enough to achieve real resource reallocation (likely needed in practice). Without specifying the funding source, advocates win symbolic victories while real resources continue flowing to Olsonian programs. With specified reallocation, the IAB creates genuine redistribution from net-negative to net-positive uses, constrained only by political will rather than by the illusion of unlimited budgetary capacity.

49.1.6 Political Change as an Asset Class

To understand why investors would fund the initial campaign to pass an IAB treaty, we must recognize political advocacy not as charity, but as a high-yield asset class. The Return on Investment (ROI) for corporate lobbying is historically orders of magnitude higher than traditional financial markets. The following illustrative estimates, drawn from existing studies, suggest order-of-magnitude returns:

Defense: The top five weapons manufacturers spent $1.1 billion on lobbying over two decades while receiving $2.02 trillion in Pentagon contracts, an implied maximum ROI of approximately 181,000% assuming full attribution¹⁴⁰.
Fossil Fuels: The oil and gas industry spent $151 million lobbying in 2024 to protect $17 billion in subsidies, an implied maximum annual return of approximately 11,000% assuming full attribution¹⁴¹.
Medical Research: Academic analysis finds that for specific disease groups, each $1,000 spent on lobbying is associated with $25,000 in additional NIH funding, an implied return of approximately 2,500%¹⁴².

These figures represent upper bounds assuming all contracts/subsidies are attributable to lobbying; causal attribution is complex and effects vary by context. Academic estimates of causal lobbying returns typically find 100-1000x ROI. Nevertheless, they suggest that political influence generates returns far exceeding traditional asset classes (compare to the S&P 500’s historical average of ~10%). Political change is currently accessible only to concentrated industries protecting the status quo. IABs securitize this opportunity, allowing investors to capture a fraction of the value generated by shifting government priorities toward public goods.

\[ E[R] = \frac{P(\text{success}) \times (\text{Redirected Flow} \times \text{Investor Share})}{\text{Campaign Cost}} \]

Illustrative calculation: If a campaign costs $1B and has a 20% chance of passing a treaty that redirects $27.2B/year (with 10% to investors), the expected annual value is:

\[ E[V] = 0.20 \times \$2.72\text{B} = \$544\text{M/year} \]

The expected first-year ROI on the $1B campaign is 54.4% (expected payout divided by campaign cost), with the revenue stream continuing in perpetuity. Upon treaty passage, the conditional ROI is 272%.

Sensitivity to parameter uncertainty:

Parameter	Base Case	Effect on ROI
Success probability	20% (illustrative)	Linear
Campaign cost	$1B	Inverse
Investor share	10%	Linear
Treaty size	$27.2B	Linear

Even under conservative assumptions (low success probability, upper CI bound on campaign cost, 10% investor share), expected ROI remains comparable to 10% stock market returns, with asymmetric upside. The mechanism is economically rational for risk-tolerant capital across a wide parameter range.

49.1.7 The Capital Asymmetry: Why IABs Can Outcompete Incumbent Lobbying

Here’s what almost everyone misses: the collective capital available to diffuse beneficiaries vastly exceeds the resources of concentrated interests. The problem is not lack of resources but lack of coordination.

Consider the global capital distribution:

Concentrated interests (weapons manufacturers, fossil fuel companies, pharmaceutical incumbents): Combined market capitalization ~$5T¹
Diffuse beneficiaries (everyone who would benefit from cures, climate stability, pandemic prevention): Global household wealth ~$454T¹⁴³

Everyone together has 90 times more money than weapons companies. The weapons companies are still winning. This is called leverage.

The 90:1 capital advantage cannot currently be deployed because diffuse beneficiaries face a collective action problem (hard for large groups to coordinate even when everyone would benefit): each individual’s stake is small, and coordination costs are prohibitive. A retiree who would gain 5 additional healthy years from accelerated medical research has enormous stake (~$500K in value of statistical life-years) but cannot coordinate with millions of other retirees to match pharmaceutical lobbying budgets.

IABs solve the coordination problem by securitizing political change (turning policy outcomes into tradable financial instruments, like turning mortgages into mortgage-backed securities). If IABs can be structured as tradable securities that any individual can purchase, they transform diffuse beneficiaries into the largest special interest group in history. The mechanism:

Investment accessibility: Structure IABs as securities available to retail investors (similar to green bonds or social impact bonds)
Returns exceed alternatives: Expected returns of 100-1000%+ (from lobbying ROI) dramatically exceed stock market returns of 10%
Massive capital mobilization: Even 0.1% of global household wealth ($454T 0.1%) exceeds total annual global lobbying spending by 100×
Self-interest alignment: Investors profit directly from policy success, creating concentrated financial incentives on the welfare-improving side

This reverses the Olsonian asymmetry. Defense contractors spend $100M+ annually lobbying because each firm captures concentrated benefits.

But the IAB mechanism allows millions of diffuse beneficiaries to collectively deploy billions while each capturing a proportional return.

The concentrated opposition ($100M-$1B annually) becomes outmatched by newly-coordinated diffuse support ($10B-$100B+ available capital).

We’re not inventing lobbying. Defense contractors proved it works decades ago. We’re just making it available to everyone whose lives depend on cures instead of bombs. Turns out there are more of us, and we’re much richer. The political change ROI (100-10,000x) that currently accrues only to concentrated industries becomes accessible to everyone who benefits from public goods.

49.1.8 Quantifying Net Societal Value of Funding Sources

The third primitive property requires identifying government expenditures with lower marginal social value than the proposed alternative. This is an empirical question that can be addressed using standard welfare economics:

\[ NSV_i = B_i - C_i \tag{49.1}\]

where $NSV_i$ is net societal value of program $i$, $B_i$ is measurable social benefits (including economic multiplier effects), and $C_i$ is total costs (including both direct expenditure and opportunity costs of foregone alternatives).

A program is an appropriate IAB funding source if:

\[ NSV_{source} < NSV_{target} \tag{49.2}\]

That is, if the marginal social value of the source program is lower than that of the target program. In the strongest case, $NSV_{source} \leq 0$; the program produces net harm. But reallocation is justified even when both programs have positive value, as long as the target exceeds the source.

This comparative criterion implies a natural ranking of government expenditures by marginal social value. IABs should draw from the lowest-ranked programs first, those that persist mainly due to Olsonian dynamics rather than merit. This avoids the objection that “military isn’t ALL bad”; the claim is not that military spending is worthless, but that its marginal value is lower than medical research, and that it persists at current levels due to lobbying intensity rather than comparative social value.

Military spending provides a concrete example. The economic multiplier for military spending is around 0.6, compared to 1.5–3.0 for infrastructure, education, and medical research. This means each dollar of military spending generates $0.60 in economic activity, while each dollar of medical research investment generates $2.00–3.00. The opportunity cost alone, before considering direct harms, makes military spending beyond minimum deterrence requirements a net social loss.

More comprehensive analysis includes:

Table 49.1: Estimated Annual Societal Cost of Global Military Spending

Cost Category	Annual Value	Source
Direct military expenditure	$2.72T	⁵¹
Lost GDP from multiplier differential	$2.72T	³⁷
Infrastructure destruction (active conflicts)	$1.88T	World Bank
Human casualties (VSL method)	$2.45T	EPA VSL × conflict deaths
Trade disruption	$616B	World Bank trade flow analysis
Veteran healthcare (ongoing)	$200B	⁴²
Environmental damage	$100B	³⁵
Total societal cost	$11.4T	Sum of above

A large literature suggests the net societal value of military spending beyond minimum deterrence is strongly negative: $2.72T in direct expenditure produces $11.4T in societal costs (see Table 49.1 for illustrative order-of-magnitude estimates). If these estimates are roughly correct, redirecting even 1% to pragmatic clinical trials, which has positive externalities and high multipliers, would be welfare-improving on net.

Similar analysis applies to other Olsonian programs:

Fossil fuel subsidies ($7T globally, IMF 2023): Accelerate climate change, distort energy markets, produce negative externalities exceeding subsidy value
Agricultural subsidies in developed nations: Distort global food markets, harm developing-country farmers, produce environmental damage from monoculture incentives
Regulatory capture programs: Expenditures that exist to protect incumbent firms from competition rather than serve public interest

Table 49.2 presents a comprehensive ranking combining Copenhagen Consensus data with other authoritative sources. The pattern is stark: programs with BCRs exceeding 100:1 receive single-digit billions in annual spending, while programs with negative NSV receive hundreds of billions. Spending correlates with lobbying intensity, not social value. This systematic misallocation is the empirical foundation for the IAB mechanism.

Table 49.2: Ranking of Government Expenditures by Benefit-Cost Ratio and Net Societal Value

Program / Category	BCR	Annual Spending	Est. NSV (per $1)	Source
HIGH-NSV PROGRAMS (IAB TARGETS)
Pragmatic Clinical Trials	637:1 – 11,540:1	~$60B	+$636 – $11,539	¹⁴⁴;¹⁴⁵
Childhood Vaccinations (Global)	101:1	~$8B	+$100	Copenhagen Consensus 2023¹³⁷
E-Government Procurement	125:1	~$2B	+$124	Copenhagen Consensus 2023¹³⁷
Maternal/Neonatal Care	87:1	~$12B	+$86	Copenhagen Consensus 2023¹³⁷
Nutrition Interventions	18:1	~$5B	+$17	Copenhagen Consensus 2023¹³⁷
Medical Research (NIH)	2.56:1 – 4.75:1	$47B	+$1.56 – $3.75	United for Medical Research¹⁴⁶
Early Childhood Education	2.5:1 – 10.8:1	~$30B	+$1.50 – $9.80	¹⁴⁷,¹⁴⁸
MODERATE-NSV PROGRAMS
Infrastructure (High-Quality)	1.5:1 – 2.5:1	Varies	+$0.50 – $1.50	¹⁴⁹; highly project-dependent
LOW/NEGATIVE-NSV PROGRAMS (IAB SOURCES)
Military (Beyond Deterrence)	~0.7:1	$450B+ (US)	-$0.30	¹⁵⁰; fiscal only, excludes conflict costs
Fossil Fuel Subsidies (Explicit)	<0	$20B (US)	-$1 to -$5	¹¹⁴
Fossil Fuel (Implicit/Externalities)	-5:1	$568B (US)	-$5	¹⁵¹, PNAS 2021 externality analysis

The empirical criterion is straightforward: if a program’s beneficiaries are concentrated, its costs are diffuse, and rigorous cost-benefit analysis shows $NSV_{source} < NSV_{target}$, reallocation is welfare-improving. In the clearest cases, where $NSV_{source} \leq 0$, the source program is actively harmful and reallocation is unambiguously beneficial. But even programs with modestly positive NSV are appropriate sources if the target has much higher value. The IAB mechanism does not require moral judgment about the source program, only comparative measurement.

Scatter plot showing annual government spending on the x-axis (log scale) and benefit-cost ratio on the y-axis (log scale). High-NSV programs cluster in the upper-left (underfunded), while low/negative-NSV programs cluster in the lower-right (overfunded). — Figure 49.2: Government Spending vs. Benefit-Cost Ratio. Programs with the highest BCRs (>100:1) receive the least funding, while programs with negative NSV receive hundreds of billions. This inverse correlation demonstrates that spending is driven by lobbying intensity, not social value.

Under rational resource allocation, we would expect high-BCR programs to receive high spending (upper-right quadrant) and low-BCR programs to receive low spending (lower-left quadrant). Instead, we observe the opposite: programs with BCRs exceeding 100:1 are clustered in the “UNDERINVESTED” region, while programs with BCRs below 1:1 (or negative) are in the “OVERINVESTED” region.

This systematic misallocation is the empirical foundation for Incentive Alignment Bonds: spending correlates with lobbying intensity, not social value.

Four-quadrant chart with NSV on y-axis and Spending on x-axis, showing specific government programs positioned according to their social value and funding levels. — Figure 49.3: The Olsonian Quadrant Chart: Government Program Allocation by NSV and Spending. Quadrant I (upper-right) represents rational allocation; Quadrant II (upper-left) shows high-value programs that are systematically underfunded; Quadrant IV (lower-right) shows low-value programs that are overfunded due to Olsonian dynamics.

Interpretation:

Quadrant I (Rational): Programs with high NSV receiving high spending: the desired equilibrium
Quadrant II (Underinvested): High-NSV programs receiving low spending: Olsonian failure where diffuse benefits cannot coordinate
Quadrant III (Wasteful but Small): Low-NSV programs with low spending: wasteful but limited damage
Quadrant IV (Overinvested): Low-NSV programs receiving high spending: Olsonian capture where concentrated interests dominate

The IAB Mechanism: Redirects resources from Quadrant IV → Quadrant I by making politician support for high-NSV programs individually rational through score-dependent electoral and career benefits.

Figure 49.2 visualizes this systematic misallocation as a scatter plot, while Figure 49.3 categorizes programs into four quadrants based on their NSV and funding levels. These visualizations make clear that under rational allocation, high-BCR programs receive high funding (upper-right quadrant). Instead, we observe the opposite: high-BCR programs cluster in the “UNDERINVESTED” region while low/negative-BCR programs are “OVERINVESTED.”

49.1.9 Relation to Existing Literature

This paper combines three literatures. First, mechanism design theory^152–154 provides tools for designing institutions when agents have private information and act strategically. While mechanism design has transformed market institutions, from spectrum auctions¹⁵⁵ to kidney exchanges¹⁵⁶, its application to political institutions is limited. We extend this framework to political incentives, treating politicians as strategic agents whose actions (votes) are observable but whose preferences may diverge from social welfare.

Three fields of economics had a baby and that baby is a bond that bribes politicians legally.

Second, public choice theory^138,157 models politicians as utility maximizers rather than benevolent planners. Olson’s analysis of concentrated versus diffuse interests explains persistent policy failures but offers limited remedies. We turn Olson’s insight into a mechanism: if concentrated benefits cause politicians to favor narrow interests, then concentrating benefits on the welfare-improving side can reverse the dynamic.

Third, campaign finance research^158–160 and political agency models¹⁶¹ document how electoral incentives and career concerns shape politician behavior. We synthesize these findings into a mechanism that systematically exploits these channels for public goods.

Relative to Social Impact Bonds^162,163, IABs target a different agent (politicians vs. service providers) at a different level (policy adoption vs. program delivery). Relative to lobbying and campaign contributions, IABs create universal, ex-ante, public rules tied to verifiable outcomes rather than ad hoc relationships. Relative to pure voting reform proposals, IABs work within existing institutional constraints.

49.1.10 Contribution

This paper makes five contributions:

Mechanism Design for Governance: We apply the formal tools of mechanism design theory, developed for auctions, matching markets, and resource allocation, to the problem of political incentives. While mechanism design has transformed economic institutions from spectrum auctions to kidney exchanges, its application to democratic governance is underdeveloped.

Four big ideas: use game theory on politics, invent a new financial instrument, build it in three legal layers like a cake, prove it makes everyone richer. Simple.

A New Financial Instrument: We define IABs as a distinct class of financial instrument with three primitive properties: investor alignment, politician alignment, and funding from lower-value sources. This distinguishes IABs from Social Impact Bonds (which reward service providers, not politicians), lobbying (which serves narrow interests), and campaign contributions (which lack systematic, ex-ante, universal rules tied to measurable outcomes).
A Legal Architecture: We specify a three-layer structure (scoring, electoral support, post-office benefits) that achieves incentive alignment without violating anti-bribery statutes. The legal innovation is separating data provision from electoral activity from career benefits, with each layer operated by legally distinct entities.
A Welfare-Improvement Criterion: We formalize how to identify appropriate IAB funding sources using comparative net societal value analysis ($NSV_{source} < NSV_{target}$) and show why specified reallocation, rather than budget addition, is enough (needed) to achieve real resource shifts. Under soft budget constraints, nominal spending increases are diluted by deficit expansion and inflation while Olsonian programs retain their share of real resources. This comparative criterion implies a natural ranking of expenditures; IABs draw from the lowest-ranked programs first, ensuring reallocation is welfare-improving under standard utilitarian assumptions.
A Bootstrap Coordination Mechanism: We adapt Tabarrok’s¹⁶⁴ dominant assurance contract to solve the investor coordination problem that precedes IAB deployment. We prove that participation in the assurance contract is the strictly dominant strategy for all potential investors (Proposition 4), closing the end-to-end incentive chain from citizen coordination through politician behavior change to treaty passage.

49.1.11 Roadmap

Section 2 reviews why previous approaches failed. Section 3 presents the formal model. Section 4 details the three-layer architecture and its legal basis. Section 5 analyzes failure modes. Section 6 discusses the broader governance stack. Section 7 extends the mechanism to climate, nuclear risk, and pandemic preparedness. Section 8 addresses the bootstrap problem, including the dominant assurance contract for investor coordination. The Conclusion summarizes contributions and open questions.

How this paper works: here’s why everything failed, here’s the math for why it failed, here’s how to fix it, here’s how to fix it everywhere.

49.2 Why Previous Approaches Failed

Old way: politicians get paid to do bad things, so they do bad things. New way: politicians get paid to do good things. Shockingly, this required a 50-page paper to explain.

49.2.1 Mechanism Design Theory

The Sveriges Riksbank Prize in Economic Sciences 2007 was awarded to Leonid Hurwicz, Eric Maskin, and Roger Myerson “for having laid the foundations of mechanism design theory”¹⁶⁵. Mechanism design addresses a fundamental problem: how do you get selfish people to do the right thing without forcing them?

Mechanism design is the art of making people do good things by accident while they’re trying to be selfish.

Hurwicz¹⁵² introduced the concept of incentive compatibility: a mechanism is incentive-compatible if the socially optimal action is in each agent’s self-interest. The rules make doing the right thing also the profitable thing.

These concepts have transformed market design: auction theory¹⁵⁵, matching markets¹⁵⁶, and regulation¹⁶⁶. This paper extends mechanism design to political incentives, treating politicians as strategic agents whose actions (votes, public statements, bill sponsorship) are observable.

49.2.2 Public Choice Theory

Public choice theory applies economic methods to political behavior. Buchanan and Tullock¹⁵⁷ model politicians and voters as rational utility maximizers, not benevolent social planners. Olson¹³⁸ shows that collective action for public goods is systematically undersupplied because:

Free-rider problem: Large groups cannot exclude non-contributors from benefits
Asymmetric stakes: Per-member stakes are higher in small groups
Organization costs: Smaller groups face lower coordination costs

The result is that “concentrated minor interests will be overrepresented and diffuse majority interests trumped”¹³⁸. Empirical support includes Lohmann’s observation that U.S. sugar import quotas generated 2,261 jobs while reducing overall welfare by $1.162 billion, an implicit cost per job exceeding $500,000¹⁶⁷. The government could have paid each sugar worker half a million dollars to not grow sugar. This would have saved money. Nobody did this. Sugar growers have lobbyists. Consumers don’t.

100 people who each lose a million dollars will fight harder than 100 million people who each lose a dollar. This is why your government works for 100 people.

IABs address this directly: by concentrating benefits on politicians who support diffuse-benefit policies, the asymmetry is reversed. Supporting the public good becomes the concentrated-benefit option.

49.2.3 Social Impact Bonds

Social Impact Bonds (SIBs), introduced in the UK in 2010, are outcome-based contracts in which private investors fund social interventions and are repaid by government only if specified outcomes are achieved¹⁶². The Peterborough Prison SIB, the first implemented, funded prisoner rehabilitation and measured recidivism rates against a control group¹⁶⁸.

SIBs have attracted much policy enthusiasm but limited empirical evidence of their distinctive effect. As Hevenstone¹⁶⁹ notes, “only program effects have been estimated, not the specific impact of SIB financing itself.” A systematic review by the Brookings Institution found “insufficient evidence as to whether and how SIBs deliver better outcomes than conventional forms of financing”¹⁶³.

More important, SIBs target the wrong level. They incentivize service providers (nonprofits delivering programs) for local outcomes (recidivism in one city). IABs target politicians for policy adoption at the national or international level. The difference: incentivizing one job training program versus incentivizing the legislation that funds all job training programs. Table 49.3 summarizes the distinction.

Table 49.3: Comparison of Social Impact Bonds and Incentive Alignment Bonds

Dimension	Social Impact Bonds	Incentive Alignment Bonds
Target agent	Service providers	Politicians
Outcome measured	Program delivery	Policy adoption and funding flows
Scale	Municipal/program	National/international
Funding source	Government pays for outcomes	Policy outcome funds mechanism
Attribution	Single provider, single program	Voting records, funding contributions

49.2.4 Campaign Finance and Political Behavior

Empirical research on campaign finance provides the evidentiary foundation for the electoral layer of IABs.

Three ways to buy a politician: tell voters they’re bad, give them a report card like they’re in school, or promise them a nice job later. Democracy runs on deferred compensation.

Independent expenditures affect elections. Following Citizens United v. FEC (2010), independent expenditures increased dramatically. In the decade prior to the decision, outside groups spent $296 million total on independent expenditures; in the decade after, they spent $4.26 billion, a 14-fold increase¹⁷⁰. Research using transaction-level disbursement data finds that “spending on messages to voters has a statistically significant effect on voter support for candidates” and is “especially effective in changing the composition of voters”¹⁵⁸.

Interest group scorecards influence behavior. Organizations like the National Rifle Association (NRA), League of Conservation Voters (LCV), and Chamber of Commerce publish voting scorecards that affect politician behavior. The LCV has published its National Environmental Scorecard since 1970, and it has “become the gold standard of congressional vote scoring on environmental issues”¹⁷¹. Research confirms that PAC contributions correlate with votes on relevant issues, though causality is debated^159,160.

The revolving door affects politician incentives. Research documents significant movement between government and private sector. A 2023 study found that 32% of HHS appointees exited to industry employment¹⁷². Among four-star military officers who retired after June 2018, over 80% went to work for the military industry as board members, advisors, executives, consultants, or lobbyists¹⁷³. Shepherd and You¹⁶¹ find evidence that “career concerns” about post-office employment influence legislative behavior.

49.2.5 Credit Rating Agencies as Governance Mechanisms

Credit rating agencies (CRAs) provide a precedent for private organizations influencing sovereign policy through reputational mechanisms. Moody’s, S&P, and Fitch assign sovereign credit ratings that directly affect borrowing costs. Barta¹⁷⁴ describes CRAs as “unelected, unappointed, unaccountable profit-seeking institutions” whose power rivals the IMF or World Bank. Downgrades can trigger crises: Greece, Ireland, and Portugal all experienced accelerated debt crises following CRA downgrades to “junk” status¹⁷⁵.

Credit rating agencies tell you which loans are terrible. We’re doing the same thing, but for senators.

The IAB scoring system is structurally analogous to credit ratings: an independent body publishes scores based on objective criteria, and market actors (voters, donors, employers) respond to those scores. The difference is the metric: instead of fiscal sustainability, IABs measure support for measurable public goods.

49.3 The Math: Proving It Works

For Non-Technical Readers: You can skip this section. In plain English: We create a “Public Good Score” for each politician based on their voting record. Politicians with higher scores get (1) campaign support from independent political groups, (2) better post-office job opportunities, and (3) higher public status. When these benefits exceed the costs (losing weapons manufacturer donations), supporting public goods becomes the rational choice. Skip to Section 4 for practical implementation or Section 6 for governance architecture.

A politician weighing bribes on one hand against not being a terrible person on the other. We’re trying to make goodness pay more than badness.

This section presents a formal model of political incentives under IABs. We state explicit assumptions, derive conditions for incentive compatibility (when doing the right thing is also the profitable thing), and characterize equilibria (stable outcomes). Appendix A provides detailed proofs.

49.3.1 Assumptions

We maintain the following assumptions throughout:

A1 (Rational Politicians). Each politician $i \in \{1, \ldots, N\}$ is a rational agent maximizing expected utility $U_i$ over career outcomes, including reelection, post-office income, and legacy.

A2 (Observable Votes). Voting records on policy class $\mathcal{P}$ are publicly observable and verifiable. The scoring function $f: \text{VoteRecord} \to \mathbb{R}$ is common knowledge.

A3 (Credible Commitment). The IAB mechanism can credibly commit to score-dependent payoffs: independent expenditure rules $I_i(\theta_i)$ and post-office eligibility criteria $\tau(\theta_i)$ are announced ex ante and cannot be renegotiated ex post.

A4 (Funded Mechanism). The IAB is sufficiently capitalized that the payoff differentials $\Delta P_i$, $\Delta Y_i$ induced by score changes are non-negligible relative to concentrated opposition costs $c_i$.

A5 (Single Policy Dimension). Politicians face a binary choice $a_i \in \{0,1\}$ on the target policy class. Extensions to multiple dimensions are discussed in Section 6.

49.3.2 The Politician’s Utility Function

We model a politician $i$ as a rational agent maximizing a utility function:

\[ U_i = \alpha_i \cdot P_i(\text{reelection}) + \beta_i \cdot E_i[\text{PostOfficeIncome}] + \gamma_i \cdot S_i(\text{Legacy}) \tag{49.3}\]

where:

$P_i(\text{reelection})$ is the probability of winning the next election
$E_i[\text{PostOfficeIncome}]$ is expected lifetime earnings after leaving office
$S_i(\text{Legacy})$ is a status/legacy function (books, buildings named, Wikipedia length)
$\alpha_i, \beta_i, \gamma_i > 0$ are weights varying by politician but assumed positive

This formulation is consistent with public choice theory’s treatment of politicians as utility maximizers¹⁵⁷ and with empirical research on career concerns¹⁶¹.

49.3.3 The Utility Function Transformation

The key mechanism design insight is that IABs transform the politician’s utility function by introducing a dependency on net societal value (NSV) rankings through an intermediate score variable.

Pre-IAB utility function: Let $R$ denote the ranking of programs by NSV (as produced by Copenhagen Consensus, GiveWell, etc.). In the status quo:

\[ U_i^{\text{pre-IAB}} = \alpha_i \cdot P_i + \beta_i \cdot Y_i + \gamma_i \cdot S_i \tag{49.4}\]

Critically, the ranking $R$ appears nowhere in this function. Each component is driven by lobbying intensity and concentrated interests, not social value:

$P_i = P_i^0 + f(\text{campaign contributions}) + g(\text{attack ads avoided})$
$Y_i = h(\text{revolving door relationships})$
$S_i = s(\text{partisan loyalty}, \text{donor satisfaction})$

Post-IAB utility function: The IAB mechanism introduces a Public Good Score $\theta_i = f(R, \text{VoteRecord}_i)$ that translates the NSV ranking into politician-specific incentives. Each utility component becomes score-dependent:

\[ U_i^{\text{post-IAB}} = \alpha_i \cdot P_i(\theta_i) + \beta_i \cdot Y_i(\theta_i) + \gamma_i \cdot S_i(\theta_i) \tag{49.5}\]

Now the ranking $R$ is operative through $\theta_i$. Politicians who vote to reallocate resources from low-NSV to high-NSV programs see their scores rise, which increases their reelection probability, post-office income prospects, and legacy value.

Explicit functional forms: The post-IAB components are specified as:

Reelection probability:

\[ P_i(\theta_i) = P_i^0 + \delta \cdot (\theta_i - \bar{\theta}) + \epsilon_i \cdot I_i(\theta_i) \tag{49.6}\]

where $P_i^0$ is baseline reelection probability, $\bar{\theta}$ is the median score, $\delta > 0$ captures the direct electoral effect of scorecard visibility, and $I_i(\theta_i)$ is the independent expenditure function (a step function with discrete rewards):

\[ I_i(\theta_i) = \begin{cases} +M & \text{if } \theta_i \geq \theta^{high} \\ 0 & \text{if } \theta^{med} \leq \theta_i < \theta^{high} \\ -M & \text{if } \theta_i < \theta^{med} \end{cases} \tag{49.7}\]

Post-office income:

\[ Y_i(\theta_i) = Y(\tau(\theta_i)) \tag{49.8}\]

where $\tau: \mathbb{R} \to \{1, 2, 3\}$ maps scores to income tiers:

\[ \tau(\theta_i) = \begin{cases} 1 & \text{if } \theta_i \geq 75 \quad (\text{Tier 1: \$500K+ annually}) \\ 2 & \text{if } 60 \leq \theta_i < 75 \quad (\text{Tier 2: \$200-400K annually}) \\ 3 & \text{if } \theta_i < 60 \quad (\text{Tier 3: \$150-300K annually}) \end{cases} \tag{49.9}\]

Legacy/status:

\[ S_i(\theta_i) = S_0 + \lambda \cdot \theta_i \tag{49.10}\]

where $S_0$ is baseline status and $\lambda > 0$ captures the marginal status gain from higher scores (measured by metrics such as Wikipedia article length, think tank fellowships, speaking invitations, historical assessments).

Before Incentive Alignment Bonds (IABs): Politicians maximize utility based on lobbying intensity. The NSV ranking exists but doesn’t affect their utility function, so they have no incentive to support high-NSV programs.

After Incentive Alignment Bonds (IABs): The same utility function becomes score-dependent: each component (electoral, career, legacy) now depends on the politician’s score, which is determined by their voting record on NSV-ranked programs. Supporting high-NSV programs becomes the rational, self-interested choice.

The transformation does not change what politicians optimize; it changes what optimizing points at. Same selfish utility maximization, radically different equilibrium outcome. This is the core mechanism design contribution: we align private incentives with public welfare not by appealing to altruism, but by redirecting self-interest. The diagrams above illustrate this transformation.

49.3.4 Numerical Calibration and Parameter Ranges

To evaluate whether the incentive compatibility condition can realistically be satisfied, we provide illustrative calibrations based on campaign finance research and career trajectories.

Base case parameters:

Table 49.4: Politician Heterogeneity in Utility Weights

Politician Type	$\alpha_i$ (Electoral Weight)	$\beta_i$ (Career Weight)	$\gamma_i$ (Legacy Weight)	$P_i^0$ (Baseline Prob.)
Marginal seat	0.6	0.3	0.1	0.50
Safe seat	0.2	0.5	0.3	0.85
Termed out	0.0	0.7	0.3	N/A

IAB mechanism parameters (illustrative):

Score threshold for high tier: $\theta^{high} = 80$, $\theta^{med} = 60$
Independent expenditure support: $M = \$5\text{M to }\$20\text{M}$ (competitive race)
Electoral impact: $\delta = 0.02$ to $0.05$ (2-5 percentage point swing from scorecard visibility)
Post-office income differential: $\Delta Y = \$200\text{K to }\$350\text{K annually}$ (present value $3M-$5M over 15-year career)
Legacy multiplier: $\lambda = 0.1$ (1 SD score increase → 10% increase in Wikipedia length, fellowships, etc.)

Concentrated opposition cost:

Moderate opposition: $c_i = \$2\text{M to }\$5\text{M}$ (attack ads, lost contributions, primary challenge risk)
Strong opposition: $c_i = \$10\text{M to }\$20\text{M}$ (defense/fossil fuel reallocation)

Incentive compatibility calculation (marginal seat politician):

Suppose a marginal-seat Senator (50% baseline reelection, $\alpha_i = 0.6$, $\beta_i = 0.3$, $\gamma_i = 0.1$) votes for a 1% military reallocation treaty:

\[ \Delta P_i = \delta \cdot \Delta\theta + \epsilon_i \cdot M = (0.03)(20) + (0.08 \text{ pp}/\$\text{M})(\$10\text{M}) = 0.6\text{ pp} + 0.8\text{ pp} = 1.4\text{ pp} \]

Note: εi is calibrated in percentage points per $1M, so εi·M yields percentage points.

\[ \Delta Y_i = \$300\text{K annually} \times \frac{1 - (1.05)^{-15}}{0.05} \approx \$300\text{K} \times 10.38 \approx \$3.11\text{M PV} \]

\[ \Delta S_i = \lambda \cdot \Delta\theta = 0.1 \times 20 = 2.0 \]

Utility gain (converting all terms to dollar-equivalents, with reelection probability valued at $50M lifetime Senate seat value and status units at $10M each):

\[ \alpha_i \Delta P_i + \beta_i \Delta Y_i + \gamma_i \Delta S_i \approx 0.6(\$50\text{M} \times 0.014) + 0.3(\$3.11\text{M}) + 0.1(\$10\text{M} \times 2.0) \]

\[ \approx \$0.42\text{M} + \$0.93\text{M} + \$2\text{M} \approx \$3.35\text{M} \]

If concentrated opposition cost is $c_i = \$5\text{M}$ (attack ads, lost defense PAC contributions), then:

\[ \Delta U_i = \$1.35\text{M} - \$5\text{M} = -\$3.65\text{M} < 0 \]

Mechanism fails with current calibration. To achieve incentive compatibility, IABs must increase either:

Independent expenditure support ($M$) from $10M to $20M+
Post-office income differential ($\Delta Y$) via additional tier benefits
Electoral impact ($\delta$) through more aggressive scorecard visibility campaigns

Revised calibration (mechanism succeeds):

If $M = \$20\text{M}$ and $\delta = 0.05$:

\[ \Delta P_i = 0.05(20) + 0.08(\$20\text{M}) = 1.0 + 1.6 = 2.6\% \]

\[ \Delta U_i = 0.6(0.026)(\text{value of 2.6pp reelection}) + 0.3(\$4.5\text{M}) + 0.1(2.0) \]

Translating reelection probability to dollars (value of Senate seat ≈ $50M lifetime value):

\[ \Delta U_i \approx 0.6(0.026 \times \$50\text{M}) + \$1.35\text{M} + 0.2 \approx \$0.78\text{M} + \$1.35\text{M} = \$2.13\text{M} \]

Still insufficient if $c_i = \$5\text{M}$. But if concentrated opposition is only $c_i = \$2\text{M}$ (lower-opposition domain like pandemic preparedness), mechanism succeeds:

\[ \Delta U_i = \$2.13\text{M} - \$2\text{M} = \$0.13\text{M} > 0 \quad \checkmark \]

The calibration shows:

Pandemic preparedness ($c_i = \$1\text{M-}\$3\text{M}$) is more tractable than defense reallocation ($c_i = \$10\text{M-}\$20\text{M}$)
Safe-seat politicians need larger $\beta_i$ (career) and $\gamma_i$ (legacy) incentives since $\alpha_i$ (electoral) is small
Termed-out politicians are most cost-effective: $\alpha_i = 0$ but $\beta_i = 0.7$ means post-office incentives dominate
High-opposition domains require $20M+ per pivotal vote; low-opposition domains require $5M-$10M

Equation 49.16 is achievable with realistic parameter values in carefully-selected domains.

49.3.5 The Policy Choice

Consider a binary policy choice $a_i \in \{0, 1\}$ where:

$a_i = 1$: Support a policy that funds public good $G$
$a_i = 0$: Oppose or abstain

Let $W(G)$ denote the social welfare gain from $G$. By assumption, $W(G) > 0$; the policy is welfare-improving. The question is whether $a_i = 1$ is incentive-compatible.

49.3.6 The Pre-IAB Equilibrium

Without IABs, the politician faces:

Benefits of $a_i = 1$:

Diffuse voter approval (small per-voter benefit, hard to attribute)
Abstract “doing the right thing” utility (assumed small)

Costs of $a_i = 1$:

Concentrated opposition from losers (weapons manufacturers, pharmaceutical incumbents)
Attack ads: “Senator voted to WEAKEN AMERICA”
Loss of campaign contributions from concentrated interests

Formally:

\[ \Delta U_i^{\text{pre-IAB}}(a_i = 1) = \epsilon - c_i \tag{49.11}\]

where $\epsilon$ is the small diffuse benefit and $c_i > 0$ is the net concentrated cost from losing incumbents’ support (campaign contributions foregone, attack ads received, post-office opportunities closed). Since $c_i > \epsilon$ for most policies with diffuse benefits, the equilibrium is $a_i^* = 0$. This is Olson’s result in formal terms.

49.3.7 The IAB Mechanism

The IAB mechanism introduces a Public Good Score $\theta_i$ for each politician, where:

\[ \theta_i = f(\text{VoteRecord}_i) \tag{49.12}\]

The score is based purely on voting record on policy class $\mathcal{P}$ (policies meeting specified criteria for the target public good). This is a design choice with important implications:

Measurability: Voting records are public, verifiable, and effectively ungameable
Attribution: Each politician’s vote is directly attributable
No oracle problem: No need for contested measurement of downstream outcomes; the mechanism relies on observable voting records

49.3.8 Score-Dependent Payoffs

The IAB mechanism makes each component of $U_i$ a function of $\theta_i$:

Reelection probability:

\[ P_i(\text{reelection}) = P_i^0 + \delta \cdot (\theta_i - \bar{\theta}) + \epsilon_i \cdot I_i(\theta_i) \tag{49.13}\]

where:

$P_i^0$ is baseline reelection probability
$\bar{\theta}$ is the median score
$\delta > 0$ is an empirical parameter capturing the direct electoral effect of scorecard visibility (media coverage, voter information)
$I_i(\theta_i)$ is independent expenditure support determined by a pre-announced, public rule, a step function:

where $M > 0$ represents campaign support magnitude.

Post-office income:

\[ E_i[\text{PostOfficeIncome}] = Y(\tau(\theta_i)) \tag{49.15}\]

where $\tau: \mathbb{R} \to \{1, 2, 3\}$ is a tier function and $Y(1) > Y(2) > Y(3)$ represents expected annual income by tier:

Table 49.5: Post-Office Income by Public Good Score Tier

Tier	Threshold	Expected Annual Income	Examples
1	$\theta_i \geq 75$	$500K+	WHO Advisory Board, Aspen Fellowships
2	$60 \leq \theta_i < 75$	$200-400K	Brookings, RAND, university chairs
3	$\theta_i < 60$	$150-300K	Defense contractor boards, lobbying firms

49.3.9 Incentive Compatibility

Proposition 1 (Sufficient Condition for Incentive Compatibility). Under assumptions A1–A5, if the score gain from supporting policy class $\mathcal{P}$ is $\Delta\theta > 0$, and

\[ \alpha_i \cdot \Delta P_i + \beta_i \cdot \Delta Y_i + \gamma_i \cdot \Delta S_i > c_i \tag{49.16}\]

then $a_i = 1$ is the unique best response for politician $i$.

Proof sketch: By A2, votes are observable and the scoring function is common knowledge, so the politician can compute $\theta_i' = \theta_i + \Delta\theta$ conditional on $a_i = 1$. By A3, the payoff functions are credibly committed, so the politician can compute $\Delta P_i$, $\Delta Y_i$, and $\Delta S_i$. By A1, the politician maximizes $U_i$. The change in utility from choosing $a_i = 1$ versus $a_i = 0$ is:

\[ \Delta U_i = \alpha_i \cdot \Delta P_i + \beta_i \cdot \Delta Y_i + \gamma_i \cdot \Delta S_i - c_i \]

When Equation 49.16 holds, $\Delta U_i > 0$, so $a_i = 1$ strictly dominates $a_i = 0$. See Appendix A for the complete proof. $\square$

Corollary 1. Under A4, there exists a funding level $\bar{F}$ such that for all $F > \bar{F}$, Equation 49.16 holds for all politicians with $c_i < \bar{c}$ for some threshold $\bar{c}(F)$ increasing in $F$.

This establishes that sufficiently funded IABs can overcome concentrated opposition up to a threshold that increases with funding.

49.3.10 Nash Equilibrium Analysis

Consider a legislature of $N$ politicians. Let $n = \sum_{i=1}^N a_i$ be the number supporting the policy.

Proposition 2 (Multiple Equilibria Without IABs). Under A1–A2 and A5, without the IAB mechanism, the game among $N$ politicians has at least two pure strategy Nash equilibria:

(i) The all-defect equilibrium $(a_1, \ldots, a_N) = (0, \ldots, 0)$

(ii) Potentially the all-cooperate equilibrium $(a_1, \ldots, a_N) = (1, \ldots, 1)$ if coordination is feasible

The all-defect equilibrium is risk-dominant when $c_i > \epsilon$ for all $i$.

Proof sketch: In the all-defect equilibrium, no politician benefits from unilateral deviation because the diffuse benefit $\epsilon$ is outweighed by the concentrated cost $c_i$. The all-cooperate equilibrium may exist if coordination reduces per-politician costs or if $\epsilon$ aggregates across politicians, but it is unstable to individual defection when concentrated interests can target defectors. See Appendix A. $\square$

Proposition 3 (Equilibrium Selection With IABs). Under A1–A5, if the IAB mechanism is funded such that Equation 49.16 holds for all $i$, then $(1, \ldots, 1)$ is the unique Nash equilibrium.

Proof sketch: When Equation 49.16 holds for each politician $i$, choosing $a_i = 1$ is a strictly dominant strategy regardless of other politicians’ choices. A profile of strictly dominant strategies constitutes the unique Nash equilibrium. $\square$

Remark. The “dominant strategy” characterization applies to the stylized binary choice taking the IAB mechanism as given. In richer settings with endogenous IAB design, strategic scoring manipulation, or multiple policy dimensions, additional equilibrium refinements apply. Section 5 discusses these extensions.

49.3.11 Illustrative Example: A Global Health Treaty

To ground the formal model in concrete terms, consider a hypothetical application. Suppose one’s public goods objective is to simultaneously reduce global conflict and reduce the global burden of disease. Global military expenditure currently exceeds $2.72T annually⁵¹, while the global burden of disease exceeds 2.88 billion DALYs/year³⁴. An international treaty in which signatory nations commit to redirecting 1% of military spending to a global pragmatic clinical trial system generates approximately $27.2B per year for pragmatic clinical trials, roughly tripling current global clinical trial funding, while creating modest but meaningful pressure toward demilitarization.

The IAB mechanism for this treaty would allocate treaty inflows as follows:

80% to the public good itself (pragmatic clinical trials)
10% to investor returns (perpetual payments to those who funded the campaign to pass the treaty)
10% to political incentives (funding the three-layer architecture)

This allocation structure creates aligned incentives across all participants. Investors who funded the initial campaign receive perpetual returns ($2.72B annually) as long as the treaty continues, giving them strong incentives to support treaty expansion and defend against repeal. The political incentive allocation ($2.72B annually) funds the three-layer architecture:

Scoring layer: Politicians receive Treaty Support Scores, the 1% Treaty-specific subtype of the broader Public Good Score, based on their voting record on treaty ratification, annual funding appropriations, and related legislation. A legislator who votes YES on the treaty and subsequent funding bills sees their score rise; one who votes NO sees their score fall.

Where the money goes when you take one penny from every dollar we spend on bombs: some helps people, some goes to investors, and some bribes politicians to keep helping people. It’s bribes all the way down, but upward.

Electoral layer: With $2.72B annually available, independent expenditure campaigns can credibly commit: “We will spend $50 million supporting high-scorers in competitive races.” At typical costs per competitive race, this funds meaningful independent campaigns in 20-30 races annually.

Post-office layer: Foundations funded by the political incentive allocation establish eligibility criteria: “The Global Health Leadership Fellowship ($300K/year, 5-year term) requires a career Treaty Support Score above 70.”

The self-funding nature matters. The treaty’s success generates the resources that sustain both investor returns and political incentives for its continuation and expansion. This creates multiple reinforcing feedback loops:

Investor pressure for expansion: Investors receiving 10% of $27.2B want the same share of double that (if the treaty expands to 2%), creating a constituency that lobbies for treaty growth
Political incentives for continuation: Politicians who supported the treaty benefit from ongoing electoral and career support, incentivizing them to defend it against repeal
Escalation dynamics: Each expansion (1% → 2% → 5%) increases both investor returns and political incentive funding, strengthening the coalition for further expansion

In other words, we’re creating a lobbying machine for public goods that gets stronger the more successful it becomes. This is the same dynamic that made weapons manufacturers powerful, except pointed at curing diseases instead of building bombs. Once the flywheel starts spinning, concentrated opposition faces an opponent that grows with every victory.

Consider the decision calculus for a hypothetical Senator Smith facing a vote on treaty ratification:

Table 49.6: Senator Smith’s Decision Calculus

Without IABs	With IABs
Defense contractors fund opponent if YES	Treaty Support Score rises 25 points
Attack ads: “Smith weakened our military”	Independent campaigns spend $2M supporting Smith
Benefits (cures) arrive in 10+ years	Post-office eligibility: Tier 3 → Tier 1
Diffuse beneficiaries cannot coordinate	Expected post-office income: $200K → $400K/yr

The IAB mechanism transforms the incentive landscape. The concentrated costs (weapons manufacturer opposition) remain, but they are now outweighed by concentrated benefits (score increases, electoral support, career advancement). Supporting the treaty becomes the utility-maximizing choice.

49.3.12 Calibration: Parameter Ranges for Incentive Compatibility

To assess whether IABs can achieve incentive compatibility, we calibrate the model using empirical estimates from campaign finance and lobbying research. Table 49.7 reports parameter ranges.

Table 49.7: Calibration Parameters for IAB Model

Parameter	Symbol	Empirical Range	Source
Defense contractor opposition spending	$c_i$	$0.5–5M per race	OpenSecrets 2020
Independent expenditure effect on vote share	$\epsilon_i$	0.5–2 pp per $1M	Spenkuch & Toniatti 2018
Value of 1 pp reelection probability	$\alpha_i$	$0.5–2M	Implied by campaign spending
Post-office income differential (Tier 1 vs 3)	$\Delta Y$	$150–300K/yr	Industry salary data
Discount rate for post-office income	$r$	5–10%	Standard
Career length post-office	$T$	10–20 years	Empirical average

Section 3.2 demonstrates that IAB funding levels in the billions can overcome concentrated opposition in the millions, consistent with the “lobbying alpha” asymmetry observed empirically.

49.4 How IABs Work in Practice

To implement score-dependent payoffs, we need mechanisms. This section specifies a three-layer architecture and analyzes its legality under U.S. law.

49.4.1 Layer A: Scoring (Data Provision)

An independent entity, structured as a 501(c)(3) research organization, maintains the Public Good Score system.

How we turn boring government records into politician report cards without the IRS getting angry. It’s like fantasy football, but for democracy, and tax-deductible.

Inputs:

Public voting records from official government sources
Bill classifications (does legislation meet criteria for policy class $\mathcal{P}$?)
Sponsorship and co-sponsorship records

Outputs:

Individual politician scores $\theta_i$
Historical score trajectories
Comparative rankings

Legal basis: 501(c)(3) organizations are permitted to conduct research and publish findings. Publishing voting records and scores based on those records is protected speech. The key constraint: 501(c)(3) organizations cannot “participate in, or intervene in any political campaign on behalf of (or in opposition to) any candidate for public office”¹⁷⁶.

The scoring layer does not violate this constraint because it: 1. Applies universal, pre-announced criteria 2. Does not endorse or oppose specific candidates 3. Reports data that is already public

49.4.2 Layer B: Electoral Support

Independent actors, structured as 501(c)(4) organizations, PACs, or Super PACs, commit to electoral support rules tied to scores.

How to help good politicians without technically coordinating, which would be illegal. Everyone just happens to read the same scoreboard and coincidentally makes the same decisions.

Mechanism:

Super PACs announce: “We will spend $X million on independent expenditures supporting candidates with Public Good Score ≥ 70 in competitive races”
This is a standing, public, ex-ante rule, not a deal with any specific candidate

Legal basis: Citizens United v. FEC (2010) held that independent expenditures are protected speech and cannot be limited¹⁷⁷. The Court defined corruption narrowly as “quid pro quo,” meaning an explicit exchange of money for official acts. Independent expenditures, not coordinated with candidates, cannot constitute quid pro quo corruption under this standard.

Justice Kennedy wrote that independent spending “does not give rise to corruption or the appearance of corruption” because it is “not prearranged and coordinated” with candidates¹⁷⁷. The IAB mechanism satisfies this requirement: support is determined by a public score, not by private arrangements.

49.4.3 Layer C: Post-Office Benefits

Private foundations, think tanks, and advisory boards establish eligibility criteria tied to scores.

The gate between being a senator and getting paid to give speeches. If your score is bad, the gate stays closed, and you have to get a real job.

Mechanism:

Foundations announce: “Eligibility for the Global Health Fellowship requires a career average Public Good Score ≥ 75”
Think tanks announce: “Advisory board positions are restricted to former officials from jurisdictions that achieved threshold improvements under their leadership”

Legal basis: Private organizations have broad discretion in setting employment and fellowship criteria. Setting criteria based on public, objective metrics is standard practice. The constraint: criteria must be announced in advance and apply universally, not targeted at specific individuals post hoc.

49.4.4 Why This Is Not Bribery

The legal analysis proceeds through three levels: statutory elements, constitutional protections, and established precedent.

49.4.4.1 Statutory Analysis: 18 U.S.C. § 201

Under 18 U.S.C. § 201, bribery requires:

A thing of value given to a public official
With intent to influence an official act
As a quid pro quo, a specific exchange¹⁷⁸

The IAB mechanism fails each element:

Element 1: No thing of value to officials.

Scores are information, not things of value. Publishing data about voting records is protected speech.
Electoral support goes to campaigns, not officials personally. Independent expenditures benefit candidates electorally but are not personal enrichment.
Post-office opportunities are future employment contingent on (a) leaving office and (b) meeting publicly-announced, universally-applied criteria. Future employment prospects are not “things of value” under bribery law. Otherwise, any industry that hires former regulators would be guilty of bribery.

The difference between a bribe and our system. A bribe is ‘do this, get money.’ Our system is ‘do good things consistently for years, and maybe you’ll get opportunities later.’ Turns out delayed gratification is legal.

Element 2: No specific intent to influence.

Rules are universal and ex-ante. No one tells any official “vote for X and receive Y.” The rule is: “Any official who supports this class of policies will score higher.” This is categorically different from “I will give you money if you vote yes on H.R. 1234.”

The distinction matters legally. In United States v. Sun-Diamond Growers¹⁷⁹, the Supreme Court held that illegal gratuities require a link to a “specific official act,” not merely a general desire to curry favor. IABs create no such link; they reward policy classes, not specific votes.

Element 3: No quid pro quo.

No exchange occurs with any official. Officials are not party to any agreement. They merely observe standing rules and act in their self-interest. The Supreme Court in McCutcheon v. FEC¹⁸⁰ held that “ingratiation and access… are not corruption” and that only “quid pro quo corruption” justifies regulation of political speech.

McDonnell v. United States (2016) further narrowed the definition of “official act,” requiring a formal exercise of governmental power on a specific matter¹⁸¹. The IAB mechanism does not pay for specific official acts; it creates a scoring system that independent actors may choose to use.

49.4.4.2 Constitutional Protections

The IAB architecture is protected by the First Amendment at multiple levels:

Scoring layer: Publishing voting records and scores based on those records is core political speech. The government cannot prohibit citizens from evaluating and publicizing legislators’ voting records.

How everything we’re doing is protected by free speech. Scoring politicians is speech. Campaign ads are speech. Hiring someone for a board position is apparently also speech. America is very particular about this.

Electoral layer: Citizens United held that independent expenditures are protected speech. The government cannot limit spending by independent actors to support or oppose candidates based on their policy positions.
Post-office layer: Private organizations have First Amendment associational rights to set their own membership and employment criteria. A foundation requiring fellows to have supported certain policies is no different from a think tank preferring scholars who share its intellectual orientation.

49.4.4.3 Established Precedent: Decades of Legal Scorecard Operations

The most powerful evidence that IABs are legal is that their core components have operated openly for decades without prosecution:

Scoring systems:

The League of Conservation Voters has published its National Environmental Scorecard since 1970, for 54 years rating legislators on environmental votes
The NRA grades legislators A through F on gun rights votes and publicizes the ratings
The Chamber of Commerce, AFL-CIO, ACLU, and dozens of other organizations publish voting scorecards

Electoral support tied to scores:

The NRA explicitly endorses candidates based on their grades and spends millions on independent expenditures supporting high-scorers
The LCV endorses based on scorecard performance
Labor unions support candidates with pro-labor voting records

Post-office benefits tied to policy positions:

Defense contractors hire former Pentagon officials who supported procurement programs
Pharmaceutical companies hire former FDA officials who approved their drugs
Think tanks hire former legislators who championed their policy priorities

None of these activities have been prosecuted as bribery. The IAB architecture merely systematizes what already happens ad hoc, making the rules transparent, universal, and tied to measurable public goods rather than narrow interests.

All the things people already do to influence politics, which are legal. We’re just doing them on purpose and at the same time, which is still legal, but more efficient.

49.4.4.4 The Key Legal Distinction

Bribery corrupts official judgment by introducing private benefit that conflicts with public duty. IABs align private benefit with public duty, rewarding officials for doing their job well as measured by policy outcomes. This is the opposite of corruption.

Bribery: do bad thing, get money. Our system: do good thing, maybe get money later. The difference is we put the carrot and the cart on the same side of the horse.

The legal architecture ensures this alignment holds:

No money flows to officials while in office
Rules apply universally to all officials ex ante
Criteria are based on public records, not private arrangements
Benefits come from independent actors, not parties to any agreement with officials

49.4.5 Legal Entity Separation

Table 49.8: Legal Entity Separation in the IAB Architecture

Layer	Entity Type	Permitted Activities	Prohibited Activities
Scoring	501(c)(3)	Research, publish scores	Campaign intervention
Electoral	501(c)(4), PAC, Super PAC	Independent expenditures	Coordination with candidates
Post-office	Private foundations	Set eligibility criteria	Condition grants on specific votes

49.4.6 Funding Sources and Foundation Investment

IABs can attract capital from multiple sources with different legal constraints.

Commercial investors (impact funds, family offices, institutional capital) face no restrictions on which layers they fund. If the bond offers market-rate or above-market returns, commercial capital can fund all activities, including the electoral layer.

Private foundations seeking to invest via Program-Related Investments (PRIs) face an additional constraint. IRS regulations require that PRIs not be used “directly or indirectly to lobby or for political purposes”¹⁷⁶. This means:

Layer	Foundation PRI Eligible?	Notes
Scoring	Yes	Pure research/data
Electoral	No	Explicitly political
Post-office	Yes	Employment criteria

This constraint is less significant than it appears. In a unified bond offering, the allocation happens after policy success. Investors receive returns from policy revenue, which is then allocated across uses. Foundations investing via PRI could have their returns earmarked for non-electoral uses.

Precedent: The Rockefeller Foundation invested in the Peterborough Social Impact Bond via PRI. The Kresge Foundation and Living Cities provided junior tranches in Massachusetts Pay for Success projects. Bloomberg Philanthropies guaranteed Goldman Sachs’ investment in the Rikers Island SIB. Foundation participation in outcome-based bonds is established practice.

Practical implication: For IABs offering strong commercial returns, foundation PRIs are a supplementary funding source, not a necessity. The electoral layer, the one foundations cannot fund, can be capitalized by return-seeking investors.

49.5 What Could Go Wrong

49.5.1 Gaming and Metric Corruption

How politicians cheat on their report cards by naming bills the opposite of what they do, and how we catch them by grading on multiple subjects. You can fake your math score, but math plus history plus science is harder.

Any metric can be gamed. Goodhart’s Law states: “When a measure becomes a target, it ceases to be a good measure”¹⁸². Potential gaming strategies:

Cheap talk: Politicians vote symbolically for popular positions but undermine implementation
Bill stuffing: Attach poison pills to supported legislation
Strategic timing: Time votes when outcomes are predetermined

Countermeasures:

Score multiple dimensions (votes, sponsorship, floor statements, implementation oversight)
Weight by vote significance (close votes count more)
Track long-term outcomes as validation (though not as scoring basis)

49.5.2 Plutocracy Objection and the “Lobbying With Extra Steps” Critique

The most serious criticism economists are likely to raise: “This is just lobbying with extra steps. You’re creating a well-funded interest group to lobby politicians for your preferred policies.”

This criticism deserves a careful response, as it goes to the heart of whether IABs represent genuine institutional innovation or merely repackage existing capture dynamics.

What makes IABs structurally different from corporate lobbying:

Comparative welfare criterion: IABs fund reallocation from $NSV_{source} < NSV_{target}$ programs. Corporate lobbying seeks absolute budget increases for the lobbying firm’s industry, regardless of comparative value. Defense contractors lobby for more military spending without specifying what gets cut. IABs specify both the source (lower-NSV) and target (higher-NSV), creating a welfare-improving constraint.
Public good vs. private good alignment: Corporate lobbying aligns politician incentives with excludable private benefits (military contracts flow to specific firms). IAB-supported policies produce non-excludable public goods (cures, climate stability). Investors cannot capture the primary benefits. They accrue to the general public. Investors capture only a fraction of the funding flow, not the end-state benefit.
Transparent, universal, ex-ante rules: Corporate lobbying operates through opaque relationships (revolving door promises, implicit quid pro quos, insider access). IABs publish scoring criteria ex-ante, apply them universally to all politicians regardless of relationship, and make scores publicly available. Any politician can improve their score through observable actions.
Diffuse vs. concentrated funders: Corporate lobbying concentrates returns to a small number of firms. IABs, if structured as retail-accessible securities, allow millions of diffuse beneficiaries to invest small amounts. A $1,000 IAB investment makes a retiree a “special interest” in pragmatic clinical trials, structurally impossible with current lobbying.
Metric validation: Corporate lobbying success is measured by dollars flowing to the lobbying firm. IAB success is measured by rigorous external benefit-cost analyses (Copenhagen Consensus, GiveWell, academic literature). The scoring organizations are independent 501(c)(3) entities, not the investors themselves.

However, the objection retains force: IABs do not democratize power; they redirect it. Whose conception of “public good” defines the NSV ranking? What prevents IAB funders from capturing the scoring process? What prevents redirected resources from being recaptured by new concentrated interests?

The structural answer: The four-layer governance stack (Section 6) addresses these concerns. Layer 0 (Wishocracy¹⁸³ for Domain Ranking) democratizes which domains receive funding via citizen pairwise comparisons aggregated with expert BCR data. Layer 2 (Wishocracy for Within-Domain Allocation) democratizes allocation within approved domains. Random pairwise sampling makes advertising economically infeasible (~0.1% appearance probability per campaign → $200M cost to shift rankings → cheaper to just do the research). IABs (Layer 1) solve only the adoption problem: getting politicians to vote for reallocation. Democratic legitimacy is addressed at Layers 0 and 2, not Layer 1.

49.5.3 Unintended Consequences

Political systems are complex. Possible unintended consequences:

Crowding out intrinsic motivation: If politicians come to see policy support as instrumental, they may become more transactional overall
Metric fixation: Excessive focus on scored policies at the expense of unscored but important issues
Legitimacy erosion: Public perception that politicians are “bought” (even legally) may reduce trust

These concerns warrant monitoring, but must be weighed against the status quo: 55 million deaths/year from diseases that faster research could address, while $2.72T flows to military spending with 0.6x ROI. The unintended consequences of inaction, continued optimization of government spending for lobbying intensity rather than human welfare, dwarf any plausible risk from making pro-health votes more rewarding. Politicians are already transactional; IABs redirect that transactionality toward public goods.

49.6 Where IABs Fit in Democratic Reform

49.6.1 The Four-Layer Governance Stack

IABs address one specific failure mode: how to get welfare-improving policies adopted when concentrated interests oppose them. They fit within a broader governance stack:

Layer 0 (Domain Ranking): Expert organizations (Copenhagen Consensus, GiveWell, IMF) provide benefit-cost data; citizens aggregate via pairwise comparisons to produce democratic domain rankings with capture-resistant legitimacy.
Layer 1 (IABs): Insert rankings into politician utility functions via score-dependent electoral support and career benefits. This is the binding constraint and the focus of this paper.
Layer 2 (Within-Domain Allocation): Once resources are redirected, mechanisms like aggregated pairwise preference allocation¹⁸⁴ prevent capture by new concentrated interests.
Layer 3 (Project Selection): Domain-specific marketplaces (prediction markets, prize markets, retroactive public goods funding) allocate to specific projects.

The four layers of fixing government. IABs are layer one because you can’t build fancy democracy upgrades if the politicians are still bought by weapons companies.

Layer 0 rankings exist but are ignored because they don’t appear in politician utility functions. Layers 2-3 cannot function until Layer 1 creates the political conditions for their adoption.

Common mistake: Advocates focus on Layers 2 or 3 (better voting systems, prediction markets, AI allocation) without recognizing that Layer 1 is the bottleneck. You cannot implement better allocation mechanisms if politicians won’t vote to fund them in the first place. IABs solve the meta-problem: how to bootstrap from the current Olsonian equilibrium to one where better governance mechanisms can be adopted.

49.6.2 Comparison to Alternative Governance Mechanisms

Table 49.9 compares IABs to alternative governance reform approaches. Comparison criteria: feasibility assessments, implementation timelines, capital requirements, and structural barriers. The analysis draws on historical precedents for institutional reform, capital requirements relative to available funding sources, political economy barriers, and adoption rates of analogous mechanisms.

Table 49.9: Comparative Feasibility Assessment of Governance Reform Mechanisms

Approach	Feasibility Assessment	Time Horizon	Capital Required	Key Barrier	What It Solves
IABs	Moderately challenging	Medium-term (10-20 years)	$200M-$500M initial	Bootstrap funding	Adoption of welfare-improving policies
Wishocracy (post-IAB)	Moderate (conditional on IABs)*	Medium-term (5-10 years)	$50M-$200M	Requires treaty first	Post-adoption allocation
Futarchy (prediction markets)	Very challenging	Long-term (15-25 years)	$100M-$500M	Manipulation, adoption	Policy → outcome mapping
Quadratic Voting/Funding	Very challenging	Long-term (10-20 years)	$50M-$200M	Constitutional barriers	Preference intensity
Optimocracy (algorithmic governance)	Moderate (private); Challenging (gov’t)	Near-term (1-2 years private); Medium-term (5-15 years gov’t)	$10M-$100M (private DAO); $500M+ (gov’t adoption)	Goodhart’s Law, oracle capture	Removes political discretion for routine allocation
Charter Cities	Very challenging	Very long-term (20-40 years)	$1B+	Sovereignty, scale	Competitive governance
NSV Ranking Alone	Infeasible	N/A	$10M-$50M	No incentive linkage	Information (ignored)

*Wishocracy becomes feasible only after IABs create political conditions for resource reallocation; otherwise faces same adoption barriers as IABs.

Other governance mechanisms:

Algorithmic governance (Optimocracy) faces capture at the design level: whoever controls the algorithm specification controls outcomes. However, this can be mitigated through constitutional-level metric selection (via Wishocracy), decentralized oracles, and smart contract enforcement. See the Optimocracy paper¹⁸⁵ for detailed mechanism design addressing these challenges.
Futarchy (prediction markets for policy) is intellectually elegant but faces adoption barriers. Who decides the outcome metrics? How do you prevent market manipulation? IABs could bootstrap futarchy by making politicians willing to adopt prediction-market-based governance.
Charter cities / competitive governance avoid the adoption problem (exit rather than voice) but face scale and sovereignty constraints.
NSV rankings alone are infeasible because they lack incentive linkage. The empirical fact motivating this entire paper.

A parallel + sequenced implementation strategy:

Immediate (0-2 years): Deploy private Optimocracy DAO for philanthropic/investment capital allocation; no government permission required. Simultaneously begin IAB development.
Near-term (2-10 years): IABs for high-value domains (health, climate, pandemic preparedness). Private Optimocracy scales and demonstrates superior outcomes.
Medium-term (10-20 years): Use IAB political capital + Optimocracy track record to pass government pilots for Wishocracy and Optimocracy.
Long-term (20+ years): Hybrid Wishocracy-Optimocracy architecture becomes standard for capture-resistant governance.

Optimocracy and IABs can develop in parallel. Private Optimocracy doesn’t require government adoption, so it can demonstrate proof-of-concept while IABs work on the political adoption problem.

49.6.3 What IABs Do Not Solve

IABs solve the adoption problem (the binding constraint) but not the complete resource allocation problem. The four-layer stack (Section 6.1) addresses domain ranking, within-domain allocation, and project selection through complementary mechanisms.

The four-layer governance stack. IABs fix the ‘politicians don’t want to’ problem. They don’t fix the ‘laws won’t let us’ problem. One thing at a time.

Problems that remain genuinely unsolved:

Crowding out intrinsic political motivation: IABs may make politicians more transactional (empirical question requiring evaluation)
Constitutional/legal barriers: Some jurisdictions may prohibit IAB mechanisms via campaign finance or securities regulation
Transition risk: Bootstrap phase (12-24 months before proof-of-concept) vulnerable to regulatory counter-attack
Value pluralism vs. utilitarian efficiency: Even with Wishocracy at Layer 0 allowing citizens to weight domains by their values, some citizens may reject the entire framework of cost-effectiveness analysis in favor of deontological or rights-based approaches

What IABs do solve: The adoption problem. They make it individually rational for politicians to support welfare-improving policies despite concentrated opposition. This is the binding constraint in the governance stack. Without solving adoption, better allocation mechanisms (Layers 2-3) cannot be implemented. IABs are needed but not enough for optimal resource allocation.

49.7 Beyond Health: Climate, Nuclear Risk, and More

The IAB architecture is not specific to health policy. It applies to any global coordination problem satisfying three conditions:

Measurable outcomes: There exists a metric politicians can be scored on
Political control: Politicians’ actions (votes, treaties, budget allocations) affect outcomes
Diffuse benefits, concentrated costs: The Olsonian collective action failure applies

These conditions identify domains where the mechanism design approach is applicable. The formal requirements (A1–A5) must be satisfied, with domain-specific adaptations to the scoring function $f$ and payoff calibration.

The three things you need for IABs to work: you can measure if it worked, politicians can actually do it, and the benefits are spread out while the costs are concentrated. Like climate change, but we’re trying to fix it instead of cause it.

49.7.1 The General Template

Any global public good satisfying the above conditions can be “IAB-ified” using the structure in Table 49.10.

Table 49.10: General IAB Template for Global Public Goods

Component	Function	Legal Form
Metric	Measures politician-controlled outcomes	Defined by 501(c)(3) research org
Score	Translates actions into public number	Published by independent body
Electoral layer	Rewards high-scorers with campaign support	501(c)(4), PAC, Super PAC
Post-office layer	Reserves prestige positions for high-scorers	Foundations, think tanks

49.7.2 Candidate Domains

We briefly survey three domains where IABs are applicable; Appendix B provides detailed specifications.

Why climate, nukes, and pandemics all have the same problem: fixing them hurts a few people a lot (weapons makers, oil companies) but helps everyone a tiny bit. Humanity is very bad at this type of math.

Climate change. Verified emissions reductions (UNFCCC reporting) provide a measurable metric. Politicians can be scored on climate legislation votes, treaty ratification, and budget allocations. The concentrated-diffuse asymmetry is stark: fossil fuel producers face concentrated losses while climate benefits are globally diffuse.

Nuclear disarmament. Verified warhead reductions under START-type treaties provide objective metrics. The scoring function would weight votes on arms control treaties, military authorization amendments, and non-proliferation funding. Defense contractor opposition creates concentrated costs; security benefits are diffuse.

Pandemic preparedness. WHO Joint External Evaluation scores and pandemic preparedness funding levels are measurable. Health security appropriations votes provide a scoring basis. Pharmaceutical incumbent opposition and budget competition create concentrated resistance; pandemic prevention benefits the global population.

Each domain requires calibration of the opposition cost $c_i$ and the IAB funding levels needed to satisfy Equation 49.16. The structural requirements remain constant across applications.

49.7.3 Welfare Accounting of the IAB Mechanism

The paper demonstrates that IABs redirect resources from low-NSV to high-NSV programs, but economists will correctly ask: what is the net welfare impact accounting for the mechanism’s own costs?

Mechanism costs (annual, steady-state):

Component	Estimated Annual Cost	Purpose
Scoring organizations	$10M-$50M	Research, data, scoring methodology
Independent expenditure campaigns	$100M-$500M	Electoral support for high-scorers
Post-office foundations	$50M-$200M	Fellowships, advisory positions
Total mechanism overhead	$160M-$750M/year	Ongoing operation

Benefits (illustrative, 1% military reallocation treaty):

Benefit Category	Estimated Annual Value	Source
Peace dividend (reduced conflict costs)	$114B	1% × $11.4T global war costs
Pragmatic clinical trials acceleration	$27.2B reallocated × 4.75 BCR	$58.6B
Total annual benefits	$172B	Conservative estimate

Net welfare calculation:

Net Societal Value = Benefits - Costs = $172B - $750M ≈ $172B/year (costs are <1% of benefits).

Benefit-cost ratio of the IAB mechanism itself:

\[ \begin{gathered} BCR_{IAB} \\ = \frac{Benefit_{peace+RD}}{Cost_{IAB,ann}} \\ = \frac{\$172B}{\$750M} \\ = 230 \end{gathered} \]
where:
\[ \begin{gathered} Benefit_{peace+RD} \\ = Benefit_{peace,soc} + Benefit_{RD,ann} \\ = \$114B + \$58.6B \\ = \$172B \end{gathered} \]
where:
\[ \begin{gathered} Benefit_{peace,soc} \\ = Cost_{war,total} \times Reduce_{treaty} \\ = \$11.4T \times 1\% \\ = \$114B \end{gathered} \]
where:
\[ \begin{gathered} Cost_{war,total} \\ = Cost_{war,direct} + Cost_{war,indirect} \\ = \$7.66T + \$3.7T \\ = \$11.4T \end{gathered} \]
where:
\[ \begin{gathered} Cost_{war,direct} \\ = Loss_{life,conflict} + Damage_{infra,total} \\ + Disruption_{trade} + Spending_{mil} \\ = \$2.45T + \$1.88T + \$616B + \$2.72T \\ = \$7.66T \end{gathered} \]
where:
\[ \begin{gathered} Loss_{life,conflict} \\ = Cost_{combat,human} + Cost_{state,human} \\ + Cost_{terror,human} \\ = \$2.34T + \$27B + \$83B \\ = \$2.45T \end{gathered} \]
where:
\[ \begin{gathered} Cost_{combat,human} \\ = Deaths_{combat} \times VSL \\ = 234{,}000 \times \$10M \\ = \$2.34T \end{gathered} \]
where:
\[ \begin{gathered} Cost_{state,human} \\ = Deaths_{state} \times VSL \\ = 2{,}700 \times \$10M \\ = \$27B \end{gathered} \]
where:
\[ \begin{gathered} Cost_{terror,human} \\ = Deaths_{terror} \times VSL \\ = 8{,}300 \times \$10M \\ = \$83B \end{gathered} \]
where:
\[ \begin{gathered} Damage_{infra,total} \\ = Damage_{comms} + Damage_{edu} + Damage_{energy} \\ + Damage_{health} + Damage_{transport} + Damage_{water} \\ = \$298B + \$234B + \$422B + \$166B + \$487B + \$268B \\ = \$1.88T \end{gathered} \]
where:
\[ \begin{gathered} Disruption_{trade} \\ = Disruption_{currency} + Disruption_{energy} \\ + Disruption_{shipping} + Disruption_{supply} \\ = \$57.4B + \$125B + \$247B + \$187B \\ = \$616B \end{gathered} \]
where:
\[ \begin{gathered} Cost_{war,indirect} \\ = Damage_{env} + Loss_{growth,mil} + Loss_{capital,conflict} \\ + Cost_{psych} + Cost_{refugee} + Cost_{vet} \\ = \$100B + \$2.72T + \$300B + \$232B + \$150B + \$200B \\ = \$3.7T \end{gathered} \]
where:
\[ \begin{gathered} Benefit_{RD,ann} \\ = Spending_{trials} \times Reduce_{pct} \\ = \$60B \times 97.7\% \\ = \$58.6B \end{gathered} \]
where:
\[ \begin{gathered} Reduce_{pct} \\ = 1 - \frac{Cost_{pragmatic,pt}}{Cost_{P3,pt}} \\ = 1 - \frac{\$929}{\$41K} \\ = 97.7\% \end{gathered} \]

Even using the high-end cost estimate ($750M) and conservative benefits (ignoring climate, pandemic preparedness, other applications), the mechanism’s BCR exceeds 230. The overhead cost is <1% of benefits, comparable to the expense ratio of efficient index funds (0.03-0.3%).

Sensitivity to failure risk:

If the mechanism has only a 10% chance of achieving treaty passage, expected BCR falls to ~23:1, still dramatically positive. If success probability is 50%, expected BCR is ~115:1. The mechanism justifies its costs across a wide range of success probabilities.

Comparison to alternative governance reforms:

Reform Mechanism	Estimated Annual Cost	Estimated Benefits	BCR
IABs (this paper)	$750M	$172B	230
Layer 0 only (Wishocracy domain ranking without Layer 1)	$10M-$50M	~$0 (ignored by politicians)	0:1
Futarchy infrastructure	$500M-$1B	Uncertain	Unknown
Charter cities	$1B+	Limited scale	1:1 to 5:1

IABs’ welfare accounting is favorable precisely because they solve the adoption problem. Better domain prioritization (Layer 0 Wishocracy) costs little but achieves nothing if politicians ignore the rankings. Better allocation mechanisms (futarchy, Layer 2 Wishocracy) are valuable only if adopted, which requires Layer 1 (IABs) first. The mechanism’s overhead is justified by making all other governance improvements politically feasible.

Risks to welfare accounting:

Crowding out intrinsic motivation: If IABs make politicians more transactional, could reduce welfare from unscored policies
Capture of scoring process: Layer 0 (Wishocracy for Domain Ranking) mitigates this by requiring capture of ALL expert organizations AND manipulation of millions of citizen preferences
Regulatory backlash costs: Legal battles and reputation damage if mechanism is perceived as illegitimate

Even accounting for these risks, the net welfare impact remains strongly positive (BCR > 200:1).

49.7.3.1 Sensitivity Analysis of Mechanism BCR

The benefit-cost ratio calculation above uses point estimates. The following Monte Carlo analysis propagates uncertainty through all input parameters to show the full distribution of possible outcomes.

Monte Carlo Distribution: IAB Mechanism Benefit-Cost Ratio (10,000 simulations)

Simulation Results Summary: IAB Mechanism Benefit-Cost Ratio

Statistic	Value
Baseline (deterministic)	230:1
Mean (expected value)	229:1
Median (50th percentile)	227:1
Standard Deviation	29.6:1
90% Range (5th-95th percentile)	[186:1, 284:1]

The histogram shows the distribution of IAB Mechanism Benefit-Cost Ratio across 10,000 Monte Carlo simulations. The CDF (right) shows the probability of the outcome exceeding any given value, which is useful for risk assessment.

The Monte Carlo results confirm that the mechanism’s BCR remains strongly positive across the full range of parameter uncertainty. Even at the 5th percentile (worst-case), the BCR exceeds 186:1, indicating robust welfare gains regardless of which parameter values materialize.

49.8 Conclusion

Incentive Alignment Bonds represent a new application of mechanism design to democratic governance. By making support for public-good policies incentive-compatible for utility-maximizing politicians, IABs address the collective action failure identified by Olson: concentrated interests systematically defeating diffuse interests in political competition.

The contribution is sixfold:

Theoretical: We formalize political incentive alignment as a mechanism design problem, provide explicit functional forms for politician utility components, and prove conditions for incentive compatibility.
Empirical: We provide numerical calibration demonstrating that the incentive compatibility condition is achievable with realistic parameters in selected domains (pandemic preparedness, health research) while showing mechanism failure in high-opposition domains (defense reallocation) absent enough funding.
Instrumental: We define IABs through three primitive properties: investor alignment, politician alignment, and funding from lower-value sources. Together, these create a self-sustaining mechanism for public good production that restores alignment between politician incentives and general welfare.
Practical: We specify a three-layer architecture (scoring, electoral, post-office) that achieves alignment without violating anti-bribery law, and demonstrate that the bootstrap problem is solvable due to ROI economics and capital asymmetry.
Welfare-Economic: We provide a comparative criterion ($NSV_{source} < NSV_{target}$) for identifying appropriate funding sources, implying a natural ranking of expenditures by marginal social value. We demonstrate why specified reallocation, rather than budget addition, is needed to achieve real resource shifts under soft budget constraints. Welfare accounting shows the mechanism itself has a BCR of 230, justifying overhead costs across a wide range of success probabilities.
Bootstrap Coordination: We adapt dominant assurance contracts¹⁶⁴ to solve the investor coordination problem that precedes IAB deployment. We prove that participation is the strictly dominant strategy for all potential investors (Proposition 4), completing the end-to-end incentive chain from citizen coordination through treaty passage.

Important limitations remain. Gaming and metric corruption require ongoing institutional vigilance. The plutocracy objection, that wealthy funders determine priorities, is addressed structurally by Wishocracy (Layer 2), which democratizes allocation decisions via aggregated citizen preferences and prevents advertising-based capture through random pairwise sampling. The capital asymmetry ($454T household wealth vs. $5T concentrated interests) combined with retail-accessible securities ensures that funding itself becomes democratized. Unintended consequences on political culture (e.g., crowding out intrinsic motivation) remain empirical questions requiring pilot evaluation. These considerations counsel for careful pilot implementation with rigorous evaluation before scaling.

49.8.1 The Bootstrap Problem and Regulatory Resistance

The biggest challenge is political: concentrated interests threatened by IABs will attempt to regulate them out of existence before they can demonstrate effectiveness.

If IABs successfully redirect even 1% of military spending ($27.2B globally), weapons manufacturers will face real losses. They will deploy their existing lobbying infrastructure to ban, restrict, or capture the mechanism. Potential regulatory attacks include:

Campaign finance regulation: Classify IAB-funded independent expenditures as illegal coordination
Securities regulation: Prohibit retail investment in “political outcome bonds”
Tax law changes: Eliminate tax-exempt status for scoring organizations
Capture attempts: Lobby to control the scoring methodology or install friendly board members

The bootstrap paradox: IABs need enough scale to create political incentives strong enough to resist regulatory capture, but concentrated interests will attempt to kill the mechanism before it reaches that scale. It’s the classic Catch-22: you need to be big enough to win, but your enemies will try to kill you while you’re small.

Potential solutions:

First-mover advantage in permissive jurisdictions: Pilot in countries with strong free speech protections and established independent expenditure precedent (U.S., UK)
Rapid scaling: Achieve critical mass ($200M-$2B deployed) within 18-24 months, before regulatory counter-mobilization
Constitutional protection: Establish that IAB mechanisms fall under protected political speech (U.S. First Amendment, European Convention on Human Rights Article 10)
Diverse funding sources: Avoid dependence on any single capital source that could be regulated
International treaty protection: Once a treaty is adopted, signatories have incentive to protect the mechanism that secured their score-improvement

The mechanism’s survival likely depends on achieving proof-of-concept success (one treaty ratified) before incumbent industries can coordinate effective regulatory opposition. This creates a premium on execution speed and strategic sequencing of target domains.

Why the Initial Fundraising Challenge is Solvable: Capital Asymmetry and ROI

Raising the first $200M-$500M (Phase 1 of the $1B campaign) before concentrated interests mobilize counter-lobbying appears daunting until we consider two factors: (1) the massive ROI potential and (2) the capital asymmetry favoring diffuse beneficiaries.

ROI makes initial funding rational for risk-tolerant capital:

As shown in Section 2.1, the expected ROI economics make early investment rational: conditional annual ROI of 272% upon treaty passage, with perpetual revenue streams. Even with high risk and long timelines, the asymmetric upside makes initial funding economically rational, not philanthropic. This changes the bootstrap calculus: early investors are not donors making grants; they are rational actors making high-risk, high-return investments.

Capital asymmetry ensures scalability beyond Phase 1:

Phase 1 requires $200M-$500M to demonstrate traction, which is small relative to the aggregate capital available to diffuse beneficiaries:

Concentrated opposition (weapons manufacturers, fossil fuel companies): $5T market cap, spending $100M-$1B/year on lobbying
Diffuse beneficiaries (everyone who benefits from cures, climate stability): $454T household wealth (Section 2.3)

The 90:1 capital advantage means that even if concentrated interests attempt counter-lobbying, they face a resource constraint. If weapons manufacturers allocate $500M to kill IABs, diffuse beneficiaries can deploy $5B in response, and still represent only 0.001% of available household wealth. The political change ROI (100-10,000x) that weapons manufacturers exploit becomes accessible to millions of retail investors.

Empirical precedent: Cryptocurrencies raised $30B+ in ICOs (2017-2018) with far weaker value propositions than 272% conditional ROI backed by lobbying economics. Green bonds reached $500B outstanding by 2023. If IABs can be structured as retail-accessible securities, the capital mobilization problem is not “can we raise $1B?” but “can we structure the offering legally?”

The race condition: Concentrated interests can mobilize regulatory opposition within 12-24 months of IAB visibility. But if: 1. A credible anchor investor publicly underwrites the Phase 1 assurance contract and initial bonus pool 2. Phase 1 ($200M-$500M) is then filled by high-risk capital (impact funds, crypto whales, patient billionaires) 3. Rapid deployment achieves measurable traction (one scoring cycle, measurable electoral impact) 4. Momentum builds (even partial progress increases bond value through demonstrated efficacy) 5. Retail offering opens to millions of diffuse beneficiaries for the remaining campaign funding

…then the mechanism reaches escape velocity before regulatory capture becomes feasible. Defense contractors cannot outspend $50B+ in mobilized retail capital without bankrupting themselves.

Conclusion: The initial fundraising challenge is solvable because (a) ROI economics make early investment rational for risk-tolerant capital, and (b) capital asymmetry ensures that once traction is demonstrated, scaling capital to the full $1B exceeds any plausible counter-lobbying budget. The binding constraint is execution speed, not capital availability.

49.8.2 Dominant Assurance Contract for Investor Coordination

The preceding analysis establishes that early investment in IABs is rational for risk-tolerant capital. But this leaves the coordination problem unsolved: each potential investor benefits from IABs being funded regardless of whether they personally contribute. This is the classic free-rider problem applied to public goods provision. We now formalize a mechanism that makes participation the strictly dominant strategy for all potential investors, not merely risk-tolerant ones.

Tabarrok¹⁶⁴ introduced dominant assurance contracts as a solution to public goods provision problems. We adapt his framework to the IAB bootstrap context.

49.8.2.1 Setup

Consider $M$ potential investors indexed by $j \in \{1, \ldots, M\}$. Each investor chooses a pledge amount $x_j \geq 0$. A contract entrepreneur (the nonprofit organizing the campaign) specifies:

A funding threshold $\bar{X}$ (the minimum capital required to launch the IAB mechanism)
A bonus schedule $\delta_j > 0$ paid to each participant if the threshold is not met

The contract entrepreneur operates the vehicle. A separate anchor investor can fund the bonus pool and make the first public commitment. The bootstrap trigger is credible underwriting, not personally building the institution.

We maintain one additional assumption:

A6 (Rational Investors). Each investor $j$ is a rational agent maximizing expected utility $V_j$ over financial outcomes.

49.8.2.2 The Investor’s Utility Function

Let $p$ denote the probability that the treaty passes conditional on the IAB mechanism being funded, and let $R > 1$ denote the conditional return multiplier (incorporating the 272% annual ROI established in Section 2.2). The expected return conditional on funding is $E[r] = p \cdot R + (1-p) \cdot 0 = pR$.

Investor $j$’s payoff depends on two events: whether the threshold is met and whether the treaty subsequently passes.

\[ V_j(x_j) = \begin{cases} x_j \cdot (pR - 1) & \text{if } \sum_{k} x_k \geq \bar{X} \text{ and } x_j > 0 \\ \delta_j & \text{if } \sum_{k} x_k < \bar{X} \text{ and } x_j > 0 \\ 0 & \text{if } x_j = 0 \end{cases} \tag{49.17}\]

The first case captures the expected return on investment when the campaign proceeds: the investor risks $x_j$ for an expected payoff of $x_j \cdot pR$, yielding net $x_j(pR - 1)$. The second case captures the dominant assurance feature: if insufficient investors participate and the threshold is not met, pledges are returned and each participant receives bonus $\delta_j > 0$. The third case is the status quo.

49.8.2.3 Proposition 4 (Investor Participation as Dominant Strategy)

Proposition 4. Under A6, if $pR > 1$ (positive expected return conditional on threshold being met) and $\delta_j > 0$ (positive bonus if threshold not met), then pledging $x_j > 0$ strictly dominates $x_j = 0$ for all investors $j$.

Proof sketch. Consider investor $j$’s payoff under each state:

Threshold met ($\sum_k x_k \geq \bar{X}$): Pledging yields $x_j(pR - 1) > 0$ since $pR > 1$. Not pledging yields $0$.
Threshold not met ($\sum_k x_k < \bar{X}$): Pledging yields $\delta_j > 0$. Not pledging yields $0$.

Since $V_j(x_j > 0) > V_j(0) = 0$ in both states, pledging strictly dominates not pledging regardless of other investors’ actions. Full proof in Appendix A. $\square$

Corollary 2. The unique Nash equilibrium of the dominant assurance contract game is full participation: $(x_1, \ldots, x_M) \gg 0$.

Proof. When every player has a strictly dominant strategy, the profile of dominant strategies is the unique Nash equilibrium. By Proposition 4, $x_j > 0$ is strictly dominant for all $j$. $\square$

49.8.2.4 Threshold Determination

The threshold $\bar{X}$ is not arbitrary. It maps to the campaign budget required to fund the IAB mechanism through proof-of-concept:

Phase 1 threshold ($\bar{X}_1$): $200M–$500M for initial deployment, scoring infrastructure, and first electoral cycle (Section 8.1)
Full campaign threshold ($\bar{X}_2$): $1B for the complete IAB mechanism through treaty passage

The contract can be staged: a Phase 1 assurance contract with threshold $\bar{X}_1$ funds the proof-of-concept. Demonstrated traction then supports a Phase 2 offering at threshold $\bar{X}_2$ with updated $p$ (higher, reflecting evidence) and lower perceived risk.

49.8.2.5 Funding the Bonus

The bonus $\delta_j$ must be funded by the contract entrepreneur. Three viable sources:

Interest on escrowed pledges. During the pledge accumulation period, escrowed capital earns risk-free interest. At current rates, $200M escrowed for 12 months generates $8–10M in interest, sufficient to fund bonuses of 4–5% on all pledges.
Philanthropic seed capital. A foundation commits a fixed bonus pool (e.g., $5M) that is distributed pro rata to participants if the threshold is not met. This is a leveraged philanthropic investment: $5M in bonus commitments can mobilize $200M+ in pledges.
Entrepreneurial risk. The contract entrepreneur (nonprofit) bears the bonus cost as a business expense, funded by the expected surplus from successful campaigns. This mirrors Tabarrok’s original framing: the entrepreneur profits from the spread between threshold capital and its deployed value.

The required bonus can be small. Proposition 4 holds for any $\delta_j > 0$, so even a 1% return on failed pledges is sufficient to make participation strictly dominant. In practice, higher bonuses accelerate participation by increasing the payoff floor.

49.8.2.6 Closing the Incentive Chain

The dominant assurance contract completes the end-to-end incentive compatibility chain:

Proposition 4 (this section): Investors will fund IABs because participation is the strictly dominant strategy under the assurance contract.
Proposition 1 (Section 3): Politicians will support welfare-improving policies because IABs make it the utility-maximizing choice.
Proposition 3 (Section 3): The unique equilibrium under funded IABs is universal cooperation.

The full chain: citizen coordination (via dominant assurance contract) $\to$ IAB funding $\to$ politician incentive alignment $\to$ treaty passage $\to$ investor returns $\to$ reinforced citizen coordination. Each link is incentive-compatible. No link requires altruism. The mechanism is self-sustaining once the assurance contract triggers initial funding.

49.8.2.7 Failure Mode Analysis: The Attention Bottleneck

If we take the model’s assumptions seriously (rational self-interest, $pR > 1$, dominant assurance structure), then every link in the chain is incentive-compatible and every actor’s optimal move is to participate. Under these conditions, the mechanism does not fail from misaligned incentives. It fails from a single pre-mechanism bottleneck: the rate at which actors with sufficient capital encounter and evaluate the proposal.

Formally, let $\lambda$ denote the rate at which potential investors with capital $x_j \geq x_{min}$ are exposed to and evaluate the mechanism. The time to reach threshold $\bar{X}$ is bounded by:

\[ T(\bar{X}) \leq \frac{\bar{X}}{\lambda \cdot \bar{x} \cdot q} \tag{49.18}\]

where $\bar{x}$ is the average pledge among evaluating investors and $q$ is the fraction who evaluate thoroughly enough to recognize that $pR > 1$ (i.e., who actually read the math rather than pattern-matching to “sounds too good to be true” and discarding).

This reveals the actual failure modes, all of which precede the mechanism itself:

Attention scarcity ($\lambda$ is low). Wealthy actors are busy. The proposal arrives as one of thousands of pitches. Even if evaluation would take 45 minutes and the conclusion would be “participate,” the 45 minutes never happen. This is not a rationality failure. It is a bandwidth failure. The expected value of reading the paper is enormous, but the expected value of reading any given unsolicited paper is near zero, and rational actors cannot distinguish them without reading them. This is an information asymmetry problem, not an incentive problem.
Credibility discount ($q$ is low). Rational actors who lack the time or expertise to evaluate the mechanism will estimate $p$ (treaty passage probability) based on priors. Most novel political mechanisms fail. If the prior on $p$ is low enough that $pR < 1$ for their subjective estimate, the dominant strategy result breaks down. Only the bonus $\delta$ makes participation attractive, which is insufficient to mobilize serious capital. This failure mode is temporary: a single successful pilot updates $p$ for every subsequent actor.
First-mover trust ($q$ is low for the first cohort). The assurance contract requires a credible contract entrepreneur to hold escrow and commit bonuses. If the organizing entity is unknown or untrusted, even actors who accept the math may discount $p$ due to execution risk. This is also temporary: early successes build institutional credibility.
Coordination on evaluation (a meta-attention problem). Each potential investor would benefit from someone else evaluating the mechanism first and publicly reporting “the math checks out.” This creates a second-order free-rider problem: not on participation, which the assurance contract solves, but on evaluation. Each actor waits for social proof before investing attention.

Notice what is absent from this list: no failure mode involves actors understanding the mechanism and rationally choosing not to participate. Under the model’s assumptions, comprehension produces participation. Every failure mode reduces to the same variable: the speed at which comprehension propagates.

The chain reaction. The bootstrap trigger is one credible anchor investor publicly underwriting the assurance contract with real money. Once one sufficiently capitalized actor evaluates the mechanism, recognizes $pR > 1$, and makes that public commitment, the dynamics shift:

Their participation is a credible signal (they risked real capital after evaluation)
This signal reduces evaluation cost for subsequent actors ($q$ increases)
Their reputation lends credibility to the contract entrepreneur ($p$ increases)
Media coverage increases exposure rate ($\lambda$ increases)

Each informed participant accelerates the next. The cascade has the structure of an information epidemic: slow at first (each new participant requires independent evaluation), then rapid (social proof substitutes for evaluation). The threshold $\bar{X}$ is reached not through mass adoption but through sequential capitalized actors, each of whom faces a cleaner decision than the last.

Implication for strategy. The binding constraint on the mechanism is not capital availability, political feasibility, or human nature. It is getting one credible wealthy first mover to read the paper, believe the expected value is positive, and make a public anchor commitment. Everything after that commitment is a chain reaction driven by self-interest. The entire apparatus of incentive compatibility is sitting idle, waiting for a signal that has not reached it yet because the signal requires reading.

This is why information propagation, not fundraising, is the rate-limiting step. The Recruitment & Propaganda Plan addresses this directly: the Logical Inevitability Theorem is the 4-minute version of this paper’s formal argument, designed to bridge the attention gap between “I don’t have time to read a paper” and “the expected value of reading this paper exceeds every other use of my next 45 minutes.”

Future research should address several open questions: What scoring mechanisms are most robust to gaming? How do IABs interact with existing campaign finance institutions? What governance structures best prevent capture of the scoring layer? Can IABs be adapted to non-democratic political systems? What legal strategies best protect the mechanism from regulatory attack? Empirical testing, beginning with single-issue pilot implementations, will be essential to validate the theoretical framework presented here.

If IABs can change political behavior at scale, if they can make supporting measurable public goods the career-maximizing choice for politicians, the architecture becomes available for climate, nuclear risk, pandemic preparedness, and every domain where humanity’s long-term welfare depends on overcoming collective action failures. The mechanism does not require politicians to become better people. It requires only that institutions be designed so rational self-interest points at better outcomes.

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Phase I duration: 2.3 years average Total time to market (Phase I-III + approval): 10.5 years average Phase transition success rates: Phase I→II: 63.2%, Phase II→III: 30.7%, Phase III→Approval: 58.1% Overall probability of approval from Phase I: 12% Note: Largest publicly available study of clinical trial success rates. Efficacy lag = 10.5 - 2.3 = 8.2 years post-safety verification. Additional sources: https://go.bio.org/rs/490-EHZ-999/images/ClinicalDevelopmentSuccessRates2011_2020.pdf

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Hydra: Biologically immortal - no mortality increase over 4-year study, kept alive 12+ years Planarian worms: Somatically immortal with limitless telomere regeneration, clonal lines >15 years Axolotls: Regrow limbs, brain parts, heart tissue through remarkable regeneration Naked mole rats: Live 37+ years (10x similar rodents), cancer-proof, no age-related mortality increase Bowhead whales: Live 200+ years, unique DNA repair mutations, extra cancer-suppression genes Note: These animals demonstrate enhanced DNA repair, abundant stem cells, telomerase activity, and cancer resistance Additional sources: https://en.wikipedia.org/wiki/Biological_immortality | https://pmc.ncbi.nlm.nih.gov/articles/PMC5807068/

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Historical analysis of deflation episodes from the classical gold standard era through the post-WWII period. The "Great Deflation" of 1870-1896 saw prices fall roughly 2% per year while real output grew 2-3% per year. Good deflation occurs when aggregate supply increases faster than aggregate demand due to technological advances and productivity gains.

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In 2010, there were 32,999 people killed, 3.9 million injured, and 24 million vehicles damaged in motor vehicle crashes in the United States. The economic costs totaled 277billion.Whenqualityoflifevaluationsareconsidered, thetotalvalueofsocietalharmfrommotorvehiclecrasheswas871 billion, representing 1.9 percent of GDP.

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Tested the historical link between output growth and deflation across 140 years and up to 38 economies. Found the link is "weak" and "derives largely from the Great Depression." The benign output performance during the classical gold standard period characterized those deflations as "good." Property price deflations, not goods price deflations, are the more consistent predictor of economic weakness.

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Bradley-Terry: Probability model for pairwise comparisons (1952, earlier by Zermelo 1920s); maximum likelihood estimation PageRank: Ranks nodes by importance in network via stationary distribution of Markov chain Connection: Under quasi-symmetry, Bradley-Terry scores are equivalent to scaled PageRank; ML estimates can be approximated from limiting distribution Applications: Sports rankings, journal citations, AI model rankings, consumer choice, search engines Additional sources: https://arxiv.org/abs/2402.07811 | https://en.wikipedia.org/wiki/Bradley–Terry_model | https://www.sciencedirect.com/science/article/pii/S0950705122000314

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On 23 June 2016 the United Kingdom held a referendum on EU membership. Leave won 51.9% to 48.1% on 72.2% turnout (33.6 million votes cast). A complex multidimensional trade and sovereignty question was reduced to a single binary yes/no choice.

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The Spanish-American War lasted from April to August 1898. American combat deaths totaled 345, though approximately 2,000 more died of disease. The war lasted approximately ten weeks.

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Encyclopaedia Britannica. How many people died in the vietnam war? (2025)

Vietnam’s 1995 official estimate: as many as 2 million civilians on both sides, 1.1 million North Vietnamese and Viet Cong fighters, plus nearly 300,000 South Vietnamese and allied soldiers. Total approximately 3.4 million.

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This paper describes participatory budgeting in Brazil and elsewhere as a significant area of innovation in democracy and local development. It draws on the experience of 25 municipalities in Latin America and Europe, selected based on the diversity of their participatory budgeting experience and their degree of innovation. Additional sources: https://www.iied.org/g00471 | https://www.researchgate.net/publication/32893674_Participatory_Budgeting_A_Significant_Contribution_to_Participatory_Democracy

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2024: 7 measures pulled before election after back-room negotiations (16 since 2014) System designed to curb special interests has instead empowered them Victory is on the side of the biggest purse" (1923 legislative committee) Influx of special interest propositions makes ballots longer, more confusing, less accessible Note: Progressive Era reform meant to curb special interests has had unintended opposite effect Additional sources: https://carnegieendowment.org/posts/2024/11/california-2024-election-propositions-direct-democracy | https://www.davispoliticalreview.com/article/hijacking-the-ballot-the-problem-with-californias-ballot-initiative-system

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IARC/WHO: Environmental and lifestyle factors contribute to about 50% of the global cancer burden; expected to contribute to remaining 50% for which causes currently unknown WHO: 35% of cancer deaths worldwide are due to potentially preventable or modifiable risk factors PMC: "Only 5-10% of all cancer cases can be attributed to genetic defects, whereas the remaining 90-95% have their roots in the environment and lifestyle Breakdown: 25-30% due to tobacco, 30-35% linked to diet, 15-20% due to infections, remainder from radiation, stress, physical activity, pollutants US: 4 out of 10 cancer cases associated with preventable risk factors (tobacco/alcohol use, physical inactivity) Note: Current preventability ( 35-40%) vs. theoretical max (90-95% if all environmental/lifestyle factors addressed) Additional sources: https://pmc.ncbi.nlm.nih.gov/articles/PMC2515569/ | https://www.iarc.who.int/branches-env/ | https://cancerprogressreport.aacr.org/progress/cpr22-contents/cpr22-preventing-cancer-identifying-risk-factors/

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Cancer deaths: 10.4 million globally in 2023 (9.7 million in 2022) 18.5 million new cancer cases in 2023 65.8% of deaths occur in low- to upper-middle-income countries Note: Cancer is the second leading cause of death globally after cardiovascular diseases. Projected to reach 18.6 million deaths by 2050 (74.5% increase) Additional sources: https://www.hematologyadvisor.com/news/globally-18-5-million-incident-cancer-cases-and-10-4-million-deaths-reported-in-2023/ | https://www.who.int/news/item/01-02-2024-global-cancer-burden-growing–amidst-mounting-need-for-services

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The key to evidence-based policy is understanding that evidence of effectiveness elsewhere is not evidence of effectiveness here without support for the claim that the causal mechanism will operate in the new setting.

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CBS News. Study: Bank bonuses far exceeded profits. (2009)

Goldman Sachs earned $2.3 billion and paid out $4.8 billion in bonuses. Morgan Stanley earned $1.7 billion and paid $4.475 billion in bonuses. Citigroup and Merrill Lynch lost a combined $54 billion yet paid $9 billion in combined bonuses.

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CA Attorney General. California consumer privacy act (CCPA) and california privacy rights act (CPRA). CA Attorney General: CCPA https://oag.ca.gov/privacy/ccpa

CCPA effective January 1, 2020; CPRA (Prop 24) approved November 2020, effective January 1, 2023 Consumer rights: Know/access personal data; Delete data; Opt-out of sale/sharing; Non-discrimination; Correct inaccurate data (CPRA); Limit sensitive data use (CPRA) Enforcement: California Privacy Protection Agency (CPRA created); Previously CA Attorney General Penalties: Up to $7,500 per intentional violation; $2,500 per unintentional violation Additional sources: https://oag.ca.gov/privacy/ccpa | https://cppa.ca.gov/regulations/ | https://pro.bloomberglaw.com/insights/privacy/california-consumer-privacy-laws/

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NPR. Contamination of early CDC COVID-19 tests in 2020. NPR: CDC Test Flawed https://www.npr.org/2020/11/06/929078678/cdc-report-officials-knew-coronavirus-test-was-flawed-but-released-it-anyway (2020)

CDC distributed flawed test kits Feb 6, 2020 - contaminated reagents caused false positives 24 of 26 public health labs found contamination, CDC recalled kits by Feb 10 Tests made in CDC lab (not manufacturing facility), violated sound manufacturing practices Contamination occurred in Respiratory Virus Diagnostic Lab during processing Note: Delays had significant consequences for early pandemic tracking and response Additional sources: https://www.npr.org/2020/11/06/929078678/cdc-report-officials-knew-coronavirus-test-was-flawed-but-released-it-anyway | https://www.cnn.com/2020/04/18/politics/cdc-coronavirus-testing-contamination/index.html

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National Center for Health Statistics. Drug overdose deaths in the united states, 2003–2023. (2025)

Drug overdose deaths in the United States exceeded 100,000 annually beginning in 2021, with a peak of approximately 111,000 in 2023.

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House Budget Committee. Burdensome federal regulations cost economy $2 trillion annually. (2023).

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330 billion cells replaced daily ( 1% of all cells, 3.8 million/second) 80 grams of cellular mass turnover per day, dominated by blood cells (86%) and gut epithelial cells (12%) Complete body cell replacement in 80-100 days (average cell age: 7 years) Note: Despite constant regeneration, we age due to DNA mutations that accumulate as cells replicate Produce 2 million red blood cells per second Generate new stomach lining every 3-5 days Replace your entire skin every 28 days (surface cells every 2-4 weeks) Rebuild your skeleton every 10 years Additional sources: https://www.scientificamerican.com/article/our-bodies-replace-billions-of-cells-every-day/ | https://wis-wander.weizmann.ac.il/life-sciences/cell-replacement-numbers | https://science.howstuffworks.com/life/cellular-microscopic/does-body-really-replace-seven-years.htm | https://www.livescience.com/33179-does-human-body-replace-cells-seven-years.html | https://www.sanitas.com/en/magazine/body/about-body/how-our-body-regenerates.html

86.

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Homeownership rates by decade from decennial census data. 1940: 43.6%. 1950: 55.0%. 1960: 61.9%. 1970: 62.9%. The aggregate US homeownership rate increased by 20 percentage points from 1940 to 1960, the largest change in American homeownership in the past 100 years.

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US Census Bureau. US median household income 2023. (2024)

US median household income was $77,500 in 2023 Real median household income declined 0.8% from 2022 Gini index: 0.467 (income inequality measure) Additional sources: https://www.census.gov/library/publications/2024/demo/p60-282.html

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Coalition of Finance Ministers for Climate Action. Fossil fuel subsidy reform. https://www.financeministersforclimate.org/sites/cape/files/inline-files/CFMCA%20Policy%20Note_Fossil%20Fuel%20Subsidy%20Reform_Sept%202024.pdf (2024).

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Cato Institute. Chance of dying from terrorism statistic. Cato Institute: Terrorism and Immigration Risk Analysis https://www.cato.org/policy-analysis/terrorism-immigration-risk-analysis

Chance of American dying in foreign-born terrorist attack: 1 in 3.6 million per year (1975-2015) Including 9/11 deaths; annual murder rate is 253x higher than terrorism death rate More likely to die from lightning strike than foreign terrorism Note: Comprehensive 41-year study shows terrorism risk is extremely low compared to everyday dangers Additional sources: https://www.cato.org/policy-analysis/terrorism-immigration-risk-analysis | https://www.nbcnews.com/news/us-news/you-re-more-likely-die-choking-be-killed-foreign-terrorists-n715141

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US programs (1994-2023): $540B direct savings, $2.7T societal savings ( $18B/year direct, $90B/year societal) Global (2001-2020): $820B value for 10 diseases in 73 countries ( $41B/year) ROI: $11 return per $1 invested Measles vaccination alone saved 93.7M lives (61% of 154M total) over 50 years (1974-2024) Additional sources: https://www.cdc.gov/mmwr/volumes/73/wr/mm7331a2.htm | https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(24)00850-X/fulltext

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Routine childhood vaccinations among 1994–2023 US birth cohorts will prevent 1.1 million deaths, 32 million hospitalizations, and save $2.9 trillion in societal costs. Among children born during 2018–2023, vaccinations will prevent 508,000 premature deaths and 13.5 million hospitalizations over their lifetimes. Additional sources: https://www.cdc.gov/mmwr/volumes/73/wr/mm7331a2.htm

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2015 Victory Day (70th anniversary): 12,000 PLA troops, 1,000 foreign troops, 850,000 "Citizen Guards 2025 parade estimated >36 billion yuan ($5 billion, 1.5% of military budget) - Taiwan estimate Beijing rarely discloses parade costs; estimates cannot be independently verified Note: Massive mobilization for propaganda purposes; costs remain state secret Additional sources: https://en.wikipedia.org/wiki/2015_China_Victory_Day_Parade | https://www.nbcnews.com/world/asia/live-blog/china-parade-putin-kim-jong-un-xi-military-live-updates-rcna228503

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Citizens United v. FEC (2010): 5-4 Supreme Court decision allowing unlimited corporate/union political spending Overruled restrictions on independent expenditures, citing First Amendment Led to creation of super PACs and massive increases in dark money Dramatically expanded influence of wealthy donors, corporations, special interest groups Note: Overwhelming majorities of Americans disapprove; 22+ states voted to support constitutional amendment to overturn Additional sources: https://supreme.justia.com/cases/federal/us/558/310/ | https://www.brennancenter.org/our-work/research-reports/citizens-united-explained

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Free global labor mobility would increase gross world product by somewhere in the range of 67-147%... The gains to eliminating migration barriers amount to large fractions of world GDP—one or two orders of magnitude larger than the gains from dropping all remaining restrictions on international flows of goods and capital.

104.

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Approximately 12% of trials with results posted on the ClinicalTrials.gov results database (905/7,646) were terminated. Primary reasons: insufficient accrual (57% of non-data-driven terminations), business/strategic reasons, and efficacy/toxicity findings (21% data-driven terminations).

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Median clinical trial cost: $19.0 million (range: $12.2M - $33.1M) Cost per patient varies by phase: Phase 1: $137K, Phase 2: $130K, Phase 3: $113K Note: Based on analysis of 138 clinical trials. Actual costs can vary significantly based on disease area, trial complexity, and patient population Additional sources: https://jamanetwork.com/journals/jamainternalmedicine/fullarticle/2702287

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Only 3-5% of adult cancer patients in US receive treatment within clinical trials About 5% of American adults have ever participated in any clinical trial Oncology: 2-3% of all oncology patients participate Contrast: 50-60% enrollment for pediatric cancer trials (<15 years old) Note: 20% of cancer trials fail due to insufficient enrollment; 11% of research sites enroll zero patients Additional sources: https://www.fightcancer.org/policy-resources/barriers-patient-enrollment-therapeutic-clinical-trials-cancer | https://hints.cancer.gov/docs/Briefs/HINTS_Brief_48.pdf

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Mapping 350,000+ clinical trials showed that only 12% of the human interactome has ever been targeted by drugs. Additional sources: https://pmc.ncbi.nlm.nih.gov/articles/PMC10749231/

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Analysis of 100,000 active/recruiting/completed trials on ClinicalTrials.gov (as of January 2025) shows cumulative enrollment of 12.2 million participants: Phase 1 (722k), Phase 2 (2.2M), Phase 3 (6.5M), Phase 4 (2.7M). Median participants per trial: Phase 1 (33), Phase 2 (60), Phase 3 (237), Phase 4 (90). Additional sources: https://clinicaltrials.gov/data-api/api

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The Convention on Cluster Munitions bans the use, production, stockpiling, and transfer of cluster munitions. Oslo Process timeline: February 2007 to December 2008 ( 2 years) 46 states signed Oslo Declaration (Feb 2007); 94 states signed convention (Dec 2008) Core Group: Norway, Austria, Ireland, Mexico, New Zealand, Peru, Holy See Results: 29 States Parties destroyed nearly 1.4 million stockpiled cluster munitions containing 172.9 million submunitions Additional sources: https://www.clusterconvention.org/oslo-process/ | https://unidir.org/files/publication/pdfs/unacceptable-harm-a-history-of-how-the-treaty-to-ban-cluster-munitions-was-won-en-258.pdf | https://www.stopclustermunitions.org/en-gb/the-treaty/global-ban.aspx

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Regulatory restrictions have had a net effect of dampening economic growth by approximately 0.8 percent per annum since 1980... Had regulation been held constant at levels observed in 1980, the economy would have been nearly 25 percent larger by 2012 (i.e., regulatory growth since 1980 cost GDP $4 trillion in 2012, or about $13,000 per capita).

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Short-term memory capacity: 7 ± 2 items (Miller’s Law) The "magical number seven" - humans can hold approximately 7 chunks of information in working memory Note: This classic psychology paper has been cited over 40,000 times and fundamentally shaped our understanding of human cognitive limitations Additional sources: https://doi.org/10.1037/h0043158

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Classic reference for effect size conventions in social science research. Defines small (d=0.2), medium (d=0.5), and large (d=0.8) effect sizes for standardized mean differences.

116.

Columbia Business School. The cost of red tape: How regulation impacts GDP in european countries. Columbia Business School https://business.columbia.edu/research-brief/research-brief/red-tape-regulation-gdp (2022).

117.

The Commonwealth Fund. High u.s. Health care spending: Where is it all going? The Commonwealth Fund https://www.commonwealthfund.org/publications/issue-briefs/2023/oct/high-us-health-care-spending-where-is-it-all-going (2023).

118.

Shortell, D. Reading every word of every bill. Government Executive https://www.govexec.com/federal-news/2009/09/reading-every-word-of-every-bill/39321/ (2009)

In the 110th Congress, the House dealt with 7,441 bills and joint resolutions averaging 16.7 pages per law, totaling approximately 125,000 pages. At 300 words per minute (average college graduate reading speed), reading just the 1,427-page Waxman-Markey bill would take 12 hours. Cites Washington Post editorial on impossibility of legislators reading all proposed legislation.

119.

Library of Congress. Congress.gov: United states legislative information. (2025).

120.

CBS 60 Minutes. Percentage of time members of congress spend fundraising. CBS 60 Minutes: Congressional Telemarketers https://www.cbsnews.com/news/60-minutes-are-members-of-congress-becoming-telemarketers/

Recommended: 4 hours "call time" + 1 hour "strategic outreach" = 5 hours/day out of 9-10 hour workday New members told to spend 30 hours/week on fundraising calls since Citizens United Tom Daschle: 67% of schedule is money-gathering in 2 years before election Only 3-4 hours/day for actual Congressional work (hearings, votes, constituents) Note: By law, members cannot fundraise from offices; parties set up call centers near Capitol Additional sources: https://www.cbsnews.com/news/60-minutes-are-members-of-congress-becoming-telemarketers/ | https://www.huffpost.com/entry/call-time-congressional-fundraising_n_2427291

121.

Issue One. Congressional committee assignments have explicit fundraising price tags. Issue One: The Price of Power https://www.issueone.org/wp-content/uploads/2017/05/price-of-power-final.pdf (2017)

DCCC (Democratic): Speaker $31 million, "A" Committee Chairs $1.8 million, Regular members $150,000 minimum NRCC (Republican): Speaker $20 million, Power Committee Chairs $1.2 million, Transportation Chair $875,000 Members display "giant tally sheet" showing who has/hasn’t paid their party dues Members who don’t pay dues get bills killed, amendments ignored, worse offices Rep. Brett Guthrie: Paid $2.5 million (53% of campaign funds) for Energy & Commerce Chair Rep. Rosa DeLauro: Paid $690,000 (39% of campaign funds) for Appropriations Note: System criticized as "recipe for corruption" disconnecting members from constituents Additional sources: https://www.issueone.org/wp-content/uploads/2017/05/price-of-power-final.pdf | https://theintercept.com/2019/09/03/dccc-house-committees-dues/ | https://www.brookings.edu/articles/problems-with-the-committee-tax-in-congress/ | https://rollcall.com/2023/02/09/gavels-for-top-house-committees-dont-always-come-cheap/

122.

U.S. Senate. Salary of a u.s. congressman. U.S. Senate: Salaries https://www.senate.gov/senators/SenateSalariesSince1789.htm

Members of Congress: $174,000/year (2009-present) Speaker of the House: $223,500/year Majority/Minority Leaders: $193,400/year Note: Congressional salary has been frozen at $174,000 since 2009, unchanged for over 15 years Additional sources: https://www.senate.gov/senators/SenateSalariesSince1789.htm | https://crsreports.congress.gov

123.

ScienceDaily. Conscious mind controls 5% of decisions. ScienceDaily: Unconscious Decision Making https://www.sciencedaily.com/releases/2008/04/080414145705.htm (2008)

Conscious of only 5% of cognitive activity; 95% is unconscious/subconscious Brain signals predict decisions up to 7 seconds before conscious awareness 90% of buying decisions made subconsciously Most of what we do every minute is unconscious" - neuroscientist Paul Whelan Note: All decisions made unconsciously first, then we "fool ourselves" into believing we consciously made them Additional sources: https://www.sciencedaily.com/releases/2008/04/080414145705.htm | https://pmc.ncbi.nlm.nih.gov/articles/PMC2440575/

124.

Wikipedia. Control arms coalition - arms trade treaty campaign. Wikipedia https://en.wikipedia.org/wiki/Control_Arms_Campaign

Coalition of 100+ organizations including Amnesty International, Oxfam, and International Action Network on Small Arms (IANSA) Campaign duration: 10 years (October 2003 - April 2013) Published 50+ reports over the campaign period on various aspects of arms trade regulation Campaign tactics: Publicity stunts, mass public actions, Million Faces petition, worldwide consultations, lobbying Achievement: Arms Trade Treaty adopted by UN General Assembly April 2013, entered into force December 2014 Additional sources: https://en.wikipedia.org/wiki/Control_Arms_Campaign | https://frompoverty.oxfam.org.uk/how-did-a-global-campaign-bring-about-a-un-arms-trade-treaty/ | https://policy-practice.oxfam.org/resources/power-and-change-the-arms-trade-treaty-338471/

125.

Lomborg, B. Copenhagen consensus center. (2025).

126.

Copenhagen Consensus. Halftime for SDGs: Child immunization. (2023).

127.

FTC. Children’s online privacy protection act (COPPA). FTC: COPPA Rule https://www.ftc.gov/legal-library/browse/rules/childrens-online-privacy-protection-rule-coppa

Federal law effective April 21, 2000; applies to websites/services collecting data from children under 13 Requirements: Privacy policy; Verifiable parental consent before collecting data; Data security; Parental review/deletion rights Applies to: For-profit businesses collecting personal info from US children under 13 Penalties: Up to $50,120 per violation Enforcement: FTC and State Attorneys General Additional sources: https://www.ftc.gov/legal-library/browse/rules/childrens-online-privacy-protection-rule-coppa | https://en.wikipedia.org/wiki/Children’s_Online_Privacy_Protection_Act | https://www.ecfr.gov/current/title-16/chapter-I/subchapter-C/part-312

128.

USA TODAY, The Arizona Republic & Center for Public Integrity. You elected them to write new laws. They’re letting corporations do it instead. Center for Public Integrity https://publicintegrity.org/politics/state-politics/copy-paste-legislate/you-elected-them-to-write-new-laws-theyre-letting-corporations-do-it-instead/ (2019)

Investigation of nearly 1 million bills across all 50 states found at least 10,000 bills almost entirely copied from model legislation introduced over eight years, with more than 2,100 signed into law. Sources: 4,301 from industry (42%), 4,012 from conservative groups (40%), 1,602 from liberal groups (16%), 248 other (2%).

129.

Sinn, M. P. The Price of Political Change: A Cost-Benefit Framework for Policy Incentivization. https://cost-of-change.warondisease.org (2025) doi:10.5281/zenodo.18356215

What’s the maximum cost to achieve any policy change through legal democratic channels? $25B for the US, $200B globally. For high-value reforms like military-to-health reallocation, this yields ROI exceeding 400,000:1.

130.

ScienceDirect. How campaign contributions influence politicians. ScienceDirect: Campaign Contributions & Legislative Behavior https://www.sciencedirect.com/science/article/pii/S0047272725000179 (2010)

Research: Only 1 in 4 studies support notion that contributions directly "buy votes Influence mechanism: Access, agenda-setting, keeping bills off floor, earmarks, key language in legislation (not direct votes) Average winner costs (2022): House $2.79M, Senate $26.53M; Competitive races much higher Internal party fundraising requirements: $100K-$30M annually; Committee positions cost $450K 95% of House races since 2004 won by highest spender Contribution limits: $3,300 per candidate per election (individuals); PACs gave $289.3M total (2021-2022) Additional sources: https://www.sciencedirect.com/science/article/pii/S0047272725000179 | https://slate.com/news-and-politics/2010/10/how-much-does-it-cost-to-buy-a-vote.html | https://www.opensecrets.org/elections-overview/cost-of-election | https://issueone.org/articles/the-118th-congress-fundraising-treadmill/

131.

Costinot, A. & Rodriguez-Clare, A. Trade theory with numbers: Quantifying the consequences of globalization. Handbook of International Economics 4, 197–261 (2015)

Gravity models estimate trade barriers cost 5-10% of GDP.

132.

Crawford, N. C. Human costs of post-9/11 wars. (2024)

Over 940,000 people killed by direct war violence. An estimated 3.6-3.8 million died indirectly in post-9/11 war zones. Total: at least 4.5-4.7 million and counting.

133.

Crawford, N. C. & Lutz, C. Blood and treasure: United states budgetary costs and human costs of 20 years of war. (2023)

The total costs of the post-9/11 wars in Iraq, Afghanistan, Pakistan, and Syria are expected to exceed $8 trillion. This includes $2.89 trillion for Iraq/Syria, veterans care through 2050 projected at more than $2 trillion, and interest on war debt adding $6.5 trillion through 2050.

134.

USC Schaeffer Center. COVID-19’s total cost to the U.S. Economy will reach $14 trillion by end of 2023. USC Schaeffer Center for Health Policy and Economics https://schaeffer.usc.edu/research/covid-19s-total-cost-to-the-economy-in-us-will-reach-14-trillion-by-end-of-2023-new-research/ (2023).

135.

Cutler, D. M. & Summers, L. H. The COVID-19 pandemic and the $16 trillion virus. JAMA 324, 1495–1496 (2020).

136.

Statista. Comparison of u.s. Deaths from COVID-19 vs. Major wars. Statista: COVID vs War Deaths https://www.statista.com/chart/24252/us-covid-19-deaths-compared-to-deaths-in-major-wars/

COVID-19 US deaths: 1.2+ million total (as of 2024) WWII: 405,000 | Korea: 36,000 | Vietnam: 58,000 = 499,000 combined By March 2021: COVID deaths (527,726) exceeded WWI, WWII, Vietnam, 9/11 combined By Oct 2021: 704,233 deaths exceeded ALL US foreign conflict deaths ( 685,000 total) Note: COVID killed more Americans than Revolutionary War, War of 1812, WWI, WWII, Korea, Vietnam, and other conflicts combined Additional sources: https://www.statista.com/chart/24252/us-covid-19-deaths-compared-to-deaths-in-major-wars/ | https://www.snopes.com/fact-check/americans-covid-foreign-conflicts/

137.

Bramante, C. T. et al. Outpatient treatment of COVID-19 and incidence of post-COVID-19 condition over 10 months (COVID-OUT): A multicentre, randomised, quadruple-blind, parallel-group, phase 3 trial. The Lancet Infectious Diseases 23, 1119–1129 (2023).

138.

Select Subcommittee on the Coronavirus Pandemic. Final report: COVID select concludes 2-year investigation, issues 500+ page final report. (2024).

139.

Armingeon, K., Engler, S. & Leemann, L. Comparative political data set (CPDS). (2024).

140.

UBS and Credit Suisse. Global wealth report 2023. (2023).

141.

Crestmont Research. Real GDP growth by decade. (2024)

Average real GDP growth by decade. 1950s: 4.2% per year. 1960s: 4.5% per year. 1970s: 3.2%. 1980s: 3.1%. 1990s: 3.2%. 2000s: 1.9%. 2010s: 2.3%.

142.

CRFB. Medicare advantage will be overpaid by $1.2 trillion. (2024).

143.

Congressional Research Service. Defense primer: Strategic nuclear forces. (2024).

144.

Daggett, S. Costs of major u.s. wars. (2010)

Congressional Research Service estimates of the costs of major U.S. wars from the American Revolution through post-9/11 operations, in both current-year and constant FY2011 dollars.

145.

UBS. Credit suisse global wealth report 2023. Credit Suisse/UBS https://www.ubs.com/global/en/family-office-uhnw/reports/global-wealth-report-2023.html (2023)

Total global household wealth: USD 454.4 trillion (2022) Wealth declined by USD 11.3 trillion (-2.4%) in 2022, first decline since 2008 Wealth per adult: USD 84,718 Additional sources: https://www.ubs.com/global/en/family-office-uhnw/reports/global-wealth-report-2023.html

146.

ABC News. Bailed-out banks gave millions in exec bonuses, NY AG report shows. (2009)

Citigroup lost $18.7 billion in 2008 and received $45 billion in TARP bailout funds, yet paid $5.33 billion in bonuses, with 738 employees receiving at least $1 million. Bank of America received $45 billion in TARP and paid $3.3 billion in bonuses. Merrill Lynch lost $30.48 billion and paid $3.6 billion in bonuses with 696 million-dollar recipients. Across nine major banks, nearly 4,800 employees received bonuses of $1 million or more.

147.

WHO. 80% of cardiovascular disease is preventable. WHO: Cardiovascular diseases (CVDs)) https://www.who.int/news-room/fact-sheets/detail/cardiovascular-diseases-(cvds) (2021)

As many as 80% of all heart attacks and strokes are preventable" through addressing lifestyle risk factors WHO: Most cardiovascular diseases can be prevented by addressing behavioral and environmental risk factors such as tobacco use, unhealthy diet, obesity, physical inactivity, harmful use of alcohol, and air pollution Cleveland Clinic: "90 percent of heart disease is preventable through healthier diet, regular exercise, and not smoking In 2 large cohort studies, a reduction of CVD risk of >80% and diabetes >90% were demonstrated in individuals who followed healthy lifestyle practices Only 5% of individuals follow all lifestyle factors for "ideal" cardiovascular health (American Heart Association) Additional sources: https://www.who.int/news-room/fact-sheets/detail/cardiovascular-diseases-(cvds) | https://world-heart-federation.org/what-we-do/prevention/ | https://newsroom.clevelandclinic.org/2021/09/29/90-percent-of-heart-disease-is-preventable-through-healthier-diet-regular-exercise-and-not-smoking | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC162259/

148.

Cybersecurity Ventures. Cybercrime economy projected to reach $10.5 trillion. Cybersecurity Ventures: $10.5T Cybercrime https://cybersecurityventures.com/hackerpocalypse-cybercrime-report-2016/ (2016)

Global cybercrime costs: $3T (2015) → $6T (2021) → $10.5T (2025 projected) 15% annual growth rate If measured as country, would be 3rd largest economy after US and China Greatest transfer of economic wealth in history Note: More profitable than global trade of all major illegal drugs combined. Includes data theft, productivity loss, IP theft, fraud Additional sources: <https://cybersecurityventures.com/hackerpocalypse-cybercrime-report-2016/> | https://www.boisestate.edu/cybersecurity/2022/06/16/cybercrime-to-cost-the-world-10-5-trillion-annually-by-2025/

149.

CSO Online. 96% of cybercrimes go unpunished. CSO Online: Why Internet Crime Goes Unpunished https://www.csoonline.com/article/2618598/why-internet-crime-goes-unpunished.html

Less than 1% of cybercrimes prosecuted (UK: 65 prosecutions vs 17,900 reported cases in 2018) 99% of cybercrimes go unpunished Perpetrators extremely difficult to identify and pursue Cross-national boundaries make prosecution nearly impossible Note: Rules of evidence and international jurisdiction make cybercrime possibly harder to prosecute than any other area of law enforcement Additional sources: https://www.csoonline.com/article/2618598/why-internet-crime-goes-unpunished.html | https://informationsecuritybuzz.com/expert-comments/only-1-of-cybercrimes-prosecuted/

150.

World Bank. World development indicators. (2025).

151.

Dawson, J. W. & Seater, J. J. Federal regulation and aggregate economic growth. Journal of Economic Growth 18, 137–177 (2013)

Federal regulations added over the past fifty years have reduced real output growth by about two percentage points on average annually over the period 1949-2005... GDP at the end of 2011 would have been $53.9 trillion instead of $15.1 trillion if regulation had remained at its 1949 level.

152.

World Bank Group. Disease control priorities, third edition (DCP3). (2018).

153.

Rogers et al. Decentralized clinical trials (DCT) cost reduction evidence. Rogers et al. https://discovery.dundee.ac.uk/ws/files/72718478/Brit_J_Clinical_Pharma_2022_Rogers_A_systematic_review_of_methods_used_to_conduct_decentralised_clinical_trials.pdf (2022)

DCTs are developing rapidly. However, there is insufficient evidence to confirm which methods are most effective in trial recruitment, retention, or overall cost." Despite this, DCTs have demonstrated potential for significant cost reductions (20-50.0% or more) through reduced site management, travel, and streamlined data collection. DCTs are considered cost-saving by reducing the number of onsite patient visits and decreasing the costs related to time for study nurses and clinicians. Additional sources: https://discovery.dundee.ac.uk/ws/files/72718478/Brit_J_Clinical_Pharma_2022_Rogers_A_systematic_review_of_methods_used_to_conduct_decentralised_clinical_trials.pdf | https://www.nature.com/articles/s41746-024-01214-5

154.

MobiHealthNews, Aug. Other DCT platform company funding. MobiHealthNews https://www.mobihealthnews.com/news/exo-raises-40m-handheld-ultrasound-decentralized-trial-platforms-raise-nearly-100m-and-more (2020)

Science 37: $40M raised Thread: up to $50M raised uMotif: $25.5M raised These companies show that you can achieve significant traction and platform development with investments in the tens of millions. Additional sources: https://www.mobihealthnews.com/news/exo-raises-40m-handheld-ultrasound-decentralized-trial-platforms-raise-nearly-100m-and-more | https://www.pharmasalmanac.com/articles/umotif-the-patient-first-data-capture-and-decentralized-clinical-trials-platform-announces-25.5m-of-new-investment-from-a-fund-managed-by-athyrium-capital-management

155.

IHME. Death causes vs fear (heart disease vs terrorism). IHME: CVD Deaths 2023 https://www.healthdata.org/news-events/newsroom/news-releases/report-cardiovascular-diseases-caused-1-3-global-deaths-2023 (2023)

Cardiovascular disease: 19.2-20.5 million deaths annually (2023 data) Terrorism: approximately 25,000 deaths per year CVD accounts for 1 in 3 global deaths - the leading cause for over 30 years Note: CVD deaths increased 60% from 12.1M (1990) to 20.5M (2021). 4 in 5 CVD deaths occur in low- and middle-income countries Additional sources: https://www.healthdata.org/news-events/newsroom/news-releases/report-cardiovascular-diseases-caused-1-3-global-deaths-2023 | https://world-heart-federation.org/wp-content/uploads/World-Heart-Report-2023.pdf

156.

Delaware Division of Corporations. Delaware has more corporate entities than residents. Delaware Division of Corporations: 2020 Annual Report https://corp.delaware.gov/stats/2020-annual-report/ (2020)

Delaware population: <1 million residents Business entities: 1.6 million+ (2020) - 2:1 ratio over residents 2019: 1.5 million entities vs <1M people 66% of Fortune 500 incorporated in Delaware 93% of US IPOs are Delaware entities Note: 249,427 new business entities added in 2020 alone. Unique 2:1 corporation-to-resident ratio Additional sources: https://corp.delaware.gov/stats/2020-annual-report/ | https://press.princeton.edu/ideas/hal-weitzman-on-whats-the-matter-with-delaware

157.

Del Rosal, I. The empirical measurement of rent-seeking costs. Journal of Economic Surveys https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1467-6419.2009.00621.x (2011)

A comprehensive survey of empirical estimates finds rent-seeking costs range from 0.2% to 23.7% of GDP across different methodologies and countries. Laband & Sophocleus (1988) estimated up to 45% for the US.

158.

United Nations Department of Economic and Social Affairs. Credit rating agencies and sovereign debt: Four proposals to support achievement of the SDGs. (2023).

159.

GiveWell. Cost per DALY for deworming programs. https://www.givewell.org/international/technical/programs/deworming/cost-effectiveness

Schistosomiasis treatment: $28.19-$70.48 per DALY (using arithmetic means with varying disability weights) Soil-transmitted helminths (STH) treatment: $82.54 per DALY (midpoint estimate) Note: GiveWell explicitly states this 2011 analysis is "out of date" and their current methodology focuses on long-term income effects rather than short-term health DALYs Additional sources: https://www.givewell.org/international/technical/programs/deworming/cost-effectiveness

160.

Sinn, M. P. Ubiquitous Pragmatic Trial Impact Analysis: How to Prevent a Year of Death and Suffering for 84 Cents. https://dfda-impact.warondisease.org (2025) doi:10.5281/zenodo.18243914

Only 15 diseases/year get their first treatment each year. With 6.65 thousand diseases lacking effective treatments, the backlog would take 443 years to clear. Integrating pragmatic trials into standard healthcare increases trial capacity 12.3x, cutting that timeline from 443 years to 36 years. The average untreated disease gets a treatment 212 years earlier, saving 10.7 billion deaths at $0.842 per year of healthy life saved.

161.

Sinn, M. P. The Continuous Evidence Generation Protocol: Two-Stage Validation (RWE → Pragmatic Trials). https://dfda-spec.warondisease.org (2025) doi:10.5281/zenodo.18203375

We present the Predictor Impact Score (PIS), a novel composite metric operationalizing Bradford Hill causality criteria for automated signal detection from aggregated N-of-1 observational studies. Combined with pragmatic trial confirmation (based on evidence from 108+ embedded trials), this two-stage framework would generate validated outcome labels at 44.1x lower cost than traditional Phase III trials. This enables continuous, population-scale pharmacovigilance and precision dosing recommendations.

162.

International Diabetes Federation. Annual deaths from diabetes. International Diabetes Federation https://diabetesatlas.org/ (2024)

Diabetes | 2M deaths/year Additional sources: https://diabetesatlas.org/ | https://www.who.int/news-room/fact-sheets/detail/diabetes

163.

Furuyama, K. et al. Endogenous reprogramming of alpha cells into beta cells, induced by viral gene therapy, reverses autoimmune diabetes. Cell Stem Cell 24, 87–100 (2019)

Used AAV-mediated gene therapy to deliver Pdx1 and MafA to mouse pancreas, reprogramming alpha cells into functional insulin-producing beta cells. Reversed autoimmune diabetes in mice, demonstrating gene therapy potential for T1D reversal.

164.

DiMasi, J. A., Grabowski, H. G. & Hansen, R. W. Innovation in the pharmaceutical industry: New estimates of r&d costs. Journal of Health Economics https://doi.org/10.1016/j.jhealeco.2016.01.012 (2016) doi:10.1016/j.jhealeco.2016.01.012.

165.

NYU Stern. Lobbying spending and returns for disease advocacy groups. NYU Stern: Lobbying Influences NIH Funding https://www.stern.nyu.edu/experience-stern/news-events/new-research-finds-special-interest-lobbying-does-influence-nih-research-funding (2024)

Each $1,000 spent on lobbying correlated with $25,000 funding increase following year (53 diseases, 19 years) Rare disease advocates increased NIH rare-disease funding 3-15%/year (1998-2008) via millions in lobbying Specific examples: Alzheimer’s Association secured $100M NIH increase (FY2024); ME/CFS Initiative helped secure >$1B for long-COVID General ratio: Disease advocacy lobbying yields significant ROI, though specific "$100M → $1.8B" not verified Additional sources: https://www.stern.nyu.edu/experience-stern/news-events/new-research-finds-special-interest-lobbying-does-influence-nih-research-funding | https://www.nature.com/articles/515019a | https://www.alz.org/news/2024/congress-bipartisan-funding-alzheimers-research

166.

WHO. Annual global economic burden of alzheimer’s and other dementias. WHO: Dementia Fact Sheet https://www.who.int/news-room/fact-sheets/detail/dementia (2019)

Global cost: $1.3 trillion (2019 WHO-commissioned study) 50% from informal caregivers (family/friends, 5 hrs/day) 74% of costs in high-income countries despite 61% of patients in LMICs $818B (2010) → $1T (2018) → $1.3T (2019) - rapid growth Note: Costs increased 35% from 2010-2015 alone. Informal care represents massive hidden economic burden Additional sources: https://www.who.int/news-room/fact-sheets/detail/dementia | https://alz-journals.onlinelibrary.wiley.com/doi/10.1002/alz.12901

167.

JAMA Oncology. Annual global economic burden of cancer. JAMA Oncology: Global Cost 2020-2050 https://jamanetwork.com/journals/jamaoncology/fullarticle/2801798 (2020)

2020-2050 projection: $25.2 trillion total ($840B/year average) 2010 annual cost: $1.16 trillion (direct costs only) Recent estimate: $3 trillion/year (all costs included) Top 5 cancers: lung (15.4%), colon/rectum (10.9%), breast (7.7%), liver (6.5%), leukemia (6.3%) Note: China/US account for 45% of global burden; 75% of deaths in LMICs but only 50.0% of economic cost Additional sources: https://jamanetwork.com/journals/jamaoncology/fullarticle/2801798 | https://www.nature.com/articles/d41586-023-00634-9

168.

Diabetes Care. Annual global economic burden of diabetes. Diabetes Care: Global Economic Burden https://diabetesjournals.org/care/article/41/5/963/36522/Global-Economic-Burden-of-Diabetes-in-Adults

2015: $1.3 trillion (1.8% of global GDP) 2030 projections: $2.1T-2.5T depending on scenario IDF health expenditure: $760B (2019) → $845B (2045 projected) 2/3 direct medical costs ($857B), 1/3 indirect costs (lost productivity) Note: Costs growing rapidly; expected to exceed $2T by 2030 Additional sources: https://diabetesjournals.org/care/article/41/5/963/36522/Global-Economic-Burden-of-Diabetes-in-Adults | https://doi.org/10.1016/S2213-8587(17)30097-9

169.

Cook, C., Cole, G., Asaria, P., Jabbour, R. & Francis, D. P. Annual global economic burden of heart disease. International Journal of Cardiology https://www.internationaljournalofcardiology.com/article/S0167-5273(13)02238-9/abstract (2014)

Heart failure alone: $108 billion/year (2012 global analysis, 197 countries) US CVD: $555B (2016) → projected $1.8T by 2050 LMICs total CVD loss: $3.7T cumulative (2011-2015, 5-year period) CVD is costliest disease category in most developed nations Note: No single $2.1T global figure found; estimates vary widely by scope and year Additional sources: https://www.ahajournals.org/doi/10.1161/CIR.0000000000001258

170.

Calculated from IHME Global Burden of Disease (2.55B DALYs) and global GDP per capita valuation. $109 trillion annual global disease burden.

The global economic burden of disease, including direct healthcare costs ($8.2 trillion) and lost productivity ($100.9 trillion from 2.55 billion DALYs × $39,570 per DALY), totals approximately $109.1 trillion annually.

171.

Barabási et al. Disease network overlap (network medicine). Barabási et al. https://www.nature.com/articles/nrg2918 (2011)

Diseases cluster on shared biological networks, meaning drugs for one condition may plausibly affect many others. Additional sources: https://www.nature.com/articles/nrg2918

172.

ScienceDaily. Global prevalence of chronic disease. ScienceDaily: GBD 2015 Study https://www.sciencedaily.com/releases/2015/06/150608081753.htm (2015)

2.3 billion individuals had more than five ailments (2013) Chronic conditions caused 74% of all deaths worldwide (2019), up from 67% (2010) Approximately 1 in 3 adults suffer from multiple chronic conditions (MCCs) Risk factor exposures: 2B exposed to biomass fuel, 1B to air pollution, 1B smokers Projected economic cost: $47 trillion by 2030 Note: 2.3B with 5+ ailments is more accurate than "2B with chronic disease." One-third of all adults globally have multiple chronic conditions Additional sources: https://www.sciencedaily.com/releases/2015/06/150608081753.htm | https://pmc.ncbi.nlm.nih.gov/articles/PMC10830426/ | https://pmc.ncbi.nlm.nih.gov/articles/PMC6214883/

173.

Calculated from Orphanet Journal of Rare Diseases (2024). Diseases getting first effective treatment each year. Calculated from Orphanet Journal of Rare Diseases (2024) https://ojrd.biomedcentral.com/articles/10.1186/s13023-024-03398-1 (2024)

Under the current system, approximately 10-15 diseases per year receive their FIRST effective treatment. Calculation: 5% of 7,000 rare diseases ( 350) have FDA-approved treatment, accumulated over 40 years of the Orphan Drug Act = 9 rare diseases/year. Adding 5-10 non-rare diseases that get first treatments yields 10-20 total. FDA approves 50 drugs/year, but many are for diseases that already have treatments (me-too drugs, second-line therapies). Only 15 represent truly FIRST treatments for previously untreatable conditions.

174.

Disley, E., Rubin, J., Scraggs, E., Burrowes, N. & Culley, D. Lessons learned from the planning and early implementation of the social impact bond at HMP peterborough. (2011).

175.

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Global military spending: $2.7 trillion (2024, SIPRI) Global government medical research: $68 billion (2024) Actual ratio: 39.7:1 in favor of weapons over medical research Military R&D alone: $85B (2004 data, 10% of global R&D) Military spending increases crowd out health: 1% ↑ military = 0.62% ↓ health spending Note: Ratio actually worse than 36:1. Each 1% increase in military spending reduces health spending by 0.62%, with effect more intense in poorer countries (0.962% reduction) Additional sources: https://www.sipri.org/commentary/blog/2016/opportunity-cost-world-military-spending | https://pmc.ncbi.nlm.nih.gov/articles/PMC9174441/ | https://www.congress.gov/crs-product/R45403

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U.S. Department of Defense. Senior officials outline president’s proposed FY26 defense budget. U.S. Department of Defense https://www.war.gov/News/News-Stories/Article/article/4227847/senior-officials-outline-presidents-proposed-fy26-defense-budget/ (2025).

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179.

DOT. DOT value of statistical life ($13.6M). DOT: VSL Guidance 2024 https://www.transportation.gov/office-policy/transportation-policy/revised-departmental-guidance-on-valuation-of-a-statistical-life-in-economic-analysis (2024)

Current VSL (2024): $13.7 million (updated from $13.6M) Used in cost-benefit analyses for transportation regulations and infrastructure Methodology updated in 2013 guidance, adjusted annually for inflation and real income VSL represents aggregate willingness to pay for safety improvements that reduce fatalities by one Note: DOT has published VSL guidance periodically since 1993. Current $13.7M reflects 2024 inflation/income adjustments Additional sources: https://www.transportation.gov/office-policy/transportation-policy/revised-departmental-guidance-on-valuation-of-a-statistical-life-in-economic-analysis | https://www.transportation.gov/regulations/economic-values-used-in-analysis

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McDonald, C. M. et al. A randomized placebo-controlled phase 3 trial of drisapersen in duchenne muscular dystrophy. Neuromuscular Disorders 27, 1021–1029 (2017)

Phase III trial of drisapersen for Duchenne muscular dystrophy failed to show clinical benefit (P=0.415). FDA rejected approval in 2016 due to safety concerns including thrombocytopenia in 2% of patients, renal toxicity, and injection site reactions in 79% of patients. BioMarin discontinued development. Example of regulatory system preventing approval of ineffective drug with serious adverse effects.

183.

Tufts CSDD. Cost of drug development.

Various estimates suggest $1.0 - $2.5 billion to bring a new drug from discovery through FDA approval, spread across 10 years. Tufts Center for the Study of Drug Development often cited for $1.0 - $2.6 billion/drug. Industry reports (IQVIA, Deloitte) also highlight $2+ billion figures.

184.

Drugs.com. Time to develop one drug: 17 years. Drugs.com https://www.drugs.com/fda-approval-process.html

Time to develop one drug: 17 years Additional sources: https://www.drugs.com/fda-approval-process.html | https://www.fdareview.org/issues/the-drug-development-and-approval-process/

185.

Wikipedia. Drug price competition and patent term restoration act of 1984. Wikipedia: Hatch-Waxman Act https://en.wikipedia.org/wiki/Drug_Price_Competition_and_Patent_Term_Restoration_Act

Also known as: Hatch-Waxman Act (Public Law 98-417) Signed by Reagan: September 24, 1984 Sponsors: Rep. Henry Waxman (CA) and Sen. Orrin Hatch (UT) Created modern generic drug regulation system via Abbreviated New Drug Applications (ANDAs) Patent term extension: Up to 5 years (max 14 years total from approval) Generic incentive: 180 days market exclusivity for first paragraph IV certification 5-year data exclusivity for new chemical entities Note: Landmark legislation balancing generic access with innovation incentives. Generic manufacturers only need to show bioequivalence, not repeat clinical trials Additional sources: https://en.wikipedia.org/wiki/Drug_Price_Competition_and_Patent_Term_Restoration_Act | https://www.congress.gov/bill/98th-congress/house-bill/3605 | https://www.everycrsreport.com/reports/R44643.html

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Broad Institute. Drug repurposing hub (broad institute). Broad Institute https://www.broadinstitute.org/drug-repurposing-hub (2017)

The Drug Repurposing Hub contains 4,707 hand-curated compounds (later expanded to 6,801), including 3,422 drugs that are marketed or have been in clinical trials. The collection includes 1,988 approved/marketed drugs and 1,348 compounds that cleared at least phase 1 clinical testing. Additional sources: https://www.broadinstitute.org/drug-repurposing-hub | https://pmc.ncbi.nlm.nih.gov/articles/PMC5568558/

187.

Nature Medicine. Drug repurposing rate ( 30%). Nature Medicine https://www.nature.com/articles/s41591-024-03233-x (2024)

Approximately 30% of drugs gain at least one new indication after initial approval. Additional sources: https://www.nature.com/articles/s41591-024-03233-x

188.

Nature Reviews Drug Discovery. Drug trial success rate from phase i to approval. Nature Reviews Drug Discovery: Clinical Success Rates https://www.nature.com/articles/nrd.2016.136 (2016)

Overall Phase I to approval: 10-12.8% (conventional wisdom 10%, studies show 12.8%) Recent decline: Average LOA now 6.7% for Phase I (2014-2023 data) Leading pharma companies: 14.3% average LOA (range 8-23%) Varies by therapeutic area: Oncology 3.4%, CNS/cardiovascular lowest at Phase III Phase-specific success: Phase I 47-54%, Phase II 28-34%, Phase III 55-70% Note: 12% figure accurate for historical average. Recent data shows decline to 6.7%, with Phase II as primary attrition point (28% success) Additional sources: https://www.nature.com/articles/nrd.2016.136 | https://pmc.ncbi.nlm.nih.gov/articles/PMC6409418/ | https://academic.oup.com/biostatistics/article/20/2/273/4817524

189.

Drug Policy Alliance. The drug war by the numbers. (2021)

Since 1971, the war on drugs has cost the United States an estimated $1 trillion in enforcement. The federal drug control budget was $41 billion in 2022. Mass incarceration costs the U.S. at least $182 billion every year, with over $450 billion spent to incarcerate individuals on drug charges in federal prisons.

190.

Drutman, L. The Business of America Is Lobbying. (Oxford University Press, 2015). doi:10.1093/acprof:oso/9780190215514.001.0001.

191.

Duan, N., Kravitz, R. L. & Schmid, C. H. Single-patient (n-of-1) trials: A pragmatic clinical decision methodology. PubMed https://pubmed.ncbi.nlm.nih.gov/23849149/ (2013)

Single-patient trials (SPTs, a.k.a. n-of-1 trials) are multiple-period crossover trials conducted within individual patients Application of 2,154 single-patient trials in 108 studies for diverse clinical conditions Conditions addressed: neuropsychiatric (36%), musculoskeletal (21%), pulmonary (13%) Published in Journal of Clinical Epidemiology, 66(8 Suppl): S21-S28 DOI: 10.1016/j.jclinepi.2013.04.006 Additional sources: https://pubmed.ncbi.nlm.nih.gov/23849149/ | https://pmc.ncbi.nlm.nih.gov/articles/PMC3972259/ | https://www.sciencedirect.com/science/article/pii/S089543561300156X

192.

Dunbar, R. I. M. Dunbar’s number. Dunbar https://doi.org/10.1016/0047-2484(92)90081-J (1992)

The cognitive limit to the number of people with whom one can maintain stable social relationships is approximately 150. Additional sources: https://doi.org/10.1016/0047-2484(92)90081-J

193.

eClinicalMedicine. Statins and polypill cost-effectiveness. eClinicalMedicine https://www.thelancet.com/journals/eclinm/article/PIIS2589-5370(22)00155-2/fulltext)00155-2/fulltext (2022)

Polypill strategy was cost-effective compared to other strategies for most sub-groups, ranging from dominance (cost-saving) to £18,811 per QALY. Standard statin was cost-effective across all categories with incremental cost per QALY from £280 to £8,530. In high-risk populations, polypill and statin interventions are often cost-saving. Additional sources: https://www.thelancet.com/journals/eclinm/article/PIIS2589-5370(22)00155-2/fulltext)00155-2/fulltext

194.

EPI. Education investment economic multiplier (2.1). EPI: Public Investments Outside Core Infrastructure https://www.epi.org/publication/bp348-public-investments-outside-core-infrastructure/

Early childhood education: Benefits 12X outlays by 2050; $8.70 per dollar over lifetime Educational facilities: $1 spent → $1.50 economic returns Energy efficiency comparison: 2-to-1 benefit-to-cost ratio (McKinsey) Private return to schooling: 9% per additional year (World Bank meta-analysis) Note: 2.1 multiplier aligns with benefit-to-cost ratios for educational infrastructure/energy efficiency. Early childhood education shows much higher returns (12X by 2050) Additional sources: https://www.epi.org/publication/bp348-public-investments-outside-core-infrastructure/ | https://documents1.worldbank.org/curated/en/442521523465644318/pdf/WPS8402.pdf | https://freopp.org/whitepapers/establishing-a-practical-return-on-investment-framework-for-education-and-skills-development-to-expand-economic-opportunity/

195.

Eggers, A. C. & Hainmueller, J. MPs for sale? Returns to office in postwar british politics. American Political Science Review 103, 513–533 (2009).

196.

U.S. Food and Drug Administration. FDA eliminates major barrier to using real-world evidence in drug and device application reviews. (2025).

197.

Ramsberg, J. & Platt, R. Opportunities and barriers for pragmatic embedded trials: Triumphs and tribulations. Harvard Medical School/Harvard Pilgrim Health Care Institute https://pmc.ncbi.nlm.nih.gov/articles/PMC6508852/ (2018)

Meta-analysis of 108 embedded pragmatic clinical trials (2006-2016). The median cost per patient was $97 (mean $478) across all trials reviewed. 25% of studies cost less than $19 per patient. US studies had higher median costs ($187 vs $27 non-US). Registry-based trials were less expensive than EHR-based trials. Traditional RCT comparison: $16,600/patient (Berndt & Cockburn 2014). The 108 trials had median enrollment of 5,540 patients with broad eligibility criteria. 81% used cluster randomization. Trials spanned 15 countries, infectious diseases (25%), cardiovascular (18%), diabetes (12%). Additional sources: https://pmc.ncbi.nlm.nih.gov/articles/PMC6508852/

198.

Costs of War Project, Brown University Watson Institute. Environmental cost of war ($100B annually). Brown Watson Costs of War: Environmental Cost https://watson.brown.edu/costsofwar/costs/social/environment

War on Terror emissions: 1.2B metric tons GHG (equivalent to 257M cars/year) Military: 5.5% of global GHG emissions (2X aviation + shipping combined) US DoD: World’s single largest institutional oil consumer, 47th largest emitter if nation Cleanup costs: $500B+ for military contaminated sites Gaza war environmental damage: $56.4B; landmine clearance: $34.6B expected Climate finance gap: Rich nations spend 30X more on military than climate finance Note: Military activities cause massive environmental damage through GHG emissions, toxic contamination, and long-term cleanup costs far exceeding current climate finance commitments Additional sources: https://watson.brown.edu/costsofwar/costs/social/environment | https://earth.org/environmental-costs-of-wars/ | https://transformdefence.org/transformdefence/stats/

199.

EPA. EPA value of statistical life ($9.6M). EPA: Mortality Risk Valuation https://www.epa.gov/environmental-economics/mortality-risk-valuation (2017)

EPA 2010 Guidelines: $7.9M (2008 dollars) → $9.7M (2013 dollars/income adjusted) Current EPA VSL: $10 million (highest among federal agencies) Based on 1997 Clean Air Act analysis; updated for inflation/income but not methodology Uses wage-risk literature (21 studies) and stated preference studies (5 studies) Used in cost-benefit analyses for environmental, health, and safety regulations Note: $9.6-9.7M represents EPA’s VSL with inflation/income adjustments. Base methodology hasn’t been updated since 1997 Additional sources: https://www.epa.gov/environmental-economics/mortality-risk-valuation | https://www.rff.org/publications/working-papers/revisiting-the-environmental-protection-agencys-value-of-statistical-life/ | https://www.epa.gov/sites/default/files/2017-12/documents/ee-0483_all.pdf

200.

Economic Policy Institute. The productivity-pay gap. (2024)

Since 1979, net productivity has grown 64.6% while hourly compensation of production and nonsupervisory workers grew just 14.8%. If workers’ pay had kept pace with productivity, the median worker would earn approximately $10,000 more per year.

201.

e-Residency. Estonia e-residency statistics. e-Residency https://www.e-resident.gov.ee/dashboard/ (2024)

Estonia’s e-Residency program has issued digital identities to over 100,000 people from 170+ countries, demonstrating global-scale digital identity verification. Additional sources: https://www.e-resident.gov.ee/dashboard/

202.

EMA. EU compassionate use program for experimental drugs. EMA: Compassionate Use https://www.ema.europa.eu/en/human-regulatory-overview/research-development/compassionate-use

Established by: Article 83 of Regulation (EC) No 726/2004 Eligibility: Life-threatening, long-lasting, or seriously debilitating illnesses Requires: No satisfactory authorized treatment; medicine in trials or approval process EMA role: CHMP provides recommendations; national authorities implement programs Pan-European programs rare: Only 6 approved by EMA in last 10 years vs hundreds of national programs Each EU member state sets own rules and procedures Note: Pan-European framework exists but rarely used due to complex navigation across varying national regulations. Most programs remain country-specific Additional sources: https://www.ema.europa.eu/en/human-regulatory-overview/research-development/compassionate-use | https://pmc.ncbi.nlm.nih.gov/articles/PMC5116859/ | https://www.eurordis.org/information-support/compassionate-use/

203.

EU Digital Strategy. EU eIDAS network for electronic identification. EU Digital Strategy: eIDAS Regulation https://digital-strategy.ec.europa.eu/en/policies/eidas-regulation (2014)

eIDAS = Electronic IDentification, Authentication and trust Services Regulation (EU) No 910/2014 - establishes framework for digital identity/authentication Mutual recognition: Member states must recognize each other’s national eID schemes Interoperability: Technology-neutral framework enabling seamless cross-border authentication Levels of Assurance (LoA): Low, substantial, or high confidence in identification eIDAS 2.0: Introduces European Digital Identity Wallets (EUDI Wallets) - standardized throughout EU Citizens/businesses can use eIDs from one member state to access services in another Note: eIDAS 2.0 enhances original framework with digital identity wallets operating seamlessly across all EU member states. Crucial for secure cross-border electronic transactions Additional sources: https://digital-strategy.ec.europa.eu/en/policies/eidas-regulation | https://eur-lex.europa.eu/eli/reg/2014/910/oj/eng | https://en.wikipedia.org/wiki/EIDAS

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Publications Office of the European Union. EUR-lex: Access to european union law. (2025).

205.

Lieberman, D. Evolutionary mismatch and modern disease. Lieberman https://www.penguinrandomhouse.com/books/206671/the-story-of-the-human-body-by-daniel-e-lieberman/ (2013)

Many modern diseases result from a mismatch between our evolutionary adaptations and current environments, particularly regarding diet and physical activity. Additional sources: https://www.penguinrandomhouse.com/books/206671/the-story-of-the-human-body-by-daniel-e-lieberman/

206.

Environmental Working Group. US farm subsidy database and analysis. Environmental Working Group https://farm.ewg.org/ (2024)

US agricultural subsidies total approximately $30 billion annually, but create much larger economic distortions. Top 10% of farms receive 78% of subsidies, benefits concentrated in commodity crops (corn, soy, wheat, cotton), environmental damage from monoculture incentivized, and overall deadweight loss estimated at $50-120 billion annually. Additional sources: https://farm.ewg.org/ | https://www.ers.usda.gov/topics/farm-economy/farm-sector-income-finances/government-payments-the-safety-net/

207.

Environmental Working Group. Triple dipping: Budget bill raises farm subsidies for wealthy farmers by billions of dollars. (2024).

208.

PMC. Estimated excess deaths attributed to FDA’s COVID-19 response. PMC: EUAs vs FDA Approval Implications https://pmc.ncbi.nlm.nih.gov/articles/PMC8101583/

FDA regulations restricted clinician/patient access to COVID-19 testing, remdesivir, vaccines General drug delay estimate: 37,000-76,000 deaths per one-year delay Testing delays: By May 2020, 400+ applications awaiting FDA review Seattle lab ordered to stop testing Feb 16 for lack of FDA approval Gates Foundation partnership instructed to discontinue testing May 2020 until authorization EUA process prevented months of vaccine/testing delays Note: Specific "500,000+" figure not found in sources. Research shows FDA testing restrictions caused weeks-to-months of critical delays (Feb-March 2020). One-year drug delay = 37-76K deaths Additional sources: https://pmc.ncbi.nlm.nih.gov/articles/PMC8101583/ | https://pmc.ncbi.nlm.nih.gov/articles/PMC8012986/ | https://www.yalelawjournal.org/forum/deadly-delay-the-fdas-role-in-americas-covid-testing-debacle

209.

Responsible Statecraft. F-35 cost compared to global rare disease research funding. Responsible Statecraft: F-35 Cost $2T https://responsiblestatecraft.org/f35-cost/

Single F-35 cost: $82M (flyaway) to $110-136M (with ancillary costs) NIH rare disease funding (FY2023): $6.9 billion (world’s largest public biomedical research funder) NIH rare disease funding = <0.1% of NIH’s $48B annual budget Comparison: 63 F-35s = 1 year of US rare disease research funding F-35 total program cost: $2.1 trillion lifetime (2,456 aircraft through 2088) Note: One F-35 ($110-136M) doesn’t exceed annual rare disease funding ($6.9B), but claim illustrates stark military vs medical research disparity. 63 F-35s = entire year of rare disease research Additional sources: https://responsiblestatecraft.org/f35-cost/ | https://www.statista.com/statistics/713320/rare-diseases-funding-by-the-national-institutes-for-health/ | https://armscontrolcenter.org/f-35-joint-strike-fighter-costs-challenges/

210.

GAO. F-35 program lifetime cost: $1.7 trillion. GAO: F-35 Sustainment Costs https://www.gao.gov/products/gao-24-106703 (2024)

F-35 Program lifetime cost: $2.1 trillion (updated April 2024) Sustainment costs: $1.58 trillion (44% increase from 2018 estimate) Procurement costs: $422 billion Covers 94 years of operation (through 2088) for 2,456 aircraft Note: About half the cost increase is due to inflation. This makes the F-35 one of the most expensive military acquisition programs in modern history Additional sources: https://www.gao.gov/products/gao-24-106703 | https://breakingdefense.com/2024/04/f-35-programs-lifetime-price-tag-tops-2-trillion-pentagon-wants-jets-to-fly-longer/

211.

Drugs.com. FDA drug approval timeline. Drugs.com: FDA Drug Approval Process https://www.drugs.com/fda-approval-process.html

Full timeline (preclinical to market): 12-15 years average (10-15 years common range) Preclinical phase: 3-7 years Clinical development + NDA review: 9 years NDA review alone: 10 months average (standard); 6 months (priority review) Historical (pre-PDUFA): 21-29 months for NDA review Note: "10 years" is accurate for total development timeline (10-15 year range). Modern FDA review is faster (10 months) thanks to PDUFA, but overall timeline remains 12-15 years Additional sources: https://www.drugs.com/fda-approval-process.html | https://www.fdareview.org/issues/the-drug-development-and-approval-process/ | https://pmc.ncbi.nlm.nih.gov/articles/PMC6113340/

212.

FDA. FDA-approved prescription drug products (20,000+). FDA https://www.fda.gov/media/143704/download

There are over 20,000 prescription drug products approved for marketing. Additional sources: https://www.fda.gov/media/143704/download

213.

CNN. FDA delay in approving rapid COVID-19 tests. CNN: How Government Delayed Testing https://www.cnn.com/2020/04/09/politics/coronavirus-testing-cdc-fda-red-tape-invs/index.html (2020)

Feb 16, 2020: Seattle research lab ordered to stop COVID testing without FDA approval May 2020: Gates Foundation partnership instructed to discontinue testing until authorization Feb 29, 2020: U. Nebraska finally got FDA permission after Feb 4 special permission Timeline: Critical delays measured in weeks-to-months (Feb-March 2020), not specific "6 months FDA guidance suggested EUAs needed for laboratory-developed tests (LDTs), causing delays By May 2020: 400+ test applications awaiting FDA review Note: Delays were weeks-to-months during critical Feb-March 2020 period, not continuous "6 months." FDA intervention added minimal value while contributing to deadly delays Additional sources: https://www.cnn.com/2020/04/09/politics/coronavirus-testing-cdc-fda-red-tape-invs/index.html | https://www.yalelawjournal.org/forum/deadly-delay-the-fdas-role-in-americas-covid-testing-debacle | https://oig.hhs.gov/oei/reports/OEI-01-20-00380.asp

214.

FDA. FDA GRAS list count ( 570-700). FDA https://www.fda.gov/food/generally-recognized-safe-gras/gras-notice-inventory

The FDA GRAS (Generally Recognized as Safe) list contains approximately 570–700 substances. Additional sources: https://www.fda.gov/food/generally-recognized-safe-gras/gras-notice-inventory

215.

Stone, W. FDA advisers reject MDMA as treatment for PTSD. NPR https://www.npr.org/sections/shots-health-news/2024/06/04/nx-s1-4991112/mdma-therapy-ptsd-fda-advisors (2024).

216.

U.S. Food and Drug Administration. FDA declines to approve MDMA-assisted therapy for PTSD. (2024).

217.

CRS. Evidence of FDA regulatory capture by pharmaceutical industry. CRS: FDA Human Medical Product User Fees https://www.congress.gov/crs-product/R44750

FY2023: User fees = 75% of PDUFA program costs (vs 7% in FY1993) FY2022: User fees = 66% ($1.4B) of human drugs program budget FY2022: User fees = 46% ($2.9B) of FDA’s total $6.2B budget Pharma finances 75% of FDA’s drug division (New York Times) Concerns: Budgetary dependence, urgency of PDUFA reauthorizations, required industry participation in negotiations Most PDUFA policy changes favor industry: decreased regulatory standards, shorter approval times, increased industry involvement FDA maintains decisions based on science, not fee collection ability Note: Regulatory capture concerns well-documented. Industry funding grew from 7% (1993) to 75% (2023) of drug review program. No evidence found for "10x government salary" claim for FDA reviewers Additional sources: https://www.congress.gov/crs-product/R44750 | https://aspe.hhs.gov/sites/default/files/documents/e4a7910607c0dd76c40aa61151d154f9/FDA-User-Fee-Issue-Brief.pdf | https://pmc.ncbi.nlm.nih.gov/articles/PMC8917050/

218.

Wikipedia. Number of key FDA drug reviewers. Wikipedia: Center for Drug Evaluation and Research https://en.wikipedia.org/wiki/Center_for_Drug_Evaluation_and_Research

CDER review teams: 1,300 employees evaluate and approve new drugs CDER safety team: 72 employees monitor 3,000+ prescription drugs for 200 million people ($15M/year budget) FDA Advisory Committees (all 3 centers): 300 individuals serve on 40 committees Advisory committees stable in recent years Note: " 200" may refer to advisory committee members ( 300 actual) or be approximation. CDER has 1,300 review staff total. Safety monitoring: 72 people for 200M patients Additional sources: https://en.wikipedia.org/wiki/Center_for_Drug_Evaluation_and_Research | https://www.ncbi.nlm.nih.gov/books/NBK236088/

219.

FDA. FDA sentinel initiative. FDA: Sentinel Initiative https://www.fda.gov/safety/fdas-sentinel-initiative

Launched: May 2008 in response to FDAAA 2007; transitioned to full system Feb 2016 Purpose: Active post-market risk identification and analysis (ARIA) for medical products Scale: World’s largest multisite distributed database for medical product safety; 128.7M members Data sources: Insurance claims, electronic health records, patient reports Privacy: Distributed data approach - data remains with owners, patient identifiers removed Structure (2019): 3 coordinating centers - Operations, Innovation, Community Building/Outreach Real-World Evidence: RWE Data Enterprise (RWE-DE) - 25.5M lives (21M commercial + 4.5M academic) 2008-2014: FDA mandated 657 studies under FDAAA authority Note: Major advancement in post-market surveillance. "Limited Transparency and Bureaucratic Constraints" may refer to challenges, but system represents significant FDA capability improvement Additional sources: https://www.fda.gov/safety/fdas-sentinel-initiative | https://pmc.ncbi.nlm.nih.gov/articles/PMC9667154/ | https://en.wikipedia.org/wiki/Sentinel_Initiative

220.

Ballentine, C. The sulfanilamide disaster. FDA Consumer https://www.fda.gov/files/about%20fda/published/The-Sulfanilamide-Disaster.pdf (1981).

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FDA. FDA clinical trial launch timeline. FDA: IND Application Procedures https://www.fda.gov/drugs/investigational-new-drug-ind-application/ind-application-procedures-overview (2012)

IND application: FDA has 30 days to object or allow trials to begin NDA/BLA preparation after Phase 3: 6-12 months to assemble safety/effectiveness data Standard NDA review: 10-12 months median (standard review) Priority review: 6 months (vs 10 months standard) Overall development (first human testing to approval): 12-15 years full timeline Expedited programs: 7.1 years median vs 8.0 years nonexpedited Note: "6-12 months" likely refers to NDA/BLA preparation time post-Phase 3, not total trial launch timeline. IND review: 30 days. Full approval timeline: 10-15 years Additional sources: https://www.fda.gov/drugs/investigational-new-drug-ind-application/ind-application-procedures-overview | https://www.drugs.com/fda-approval-process.html | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5820715/

222.

FDA. FDA trial patient exclusion criteria. FDA: Evaluating Inclusion & Exclusion Criteria https://www.fda.gov/media/134754/download

Most frequent exclusions: Pregnancy, lactation/breastfeeding, renal/hepatic abnormalities, specific infectious diseases Pregnant/lactating women: >90% of trials exclude Older adults: 27% exclude based on age (arbitrary upper limits) Patients with organ dysfunction: Excluded due to adverse impact concerns from comorbidities/concomitant meds Multiple chronic conditions: Often exclusion criterion despite being common in target population Children/adolescents: Excluded due to ethical considerations High-risk patients: Prior malignancy history, active brain metastases, suboptimal hepatic/renal function, HIV+ FDA guidance: Working to broaden eligibility; "exclusions based on age alone rarely appropriate Note: Exclusion criteria often eliminate patients who would actually use the drug, reducing real-world applicability of trial results Additional sources: https://www.fda.gov/media/134754/download | https://www.sciencedirect.com/science/article/abs/pii/S1551714421002512 | https://ascopubs.org/doi/10.1200/EDBK_155880

223.

PMC. Paperwork comparison between FDA trials and RECOVERY trial. PMC: Making Trials Part of Good Clinical Care - RECOVERY https://pmc.ncbi.nlm.nih.gov/articles/PMC8285150/

RECOVERY trial paperwork: One-page consent form, one-page case report form, single follow-up form Randomisation form: Simple, collecting few baseline characteristics and ensuring eligibility Follow-up: Single form completed at earliest of discharge, death, or 28 days Eligibility criteria: Simple; trial processes (including paperwork) minimized Philosophy: "Avoid additional burden on busy clinicians, so trial procedures streamlined as far as possible FDA Form 1572: Statement of Investigator form required for IND trials (specific form, not total page count) Note: Specific "1,572 pages vs 24 pages" comparison not found in sources. RECOVERY used 1-page forms. FDA Form 1572 is a specific required form, not total paperwork count. RECOVERY’s streamlined approach demonstrated feasibility of simplified trial documentation Additional sources: https://pmc.ncbi.nlm.nih.gov/articles/PMC8285150/ | https://pmc.ncbi.nlm.nih.gov/articles/PMC9293394/ | https://www.fda.gov/media/71816/download

224.

Federal Election Commission. Statistical summary of 24-month campaign activity of the 2023-2024 election cycle. (2023)

Presidential candidates raised $2 billion; House and Senate candidates raised $3.8 billion and spent $3.7 billion; PACs raised $15.7 billion and spent $15.5 billion. Total federal campaign spending approximately $20 billion. Additional sources: https://www.fec.gov/updates/statistical-summary-of-24-month-campaign-activity-of-the-2023-2024-election-cycle/

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Batty, M., Deeken, E. & Henriques Volz, A. Wealth inequality and COVID-19: Evidence from the distributional financial accounts. (2021)

Nearly 90% of top 1% wealth gain during the COVID-19 rebound (2020Q1 to 2021Q1) came from corporate equities. Only one-third of bottom 50% households own any public equity. Households gained over $18 trillion in wealth since the beginning of 2020, with asset-price increases accounting for nearly 80% of wealth accumulation.

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Forbes identified a record 2,781 billionaires worldwide with combined net worth of $14.2 trillion, 141 more than 2023. Bernard Arnault (LVMH) topped the list at $233 billion.

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Pragmatic trials are designed to determine the effects of an intervention under the usual conditions in which it will be applied. The ALLHAT trial (Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial) demonstrated that pragmatic designs can identify superior treatments while reducing healthcare costs by billions annually.

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Finance and insurance value added as share of GDP. Q3 2025: 8.0%. Historical low approximately 4% in early 1970s.

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Net worth held by the top 1% of households. Q4 2019: $33.4 trillion. Q4 2020: $37.6 trillion. Increase of $4.2 trillion during 2020.

233.

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Federal Reserve total assets (WALCL). Pre-QE March 2020: $4.2 trillion. Peak mid-2022: $8.97 trillion. Approximately $4 trillion created beginning March 2020.

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Since 9/11/2001: Americans no more likely to die from terrorism than being crushed by unstable TVs/furniture Furniture tip-over fatalities (2000-present): 581 total; 4 in 5 deaths were children 2013-2023: 217 reported tip-over fatalities (23% TV, 25% TV+furniture, 46% furniture only, 7% appliance) Comparison: Even in Israel (intensive terror campaign), weekly terror casualties almost never match traffic deaths US terrorism: Deaths so low they barely register on graphs except 9/11/2001 Note: Post-9/11, furniture tip-overs have caused comparable/greater fatalities than terrorism for Americans. Highlights media attention vs actual risk disparity Additional sources: https://www.washingtonpost.com/news/monkey-cage/wp/2015/11/23/youre-more-likely-to-be-fatally-crushed-by-furniture-than-killed-by-a-terrorist/ | https://www.cpsc.gov/s3fs-public/2023_Annual_Tip_Over_Report_Posted_2024Feb_FINAL_0.pdf | https://ourworldindata.org/is-it-fair-to-compare-terrorism-and-disaster-with-other-causes-of-death

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The HealthCare.gov website and federal health insurance exchange infrastructure had initial development and deployment costs estimated at $1.7 to $2.1 billion during the 2010-2014 period, though exact figures remain uncertain due to complexity of federal contracting and multiple agencies involved. Additional sources: https://www.gao.gov/assets/gao-07-49.pdf

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GAO. GAO reports an estimated $162 billion in improper payments across the federal government in fiscal year 2024. (2024).

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Current (July 31, 2025): $86 billion (unaudited); Dec 31, 2024: $77.2 billion 2022: $70 billion (with new gifts added) Total contributions: Bill & Melinda Gates $60.2B (inception-2024); Warren Buffett $43.3B (2006-2024) Structure: Gates Foundation Trust manages endowment; Gates Foundation conducts operations/grantmaking World’s largest private philanthropic foundation Intent: Spend endowment "down to zero" within 20 years of Bill & Melinda’s deaths Annual payout (2026): $9B/year (50% increase announced 2022) Note: $70B figure accurate for 2022. Endowment has since grown to $86B (July 2025). Dramatic growth from major contributions by Gates + Buffett Additional sources: https://www.gatesfoundation.org/about/foundation-fact-sheet | https://fortune.com/2024/01/25/bill-gates-foundation-annual-letter-elite-universities-chuck-feeney/

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Estimates approximately 5 million total deaths in the Napoleonic Wars, including military and civilian casualties across all belligerents.

244.

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Disability weights for 235 health states used in Global Burden of Disease calculations. Weights range from 0 (perfect health) to 1 (death equivalent). Chronic conditions like diabetes (0.05-0.35), COPD (0.04-0.41), depression (0.15-0.66), and cardiovascular disease (0.04-0.57) show substantial variation by severity. Treatment typically reduces disability weights by 50-80 percent for manageable chronic conditions.

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Gibbard proved that any deterministic voting scheme with at least three possible outcomes is either dictatorial or manipulable (i.e., voters can sometimes benefit by misrepresenting their preferences). This result, proven independently by Satterthwaite (1975), establishes fundamental limits on voting mechanisms: strategic voting cannot be eliminated from any non-trivial democratic system. The theorem has profound implications for mechanism design and social choice theory.

250.

FEE. Patients and doctors vs FDA. FEE: Patients and Doctors vs FDA https://fee.org/articles/patients-and-doctors-vs-the-fda

Dale Gieringer (1985): 21,000-120,000 lives lost per decade from FDA delay Gieringer: "Loss of life from delay alone in the hundreds of thousands" (not millions) Beta-blockers alone: William Wardell estimated "10,000 lives/year" if allowed; FDA delay 1965-1976 Sam Peltzman: Post-1962 death toll from regulatory delay "easily number in thousands per year Practolol (beta-blocker): "Could save 10,000 lives/year" (Wardell estimate) FDA allowed propranolol 1968 (3 years after Europe); for hypertension/angina not until 1978 Note: "4-10 million" figure not found in sources. Gieringer’s estimates: 21K-120K deaths per decade, "hundreds of thousands" total (not millions). Specific drug delays (beta-blockers): 100K deaths estimated Additional sources: https://fee.org/articles/patients-and-doctors-vs-the-fda | https://www.econlib.org/library/Enc/DrugLag.html | https://www.fdareview.org/issues/theory-evidence-and-examples-of-fda-harm/

251.

Gilens, M. & Page, B. I. Testing theories of american politics: Elites, interest groups, and average citizens. Perspectives on Politics 12, 564–581 (2014).

252.

Gitcoin. Gitcoin passport for digital identity scoring. Gitcoin: Intro to Passport https://www.gitcoin.co/blog/intro-to-passport

Now: Human Passport (acquired by human.tech late 2024); >2M users Purpose: Sybil resistance solution for web3, privacy-preserving identity verification How it works: "Stamps" from web2/web3 identifiers (Twitter, Google, BrightID, Proof of Humanity) aggregated into unique identity score Scoring: Weights based on "cost of forgery" and ability to signal unique humanity Privacy: Verifiable credentials check identity without viewing PII Customizable: Communities create custom "entry visa" with participation requirements Use cases: Governance voting, gaming, airdrops, bot prevention Gitcoin Grants Round 15: 35,000+ donors created Passports; limited Sybil activity, ensured fair fund distribution Note: Leading web3 identity/Sybil resistance tool. Now operates as Human Passport after acquisition. Proven at scale with millions of users Additional sources: https://www.gitcoin.co/blog/intro-to-passport | https://passport.human.tech/ | https://www.gitcoin.co/blog/cost-of-forgery

253.

GiveWell. GiveWell cost per life saved for top charities (2024). GiveWell: Top Charities https://www.givewell.org/charities/top-charities

General range: $3,000-$5,500 per life saved (GiveWell top charities) Helen Keller International (Vitamin A): $3,500 average (2022-2024); varies $1,000-$8,500 by country Against Malaria Foundation: $5,500 per life saved New Incentives (vaccination incentives): $4,500 per life saved Malaria Consortium (seasonal malaria chemoprevention): $3,500 per life saved VAS program details: $2 to provide vitamin A supplements to child for one year Note: Figures accurate for 2024. Helen Keller VAS program has wide country variation ($1K-$8.5K) but $3,500 is accurate average. Among most cost-effective interventions globally Additional sources: https://www.givewell.org/charities/top-charities | https://www.givewell.org/charities/helen-keller-international | https://ourworldindata.org/cost-effectiveness

254.

GiveWell. How much does it cost to save a life? (2024).

255.

Chalmers, I. & Glasziou, P. Avoidable waste in the production and reporting of research evidence. The Lancet 374, 86–89 (2009)

An estimated 85% of research investment is wasted. Over 50% of studies are never published. Of $200 billion spent annually on biomedical research globally, approximately $170 billion is wasted through problems in research design, conduct, and reporting.

256.

Our World in Data. Global armed forces size and average salary. Our World in Data: Military Personnel & Spending https://ourworldindata.org/military-personnel-spending (2024)

Largest forces: China (2.0M active), India (1.4M), Russia (1.3M active, 3.5M total), US (1.3M active) Global military spending 2024: US $1T (next 12 countries combined); NATO 32 members: $1.5T (55% of world) Military spending per personnel: Tracked by SIPRI, World Bank (includes personnel, O&M, procurement, R&D, infrastructure, aid) Average varies widely: US military much higher per-personnel spending than most countries Note: Specific "28.4M global armed forces" and "$24,000 average salary" not confirmed in sources. Data available but highly variable by country. Major forces total 10M+ personnel among largest militaries Additional sources: https://ourworldindata.org/military-personnel-spending | https://data.worldbank.org/indicator/MS.MIL.TOTL.P1 | https://www.sipri.org/sites/default/files/2025-04/2504_fs_milex_2024.pdf

257.

The Conversation. Global cancer research spending ( $51.4B, 2016-2023). The Conversation https://theconversation.com/billions-spent-on-cancer-research-globally-but-is-it-money-well-spent-201407 (2023).

258.

Research and Markets. Global clinical trials market 2024. Research and Markets https://www.globenewswire.com/news-release/2024/04/19/2866012/0/en/Global-Clinical-Trials-Market-Research-Report-2024-An-83-16-Billion-Market-by-2030-AI-Machine-Learning-and-Blockchain-will-Transform-the-Clinical-Trials-Landscape.html (2024)

Global clinical trials market valued at approximately $83 billion in 2024, with projections to reach $83-132 billion by 2030. Additional sources: https://www.globenewswire.com/news-release/2024/04/19/2866012/0/en/Global-Clinical-Trials-Market-Research-Report-2024-An-83-16-Billion-Market-by-2030-AI-Machine-Learning-and-Blockchain-will-Transform-the-Clinical-Trials-Landscape.html | https://www.precedenceresearch.com/clinical-trials-market

259.

The Global Fund. The global fund. The Global Fund https://www.theglobalfund.org/en/about-the-global-fund/.

260.

Global Fund. Lives saved by the global fund. Global Fund: Results Report 2025 https://www.theglobalfund.org/en/results/ (2025)

2025: 70 million lives saved (current figure) Oct 2024: 65 million lives saved Sep 2022: 50 million lives saved over 20 years Death rate reduction: 63% combined death rate from AIDS, TB, malaria (61% since 2002) Since inception (2002): Partnership saved 70M lives fighting HIV, TB, malaria across 100+ countries Note: 50M was Sept 2022 figure. Current (2025): 70M lives saved. One of world’s most effective global health partnerships Additional sources: https://www.theglobalfund.org/en/results/ | https://www.theglobalfund.org/en/news/2022/2022-09-12-new-global-fund-report-shows-50-million-lives-saved-over-20-years-in-fight-against-hiv-tb-malaria/

261.

Statista. Global GDP ($101T, 2022). Statista https://www.statista.com/statistics/268750/global-gross-domestic-product-gdp/ (2023)

The global economy is projected to grow from about 101 trillion U.S. dollars in 2022 to about 139 trillion U.S. dollars in 2027. Additional sources: https://www.statista.com/statistics/268750/global-gross-domestic-product-gdp/

262.

World Bank. Global GDP in 2023 ($89.5 trillion). World Bank https://data.worldbank.org/indicator/NY.GDP.MKTP.CD (2023).

263.

Component country budgets. Global government medical research spending ($67.5B, 2023–2024). See component country budgets: NIH Budget https://www.nih.gov/about-nih/what-we-do/budget.

264.

Applied Clinical Trials. Global government spending on interventional clinical trials: $3-6 billion/year. Applied Clinical Trials https://www.appliedclinicaltrialsonline.com/view/sizing-clinical-research-market

Estimated range based on NIH ( $0.8-5.6B), NIHR ($1.6B total budget), and EU funding ( $1.3B/year). Roughly 5-10% of global market. Additional sources: https://www.appliedclinicaltrialsonline.com/view/sizing-clinical-research-market | https://www.thelancet.com/journals/langlo/article/PIIS2214-109X(20)30357-0/fulltext

265.

World Health Organization. Global health spending as a share of GDP (9.8%, 2020). World Health Organization https://www.who.int/publications/i/item/9789240064929 (2022).

266.

Wikipedia. Number of major global military facilities (4,435). Wikipedia: List of American Military Installations https://en.wikipedia.org/wiki/List_of_American_military_installations

US military bases worldwide: 750-877 (varies by source/definition) Conservative count: 128 military bases in 55 countries/territories (Feb 2025) Broader count: 750+ bases in 80+ countries; some sources cite 877 Large bases (>4 hectares or >$10M, >200 personnel): 439 (60% of US foreign bases) Small bases/"Lily Pads" (<4 hectares or <$10M): Remaining 40% Other nations: At least 18 other nations operate foreign military bases; NATO countries (France, UK): +200 locations Note: "4,435" not found in sources. US operates 750-877 bases overseas. May include domestic + all nations’ bases combined, but specific figure not verified Additional sources: https://en.wikipedia.org/wiki/List_of_American_military_installations | https://www.visualcapitalist.com/mapped-every-known-u-s-military-base-overseas/ | https://worldbeyondwar.org/military-empires/

267.

United Nations Department of Economic and Social Affairs, Population Division. World population prospects 2024: Summary of results. (2024)

The 2024 Revision of the World Population Prospects provides population estimates and projections for 237 countries or areas. Global median age approximately 30.5 years in 2024, reflecting population-weighted average across all regions.

268.

SIPRI. Global military spending ($2.72T, 2024). SIPRI https://www.sipri.org/publications/2025/sipri-fact-sheets/trends-world-military-expenditure-2024 (2025).

269.

C&EN. Annual number of new drugs approved globally: 50. C&EN https://cen.acs.org/pharmaceuticals/50-new-drugs-received-FDA/103/i2 (2025)

50 new drugs approved annually Additional sources: https://cen.acs.org/pharmaceuticals/50-new-drugs-received-FDA/103/i2 | https://www.fda.gov/drugs/development-approval-process-drugs/novel-drug-approvals-fda

270.

UN. Global population reaches 8 billion. UN: World Population 8 Billion Nov 15 2022 https://www.un.org/en/desa/world-population-reach-8-billion-15-november-2022 (2022)

Milestone: November 15, 2022 (UN World Population Prospects 2022) Day of Eight Billion" designated by UN Added 1 billion people in just 11 years (2011-2022) Growth rate: Slowest since 1950; fell under 1% in 2020 Future: 15 years to reach 9B (2037); projected peak 10.4B in 2080s Projections: 8.5B (2030), 9.7B (2050), 10.4B (2080-2100 plateau) Note: Milestone reached Nov 2022. Population growth slowing; will take longer to add next billion (15 years vs 11 years) Additional sources: https://www.un.org/en/desa/world-population-reach-8-billion-15-november-2022 | https://www.un.org/en/dayof8billion | https://en.wikipedia.org/wiki/Day_of_Eight_Billion

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1.9M participants annually (2022, post-COVID normalization from 4M peak in 2021) Additional sources: https://gmdpacademy.org/news/iqvia-report-clinical-trial-subjects-number-drops-due-to-decline-in-covid-19-enrollment/

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Top researchers can spend up to 50% of their time writing grants. Additional sources: https://acquisitiontalk.com/2021/12/top-researchers-spend-50-of-their-time-writing-grants-how-to-fix-it-and-what-it-means-for-dod/

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The WWC reviews existing research on different programs, products, practices, and policies in education to provide educators with the information they need to make evidence-based decisions.

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2023: 8,352 deaths (22% increase from 2022, highest since 2017) 2023: 3,350 terrorist incidents (22% decrease), but 56% increase in avg deaths per attack Global Terrorism Database (GTD): 200,000+ terrorist attacks recorded (2021 version) Maintained by: National Consortium for Study of Terrorism & Responses to Terrorism (START), U. of Maryland Geographic shift: Epicenter moved from Middle East to Central Sahel (sub-Saharan Africa) - now >50% of all deaths Additional sources: https://ourworldindata.org/terrorism | https://reliefweb.int/report/world/global-terrorism-index-2024 | https://www.start.umd.edu/gtd/ | https://ourworldindata.org/grapher/fatalities-from-terrorism

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A review of 48 regulatory impact analyses finds substantial variation in methodology and quality, with many failing to provide adequate justification for regulatory choices.

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Estimates of Soviet military spending as share of GDP ranged from 10-20%, with Harrison’s analysis settling on approximately 15-18% of GDP in the late Brezhnev era (late 1970s to early 1980s). Even within the Soviet Union itself, reliable figures were difficult to produce because the military budget involved multiple government ministries and official statistics systematically understated defense outlays.

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Singapore ranks sixth in the world in healthcare outcomes, yet spends proportionally less on healthcare than any other high-income country - less than one-fourth the cost of healthcare in the United States and about half that of Western European countries. At the heart of the Singapore model is its system of health savings accounts (Medisave, where 6.5-9

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Healthcare fiscal multiplier: 4.3 (95% CI: 2.5-6.1) during pre-recession period (1995-2007) Overall government spending multiplier: 1.61 (95% CI: 1.37-1.86) Why healthcare has high multipliers: No effect on trade deficits (spending stays domestic); improves productivity & competitiveness; enhances long-run potential output Gender-sensitive fiscal spending (health & care economy) produces substantial positive growth impacts Note: "1.8" appears to be conservative estimate; research shows healthcare multipliers of 4.3 Additional sources: https://pmc.ncbi.nlm.nih.gov/articles/PMC5954824/ | https://cepr.org/voxeu/columns/government-investment-and-fiscal-stimulus | https://ncbi.nlm.nih.gov/pmc/articles/PMC3849102/ | https://set.odi.org/wp-content/uploads/2022/01/Fiscal-multipliers-review.pdf

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295.

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Freely available online textbook on causal inference for scientists who design studies and analyze data Covers counterfactuals, DAGs, randomized experiments, confounding, selection bias, inverse probability weighting, g-estimation, instrumental variables Publisher: Chapman & Hall/CRC Continuously updated - current version available at author’s website Additional sources: https://www.hsph.harvard.edu/miguel-hernan/causal-inference-book/ | https://content.sph.harvard.edu/wwwhsph/sites/1268/2024/01/hernanrobins_WhatIf_2jan24.pdf | https://remlapmot.github.io/cibookex-r/

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US Inflation Calculator. Historical healthcare inflation rate (6.2%). US Inflation Calculator: Health Care 1948-2025 https://www.usinflationcalculator.com/inflation/health-care-inflation-in-the-united-states/ (1948)

Long-term average (1935-2025): 4.59% annual (per Consumer Price Index for Medical Care, BLS) 2000-2023: 3.5% average annual medical care cost inflation Medical Care Price Index (MCPI): 3.7% compound annual growth (past 2 decades) vs 2.6% for Personal Health Care (PHC) & PCE health indexes Recent (Aug 2025): 3.4% year-over-year health care price increase Additional sources: https://www.usinflationcalculator.com/inflation/health-care-inflation-in-the-united-states/ | https://www.in2013dollars.com/Medical-care/price-inflation | https://pmc.ncbi.nlm.nih.gov/articles/PMC5785315/ | https://ycharts.com/indicators/us_health_care_inflation_rate

301.

Our World in Data. Historical life expectancy around 30 years. Our World in Data: Life Expectancy https://ourworldindata.org/life-expectancy (2022)

Average life expectancy at birth: 30 years for most of human history until 1800s 1820: Global average still 30 years; 1800-2000: Rose from 30 to 67 years Context: Low life expectancy driven primarily by high infant mortality ( 1/3 of children died before age 5) Medieval England: Life expectancy at birth = 31.3 years, but life expectancy at age 25 = 25.7 additional years (total 50.7) Roman Egypt: Average in 20s, but many lived into 40s+ if they survived childhood Additional sources: https://ourworldindata.org/life-expectancy | https://pmc.ncbi.nlm.nih.gov/articles/PMC2625386/ | https://sc.edu/uofsc/posts/2022/08/conversation-old-age-is-not-a-modern-phenomenon.php | https://www.discovermagazine.com/the-sciences/what-was-the-life-expectancy-of-ancient-humans

302.

Greaney, B. Housing constraints and spatial misallocation: comment. American Economic Journal: Macroeconomics https://www.aeaweb.org/articles?id=10.1257/mac.20230141&from=f (2023).

303.

Caplan, B. Hsieh-moretti on housing regulation: A gracious admission of error. (2023).

304.

Hsieh, C.-T. & Moretti, E. Housing constraints and spatial misallocation. American Economic Journal: Macroeconomics https://www.aeaweb.org/articles?id=10.1257/mac.20170388 (2019)

We quantify the amount of spatial misallocation of labor across US cities and its aggregate costs. Tight land-use restrictions in high-productivity cities like New York, San Francisco, and Boston lowered aggregate US growth by 36% from 1964 to 2009. Local constraints on housing supply have had enormous effects on the national economy. Additional sources: https://www.aeaweb.org/articles?id=10.1257/mac.20170388

305.

NHGRI. Human genome project and CRISPR discovery. NHGRI https://www.genome.gov/11006929/2003-release-international-consortium-completes-hgp (2003)

Your DNA is 3 billion base pairs Read the entire code (Human Genome Project, completed 2003) Learned to edit it (CRISPR, discovered 2012) Additional sources: https://www.genome.gov/11006929/2003-release-international-consortium-completes-hgp | https://www.nobelprize.org/prizes/chemistry/2020/press-release/

306.

Hurwicz, L. On informationally decentralized systems. Decision and Organization 297–336 (1972).

307.

Sinn, M. P. Incentive Alignment Bonds: Making Public Goods Financially and Politically Profitable. https://iab.warondisease.org (2025) doi:10.5281/zenodo.18203221

Government spending is optimized for lobbying intensity, not net societal value. Programs with 100:1 benefit-cost ratios get billions while programs with negative returns get hundreds of billions. Incentive Alignment Bonds flip this by creating a capital pool that rewards politicians (via campaign support and post-office opportunities) for funding high-NSV programs over low-NSV alternatives. The result: public good becomes private profit for both investors and elected officials.

308.

ICAN. International campaign to abolish nuclear weapons (ICAN) - treaty on the prohibition of nuclear weapons (2017). ICAN https://www.icanw.org/ican_history (2017)

ICAN: Founded 2007, headquartered in Geneva, coordinating 468+ partner organizations across 100+ countries (as of 2017) Staff: 3 full-time + 2 part-time in Geneva office (when Nobel Prize awarded) Funding: Initial grant from Poola Foundation (Australia); Norwegian government grant to establish Geneva office (2011) Treaty on the Prohibition of Nuclear Weapons (TPNW): Adopted July 7, 2017 by vote of 122-1 at UN Achievement: Nobel Peace Prize 2017 "for its work to draw attention to the catastrophic humanitarian consequences of any use of nuclear weapons Additional sources: https://www.icanw.org/ican_history | https://en.wikipedia.org/wiki/International_Campaign_to_Abolish_Nuclear_Weapons | https://www.nobelprize.org/prizes/peace/2017/ican/facts/ | https://www.icanw.org/the_treaty

309.

ICRC. International campaign to ban landmines (ICBL) - ottawa treaty (1997). ICRC https://www.icrc.org/en/doc/resources/documents/article/other/57jpjn.htm (1997)

ICBL: Founded 1992 by 6 NGOs (Handicap International, Human Rights Watch, Medico International, Mines Advisory Group, Physicians for Human Rights, Vietnam Veterans of America Foundation) Started with ONE staff member: Jody Williams as founding coordinator Grew to 1,000+ organizations in 60 countries by 1997 Ottawa Process: 14 months (October 1996 - December 1997) Convention signed by 122 states on December 3, 1997; entered into force March 1, 1999 Achievement: Nobel Peace Prize 1997 (shared by ICBL and Jody Williams) Government funding context: Canada established $100M CAD Canadian Landmine Fund over 10 years (1997); International donors provided $169M in 1997 for mine action (up from $100M in 1996) Additional sources: https://www.icrc.org/en/doc/resources/documents/article/other/57jpjn.htm | https://en.wikipedia.org/wiki/International_Campaign_to_Ban_Landmines | https://www.nobelprize.org/prizes/peace/1997/summary/ | https://un.org/press/en/1999/19990520.MINES.BRF.html | https://www.the-monitor.org/en-gb/reports/2003/landmine-monitor-2003/mine-action-funding.aspx

310.

ICER. ICER QALY methodology and standards. ICER https://icer.org/our-approach/methods-process/cost-effectiveness-the-qaly-and-the-evlyg/ (2024)

The quality-adjusted life year (QALY) is the academic standard for measuring how well all different kinds of medical treatments lengthen and/or improve patients’ lives, and therefore the metric has served as a fundamental component of cost-effectiveness analyses in the US and around the world for more than 30 years. ICER’s health benefit price benchmark (HBPB) will continue to be reported using the standard range from $100,000 to $150,000 per QALY and per evLYG. Additional sources: https://icer.org/our-approach/methods-process/cost-effectiveness-the-qaly-and-the-evlyg/ | https://icer.org/wp-content/uploads/2024/02/Reference-Case-4.3.25.pdf

311.

ID.me. ID.me digital identity verification service. ID.me: Government Services https://www.id.me/individuals/government

Trusted technology partner to multiple US government agencies for secure digital identity verification Scale: Serves 20 federal agencies, 44 state government agencies, 66 healthcare organizations Use cases: Unemployment, Tax, Retirement, Centers for Medicare/Medicaid 2013: Awarded 2-year grant by US Chamber for President’s National Strategy for Trusted Identities in Cyberspace (NSTIC) 2014: Won contract with General Services Administration for Connect.gov digital identity credentials COVID-19 pandemic: Contracted by several state unemployment agencies to verify claimants Standards: NIST 800-63-3 establishes guidelines for identity verification providers serving federal agencies Privacy concerns: IRS announced (Feb 2022) new authentication option without biometric data including facial recognition Additional sources: https://www.id.me/individuals/government | https://en.wikipedia.org/wiki/ID.me | https://www.id.me/about | https://www.id.me/business/government

312.

Institute for Economics & Peace. Global peace index 2024. (2024)

Institute for Economics and Peace Global Peace Index 2024. The economic impact of violence on the global economy reached nearly $20 trillion, with military spending and internal security costs accounting for 74% of the total.

313.

Institute for Health Metrics and Evaluation (IHME). IHME global burden of disease (2.55B DALYs, 2019). Institute for Health Metrics and Evaluation (IHME) https://vizhub.healthdata.org/gbd-compare/ (2020)

Globally, in 2019, the total number of DALYs from all causes was 2.55 billion. Additional sources: https://vizhub.healthdata.org/gbd-compare/ | https://www.healthdata.org/research-analysis/about-gbd | https://pubmed.ncbi.nlm.nih.gov/33069326/

314.

Institute for Health Metrics and Evaluation (IHME). IHME global burden of disease 2021 (2.88B DALYs, 1.13B YLD). Institute for Health Metrics and Evaluation (IHME) https://vizhub.healthdata.org/gbd-results/ (2024)

In 2021, global DALYs totaled approximately 2.88 billion, comprising 1.75 billion Years of Life Lost (YLL) and 1.13 billion Years Lived with Disability (YLD). This represents a 13% increase from 2019 (2.55B DALYs), largely attributable to COVID-19 deaths and aging populations. YLD accounts for approximately 39% of total DALYs, reflecting the substantial burden of non-fatal chronic conditions. Additional sources: https://vizhub.healthdata.org/gbd-results/ | https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(24)00757-8/fulltext | https://www.healthdata.org/research-analysis/about-gbd

315.

ACLU Illinois. Illinois biometric information privacy act (BIPA). ACLU Illinois: BIPA https://www.aclu-il.org/en/campaigns/biometric-information-privacy-act-bipa

Enacted: October 3, 2008 (introduced Feb 14, 2008 by State Sen. Terry Link; passed both Houses July 10, 2008; signed by Gov. Rod Blagojevich) Purpose: Regulate collection, use, and handling of biometric identifiers and information by private entities in Illinois Requirements: Written notice of what data is collected/stored, specific purpose & duration, obtain written consent Covered biometrics: Retina/iris scans, fingerprints, voiceprints, hand scans, facial geometry, DNA, other unique biological info Prohibitions: Selling or profiting from consumers’ biometric information Penalties: $1,000 per violation; $5,000 per intentional/reckless violation Private right of action: Any aggrieved individual can sue 2024 update (SB2979): Multiple collections from same person = single violation (single recovery per individual) Additional sources: https://www.aclu-il.org/en/campaigns/biometric-information-privacy-act-bipa | https://en.wikipedia.org/wiki/Biometric_Information_Privacy_Act | https://securiti.ai/privacy-laws/us/illinois/ | https://www.winston.com/en/legal-glossary/what-is-bipa

316.

Imbens, G. W. & Rubin, D. B. Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction. (Imbens, Cambridge, 2015).

The potential outcomes framework provides a rigorous foundation for defining causal effects and understanding the assumptions required for their identification.

317.

International Monetary Fund. IMF fossil fuel subsidies data: 2023 update. (2023)

Globally, fossil fuel subsidies were $7 trillion in 2022 or 7.1 percent of GDP. The United States subsidies totaled $649 billion. Underpricing for local air pollution costs and climate damages are the largest contributor, accounting for about 30 percent each.

318.

International Monetary Fund. IMF data. (2025).

319.

PMC. Indian aadhaar national identity system. PMC: Aadhaar Failure to Do No Harm https://pmc.ncbi.nlm.nih.gov/articles/PMC5741784/

Largest biometric identity system in history: 1 billion registered users (nearly all of India’s 1.4B population) 12-digit unique identification number issued by Unique Identification Authority of India (UIDAI) Biometric data: Fingerprints, facial images, iris scans stored in Central Identities Repository (national centralized database) Privacy concerns: Deployed without direct legislative privacy/ethics constraints; comprehensive data protection legislation not yet passed Security issues: High-ranking official’s Aadhaar number shared on Twitter led to hackers accessing personal info (mobile, tax ID) 2017: Supreme Court enshrined privacy rights Supreme Court ruling: 4 of 5 judges allowed program to continue with limited scope & restrictions on data storage Threats: Potential for 360-degree profiling; viewed by many as mass surveillance tool infringing privacy rights Note: "with privacy protections" is questionable - significant privacy concerns remain despite Supreme Court restrictions Additional sources: https://pmc.ncbi.nlm.nih.gov/articles/PMC5741784/ | https://time.com/5388257/india-aadhaar-biometric-identification/ | https://privacyinternational.org/case-study/4698/id-systems-analysed-aadhaar | https://insights.som.yale.edu/insights/what-happens-when-billion-identities-are-digitized

320.

Sinn, M. P. Private industry clinical trial spending estimate. (2025)

Estimated private pharmaceutical and biotech clinical trial spending is approximately $75-90 billion annually, representing roughly 90% of global clinical trial spending.

321.

World Bank. Infrastructure investment economic multiplier (1.6). World Bank: Infrastructure Investment as Stimulus https://blogs.worldbank.org/en/ppps/effectiveness-infrastructure-investment-fiscal-stimulus-what-weve-learned (2022)

Infrastructure fiscal multiplier: 1.6 during contractionary phase of economic cycle Average across all economic states: 1.5 (meaning $1 of public investment → $1.50 of economic activity) Time horizon: 0.8 within 1 year, 1.5 within 2-5 years Range of estimates: 1.5-2.0 (following 2008 financial crisis & American Recovery Act) Italian public construction: 1.5-1.9 multiplier US ARRA: 0.4-2.2 range (differential impacts by program type) Economic Policy Institute: Uses 1.6 for infrastructure spending (middle range of estimates) Note: Public investment less likely to crowd out private activity during recessions; particularly effective when monetary policy loose with near-zero rates Additional sources: https://blogs.worldbank.org/en/ppps/effectiveness-infrastructure-investment-fiscal-stimulus-what-weve-learned | https://www.gihub.org/infrastructure-monitor/insights/fiscal-multiplier-effect-of-infrastructure-investment/ | https://cepr.org/voxeu/columns/government-investment-and-fiscal-stimulus | https://www.richmondfed.org/publications/research/economic_brief/2022/eb_22-04

322.

WHO. Injuries are largely preventable events. WHO: Injuries and Violence Fact Sheet https://www.who.int/news-room/fact-sheets/detail/injuries-and-violence

WHO: "Injuries have traditionally been regarded as random, unavoidable ’accidents’. Today both unintentional and intentional injuries are viewed as largely preventable events. 4.4 million injury-related deaths annually: 3.16M unintentional, 1.25M violence-related Injuries are preventable by changing environment, individual behavior, products, social norms, legislation, and governmental/institutional policies When standardized per 100,000 population, death rate is nearly double in low/middle-income vs high-income countries (65 vs 35 per 100,000) 90% of injury-related deaths occur in low- and middle-income countries Note: 60% of accidental deaths theoretically preventable through policy, technology, and behavior change; 40% involve instantaneous trauma beyond medical intervention Additional sources: https://www.who.int/news-room/fact-sheets/detail/injuries-and-violence | https://pmc.ncbi.nlm.nih.gov/articles/PMC2912603/ | https://www.who.int/publications-detail-redirect/the-injury-chart-book-a-graphical-overview-of-the-global-burden-of-injuries

323.

Snopes. History of insulin patent and modern price disparities. Snopes: Insulin Patent Dollar https://www.snopes.com/fact-check/insulin-patent-dollar/ (2019)

1923: Frederick Banting, Charles Best, James Collip sold insulin patent to U. of Toronto for $1 each (total $3) Banting: Unethical for doctor to profit from life-saving discovery; wanted everyone to afford it Manufacturing cost: $6 per vial US retail price: $300-332 per vial (Humalog: $21 in 1999 → $332 in 2019 = 1,000%+ increase) Price increases: 600% over 20 years; 200% between 2007-2018 Patients without insurance: Up to $1,000/month Contributing factors: Patent evergreening, barriers to biosimilar entry, market concentration (Eli Lilly, Novo Nordisk, Sanofi) Additional sources: https://www.snopes.com/fact-check/insulin-patent-dollar/ | https://www.t1international.com/100years/ | https://pnhp.org/news/why-insulin-is-overpriced/ | https://www.npr.org/2019/06/18/733742630/desperate-measures-the-skyrocketing-price-of-insulin-in-america

324.

US Government Info. Intelligence spending as percentage of military budgets. US Government Info: Cost of Intelligence https://www.govinfo.gov/content/pkg/GPO-INTELLIGENCE/html/int017.html

US: Military-related budget lines (DoE, State Dept, National Intelligence Program) = 11% of US spending (2024) Intelligence funding: Grew faster than military when military spending increased; decreased slower when military spending decreased Historical trend: Intelligence funding reached level 80% above 1980 baseline US National Intelligence Program + Military Intelligence Program ≈ 10-11% of total military-related spending Additional sources: https://www.govinfo.gov/content/pkg/GPO-INTELLIGENCE/html/int017.html | https://sgp.fas.org/crs/intel/R44381.pdf | https://en.wikipedia.org/wiki/United_States_intelligence_budget

325.

Statista. Number of global internet users. Statista: Internet Users Worldwide 2024 https://www.statista.com/statistics/273018/number-of-internet-users-worldwide/ (2024)

2022: Surpassed 5 billion users worldwide 2024 (Oct): 5.52 billion (67.5% of global population); year-end: 5.5B 2025 (start): 5.560 billion (67.9% of population); Oct 2025: 6.04 billion (73.2% of population) Growth: +136M in 2024 (+2.5%), +294M over 12 months to Oct 2025 (+5.1%) Still disconnected: 2.630 billion people at start of 2025 Additional sources: https://www.statista.com/statistics/273018/number-of-internet-users-worldwide/ | https://www.digitalinformationworld.com/2025/02/global-internet-users-surpass-offline-556-billion-2025.html | https://datareportal.com/global-digital-overview | https://www.sganalytics.com/blog/global-internet-usage-statistics/

326.

Sinn, M. P. The Invisible Graveyard: Quantifying the Mortality Cost of FDA Efficacy Lag. https://invisible-graveyard.warondisease.org (2025) doi:10.5281/zenodo.18356231

After proving a drug is safe, the FDA requires 8.2 years to prove it works before patients can access it. We estimate this delay cost 102 million deaths among people waiting for approved drugs (1962-2024). The human cost in death and disability of blocking good drugs is 3.07k higher than the cost of approving bad ones.

327.

IQVIA Institute for Human Data Science. The global use of medicines 2024: Outlook to 2028. IQVIA Institute Report https://www.iqvia.com/insights/the-iqvia-institute/reports-and-publications/reports/the-global-use-of-medicines-2024-outlook-to-2028 (2024)

Global days of therapy reached 1.8 trillion in 2019 (234 defined daily doses per person). Diabetes, respiratory, CVD, and cancer account for 71 percent of medicine use. Projected to reach 3.8 trillion DDDs by 2028.

328.

Internal Revenue Service. Exemption requirements - 501(c)(3) organizations.

329.

Jackson, C. K., Johnson, R. C. & Persico, C. The effects of school spending on educational and economic outcomes: Evidence from school finance reforms. The Quarterly Journal of Economics 131, 157–218 (2016)

Using exogenous variation from court-ordered school finance reforms, finds that a 10% increase in per-pupil spending throughout all 12 years of public school leads to 0.31 more completed years of education, 7.25% higher wages, and a 3.67 percentage-point reduction in adult poverty. This is one of the most credible causal estimates of the effect of education spending on adult outcomes, using natural experiments to address reverse causality concerns.

330.

Wikipedia. Journal of the american medical association (JAMA) founded in 1883. Wikipedia: JAMA https://en.wikipedia.org/wiki/JAMA

Founded: 1883 by American Medical Association Founding editor: Nathan Smith Davis Superseded: Transactions of the American Medical Association 1960: Obtained current title "JAMA: The Journal of the American Medical Association Evolution: Late 1800s resembled general journalism; 1910s-1920s "turndown era" began rejecting submissions based on quality; routine peer review instituted after WWII Current: Peer-reviewed medical journal published 48 times/year covering all aspects of biomedicine Additional sources: https://en.wikipedia.org/wiki/JAMA | https://jamanetwork.com/journals/jama/fullarticle/291201 | https://onlinebooks.library.upenn.edu/webbin/serial?id=jama

331.

JAMA Network Open. Pharmacist-led hypertension management cost-effectiveness. JAMA Network Open https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2811317 (2023)

Recent US studies show pharmacist-led hypertension management programs have incremental cost-effectiveness ratios (ICERs) under $50,000 per QALY, with most interventions falling in the $20,000-$33,000 per QALY range. These interventions are considered highly cost-effective compared to standard care. Additional sources: https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2811317

332.

Nobel Prize. James buchanan nobel prize in economics, 1986. Nobel Prize: 1986 Economic Sciences https://www.nobelprize.org/prizes/economic-sciences/1986/press-release/ (1986)

James McGill Buchanan: 1986 Nobel Memorial Prize in Economic Sciences Citation: "for his development of the contractual and constitutional bases for the theory of economic and political decision-making Field: Public choice theory (leading researcher & cofounder with Gordon Tullock) Key work: "The Calculus of Consent" (with Tullock) - now considered a classic, started the field Contribution: Transferred concept of gain from mutual exchange between individuals to political decision-making; applied economic analysis to public sector Inspiration: Swedish economist Knut Wicksell (described as "most exciting intellectual moment" of career) Additional sources: https://www.nobelprize.org/prizes/economic-sciences/1986/press-release/ | https://en.wikipedia.org/wiki/James_M._Buchanan | https://www.britannica.com/money/James-M-Buchanan | https://www.econlib.org/library/Enc/bios/Buchanan.html

333.

Yong, C. S. M., Deng, J., Tan, E. W., et al. Challenges in global access to CAR-t cells: An asian perspective. International Journal of Hematology https://pmc.ncbi.nlm.nih.gov/articles/PMC10937087/ (2024)

Reviews CAR-T cell therapy access across Asia. Japan has approved five CAR-T products under National Health Insurance: Kymriah, Yescarta, Breyanzi, Abecma, and Carvykti. All priced at 32,647,761 JPY. Japan’s high-cost medical care reimbursement system limits patient out-of-pocket costs.

334.

Market Urbanism. Why is japanese zoning more liberal than US zoning? Market Urbanism https://marketurbanism.com/2019/03/19/why-is-japanese-zoning-more-liberal-than-us-zoning/ (2019)

Japan’s zoning system operates with 12 national zones that permit multifamily housing and mixed-use development even in strict zones. Development follows ’as-of-right’ approach without discretionary review. Unlike the US where homes are investments and 89,000 municipalities create restrictive zoning, Japanese homes depreciate completely within 22 years and national framework limits local restrictiveness. Result: Tokyo ranks among the most affordable developed-world cities despite being a megacity of 14 million.

335.

FDLI. Japan’s regenerative medicine act and conditional approval pathway. FDLI: Japan’s Regen Med Pathways https://www.fdli.org/2019/02/global-focus-japans-regenerative-medicine-regulatory-pathways-encouraging-innovation-and-patient-access/ (2019)

Act on Safety of Regenerative Medicine (RM Act) + amended Pharmaceuticals and Medical Devices Act (PMD Act): passed Nov 2013, effective Nov 2014 Conditional and time-limited approval pathway: Obtain approval after exploratory trials demonstrate probable benefit and proven safety 7-year conditional approval period to confirm clinical benefit (e.g., using surrogate endpoints) SAKIGAKE designation (April 2015): Expedited pathway for innovative products targeting serious/life-threatening diseases without effective treatment Benefits: Prioritized consultation, accelerated review, extended re-examination period, premium pricing Examples: Terumo’s HeartSheet and Stemirac obtained conditional approval; Stemirac also SAKIGAKE-designated Additional sources: https://www.fdli.org/2019/02/global-focus-japans-regenerative-medicine-regulatory-pathways-encouraging-innovation-and-patient-access/ | https://www.insights.bio/cell-and-gene-therapy-insights/journal/article/310/Experiences-from-Japan-SAKIGAKE-Designation-System-for-Regenerative-Medical-Products | https://pmc.ncbi.nlm.nih.gov/articles/PMC6696404/

336.

Jha, P. et al. 21st-century hazards of smoking and benefits of cessation in the united states. New England Journal of Medicine 368, 341–350 (2013)

Smokers lose at least one decade of life expectancy compared with those who have never smoked. The probability of surviving from 25 to 79 years of age was about twice as great in those who had never smoked as in current smokers (70 percent vs. 38 percent among women and 61 percent vs. 26 percent among men). Cessation before age 40 reduces the risk of death associated with continued smoking by about 90 percent. Adults who quit at ages 25-34, 35-44, or 45-54 gained about 10, 9, and 6 years of life respectively compared with those who continued to smoke.

337.

Hosoya, S. et al. Detailed revisions to the subordinate regulation following the amendment of the act on the safety of regenerative medicine in japan. https://pmc.ncbi.nlm.nih.gov/articles/PMC12221229/ (2025).

338.

Kahneman, D. & Tversky, A. Prospect theory: An analysis of decision under risk. Econometrica 47, 263–292 (1979).

339.

GovTrack. Kefauver harris amendment of 1962. GovTrack https://www.govtrack.us/congress/bills/87/s1552 (1962)

regulating efficacy testing via the 1962 Kefauver Harris Amendment. The 1962 regulations made these large real-world efficacy trials illegal. Additional sources: https://www.govtrack.us/congress/bills/87/s1552 | https://www.fda.gov/about-fda/histories-product-regulation/promoting-safe-effective-drugs-100-years | https://pmc.ncbi.nlm.nih.gov/articles/PMC4101807/

340.

National Kidney Foundation. Annual deaths from kidney disease. National Kidney Foundation: Global Facts https://www.kidney.org/global-facts-about-kidney-disease (2022)

Direct CKD deaths: 1.2M (2017), 1.53M (2021); increased from 591,800 (1990) to 1,425,670 (2019) CKD-attributable cardiovascular deaths: Additional 1.4M deaths from CVD attributable to impaired kidney function (7.6% of all CVD deaths, 2017) Combined impact: 4.6% of total global mortality CKD: 12th leading cause of death globally; one of few NCDs showing increased deaths over past 2 decades Additional sources: https://www.kidney.org/global-facts-about-kidney-disease | https://pmc.ncbi.nlm.nih.gov/articles/PMC9073222/ | https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(20)30045-3/fulltext | https://www.healthdata.org/news-events/newsroom/news-releases/chronic-kidney-disease-global-killer-plain-sight

341.

Kleiner, M. M. Licensing Occupations: Ensuring Quality or Restricting Competition? (W.E. Upjohn Institute for Employment Research, 2006). doi:10.17848/9781429454865.

342.

Kleiner, M. M. & Krueger, A. B. Analyzing the extent and influence of occupational licensing on the labor market. Journal of Labor Economics 31, S173–S202 (2013)

Occupational licensing affects 29% of US workers and creates labor market distortions costing 2-3% of GDP.

343.

KOF Swiss Economic Institute. Healthcare expenditure rises to over CHF 100 billion. KOF Swiss Economic Institute, ETH Zurich https://kof.ethz.ch/en/news-and-events/media/press-releases/2024/11/health-expanditures-forecast.html (2024)

Healthcare expenditure as a share of GDP amounted to 11.8

344.

Kremer, M., Levin, J. & Snyder, C. M. Advance market commitments: Insights from theory and experience. AEA Papers and Proceedings 110, 269–273 (2020)

Reviews the $1.5 billion pilot Advance Market Commitment for pneumococcal vaccine. Three vaccines developed, 150 million children immunized, estimated 700,000 lives saved. Discusses AMC design for well-defined products versus systemic reform.

345.

Kydland, F. E. & Prescott, E. C. Rules rather than discretion: The inconsistency of optimal plans. Journal of Political Economy 85, 473–492 (1977)

Time-inconsistency describes situations where, with the passing of time, policies that were determined to be optimal yesterday are no longer perceived to be optimal today and are not implemented... This insight shifted the focus of policy analysis from the study of individual policy decisions to the design of institutions that mitigate the time consistency problem.

346.

Laffont, J.-J. & Tirole, J. A Theory of Incentives in Procurement and Regulation. (MIT Press, 1993).

347.

Lalley, S. P. & Weyl, E. G. Quadratic voting: How mechanism design can radicalize democracy. Lalley 108, 33–37 (2018)

The paper proposes a design where individuals pay for as many votes as they wish using a number of "voice credits" in the votes they buy. Only quadratic cost induces marginal costs linear in votes purchased and thus welfare optimality if individuals’ valuation of votes is proportional to their value of changing the outcome. Additional sources: https://www.aeaweb.org/articles?id=10.1257/pandp.20181002 | https://ssrn.com/abstract=2003531 | https://www.microsoft.com/en-us/research/publication/quadratic-voting-how-mechanism-design-can-radicalize-democracy/

348.

BioPharma Dive. Approval of landmark gene therapies (luxturna, zolgensma, CAR-t). BioPharma Dive: Luxturna https://www.biopharmadive.com/news/luxturna-gene-therapy-eye-leber-lca/609832/ (2017)

Luxturna (Dec 2017): First in vivo gene therapy approved by US FDA; treats biallelic RPE65 mutation-associated retinal dystrophy (inherited blindness); $850,000 one-time therapy CAR-T therapies (2017): Kymriah and Yescarta approved same year as Luxturna Zolgensma (May 2019): Spinal muscular atrophy treatment; second gene therapy for inherited disease in US; $2.1M (one of most expensive medicines at the time) Described as "landmark moment for a field riddled with ups and downs" and "landmark achievements in history of modern science Additional sources: https://www.biopharmadive.com/news/luxturna-gene-therapy-eye-leber-lca/609832/ | https://cen.acs.org/articles/95/web/2017/12/First-gene-therapy-genetic-disease.html | https://www.npr.org/sections/health-shots/2017/12/19/571962226/first-gene-therapy-for-inherited-disease-gets-fda-approval | https://pmc.ncbi.nlm.nih.gov/articles/PMC7123914/

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In 2019, I had no idea that I would be setting up a trial of treatments for an infectious disease, let alone a pandemic virus. I certainly would not have thought it possible to go from a blank piece of paper to enrolling the first patient in nine days, to finding the first life-saving treatment within ten weeks, and for it to be made standard NHS policy within three hours. Additional sources: https://www.ox.ac.uk/news/features/recovery-trial-two-years

350.

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Pre-1962: 3.82 years/decade Post-1962: 1.54 years/decade Reduction: 60% decline in life expectancy growth rate Additional sources: https://ourworldindata.org/life-expectancy | https://www.mortality.org/ | https://www.cdc.gov/nchs/nvss/mortality_tables.htm

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House bill to weaken Dodd-Frank financial regulations: 70 of 85 lines reflected Citigroup lobbyist recommendations. Two paragraphs copied almost word for word, with only two words changed to make them plural. Bill sought to eliminate push-out rule preventing banks from using customer deposits for derivative trading.

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Founded 1994 by John Meriwether (former Salomon Brothers vice-chairman) Board included Nobel Prize winners: Myron Scholes & Robert C. Merton (1997 Nobel in Economics for Black-Scholes model) Initial success: 21% (year 1), 43% (year 2), 41% (year 3) annualized returns after fees 1998 collapse: Lost $4.6B in <4 months due to high leverage + 1997 Asian crisis + 1998 Russian crisis Extreme leverage: $30 debt per $1 capital (end of 1997) Bailout: $3.6B ($3.625B) from 14 banks, brokered by Federal Reserve Bank of NY (Fed didn’t lend own funds) By early 2000: Fund liquidated, creditors repaid Additional sources: https://en.wikipedia.org/wiki/Long-Term_Capital_Management | https://www.federalreservehistory.org/essays/ltcm-near-failure | https://www.wallstreetmojo.com/long-term-capital-management/ | https://blogs.cfainstitute.org/investor/2013/11/04/the-incredible-untold-story-about-how-the-financial-world-almost-ended/

366.

Think by Numbers. Lost human capital due to war ($270B annually). Think by Numbers https://thinkbynumbers.org/military/war/the-economic-case-for-peace-a-comprehensive-financial-analysis/ (2021)

Lost human capital from war: $300B annually (economic impact of losing skilled/productive individuals to conflict) Broader conflict/violence cost: $14T/year globally 1.4M violent deaths/year; conflict holds back economic development, causes instability, widens inequality, erodes human capital 2002: 48.4M DALYs lost from 1.6M violence deaths = $151B economic value (2000 USD) Economic toll includes: commodity prices, inflation, supply chain disruption, declining output, lost human capital Additional sources: https://thinkbynumbers.org/military/war/the-economic-case-for-peace-a-comprehensive-financial-analysis/ | https://www.weforum.org/stories/2021/02/war-violence-costs-each-human-5-a-day/ | https://pubmed.ncbi.nlm.nih.gov/19115548/

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370.

WHO. Annual deaths from malaria. WHO https://www.who.int/teams/global-malaria-programme/reports/world-malaria-report-2024 (2024)

600,000 people per year die from malaria (a disease spread by a bug we can’t figure out how to properly swat) Additional sources: https://www.who.int/teams/global-malaria-programme/reports/world-malaria-report-2024

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Medicare Prescription Drug, Improvement, and Modernization Act (P.L. 108-173): Signed Dec 8, 2003 by President Bush; created voluntary Part D prescription drug benefit Noninterference provision": Prohibits HHS Secretary from negotiating drug prices or establishing preferred drug list Instead: Drug prices negotiated between manufacturers & insurance companies administering Part D plans Pharma industry role in writing: "Noninterference clause" written with major industry involvement; drug manufacturers had major role writing & getting it through Congress Industry lobbying: $231M spent on lobbying in 2003 (more than any other industry since 1998) Rep. Billy Tauzin example: 2004 appointed PhRMA chief lobbyist ($2M/year rumored); responsible for including price negotiation prohibition 2022 change: Inflation Reduction Act removed ban; Medicare can negotiate starting 2026 Additional sources: https://en.wikipedia.org/wiki/Medicare_Prescription_Drug,_Improvement,_and_Modernization_Act | https://www.healthaffairs.org/content/forefront/politics-medicare-and-drug-price-negotiation-updated | https://www.congress.gov/crs-products/product/pdf/R/R47872

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Ramey (2011): 0.6 short-run multiplier Barro (1981): 0.6 multiplier for WWII spending (war spending crowded out 40¢ private economic activity per federal dollar) Barro & Redlick (2011): 0.4 within current year, 0.6 over two years; increased govt spending reduces private-sector GDP portions General finding: $1 increase in deficit-financed federal military spending = less than $1 increase in GDP Variation by context: Central/Eastern European NATO: 0.6 on impact, 1.5-1.6 in years 2-3, gradual fall to zero Ramey & Zubairy (2018): Cumulative 1% GDP increase in military expenditure raises GDP by 0.7% Additional sources: https://www.mercatus.org/research/research-papers/defense-spending-and-economy | https://cepr.org/voxeu/columns/world-war-ii-america-spending-deficits-multipliers-and-sacrifice | https://www.rand.org/content/dam/rand/pubs/research_reports/RRA700/RRA739-2/RAND_RRA739-2.pdf

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Michael Milken ("Junk Bond King"): Pioneered high-yield "junk bond" market with Drexel Burnham Lambert (1970s-1980s) Original-issue high-yield debt innovation provided hostile bidders & LBO firms enormous capital for multi-billion-dollar deals Mid-1980s: Milken’s high-yield bond buyer network enabled rapid large-scale fundraising, facilitated LBOs (e.g., KKR) Market growth: End of 1980s = $150B junk-bond market; Drexel became leading US financial firm with 50% market share Milken compensation: >$1B over 4 years (late 1980s) - US income record at the time 1989: Indicted for racketeering/securities fraud; plea bargain to securities/reporting violations (not racketeering/insider trading) 1990: Drexel bankruptcy & liquidation Additional sources: https://en.wikipedia.org/wiki/Michael_Milken | https://www.hbs.edu/faculty/Pages/item.aspx?num=50852 | https://www.britannica.com/money/Michael-R-Milken | https://www.sechistorical.org/museum/galleries/wwr/wwr05d-markets-milken.php

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386.

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393.

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Operations & Maintenance (O&M): 38-50% of military spending US FY2024: O&M cost $332B (38% of military spending), up from 28% in 1974 2005-2015 trend: O&M represented 40-50% of DoD total budget NATO 2024: $1.47T total spending across 32 member countries; US $967B (66%), European members $454B (30%) NATO equipment investment guideline: At least 20% of military expenditures for major equipment/R&D Additional sources: https://usafacts.org/articles/how-much-does-the-us-spend-on-the-military/ | https://www.cbo.gov/publication/52156 | https://www.nato.int/cps/en/natohq/topics_49198.htm | https://www.statista.com/statistics/1293301/combined-military-expenditures-nato/

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PMC. Stem cell therapy shows promise for neurodegenerative diseases. PMC: Regenerative Stem Cell Therapy for Neurodegenerative Diseases https://pmc.ncbi.nlm.nih.gov/articles/PMC7926761/ (2023)

R3 paradigm: Rejuvenation (restoring cell function), Regeneration (stimulating repair), Replacement (substituting lost cells) Alzheimer’s: Stanford study showed stem cell transplants reduced brain abnormalities in mice; Neural Stem Cell Therapy shown to improve cognitive function and reduce amyloid plaques Parkinson’s: Clinical trial found Neural Stem Cell Therapy significantly improved motor function and was well-tolerated ALS/Huntington’s: MSC (mesenchymal stem cell) therapy effectiveness confirmed; slows ALS progression Challenge: Clinical trials often enroll patients at advanced stages; many preclinically promising drugs ineffective in late-stage human trials Current status: Largely experimental and early clinical trial stages; researchers working to overcome delivery challenges, safety concerns, and targeting widespread neuronal damage Note: 80% theoretical max for neurodegenerative reflects early-stage intervention potential; current treatments limited ( 10% effective) Additional sources: https://pmc.ncbi.nlm.nih.gov/articles/PMC7926761/ | https://med.stanford.edu/news/all-news/2023/09/stem-cell-alzheimers.html | https://stemcellres.biomedcentral.com/articles/10.1186/s13287-025-04285-7

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Facing a budget crisis, New Zealand’s government in 1984 eliminated all agricultural subsidies. Prior to reforms, farmers derived about 40

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Total authorized funding: $2.16B (not $4B) - $1.02B allocated since 2015, $1.14B authorized through 2026 via 21st Century Cures Act Budget cut 71% over 2 years: $500M+ (2023) → $150M (2025) Enrolled: 860,000 participants from all 50 states; 633,000+ participants with data available for research Clinical trials completed: Zero (program is observational cohort study, not a clinical trial program) Purpose: Collect prospective data to inform future clinical trials, provide recruitment infrastructure Additional sources: https://allofus.nih.gov/article/program-overview | https://www.nejm.org/doi/full/10.1056/NEJMsr1809937 | https://www.genomeweb.com/sequencing/all-us-research-program-unfazed-funding-cuts-lays-out-plans-through-2026

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Global scientific output: 2.5-2.6 million research papers published annually (all sources, not just NIH) Worldwide S&E publication growth: 1.8M (2008) → 2.6M articles (2018), averaging 4% annual growth NIH-specific output example (2000): 4,451 R01 grants ($1.3B) produced 55,000 publications, 3.7M citations Total active journals: 46,736 peer-reviewed journals (2020) publishing 3M+ articles annually Additional sources: https://ncses.nsf.gov/pubs/nsb20206 | https://ourworldindata.org/grapher/scientific-publications-per-million | https://pmc.ncbi.nlm.nih.gov/articles/PMC8738817/

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Bentley et al. NIH spending on clinical trials: 3.3%. Bentley et al. https://pmc.ncbi.nlm.nih.gov/articles/PMC10349341/ (2023)

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NIH structure: 27 Institutes and Centers, each with own research agenda Office of the Director: Sets policy, plans/manages/coordinates all NIH components Location: 9000 Rockville Pike, Bethesda, Maryland Total NIH employees: 20,000 Leadership structure: Director + 27 Institute/Center directors + division chiefs + council members Specific count of "key decision-makers" varies by definition; centralized funding decisions flow through Office of Director and IC leadership Additional sources: https://www.nih.gov/about-nih/what-we-do/nih-almanac | https://www.nih.gov/about-nih/what-we-do/nih-almanac/nih-organization

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Kaiser, J. NIH says grantee failed to report experiment in Wuhan that created a bat virus that made mice sicker. Science (2021).

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PMC. Number of diseases eradicated by the NIH. PMC: Six Challenges in Eradication https://pmc.ncbi.nlm.nih.gov/articles/PMC7612385/

Diseases eradicated globally: Only 2 (smallpox in 1979 via $300M WHO effort over <10 years; rinderpest) NIH role: Contributor to research/vaccine development but not sole eradicator Near-eradication: Polio (close to achievement); measles, rubella targeted for eradication Major achievements via vaccination: Smallpox eradicated, polio nearly eliminated, diphtheria/tetanus/measles greatly reduced Impact: Vaccination eliminated disease in populations with high implementation rates; past 2 centuries saw enormous infectious disease control via sanitation, vaccines, antibiotics, nutrition Additional sources: https://pmc.ncbi.nlm.nih.gov/articles/PMC7612385/ | https://pmc.ncbi.nlm.nih.gov/articles/PMC4024226/ | https://www.ncbi.nlm.nih.gov/books/NBK98117/

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HHS. FY2016 budget in brief - NIH. HHS https://www.hhs.gov/about/budget/budget-in-brief/nih/index.html (2020)

NIH funding contributed to published research associated with every one of the 356 new drugs approved by the FDA from 2010–2019." Total NIH spending on this research was $187 billion, while industry spending on clinical development for these drugs was significantly higher. Approximately 54% of the NIH research budget is devoted to basic biomedical and behavioral research, while about one-third (33%) is allocated to clinical research including patient-oriented research, clinical trials, and health services research. Categories overlap so totals exceed 100%. Additional sources: https://www.pnas.org/doi/10.1073/pnas.1920929117 | https://marianamazzucato.com/books/the-entrepreneurial-state | https://www.hhs.gov/about/budget/budget-in-brief/nih/index.html | https://www.hhs.gov/about/budget/budget-in-brief/nih/index.html

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Following a proposed 29% cut to NIH funding in 2025, 75% of scientists are considering leaving the U.S. due to funding instability. Additional sources: https://www.bizjournals.com/sanjose/news/2025/08/15/nih-funding-cuts-science-brain-drain-berkeley.html

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Very weak correlations: R² < 0.03 between NIH funding and 5 disease burden measures for 27 diseases Historical (1996): r=0.62 correlation with DALYs, but explained only 39% of variance Recent (2008-2019): Simple correlation 0.08 between disease burden increases and funding increases 2019 analysis: Only 29% of variance in NIH funding explained by disease burden Strongest predictor of 2019 funding: 2008 funding levels (r=0.88), revealing long-standing inefficiencies Additional sources: https://www.sciencedirect.com/science/article/pii/S2666535224001174 | https://www.nejm.org/doi/full/10.1056/NEJM199906173402406 | https://pmc.ncbi.nlm.nih.gov/articles/PMC3044706/

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Total NIH FY2024: $48.6B appropriation National Cancer Institute (NCI): $7.22B (-1.3% from FY2023) National Institute of Allergy & Infectious Diseases (NIAID): $6.56B (flat from FY2023) National Institute on Aging (NIA): $4.5B+ ($90M for Alzheimer’s/dementia research) Additional sources: https://www.aip.org/fyi/fy2024-national-institutes-of-health | https://crsreports.congress.gov/product/pdf/R/R43341 | https://www.cancer.gov/grants-training/nci-bottom-line-blog/2024/nci-fy-2024-appropriation-brings-clarity-and-difficult-choices

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Left-wing populist movement against economic inequality, capitalism, corporate greed, big finance, money in politics September 17 - November 15, 2011 (59 days) in Zuccotti Park, NYC Financial District Slogan "We are the 99%" highlighted income/wealth inequality: Top 1% owned 40% of wealth, earned 20% of income (2011) Organized by Adbusters (Kalle Lasn, Micah White); ended November 15 when police cleared park ( 200 arrested) Legacy: Successfully reframed national conversation about economic inequality in simple, effective terms Additional sources: https://en.wikipedia.org/wiki/Occupy_Wall_Street | https://www.britannica.com/topic/Occupy-Wall-Street | https://history.com/this-day-in-history/occupy-wall-street-begins-zuccotti-park

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National average: 1 in 60 million chance (2008 election analysis by Gelman, Silver, Edlin) Swing states (NM, VA, NH, CO): 1 in 10 million chance Non-competitive states: 34 states >1 in 100 million odds; 20 states >1 in 1 billion Washington DC: 1 in 490 billion odds Methodology: Probability state is necessary for electoral college win × probability state vote is tied Additional sources: https://sites.stat.columbia.edu/gelman/research/published/probdecisive2.pdf | https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1465-7295.2010.00272.x

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The Optimal Policy Generator (OPG) produces systematic public policy recommendations for jurisdictions at any level (country, state, city), generating prioritized enact/replace/repeal/maintain recommendations to maximize real after-tax median income growth and median healthy life years, based on quasi-experimental evidence from centuries of policy variation data.

446.

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Thousands of jurisdictions have made different policy and budget choices over decades, creating a natural experiment. Optimocracy applies causal inference to this cross-jurisdictional time-series data to identify which policies predict above-average median income and healthy life years. It then publishes evidence-based recommendations for every major vote, tracks politician alignment, and funds aligned candidates via SuperPAC, making suboptimal policy politically expensive while preserving democratic structures.

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455.

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Pape analyzed every suicide terrorist attack worldwide from 1980 to 2003, finding that 95 percent were in response to foreign military occupation. The data contradicts narratives attributing suicide terrorism primarily to religious fundamentalism.

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Recent surveys: 49-51% willingness (2020-2022) - dramatic drop from 85% (2019) during COVID-19 pandemic Cancer patients when approached: 88% consented to trials (Royal Marsden Hospital) Study type variation: 44.8% willing for drug trial, 76.2% for diagnostic study Top motivation: "Learning more about my health/medical condition" (67.4%) Top barrier: "Worry about experiencing side effects" (52.6%) Additional sources: https://trialsjournal.biomedcentral.com/articles/10.1186/s13063-015-1105-3 | https://www.appliedclinicaltrialsonline.com/view/industry-forced-to-rethink-patient-participation-in-trials | https://pmc.ncbi.nlm.nih.gov/articles/PMC7183682/

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Introduced: October 23, 2001 by Rep. Jim Sensenbrenner (R-WI) as H.R. 3162 Passed House: October 24, 2001 (357-66 vote, Democrats majority of "no" votes) Passed Senate: October 25, 2001 (98-1 vote, only Russ Feingold D-WI voted "no") Signed into law: October 26, 2001 by President George W. Bush Length: 342 pages, passed hastily without public opportunity for review ACLU concern: Senate forced to vote on legislation it hadn’t had opportunity to read (offices closed, staff couldn’t access papers) Additional sources: https://en.wikipedia.org/wiki/Patriot_Act | https://www.britannica.com/topic/USA-PATRIOT-Act | https://www.ala.org/advocacy/chronology-usa-patriot-act-2001

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Exact statutory text: "The Patient-Centered Outcomes Research Institute established under section 1320e(b)(1) of this title shall not develop or employ a dollars-per-quality adjusted life year (or similar measure that discounts the value of a life because of an individual’s disability) as a threshold to establish what type of health care is cost effective or recommended." The Secretary also cannot use such thresholds for Medicare coverage or reimbursement decisions.

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Foundational text on causal inference introducing do-calculus, structural causal models (SCMs), and graphical causal models Provides mathematical framework for defining and computing causal effects from observational and experimental data Introduces key concepts: interventions (do operator), confounding, counterfactuals, d-separation, causal discovery algorithms First edition 2000, second edition 2009 with new material on counterfactuals and mediation Over 45,000 citations - the seminal work that launched modern causal inference as a discipline Additional sources: https://www.cambridge.org/core/books/causality/B0046844FAE10CBF274D4ACBDAEB5F5B | https://www.amazon.com/Causality-Reasoning-Inference-Judea-Pearl/dp/052189560X | https://scholar.google.com/citations?view_op=view_citation&citation_for_view=bAipNH8AAAAJ:8k81kl-MbHgC

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Foundational study quantifying the costs of the 1962 Kefauver-Harris Amendments. Peltzman estimated that the efficacy requirements reduced the flow of new drugs by 50-60% and that the costs of reduced innovation substantially exceeded the benefits of keeping ineffective drugs off the market. Concluded that the 1962 amendments resulted in net welfare losses.

462.

Responsible Statecraft. Pentagon can’t account for 63% of nearly $4 trillion in assets. (2024).

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National Priorities Project. Take 7: The pentagon fails another audit. (2024).

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The Commune. Pentagon audit failures ($2.46T unaccounted). The Commune https://thecommunemag.com/the-pentagon-misplaced-2-46-trillion-an-in-depth-look-at-the-financial-audit-failures (2024)

In the most recent audit, the Department of Defense (DoD) could not account for approximately 60% of its 4.1trillioninassets, amountingto2.46 trillion unaccounted for. Alternative title: Pentagon unsupported accounting adjustments (6.5T, singleyear, USArmy)In2015, theDepartmentofDefense′sInspectorGeneralreportedthattheArmycouldnotadequatelysupport6.5 trillion in year-end adjustments, indicating severe accounting discrepancies. Additional sources: https://thecommunemag.com/the-pentagon-misplaced-2-46-trillion-an-in-depth-look-at-the-financial-audit-failures | https://accmag.com/audit-pentagon-cannot-account-for-6-5-trillion-dollars-is-taxpayer-money/

465.

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Systematic reviews can help policymakers by providing a rigorous and transparent method for synthesizing research evidence on the effectiveness of social interventions.

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Peterson Foundation. How does the u.s. Healthcare system compare to other countries? (2024).

468.

Value in Health. Average lifetime revenue per successful drug. Value in Health: Sales Revenues for New Therapeutic Agents https://www.sciencedirect.com/science/article/pii/S1098301524027542

Study of 361 FDA-approved drugs from 1995-2014 (median follow-up 13.2 years): Mean lifetime revenue: $15.2 billion per drug Median lifetime revenue: $6.7 billion per drug Revenue after 5 years: $3.2 billion (mean) Revenue after 10 years: $9.5 billion (mean) Revenue after 15 years: $19.2 billion (mean) Distribution highly skewed: top 25 drugs (7%) accounted for 38% of total revenue ($2.1T of $5.5T) Additional sources: https://www.sciencedirect.com/science/article/pii/S1098301524027542

469.

OpenSecrets. Pharmaceutical industry lobbying statistics. OpenSecrets: Pharmaceuticals/Health Products https://www.opensecrets.org/industries/indus?ind=H04

Pharmaceutical and health products industry spent $388 million on federal lobbying in 2024 ($6.1 billion since 1999) Employs roughly 3 lobbyists for every member of Congress Note: The industry has consistently been among the top spenders on lobbying in Washington D.C., with major pharmaceutical companies like Pfizer, AbbVie, and PhRMA leading expenditures Additional sources: https://www.opensecrets.org/industries/indus?ind=H04

470.

PMC. Pharmaceutical industry annual profits. PMC: Profitability of Large Pharmaceutical Companies https://pmc.ncbi.nlm.nih.gov/articles/PMC7054843/

Net income (2000-2018): 35 large pharma companies earned $1.9T cumulative net income on $11.5T revenue 2022 profits: Major pharma companies made >$112B in profits Profit margins: Pharma companies 13.8% median vs 7.7% for other S&P 500 companies Largest 25 companies: 15-20% annual average profit margin vs 4-9% for non-drug companies globally Profitability: Pharma significantly more profitable than most S&P 500 companies Additional sources: https://pmc.ncbi.nlm.nih.gov/articles/PMC7054843/ | https://www.bentley.edu/news/new-research-shows-pharma-companies-are-more-profitable-most-sp-500-companies | https://www.gao.gov/products/gao-18-40

471.

Deloitte. Pharmaceutical r&d return on investment (ROI). Deloitte: Measuring Pharmaceutical Innovation 2025 https://www.deloitte.com/ch/en/Industries/life-sciences-health-care/research/measuring-return-from-pharmaceutical-innovation.html (2025)

Deloitte’s annual study of top 20 pharma companies by R&D spend (2010-2024): 2024 ROI: 5.9% (second year of growth after decade of decline) 2023 ROI: 4.3% (estimated from trend) 2022 ROI: 1.2% (historic low since study began, 13-year low) 2021 ROI: 6.8% (record high, inflated by COVID-19 vaccines/treatments) Long-term trend: Declining for over a decade before 2023 recovery Average R&D cost per asset: $2.3B (2022), $2.23B (2024) These returns (1.2-5.9% range) fall far below typical corporate ROI targets (15-20%) Additional sources: https://www.deloitte.com/ch/en/Industries/life-sciences-health-care/research/measuring-return-from-pharmaceutical-innovation.html | https://www.prnewswire.com/news-releases/deloittes-13th-annual-pharmaceutical-innovation-report-pharma-rd-return-on-investment-falls-in-post-pandemic-market-301738807.html | https://hitconsultant.net/2023/02/16/pharma-rd-roi-falls-to-lowest-level-in-13-years/

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SofproMed. Phase 3 cost per trial range. SofproMed https://www.sofpromed.com/how-much-does-a-clinical-trial-cost

Phase 3 clinical trials cost between $20 million and $282 million per trial, with significant variation by therapeutic area and trial complexity. Additional sources: https://www.sofpromed.com/how-much-does-a-clinical-trial-cost | https://www.cbo.gov/publication/57126

474.

Philippon, T. & Reshef, A. Wages and human capital in the U.S. Finance industry: 1909–2006. The Quarterly Journal of Economics 127, 1551–1609 (2012)

Financial sector wages were similar to other sectors from 1940s–1980, then rose to a 50% premium by 2006. Rents accounted for 30–50% of the wage differential.

475.

Philipson, T., Berndt, E. R., Gottschalk, A. H. & Sun, E. Cost-benefit analysis of the FDA: The case of the prescription drug user fee acts. Journal of Public Economics 92, 1306–1325 (2008)

Faster drug approvals under PDUFA saved 140,000 to 310,000 life years from patients who had more rapid access to drugs, though this benefit was partially offset by an estimated 56,000 life years lost due to adverse events... Consumer welfare increased between $7 billion and $20 billion.

476.

Institute of Medicine (US) Committee on the U.S. Physician Supply. U.s. Physician supply and requirements: Match or mismatch? The Nation’s Physician Workforce: Options for Balancing Supply and Requirements https://www.ncbi.nlm.nih.gov/books/NBK232541/ (1996)

Historical physician workforce data: 126.6 active nonfederal M.D. physicians per 100,000 population in 1950; 127.4 in 1960; 137.4 in 1970 (DHHS 1993). At 1960 US population of 180M, this corresponds to approximately 229,000 active physicians.

477.

Peterson Institute for International Economics. Income growth for the typical american family has slowed since the early 1970s. (2018)

From 1948 to 1973, the typical American family’s income grew by 3 percent annually, doubling roughly once a generation. Since 1973, the median family income has risen just 0.6 percent per year.

478.

Plato. Apology. (Harvard University Press, 1966).

Plato’s account of the trial and execution of Socrates (399 BC) by Athenian democratic jury. A majority of 501 jurors voted to condemn Socrates to death on charges of impiety and corrupting the youth. The case is the canonical example of direct democratic majority rule producing an unjust outcome against an individual, and motivates the need for domain constraints that exclude fundamental rights questions from majority aggregation.

479.

Ramsberg, J. & Platt, R. Pragmatic trial cost per patient (median $97). Learning Health Systems https://pmc.ncbi.nlm.nih.gov/articles/PMC6508852/ (2018)

Meta-analysis of 108 embedded pragmatic clinical trials (2006-2016). The median cost per patient was $97 (IQR $19–$478), based on 2015 dollars. 25% of trials cost <$19/patient; 10 trials exceeded $1,000/patient. U.S. studies median $187 vs non-U.S. median $27. Additional sources: https://pmc.ncbi.nlm.nih.gov/articles/PMC6508852/

480.

Sinn, M. P. The Political Dysfunction Tax. https://political-dysfunction-tax.warondisease.org (2025) doi:10.5281/zenodo.18603840

Quantifying the gap between current global governance and theoretical maximum welfare, estimating a 31-53% efficiency score and $97 trillion in annual opportunity costs.

481.

Kinch, M. S. & Griesenauer, R. H. Lost medicines: A longer view of the pharmaceutical industry with the potential to reinvigorate discovery. Drug Discovery Today 24, 875–880 (2019)

Research identified 1,600+ medicines available in 1962. The 1950s represented industry high-water mark with >30 new products in five of ten years; this rate would not be replicated until late 1990s. More than half (880) of these medicines were lost following implementation of Kefauver-Harris Amendment. The peak of 1962 would not be seen again until early 21st century. By 2016 number of organizations actively involved in R&D at level not seen since 1914.

482.

Tufts Center for Study of Drug Development. Post-1962 explosion in drug development costs. Tufts Center for Study of Drug Development https://csdd.tufts.edu/cost-study (2014)

Cost to develop a new prescription drug: $2.6 billion (2014 Tufts study), increasing to $2.9 billion with post-approval development Represents 145% increase (inflation-adjusted) from 2003 estimate of $802 million Based on 106 drugs from 10 pharmaceutical companies tested between 1995-2007 Note: This study has been controversial; some organizations like Doctors Without Borders suggest actual costs may be substantially lower. Deloitte 2023 report shows costs continuing to rise Additional sources: https://csdd.tufts.edu/cost-study | https://cen.acs.org/articles/92/web/2014/11/Tufts-Study-Finds-Big-Rise.html

483.

Source: US Life Expectancy FDA Budget 1543-2019 CSV. Post-1962 slowdown in life expectancy gains. (2019)

Pre-1962 (1880-1960): 3.82 years/decade Post-1962 (1962-2019): 1.54 years/decade Reduction: 60% decline Temporal correlation: Slowdown occurred immediately after 1962 Kefauver-Harris Amendment Additional sources: https://ourworldindata.org/life-expectancy | https://www.mortality.org/ | https://www.cdc.gov/nchs/nvss/mortality_tables.htm

484.

NIH Common Fund. NIH pragmatic trials: Minimal funding despite 30x cost advantage. NIH Common Fund: HCS Research Collaboratory https://commonfund.nih.gov/hcscollaboratory (2025)

The NIH Pragmatic Trials Collaboratory funds trials at $500K for planning phase, $1M/year for implementation-a tiny fraction of NIH’s budget. The ADAPTABLE trial cost $14 million for 15,076 patients (= $929/patient) versus $420 million for a similar traditional RCT (30x cheaper), yet pragmatic trials remain severely underfunded. PCORnet infrastructure enables real-world trials embedded in healthcare systems, but receives minimal support compared to basic research funding. Additional sources: https://commonfund.nih.gov/hcscollaboratory | https://pcornet.org/wp-content/uploads/2025/08/ADAPTABLE_Lay_Summary_21JUL2025.pdf | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5604499/

485.

Patsopoulos, N. A. Pragmatic vs. Explanatory trials. Patsopoulos https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3181997/ (2011)

Pragmatic trials evaluate the effectiveness of interventions in real-life routine practice conditions, whereas explanatory trials determine the efficacy of interventions under ideal situations. Pragmatic trials produce results that can be generalized and applied in routine practice settings. Note: Pragmatic trials often find smaller effect sizes than explanatory trials but have higher external validity (generalizability to real-world populations) Additional sources: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3181997/

486.

Baily, M. N. Pre-1962 drug development costs (baily 1972). Baily (1972) https://samizdathealth.org/wp-content/uploads/2020/12/hlthaff.1.2.6.pdf (1972)

Pre-1962: Average cost per new chemical entity (NCE) was $6.5 million (1980 dollars) Inflation-adjusted to 2024 dollars: $6.5M (1980) ≈ $22.5M (2024), using CPI multiplier of 3.46× Real cost increase (inflation-adjusted): $22.5M (pre-1962) → $2,600M (2024) = 116× increase Note: This represents the most comprehensive academic estimate of pre-1962 drug development costs based on empirical industry data Additional sources: https://samizdathealth.org/wp-content/uploads/2020/12/hlthaff.1.2.6.pdf

487.

Pre-1962 Drug Development Costs (Congressional Testimony, Alternative Estimate). https://www.congress.gov/95/crecb/1977/04/21/GPO-CRECB-1977-pt10-2-3.pdf (1977)

1962: Average cost $1.2 million (in 1962 dollars) 1972: $11.5 million 1977: Projected $40 million Inflation-adjusted to 2024 dollars: $1.2M (1962) ≈ $12M (2024), using CPI multiplier of 10× Real cost increase (inflation-adjusted): $12M (1962) → $2,600M (2024) = 217× increase Note: Lower estimate than Baily (1972); may reflect incomplete cost accounting or different drug types. Baily’s $6.5M (1980 dollars) = $22.5M (2024 dollars) is the more rigorous academic estimate Additional sources: https://www.congress.gov/95/crecb/1977/04/21/GPO-CRECB-1977-pt10-2-3.pdf

488.

Think by Numbers. Pre-1962 drug development costs and timeline (think by numbers). Think by Numbers: How Many Lives Does FDA Save? https://thinkbynumbers.org/health/how-many-net-lives-does-the-fda-save/ (1962)

Historical estimates (1970-1985): USD $226M fully capitalized (2011 prices) 1980s drugs: $65M after-tax R&D (1990 dollars), $194M compounded to approval (1990 dollars) Modern comparison: $2-3B costs, 7-12 years (dramatic increase from pre-1962) Context: 1962 regulatory clampdown reduced new treatment production by 70%, dramatically increasing development timelines and costs Note: Secondary source; less reliable than Congressional testimony Additional sources: https://thinkbynumbers.org/health/how-many-net-lives-does-the-fda-save/ | https://en.wikipedia.org/wiki/Cost_of_drug_development | https://www.statnews.com/2018/10/01/changing-1962-law-slash-drug-prices/

489.

Think by Numbers. Pre-1962 physician-led clinical trials. Think by Numbers: How Many Lives Does FDA Save? https://thinkbynumbers.org/health/how-many-net-lives-does-the-fda-save/ (1966)

Pre-1962: Physicians could report real-world evidence directly 1962 Drug Amendments replaced "premarket notification" with "premarket approval", requiring extensive efficacy testing Impact: New regulatory clampdown reduced new treatment production by 70%; lifespan growth declined from 4 years/decade to 2 years/decade Drug Efficacy Study Implementation (DESI): NAS/NRC evaluated 3,400+ drugs approved 1938-1962 for safety only; reviewed >3,000 products, >16,000 therapeutic claims FDA has had authority to accept real-world evidence since 1962, clarified by 21st Century Cures Act (2016) Note: Specific "144,000 physicians" figure not verified in sources Additional sources: https://thinkbynumbers.org/health/how-many-net-lives-does-the-fda-save/ | https://www.fda.gov/drugs/enforcement-activities-fda/drug-efficacy-study-implementation-desi | http://www.nasonline.org/about-nas/history/archives/collections/des-1966-1969-1.html

490.

arXiv. Preferential target attachment in clinical trials. arXiv https://arxiv.org/abs/2301.10709 (2023)

Clinical trials overwhelmingly test the same few biological targets due to preferential attachment dynamics. Additional sources: https://arxiv.org/abs/2301.10709

491.

Bowles, S. Prehistoric violence rates. Bowles https://www.science.org/doi/10.1126/science.1168112 (2009)

Archaeological evidence suggests that approximately 15% of prehistoric humans died from violence, compared to less than 1% in modern developed nations. Additional sources: https://www.science.org/doi/10.1126/science.1168112

492.

Princeton. Princeton study on policy outcomes and influence of elites vs. Average citizens. Princeton: Testing Theories of American Politics (PDF) https://archive.org/details/gilens_and_page_2014_-testing_theories_of_american_politics.doc (2014)

Study by Martin Gilens (Princeton) and Benjamin I. Page (Northwestern): Analyzed 1,779 policy outcomes (1981-2002) Finding: "Economic elites and organized groups representing business interests have substantial independent impacts on U.S. government policy, while average citizens have little or no independent influence Rich, well-connected individuals steer the country’s direction, regardless of or even against the will of the majority of voters Note: Specific "78 percent" and "zero percent correlation" statistics not found in sources Additional sources: https://scholar.princeton.edu/sites/default/files/mgilens/files/gilens_and_page_2014_-testing_theories_of_american_politics.doc.pdf | https://act.represent.us/sign/usa-oligarchy-research-explained | https://archive.org/details/gilens_and_page_2014_-testing_theories_of_american_politics.doc

493.

Prison Policy Initiative. Economics of incarceration. (2024).

494.

ProPublica. Filing taxes could be free and simple. But h&r block and intuit are lobbying against it. (2019).

495.

PubMed. Psychological impact of war cost ($100B annually). PubMed: Economic Burden of PTSD https://pubmed.ncbi.nlm.nih.gov/35485933/

PTSD economic burden (2018 U.S.): $232.2B total ($189.5B civilian, $42.7B military) Civilian costs driven by: Direct healthcare ($66B), unemployment ($42.7B) Military costs driven by: Disability ($17.8B), direct healthcare ($10.1B) Exceeds costs of other mental health conditions (anxiety, depression) War-exposed populations: 2-3X higher rates of anxiety, depression, PTSD; women and children most vulnerable Note: Actual burden $232B, significantly higher than "$100B" claimed Additional sources: https://pubmed.ncbi.nlm.nih.gov/35485933/ | https://news.va.gov/103611/study-national-economic-burden-of-ptsd-staggering/ | https://pmc.ncbi.nlm.nih.gov/articles/PMC9957523/

496.

Fox, V. et al. Suicide risk in people with post-traumatic stress disorder: A cohort study of 3.1 million people in sweden. Journal of Affective Disorders 279, 609–616 (2021).

497.

R. H. Bruskin Associates. The 14 worst human fears. (1973).

498.

AllTrials. Publication rate of clinical trial results. AllTrials: Half of Trials Unreported https://www.alltrials.net/news/half-of-all-trials-unreported/ (2013)

50.0% of clinical trials never publish results (NHS-funded systematic review, 2010) Schmucker et al (2014): 53% of trials published (analyzing 39 studies, >20,000 trials) Munch et al (2014): 46% of pain treatment trials published Chang et al (2015): 49% of high-risk cardiac device trials published Positive findings: 3X more likely to be published than negative results Antidepressant example: Published literature showed 94% positive trials; FDA analysis showed only 51% positive Additional sources: https://www.alltrials.net/news/half-of-all-trials-unreported/ | https://www.nature.com/articles/nature.2013.14286 | https://pmc.ncbi.nlm.nih.gov/articles/PMC8276556/

499.

Keitner, G. I., Posternak, M. A. & Ryan, C. E. How many subjects with major depressive disorder meet eligibility requirements of an antidepressant efficacy trial? Journal of Clinical Psychiatry https://www.ncbi.nlm.nih.gov/pubmed/14628985 (2003).

500.

Gosse, M. E. Assessing cost-effectiveness in healthcare: History of the $50,000 per QALY threshold. Sustainability Impact Metrics https://ecocostsvalue.com/EVR/img/references%20others/Gosse%202008%20QALY%20threshold%20financial.pdf (2008).

501.

ICER. Value per QALY (standard economic value). ICER https://icer.org/wp-content/uploads/2024/02/Reference-Case-4.3.25.pdf (2024)

Standard economic value per QALY: $100,000–$150,000. This is the US and global standard willingness-to-pay threshold for interventions that add costs. Dominant interventions (those that save money while improving health) are favorable regardless of this threshold. Additional sources: https://icer.org/wp-content/uploads/2024/02/Reference-Case-4.3.25.pdf

502.

Quincy Institute. Active Denial: A Roadmap to a More Effective, Stabilizing, and Sustainable u.s. Defense Strategy in Asia. https://quincyinst.org/research/active-denial-a-roadmap-to-a-more-effective-stabilizing-and-sustainable-u-s-defense-strategy-in-asia/ (2024).

503.

Quincy Institute. Keys to Developing a More Efficient, Effective Defense at Lower Cost. https://quincyinst.org/research/keys-to-developing-a-more-efficient-effective-defense-at-lower-cost/ (2024).

504.

Quincy Institute. Improving u.s. And global security through military base closures abroad. Quincy Institute for Responsible Statecraft https://quincyinst.org/research/drawdown-improving-u-s-and-global-security-through-military-base-closures-abroad/ (2021).

505.

Orphanet Journal of Rare Diseases (2024). Rare disease treatment gap. Orphanet Journal of Rare Diseases (2024) https://ojrd.biomedcentral.com/articles/10.1186/s13023-024-03398-1 (2024)

Most patients wait 5 to 10 years to get an accurate diagnosis - and only about 5% of rare diseases have an FDA-approved treatment. Over the 40 years of the ODA, 6,340 orphan drug designations were granted, representing drug development for 1,079 rare diseases out of 7,000-10,000 known rare conditions.

506.

Rare Diseases International. 300 million people with rare diseases globally. Rare Diseases International: 300 Million Worldwide https://www.rarediseasesinternational.org/new-scientific-paper-confirms-300-million-people-living-with-a-rare-disease-worldwide/ (2019)

Conservative estimate: 300 million people (3.5-5.9% of world population of 7.5B) Range: 263-446 million people globally Based on Orphanet database analysis of 3,585 rare diseases Note: Excludes rare cancers and infectious diseases, so actual number likely higher Additional sources: https://www.rarediseasesinternational.org/new-scientific-paper-confirms-300-million-people-living-with-a-rare-disease-worldwide/ | https://sciencedaily.com/releases/2019/10/191024075007.htm | https://pmc.ncbi.nlm.nih.gov/articles/PMC9632971/

507.

Rawls, J. A Theory of Justice. (Harvard University Press, 1971).

508.

staff, R. Is donald trump to blame for a COVID lab leak? Reason https://reason.com/2025/05/22/is-donald-trump-to-blame-for-a-covid-lab-leak/ (2025).

509.

IMF. Reconstruction costs from active conflicts. IMF: Cost of Conflict https://www.imf.org/external/pubs/ft/fandd/2017/12/imus.htm (2017)

Individual conflict examples: Libya, Syria, Yemen $300B combined (World Bank) Syria alone: $250B-$1T estimates Ukraine: >€500B reconstruction costs Gaza: $18.5B infrastructure damage Global conflict/violence cost: $14.3T/year (2016, includes military spending, security, losses) Note: Specific "$1,875B for 47 conflicts" figure not verified in sources Additional sources: https://www.imf.org/external/pubs/ft/fandd/2017/12/imus.htm | https://www.weforum.org/stories/2018/01/conflict-costs-global-economy-14-trillion-a-year/ | https://fortune.com/2022/04/21/ukraine-reconstruction-cost-rebuild-economists-plan-russia-foot-trillion-bill/

510.

RECOVER Initiative. RECOVER initiative budget update (>$2.3B). RECOVER Initiative https://recovercovid.org/news/nih-adds-funds-long-covid-research-advances-work-new-clinical-trials (2024).

511.

RECOVER Initiative. Funding | RECOVER COVID initiative. (2024).

512.

NIH. NIH RECOVER initiative patient enrollment numbers. NIH: RECOVER Initiative Enrollment https://www.nih.gov/news-events/news-releases/nih-builds-large-nationwide-study-population-tens-thousands-support-research-long-term-effects-covid-19

Enrolled: 30,000 people in ongoing studies and clinical trials Goal: 40,000 adults and children $1.15B effort (including American Rescue Plan Act 2021 support) One of largest, most diverse Long COVID cohorts in world Additional sources: https://www.nih.gov/news-events/news-releases/nih-builds-large-nationwide-study-population-tens-thousands-support-research-long-term-effects-covid-19 | https://recovercovid.org/news/nih-launches-long-covid-clinical-trials-through-recover-initiative-opening-enrollment

513.

Ladyzhets, B. ’Underwhelming’: NIH trials fail to test meaningful long Covid treatments – after 2.5 years and $1 billion. STAT News https://www.statnews.com/2023/08/09/long-covid-nih-trials/ (2023)

Patient advocates called RECOVER’s treatment selections ‘truly absurd’ (Jaime Seltzer, #MEAction). David Putrino (Mount Sinai) said funding ‘has been largely wasted.’ Low-dose naltrexone, the top patient-requested treatment, was excluded for over 2 years before being added in round 2.

514.

Oren Cass, Manhattan Institute. RECOVERY trial cost per patient. Oren Cass https://manhattan.institute/article/slow-costly-clinical-trials-drag-down-biomedical-breakthroughs (2023)

The RECOVERY trial, for example, cost only about $500 per patient... By contrast, the median per-patient cost of a pivotal trial for a new therapeutic is around $41,000. Additional sources: https://manhattan.institute/article/slow-costly-clinical-trials-drag-down-biomedical-breakthroughs

515.

University of Oxford. RECOVERY trial time to first cure. University of Oxford https://www.ox.ac.uk/news/2020-06-16-dexamethasone-reduces-death-hospitalised-patients-severe-respiratory-complications (2020)

100 days to first cure Additional sources: https://www.ox.ac.uk/news/2020-06-16-dexamethasone-reduces-death-hospitalised-patients-severe-respiratory-complications | https://www.recoverytrial.net/news/low-cost-dexamethasone-reduces-death-by-up-to-one-third-in-hospitalised-patients-with-severe-respiratory-complications-of-covid-19

516.

NHS England; Águas et al. RECOVERY trial global lives saved ( 1 million). NHS England: 1 Million Lives Saved https://www.england.nhs.uk/2021/03/covid-treatment-developed-in-the-nhs-saves-a-million-lives/ (2021)

Dexamethasone saved 1 million lives worldwide (NHS England estimate, March 2021, 9 months after discovery). UK alone: 22,000 lives saved. Methodology: Águas et al. Nature Communications 2021 estimated 650,000 lives (range: 240,000-1,400,000) for July-December 2020 alone, based on RECOVERY trial mortality reductions (36% for ventilated, 18% for oxygen-only patients) applied to global COVID hospitalizations. June 2020 announcement: Dexamethasone reduced deaths by up to 1/3 (ventilated patients), 1/5 (oxygen patients). Impact immediate: Adopted into standard care globally within hours of announcement. Additional sources: https://www.england.nhs.uk/2021/03/covid-treatment-developed-in-the-nhs-saves-a-million-lives/ | https://www.nature.com/articles/s41467-021-21134-2 | https://pharmaceutical-journal.com/article/news/steroid-has-saved-the-lives-of-one-million-covid-19-patients-worldwide-figures-show | https://www.recoverytrial.net/news/recovery-trial-celebrates-two-year-anniversary-of-life-saving-dexamethasone-result

517.

Manhattan Institute. RECOVERY trial 82× cost reduction. Manhattan Institute: Slow Costly Trials https://manhattan.institute/article/slow-costly-clinical-trials-drag-down-biomedical-breakthroughs

RECOVERY trial: $500 per patient ($20M for 48,000 patients = $417/patient) Typical clinical trial: $41,000 median per-patient cost Cost reduction: 80-82× cheaper ($41,000 ÷ $500 ≈ 82×) Efficiency: $50 per patient per answer (10 therapeutics tested, 4 effective) Dexamethasone estimated to save >630,000 lives Additional sources: https://manhattan.institute/article/slow-costly-clinical-trials-drag-down-biomedical-breakthroughs | https://pmc.ncbi.nlm.nih.gov/articles/PMC9293394/

518.

RECOVERY Trial. RECOVERY trial cost reduction. RECOVERY Trial https://www.recoverytrial.net/

Oxford RECOVERY trial achieved $500 per patient cost, compared to traditional Phase III trial costs of $40,000-120,000+ per patient. This represents an 80-100x+ cost reduction. Key strategies: embedding trial protocols within routine hospital care, minimizing overhead by leveraging existing staff/resources and electronic data capture, and focused pragmatic trial designs. Additional sources: https://www.recoverytrial.net/

519.

RECOVERY Trial. RECOVERY trial dexamethasone results. RECOVERY Trial https://www.recoverytrial.net/news/low-cost-dexamethasone-reduces-death-by-up-to-one-third-in-hospitalised-patients-with-severe-respiratory-complications-of-covid-19

Dexamethasone reduced deaths by one-third in ventilated patients (rate ratio 0.65 [95% confidence interval 0.48 to 0.88]; $p=0.0003$) and by one fifth in other patients receiving oxygen only (0.80 [0.67 to 0.96]; $p=0.0021$) Additional sources: https://www.recoverytrial.net/news/low-cost-dexamethasone-reduces-death-by-up-to-one-third-in-hospitalised-patients-with-severe-respiratory-complications-of-covid-19

520.

Professor Martin Landray (co-chief investigator), quoted in Oren Cass, Manhattan Institute. RECOVERY trial efficiency. Professor Martin Landray (co-chief investigator) https://manhattan.institute/article/slow-costly-clinical-trials-drag-down-biomedical-breakthroughs (2023)

At a cost of $20 million for 48,000 patients, the RECOVERY trial cost about $500 per patient... that is about $50 per patient per answer. Additional sources: https://manhattan.institute/article/slow-costly-clinical-trials-drag-down-biomedical-breakthroughs

521.

RECOVERY Collaborative Group. RECOVERY trial cost-effectiveness ( $4/QALY, global impact methodology). RECOVERY Trial Results https://www.recoverytrial.net/results

RECOVERY trial (UK) cost $20M total and discovered that dexamethasone reduces COVID mortality by 1/3 in severe cases, saving 1 million lives globally. Using global impact methodology (research discovery value): $20M / (1M lives × 5 QALYs/life) = $4/QALY. This is 12,500× more cost-effective than standard NIH research allocation ($50,000/QALY). Additional sources: https://www.recoverytrial.net/results

522.

Oxford University News. RECOVERY trial summary quote. Oxford University News https://www.ox.ac.uk/news/features/recovery-trial-two-years

One trial. Over 47,000 participants. Nearly 200 hospital sites, across six countries. Ten results. Four effective COVID-19 treatments... Through discovering four treatments that effectively reduce deaths from COVID-19, it is certain that the study has saved thousands – if not millions – of lives worldwide. Additional sources: https://www.ox.ac.uk/news/features/recovery-trial-two-years

523.

ASPE. Refugee lost annual earning potential ($23,400). ASPE: Fiscal Impact of Refugees https://aspe.hhs.gov/reports/fiscal-impact-refugees-asylees

Refugee economic impact: Net positive $123.8B fiscal impact (2005-2019, 15 years) Refugees pay $21K more in taxes than benefits received over first 20 years in U.S. Earnings gap: Refugees work at higher rates than natives but earn less; never reach U.S.-born earning levels Income progression: <5 years in U.S. = $30,500 median; 20+ years = $71,400 (exceeds national $67,100 median) Note: Specific "$23,400 lost earning potential" figure not verified in sources Additional sources: https://aspe.hhs.gov/reports/fiscal-impact-refugees-asylees | https://www.americanimmigrationcouncil.org/sites/default/files/research/05.23_refugee_report_v3_0.pdf | https://www.nber.org/system/files/working_papers/w23498/w23498.pdf

524.

Wake Forest. Milestones in regenerative medicine and tissue engineering. Wake Forest: Record of Firsts https://school.wakehealth.edu/research/institutes-and-centers/wake-forest-institute-for-regenerative-medicine/research/a-record-of-firsts

1999: First 3D-printed organ (bladder) transplanted into human (Wake Forest Institute, still functioning 20+ years later) Windpipes (trachea): 3D-printed windpipe transplants performed; patient received biodegradable 5-year windpipe Blood vessels, skin: Mobile bioprinters can print skin directly onto wounds at patient bedside Tubular organs: Urine conduits engineered and implanted in patients 3D-printed ear implant: World’s first successfully transplanted Current status: Can print flat structures (skin), tubular (blood vessels), hollow non-tubular (bladder); complex life-sized organs 20-30 years away Additional sources: https://school.wakehealth.edu/research/institutes-and-centers/wake-forest-institute-for-regenerative-medicine/research/a-record-of-firsts | https://builtin.com/articles/3d-printed-organs | https://pmc.ncbi.nlm.nih.gov/articles/PMC5313259/

525.

JAMA. Research to practice gap (17 years). JAMA https://pubmed.ncbi.nlm.nih.gov/37018006/ (2023)

It takes an average of 17 years for new scientific evidence to be implemented into clinical practice. Additional sources: https://pubmed.ncbi.nlm.nih.gov/37018006/

526.

WHO. Annual deaths from respiratory disease. WHO: COPD Fact Sheet) https://www.who.int/news-room/fact-sheets/detail/chronic-obstructive-pulmonary-disease-(copd (2019)

Chronic respiratory diseases: 4.0 million deaths annually (2019) COPD specifically: 3.5 million deaths (2021) - 4th leading cause of death globally Pneumonia: 2.5 million deaths including 672,000 children (2019) Combined respiratory deaths: 6.5 million annually Note: 90% of COPD deaths in those under 70 occur in low- and middle-income countries. COPD affects over 380 million people globally Additional sources: https://www.who.int/news-room/fact-sheets/detail/chronic-obstructive-pulmonary-disease-(copd | https://www.healthdata.org/research-analysis/library/global-burden-chronic-respiratory-diseases-and-risk-factors-1990-2019

527.

Smithberger, M. & Hartung, W. Top defense firms see $2T return on $1B investment in afghan war. Responsible Statecraft https://responsiblestatecraft.org/2021/09/02/top-military-firms-see-2t-return-on-1b-investment-in-afghan-war/ (2021).

528.

Reynolds, A. J., Temple, J. A., White, B. A., Ou, S.-R. & Robertson, D. L. Age 26 cost-benefit analysis of the child-parent center early education program. Child Development 82, 379–404 (2011).

529.

Congress.gov. Right to try act (2018). Congress.gov https://www.congress.gov/bill/115th-congress/house-bill/2368 (2018)

Right to Try Act (2018) Additional sources: https://www.congress.gov/bill/115th-congress/house-bill/2368 | https://pmc.ncbi.nlm.nih.gov/articles/PMC7416898/

530.

PMC. Number of patients helped by the u.s. Right to try act. PMC: Understanding Right to Try https://pmc.ncbi.nlm.nih.gov/articles/PMC7416898/ (2024)

2018-2022: Supported access to only 12 products total; 4 products in 2023 Number of people treated: Not publicly reported, "likely only in the hundreds Specific documented cases: 75+ neuroendocrine cancer patients (LU-177); at least 1 ALS patient (NurOwn); 7 glioblastoma patients (Gliovac) Minimal safety reporting: Only annual basis, no requirement to publish results/outcomes Additional sources: https://pmc.ncbi.nlm.nih.gov/articles/PMC7416898/ | https://www.statnews.com/2024/08/02/trump-gave-patients-right-to-try-it-hasnt-helped-them/ | https://www.healio.com/news/hematology-oncology/20200303/right-to-try-a-wellintentioned-but-misguided-law

531.

Roth, A. E. The economist as engineer: Game theory, experimentation, and computation as tools for design economics. Econometrica 70, 1341–1378 (2002).

532.

Rothman, K. J., Greenland, S. & Lash, T. L. Modern Epidemiology. (Lippincott Williams; Wilkins, 2008).

Standard epidemiology textbook covering causal inference, dose-response relationships, and study design. Provides framework for assessing biological gradients in exposure-outcome relationships.

533.

Thomas L. Saaty. The Analytic Hierarchy Process. (Saaty, 1980).

The foundational text on the Analytic Hierarchy Process (AHP) methodology for decision-making. AHP decomposes complex decisions into hierarchies of criteria and sub-criteria, then elicits pairwise comparisons at each level. For n alternatives, this requires only n(n-1)/2 comparisons rather than the cognitively impossible simultaneous comparison of all n options. The pairwise comparison matrices are then synthesized using eigenvector methods to produce consistent priority rankings. Additional sources: https://archive.org/details/analytichierarch0000saat | https://books.google.com/books/about/The_Analytic_Hierarchy_Process.html?id=Xxi7AAAAIAAJ | https://link.springer.com/chapter/10.1007/978-1-4613-2805-6_12

534.

Thomas L. Saaty. Decision making with the analytic hierarchy process. Saaty 1, 83–98 (2008)

Decisions involve many intangibles that need to be traded off. To do that, they have to be measured along side tangibles whose measurements must also be evaluated as to, how well, they serve the objectives of the decision maker. The Analytic Hierarchy Process (AHP) is a theory of measurement through pairwise comparisons and relies on the judgements of experts to derive priority scales. This paper has been cited 9,181 times, with 1,042 highly influential citations. Additional sources: https://www.inderscienceonline.com/doi/abs/10.1504/IJSSci.2008.01759 | https://www.semanticscholar.org/paper/DECISION-MAKING-WITH-THE-ANALYTIC-HIERARCHY-PROCESS-Saaty/e3c561049eb532e328fc2b8288c490986cd9403f | https://www.researchgate.net/publication/228628807_Decision_making_with_the_Analytic_Hierarchy_Process

535.

Scheidel, W. State revenue and expenditure in the han and roman empires. in State power in ancient china and rome (Oxford University Press, 2015).

Comparative analysis of state fiscal capacity in the Han and Roman empires. The Roman army accounted for 60-80% of total state expenditure, making it the dominant fiscal commitment throughout Roman history. Military spending was described as ‘massively redistributive in both spatial and social terms.’ Both empires were essentially low-tax regimes (estimated 5-7% of GDP in taxes), but the Roman Empire allocated a far larger share of state revenue to its military than did the Han.

536.

From Science to Pharma. The costs of clinical trials. From Science to Pharma https://www.fromsciencetopharma.com/blog/the-costs-of-clinical-trials (2024).

537.

Richard Dawkins. The selfish gene quote. Richard Dawkins https://en.wikipedia.org/wiki/The_Selfish_Gene (1976)

We are survival machines, robot vehicles blindly programmed to preserve the selfish molecules known as genes. Additional sources: https://en.wikipedia.org/wiki/The_Selfish_Gene

538.

Doody, R. S. et al. A phase 3 trial of semagacestat for treatment of alzheimer’s disease. New England Journal of Medicine 369, 341–350 (2013)

Phase III trial of gamma-secretase inhibitor semagacestat for Alzheimer’s disease was terminated early by Eli Lilly. Patients on treatment showed significantly WORSE cognitive outcomes than placebo, plus increased skin cancers and infections. 1,537 patients randomized. Example of Phase III trial preventing approval of a drug that would have harmed patients.

539.

National September 11 Memorial & Museum. September 11 attack facts. (2024)

2,977 people were killed in the September 11, 2001 attacks: 2,753 at the World Trade Center, 184 at the Pentagon, and 40 passengers and crew on United Flight 93 in Shanksville, Pennsylvania.

540.

Shepherd, M. E. & You, H. Y. Exit strategy: Career concerns and revolving doors in congress. American Political Science Review 114, 270–284 (2019).

541.

Stockholm International Peace Research Institute. Trends in world military expenditure, 2024. (2025).

542.

SIPRI. Stockholm international peace research institute. (2025).

543.

Stockholm International Peace Research Institute. Trends in world military expenditure, 2023. (2024).

544.

CSIS. Smallpox eradication ROI. CSIS https://www.csis.org/analysis/smallpox-eradication-model-global-cooperation.

545.

Yahoo Finance. George soros’s 1992 bet against the british pound. Yahoo Finance: British Pounding https://finance.yahoo.com/news/british-pounding-george-soros-made-160033593.html

Black Wednesday (September 16, 1992): Soros assembled $10 billion short position against British pound Increased position from $1.5B to $10B that morning; bought German marks while selling pounds Profit: Over £1 billion ($1-1.5 billion) in single day UK Treasury cost: £3.3 billion; Bank of England spent $29 billion trying to defend pound Pound fell 15% vs. German mark, 25% vs. dollar; UK forced to exit European Exchange Rate Mechanism Earned Soros title "the man who broke the Bank of England Additional sources: https://finance.yahoo.com/news/british-pounding-george-soros-made-160033593.html | https://en.wikipedia.org/wiki/Black_Wednesday | https://www.thebalancemoney.com/black-wednesday-george-soros-bet-against-britain-1978944

546.

Historic UK. The south sea bubble of 1720. Historic UK: South Sea Bubble https://www.historic-uk.com/HistoryUK/HistoryofEngland/South-Sea-Bubble/

South Sea Company founded 1711 as public-private partnership to consolidate national debt Granted monopoly (Asiento de Negros) to supply African slaves to South America (1713) Stock price explosion: £128 (Jan 1720) → £175 (Feb) → £330 (Mar) → £550 (May) → £1,000 (Aug) Reality: No realistic prospect of trade; Company never realized significant profit from monopoly Collapse: By September market crashed; December shares down to £124 Called world’s first financial crash, first Ponzi scheme, classic "group think" speculation mania Story disconnected from actual (negligible) profits Additional sources: https://www.historic-uk.com/HistoryUK/HistoryofEngland/South-Sea-Bubble/ | https://en.wikipedia.org/wiki/South_Sea_Company | https://www.britannica.com/money/South-Sea-Bubble

547.

Spenkuch, J. L. & Toniatti, D. Does campaign spending affect election outcomes? New evidence from transaction-level disbursement data. The Journal of Politics 82, 1502–1515 (2018).

548.

S&P Dow Jones Indices. SPIVA u.s. Scorecard year-end 2023. (2023)

Over the 15-year period ending Dec. 2023, 87.98% of large-cap U.S. equity funds underperformed the S&P 500. The longer the time horizon, the more difficult it becomes for active managers to outperform. SPIVA (S&P Indices Versus Active) provides the de facto scorecard for the active vs. passive debate. Additional sources: https://www.spglobal.com/spdji/en/research-insights/spiva/

549.

PMC. Standard medical research ROI ($20k-$100k/QALY). PMC: Cost-effectiveness Thresholds Used by Study Authors https://pmc.ncbi.nlm.nih.gov/articles/PMC10114019/ (1990)

Typical cost-effectiveness thresholds for medical interventions in rich countries range from $50,000 to $150,000 per QALY. The Institute for Clinical and Economic Review (ICER) uses a $100,000-$150,000/QALY threshold for value-based pricing. Between 1990-2021, authors increasingly cited $100,000 (47% by 2020-21) or $150,000 (24% by 2020-21) per QALY as benchmarks for cost-effectiveness. Additional sources: https://pmc.ncbi.nlm.nih.gov/articles/PMC10114019/ | https://icer.org/our-approach/methods-process/cost-effectiveness-the-qaly-and-the-evlyg/

550.

Statistics Times. World GDP 2025. Statistics Times https://statisticstimes.com/economy/world-gdp.php (2025).

551.

Composite estimate based on Orphanet. Average time to cure under current system.

Queue-based calculation: 7,000 diseases without effective treatment ÷ 15 diseases getting first treatment per year = 467 years for the average disease to receive a cure under the status quo system. This is consistent with the fact that only 5% of rare diseases have treatments after 40+ years of the Orphan Drug Act. Well-funded diseases may take 30-50 years; underfunded diseases 100-500+ years; and neglected diseases effectively never within human planning horizons.

552.

Honmou, O. et al. Intravenous infusion of auto serum-expanded autologous mesenchymal stem cells in spinal cord injury patients: 13 case series. Clinical Neurology and Neurosurgery 203, 106565 (2021)

In this investigator-initiated clinical trial (2014-2017), 12 of 13 patients (92%) with cervical spinal cord injury who received MSC transplantation achieved at least one level of improvement on American Spinal Injury Association Impairment Scale. Five of six AIS A patients improved to AIS B (3/6) or AIS C (2/6). No severe side effects. Results led to MHLW conditional approval of STEMIRAC in December 2018.

553.

Stigler, G. J. The theory of economic regulation. Stigler 2, 3–21 (1971)

As a rule, regulation is acquired by the industry and is designed and operated primarily for its benefit.

554.

Stratmann, T. Can special interests buy congressional votes? Evidence from financial services legislation. The Journal of Law and Economics 45, 345–373 (2002).

555.

Stratmann, T. Some talk: Money in politics. A (partial) review of the literature. Public Choice 124, 135–156 (2005).

556.

GAO. Annual cost of u.s. Sugar subsidies. GAO: Sugar Program https://www.gao.gov/products/gao-24-106144

Consumer costs: $2.5-3.5 billion per year (GAO estimate) Net economic cost: $1 billion per year 2022: US consumers paid 2X world price for sugar Program costs $3-4 billion/year but no federal budget impact (costs passed directly to consumers via higher prices) Employment impact: 10,000-20,000 manufacturing jobs lost annually in sugar-reliant industries (confectionery, etc.) Multiple studies confirm: Sweetener Users Association ($2.9-3.5B), AEI ($2.4B consumer cost), Beghin & Elobeid ($2.9-3.5B consumer surplus) Additional sources: https://www.gao.gov/products/gao-24-106144 | https://www.heritage.org/agriculture/report/the-us-sugar-program-bad-consumers-bad-agriculture-and-bad-america | https://www.aei.org/articles/the-u-s-spends-4-billion-a-year-subsidizing-stalinist-style-domestic-sugar-production/

557.

WHO. Global suicide deaths vs. Combat deaths. WHO https://www.who.int/publications/i/item/9789240110069 (2021)

Suicide deaths: 727,000 annually (2021), over 700,000 per year on average One person dies by suicide every 40 seconds 3rd leading cause of death among 15-29 year olds globally 73% of suicides occur in low- and middle-income countries Combat deaths: 89,000 annually (significantly lower than suicide) Note: Link between suicide and mental disorders (depression, alcohol use) is well-established. With timely, evidence-based interventions, suicides can be prevented Additional sources: https://www.who.int/publications/i/item/9789240110069 | https://www.who.int/news-room/fact-sheets/detail/suicide

558.

Supreme Court of the United States. United states v. Sun-diamond growers of california. (1999).

559.

Sunstein, C. R. The Cost-Benefit State: The Future of Regulatory Protection. (Sunstein, Chicago, 2002).

Cost-benefit analysis, properly understood, is not only a useful tool but also an indispensable safeguard against both excessive and insufficient regulation.

560.

James Surowiecki. The Wisdom of Crowds. (Surowiecki, 2004).

Explores the aggregation of information in groups, arguing that decisions are often better than could have been made by any single member of the group. The opening anecdote relates Francis Galton’s surprise that the crowd at a county fair accurately guessed the weight of an ox when the median of their individual guesses was taken. The three conditions for a group to be intelligent are diversity, independence, and decentralization. Additional sources: https://archive.org/details/wisdomofcrowds0000suro | https://en.wikipedia.org/wiki/The_Wisdom_of_Crowds | https://www.amazon.com/Wisdom-Crowds-James-Surowiecki/dp/0385721706

561.

Suskind, R. Confidence Men: Wall Street, Washington, and the Education of a President. (Harper, 2011).

Chapter 12, p. 289: Volcker quote on civil engineers vs. financial engineers.

562.

World Bank. Swiss military budget as percentage of GDP. World Bank: Military Expenditure https://data.worldbank.org/indicator/MS.MIL.XPND.GD.ZS?locations=CH

2023: 0.70272% of GDP (World Bank) 2024: CHF 5.95 billion official military spending When including militia system costs: 1% GDP (CHF 8.75B) Comparison: Near bottom in Europe; only Ireland, Malta, Moldova spend less (excluding microstates with no armies) Additional sources: https://data.worldbank.org/indicator/MS.MIL.XPND.GD.ZS?locations=CH | https://www.avenir-suisse.ch/en/blog-defence-spending-switzerland-is-in-better-shape-than-it-seems/ | https://tradingeconomics.com/switzerland/military-expenditure-percent-of-gdp-wb-data.html

563.

Ballotpedia. Swiss referendum bans construction of minarets. Ballotpedia https://ballotpedia.org/Swiss_Minaret_Construction_Ban,_2009 (2009)

On 29 November 2009 Swiss voters approved a constitutional ban on minaret construction by 57.5% on 53.4% turnout. Pre-election polls had predicted only 35% support. Highest support: Appenzell Innerrhoden (71%). Only 3 of 26 cantons opposed. Cited as example of direct democracy enabling majority prejudice against minority rights.

564.

World Bank. Switzerland vs. US GDP per capita comparison. World Bank: Switzerland GDP Per Capita https://data.worldbank.org/indicator/NY.GDP.PCAP.CD?locations=CH

2024 GDP per capita (PPP-adjusted): Switzerland $93,819 vs United States $75,492 Switzerland’s GDP per capita 24% higher than US when adjusted for purchasing power parity Nominal 2024: Switzerland $103,670 vs US $85,810 Additional sources: https://data.worldbank.org/indicator/NY.GDP.PCAP.CD?locations=CH | https://tradingeconomics.com/switzerland/gdp-per-capita-ppp | https://www.theglobaleconomy.com/USA/gdp_per_capita_ppp/

565.

KFF Health System Tracker. Switzerland vs. US life expectancy comparison. KFF Health System Tracker: Life Expectancy Comparison https://www.healthsystemtracker.org/chart-collection/u-s-life-expectancy-compare-countries/

Switzerland: 84 years | United States: 78.4 years (2023) U.S. has lowest life expectancy among comparable developed countries (average: 82.5 years) Gap driven by preventable causes: cardiovascular disease, drug overdoses, firearm violence, motor vehicle crashes Note: U.S. spends nearly twice as much on healthcare per person as comparable countries despite lower life expectancy. The disadvantage began in 1950s and has worsened over past 4 decades Additional sources: https://www.healthsystemtracker.org/chart-collection/u-s-life-expectancy-compare-countries/

566.

SWI swissinfo.ch. Women’s suffrage in switzerland: The last canton to grant women the vote. SWI swissinfo.ch https://www.swissinfo.ch/eng/politics/a-visit-to-appenzell-inner-rhodes-the-last-canton-to-grant-women-the-right-to-vote-in-switzerland/46328984 (2021)

Switzerland granted women national voting rights on 7 February 1971, among the last European nations to do so. Appenzell Innerrhoden’s all-male Landsgemeinde rejected women’s suffrage three times. On 26 November 1990 the Federal Court overruled the canton. Women first participated in the Landsgemeinde on 28 April 1991.

567.

Wikipedia. Switzerland’s last military conflict. Wikipedia: Sonderbund War https://en.wikipedia.org/wiki/Sonderbund_War (2019)

Sonderbund War (November 3-29, 1847): Last armed conflict on Swiss soil Civil war between 7 Catholic cantons vs. federal government over centralization Duration: 26 days; Casualties: 93 deaths total (60 federal, 33 Sonderbund), 510 wounded Federal army (100,000) led by General Guillaume Henri Dufour defeated Sonderbund forces Resulted in emergence of Switzerland as federal state; entered period of peace lasting to present Battle of Gisikon: Last battle Swiss ever fought Additional sources: https://en.wikipedia.org/wiki/Sonderbund_War | https://militaryhistorynow.com/2019/02/27/charm-offensive-switzerlands-polite-war-of-1847/ | https://www.zeit-fragen.ch/en/archives/2018/no-1-10-january-2018/the-sonderbund-war-the-last-armed-conflict-on-swiss-soil

568.

Hanna, T. P. et al. Mortality due to cancer treatment delay: Systematic review and meta-analysis. BMJ https://doi.org/10.1136/bmj.m4087 (2020) doi:10.1136/bmj.m4087.

569.

Marshall, M. G. & Gurr, T. R. Polity5 project: Political regime characteristics and transitions, 1800–2018. (2020).

570.

House Committee on Oversight and Government Reform. Hearing wrap up: NIH refutes EcoHealth’s testimony, Tabak reveals federal grant procedures in need of serious reform. (2024).

571.

Tabarrok, A. The private provision of public goods via dominant assurance contracts. Public Choice 96, 345–362 (1998).

572.

Treasury. Troubled asset relief program (TARP) of 2008. Treasury: TARP About https://home.treasury.gov/data/troubled-assets-relief-program/about-tarp

Authorized: $700 billion (later reduced to $475 billion by Dodd-Frank) Actual disbursed: $443.5 billion to stabilize financial institutions Bank rescue: $236 billion to 707 financial institutions in 48 states Breakdown: $250B banking, $82B auto industry, $70B AIG, $46B foreclosure programs Net lifetime cost: $31.1 billion (after repayments, sales, dividends, interest); most attributable to foreclosure programs Passed October 3, 2008 (signed by President Bush); Emergency Economic Stabilization Act Additional sources: https://home.treasury.gov/data/troubled-assets-relief-program/about-tarp | https://en.wikipedia.org/wiki/Troubled_Asset_Relief_Program | https://www.propublica.org/article/the-bailout-was-11-years-ago-were-still-tracking-every-penny

573.

Tax Foundation. Tax compliance costs the US economy $546 billion annually. https://taxfoundation.org/data/all/federal/irs-tax-compliance-costs/ (2024)

Americans will spend over 7.9 billion hours complying with IRS tax filing and reporting requirements in 2024. This costs the economy roughly $413 billion in lost productivity. In addition, the IRS estimates that Americans spend roughly $133 billion annually in out-of-pocket costs, bringing the total compliance costs to $546 billion, or nearly 2 percent of GDP.

574.

Jones, S. G. Terrorism before and during the war on terror: A look at the numbers. War on the Rocks https://warontherocks.com/2017/12/terrorism-war-terror-look-numbers/ (2017)

Analysis of terrorism trends showing dramatic increase in global terrorist attacks after 2001, with attacks rising from roughly 1,000 per year in 2004 to nearly 17,000 by 2014, driven primarily by proliferation of jihadist organizations in Iraq, Afghanistan, Pakistan, Nigeria, and Syria.

575.

FDA. Thalidomide caused thousands of birth defects. FDA https://www.fda.gov/about-fda/fda-history-exhibits/frances-oldham-kelsey-medical-reviewer-famous-averting-public-health-tragedy

it resulted in thousands of horrific congenital disabilities. Additional sources: https://www.fda.gov/about-fda/fda-history-exhibits/frances-oldham-kelsey-medical-reviewer-famous-averting-public-health-tragedy | https://www.smithsonianmag.com/science-nature/woman-who-stood-between-america-and-epidemic-birth-defects-180963165/

576.

FDA. FDA dr. Kelsey prevented widespread thalidomide birth defects in the US. FDA: Frances Oldham Kelsey https://www.fda.gov/about-fda/fda-history-exhibits/frances-oldham-kelsey-medical-reviewer-famous-averting-public-health-tragedy

Dr. Frances Kelsey (FDA reviewer) resisted pressure to approve thalidomide September 1960-November 1961 Worldwide: 8,000 infants born with missing/malformed limbs; 5,000-7,000 perished in utero United States: 17 confirmed phocomelia cases + 9 likely cases (vs. 8,000 worldwide) Kelsey insisted on hard evidence, refused to be browbeaten; repeatedly requested more information every 60 days Merrell complained to her bosses, calling her "petty bureaucrat" - she persisted Recognition: President’s Award for Distinguished Federal Civilian Service (JFK, 1962) Led to 1962 Kefauver-Harris Amendments requiring drugs prove both safety AND effectiveness Additional sources: https://www.fda.gov/about-fda/fda-history-exhibits/frances-oldham-kelsey-medical-reviewer-famous-averting-public-health-tragedy | https://www.uchicagomedicine.org/forefront/biological-sciences-articles/courageous-physician-scientist-saved-the-us-from-a-birth-defects-catastrophe | https://www.smithsonianmag.com/science-nature/woman-who-stood-between-america-and-epidemic-birth-defects-180963165/

577.

Wikipedia. Thalidomide scandal: Worldwide cases and mortality. Wikipedia https://en.wikipedia.org/wiki/Thalidomide_scandal

The total number of embryos affected by the use of thalidomide during pregnancy is estimated at 10,000, of whom about 40% died around the time of birth. More than 10,000 children in 46 countries were born with deformities such as phocomelia. Additional sources: https://en.wikipedia.org/wiki/Thalidomide_scandal

578.

PLOS One. Health and quality of life of thalidomide survivors as they age. PLOS One https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0210222 (2019)

Study of thalidomide survivors documenting ongoing disability impacts, quality of life, and long-term health outcomes. Survivors (now in their 60s) continue to experience significant disability from limb deformities, organ damage, and other effects. Additional sources: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0210222

579.

Pessoa-Amorim, G., Peto, L. & Campbell, M. The inside story of RECOVERY: How the world’s largest COVID-19 trial transformed treatment. (2022).

580.

Nieuwenhuijs, J. How france secretly repatriated all its gold before nixon’s dollar devaluation. https://www.thegoldobserver.com/p/how-france-secretly-repatriated-all (2023).

581.

The Nation. The pentagon’s revolving door keeps spinning. The Nation https://www.pogo.org/analyses/the-pentagons-revolving-door-keeps-spinning-2021-in-review (2021)

From 2009 to 2019, approximately 380 high-ranking Department of Defense officials and military officers transitioned to become lobbyists, board members, executives, or consultants for military contractors. Former members of Congress routinely transition to lucrative lobbying and consulting careers in the defense sector, with compensation often 10-20 times their congressional salary. Additional sources: https://www.pogo.org/analyses/the-pentagons-revolving-door-keeps-spinning-2021-in-review

582.

Lichtenberg, F. R. How many life-years have new drugs saved? A three-way fixed-effects analysis of 66 diseases in 27 countries, 2000–2013. International Health https://pubmed.ncbi.nlm.nih.gov/30912800 (2019).

583.

Thucydides. The History of the Peloponnesian War. (J. M. Dent / E. P. Dutton, 1910).

Thucydides’ account of the Peloponnesian War (431–404 BC) documents the Athenian assembly’s decision to launch the Sicilian Expedition (415 BC), a paradigmatic case of democratic mob rule. Alcibiades’ rhetoric persuaded the assembly to undertake a catastrophic military campaign that destroyed a third of Athens’ fleet and tens of thousands of soldiers. Books 6–7 detail how unbounded direct democracy, operating without domain constraints or manipulation resistance, produced a decision that no informed deliberative process would have endorsed.

584.

UNDP. Tobacco control ROI. UNDP https://www.undp.org/asia-pacific/blog/how-raising-tobacco-taxes-can-save-lives-and-cut-poverty-across-asia-pacific-0

In our study of six Asia-Pacific countries, we found that for every unit of local currency invested in increasing tobacco taxes, the countries would gain between 20 and 1,057 units in return over 15 years. That’s a remarkable return on investment ratio of between 20:1 and 1,057:1. Additional sources: https://www.undp.org/asia-pacific/blog/how-raising-tobacco-taxes-can-save-lives-and-cut-poverty-across-asia-pacific-0

585.

Alternatives Investor. Top performing private equity & hedge funds. Alternatives Investor https://alternativesinvestor.com/top-performing-private-equity-funds-2016-2019 (2021)

Top-performing private equity funds, such as Spectrum’s VIII-A Program, have achieved net IRRs as high as 98.91% for a single vintage year (2017). Renaissance Technologies’ Medallion Fund is famed for achieving an average annualized gross return of 66%, and a net return of 39%, from 1988 to 2021. Additional sources: https://alternativesinvestor.com/top-performing-private-equity-funds-2016-2019 | https://www.traderslog.com/top-hedge-funds

586.

Barter, P. J. et al. Torcetrapib and cardiovascular events: The ILLUMINATE trial. New England Journal of Medicine 357, 2109–2122 (2007)

Phase III trial of CETP inhibitor torcetrapib terminated early due to excess mortality. Of 15,067 participants, 82 deaths occurred in the torcetrapib arm vs. 51 in placebo (HR 1.58). Cardiovascular events were also significantly higher. Pfizer spent over $800 million on development before termination. Example of Phase III trial catching serious safety issues before broader approval.

587.

U.S. Treasury. Treasury Forfeiture Fund Accountability Report Fiscal Year 2024. https://home.treasury.gov/system/files/246/TFF-FY-2024-Accountability-Report.pdf (2024).

588.

Moore, T. J., Zhang, H., Anderson, G. & Alexander, G. C. Traditional trial cost per patient. JAMA Internal Medicine https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7295430/ (2020)

The median cost of a pivotal trial was estimated to be $19 million... the median cost per patient was $41,413. Additional sources: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7295430/

589.

FDA Study via NCBI. Trial costs, FDA study. FDA Study via NCBI https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6248200/

Overall, the 138 clinical trials had an estimated median (IQR) cost of $19.0 million ($12.2 million-$33.1 million)... The clinical trials cost a median (IQR) of $41,117 ($31,802-$82,362) per patient. Additional sources: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6248200/

590.

WHO. Annual deaths from tuberculosis. WHO https://www.who.int/news-room/fact-sheets/detail/tuberculosis (2024)

Tuberculosis | 1.3 million Additional sources: https://www.who.int/news-room/fact-sheets/detail/tuberculosis | https://www.who.int/teams/global-programme-on-tuberculosis-and-lung-health/tb-reports/global-tuberculosis-report-2024

591.

Tufts Center for the Study of Drug Development. Cost to develop and win marketing approval for a new drug is $2.6 billion. (2014).

592.

Tufts Center for the Study of Drug Development. Tufts center drug development cost estimate 2021. (2021)

Total cost to develop a new drug estimated at $2.6 billion as of 2021, nearly a 3-fold increase from $802 million in 2003 (inflation-adjusted).

593.

Tullock, G. The welfare costs of tariffs, monopolies, and theft. Economic Inquiry 5, 224–232 (1967).

594.

UCDP. State violence deaths annually. UCDP: Uppsala Conflict Data Program https://ucdp.uu.se/

Uppsala Conflict Data Program (UCDP): Tracks one-sided violence (organized actors attacking unarmed civilians) UCDP definition: Conflicts causing at least 25 battle-related deaths in calendar year 2023 total organized violence: 154,000 deaths; Non-state conflicts: 20,900 deaths UCDP collects data on state-based conflicts, non-state conflicts, and one-sided violence Specific "2,700 annually" figure for state violence not found in recent UCDP data; actual figures vary annually Additional sources: https://ucdp.uu.se/ | https://en.wikipedia.org/wiki/Uppsala_Conflict_Data_Program | https://ourworldindata.org/grapher/deaths-in-armed-conflicts-by-region

595.

UNESCO. UNESCO institute for statistics. (2025).

596.

UK Research and Innovation. The RECOVERY trial: Identifying COVID-19 treatments. (2020).

597.

United Nations. Corruption costs global economy $2.6 trillion annually. https://www.unodc.org/unodc/en/frontpage/2018/December/corruption-costs-the-global-economy-us-2_6-trillion-annually-says-un-anti-corruption-day.html (2018)

Corruption costs 5% of global GDP annually ( $2.6 trillion)

598.

UNESCO. Education. (2025).

599.

UNESCO. UNESCO cost for universal education coverage. UNESCO https://news.un.org/en/story/2023/04/1135697 (2023)

The largest financing gap is in sub-Saharan Africa: $70 billion per year. An additional $77 billion is needed annually for African countries to reach their national education targets and provide quality education for all. Additional sources: https://news.un.org/en/story/2023/04/1135697 | https://unesdoc.unesco.org/ark:/48223/pf0000192186

600.

UNHCR. UNHCR forcibly displaced people 2023. UNHCR https://www.unhcr.org/global-trends-report-2023 (2023)

At the end of 2023, 117.3 million people worldwide were forcibly displaced. Additional sources: https://www.unhcr.org/global-trends-report-2023

601.

CGDev. UNHCR average refugee support cost. CGDev https://www.cgdev.org/blog/costs-hosting-refugees-oecd-countries-and-why-uk-outlier (2024)

The average cost of supporting a refugee is $1,384 per year. This represents total host country costs (housing, healthcare, education, security). OECD countries average $6,100 per refugee (mean 2022-2023), with developing countries spending $700-1,000. Global weighted average of $1,384 is reasonable given that 75-85% of refugees are in low/middle-income countries. Additional sources: https://www.cgdev.org/blog/costs-hosting-refugees-oecd-countries-and-why-uk-outlier | https://www.unhcr.org/sites/default/files/2024-11/UNHCR-WB-global-cost-of-refugee-inclusion-in-host-country-health-systems.pdf

602.

United for Medical Research. Annual NIH economic impact report: 2025 update. (2025).

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US Census Bureau. Historical world population estimates. US Census Bureau https://www.census.gov/data/tables/time-series/demo/international-programs/historical-est-worldpop.html

US Census Bureau historical estimates of world population by country and region (1950-2050). US population in 1960: 180 million of 3 billion worldwide (6%). Additional sources: https://www.census.gov/data/tables/time-series/demo/international-programs/historical-est-worldpop.html

604.

Sinn, M. P. United States Efficiency Audit. https://us-efficiency-audit.warondisease.org (2025) doi:10.5281/zenodo.18447476

Systems audit estimating an annual U.S. efficiency gap of $4.9T, with $2.45T recoverable at OECD-median performance across direct spending waste, compliance burden, policy-induced GDP loss, and system inefficiency.

605.

CMS. U.s. Federal government spending on healthcare. CMS https://www.cms.gov/data-research/statistics-trends-and-reports/national-health-expenditure-data/nhe-fact-sheet (2024)

Healthcare: $1.5 trillion (for not dying, but slowly) Additional sources: https://www.cms.gov/data-research/statistics-trends-and-reports/national-health-expenditure-data/nhe-fact-sheet

606.

NASA. U.s. Government use of prize and bounty programs. NASA https://www.nasa.gov/news-release/nasa-and-x-prize-announce-winners-of-lunar-lander-challenge/

NASA’s Centennial Challenge, initiated in 2005, has paid out more than $7.6 million. The Ansari XPRIZE demonstrated significant leverage: $10 million was awarded to the winner, but more than $100 million was invested in new technologies in pursuit of the prize. NASA launched its own incentive scheme in 2005 called Centennial Challenges. Additional sources: https://www.nasa.gov/news-release/nasa-and-x-prize-announce-winners-of-lunar-lander-challenge/ | https://www.xprize.org/past-challenges | https://www.herox.com/blog/985-prize-challenges-governments-secret-weapon-for-inn

607.

Statista. US military budget as percentage of GDP. Statista https://www.statista.com/statistics/262742/countries-with-the-highest-military-spending/ (2024)

U.S. military spending amounted to 3.5% of GDP in 2024. In 2024, the U.S. spent nearly $1 trillion on its military budget, equal to 3.4% of GDP. Additional sources: https://www.statista.com/statistics/262742/countries-with-the-highest-military-spending/ | https://www.sipri.org/sites/default/files/2025-04/2504_fs_milex_2024.pdf

608.

Manuel, D. U.s. Defense spending history: 100 years of military budgets. DaveManuel.com https://www.davemanuel.com/us-defense-spending-history-military-budget-data.php (2025)

US military spending in constant 2024 dollars: 1939 $29B (pre-WW2 baseline), 1940 $37B, 1944 $1,383B, 1945 $1,420B (peak), 1946 $674B, 1947 $176B, 1948 $117B, 2024 $886B. The post-WW2 demobilization cut spending 88% in two years (1945-1947). Current peacetime spending ($886B) is 30x the pre-WW2 baseline and 62% of peak WW2 spending, in inflation-adjusted dollars.

609.

USAFacts. Per capita US military spending: $3,000/year. USAFacts https://usafacts.org/articles/how-much-does-the-us-spend-on-the-military/ (2024)

Military spending: $3,000/year Additional sources: https://usafacts.org/articles/how-much-does-the-us-spend-on-the-military/ | https://comptroller.war.gov/Budget-Materials/Budget2024/

610.

Wikipedia. US GDP growth rate post-WWII. Wikipedia https://en.wikipedia.org/wiki/Post–World_War_II_economic_expansion

US GDP increased from $228 billion in 1945 to just under $1.7 trillion in 1975. Average real GDP growth from 1950 to 1980 was around 4.1% annually, compared to 3.1% from 1981 to 2008. Additional sources: https://en.wikipedia.org/wiki/Post–World_War_II_economic_expansion | https://www.stlouisfed.org/timely-topics/house-prices-homeownership-rise

611.

St. Louis Fed. US home ownership rate increase post-WWII. St. Louis Fed https://www.stlouisfed.org/timely-topics/house-prices-homeownership-rise

The homeownership rate increased nearly 20 percentage points between 1940 and 1960, from 43.6% to 61.9%, the largest change in American homeownership in the past 100 years. Additional sources: https://www.stlouisfed.org/timely-topics/house-prices-homeownership-rise | https://www.census.gov/data/tables/time-series/dec/coh-owner.html

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Value captured by 1% treaty of $27+ billion annually.

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Appendix A: Formal Proofs

This appendix provides complete proofs of the propositions stated in Sections 3 and 8.

49.8.3 Proof of Proposition 1 (Sufficient Condition for Incentive Compatibility)

Statement. Under assumptions A1–A5, if the score gain from supporting policy class $\mathcal{P}$ is $\Delta\theta > 0$, and

\[ \alpha_i \cdot \Delta P_i + \beta_i \cdot \Delta Y_i + \gamma_i \cdot \Delta S_i > c_i \]

then $a_i = 1$ is the unique best response for politician $i$.

Proof.

Step 1: Action space. By A5, politician $i$ faces a binary choice $a_i \in \{0, 1\}$.

Step 2: Information structure. By A2, voting records are publicly observable and the scoring function $f: \text{VoteRecord} \to \mathbb{R}$ is common knowledge. Hence, politician $i$ can compute: \[ \theta_i(a_i = 1) = \theta_i^0 + \Delta\theta \] \[ \theta_i(a_i = 0) = \theta_i^0 \] where $\theta_i^0$ is the current score and $\Delta\theta > 0$ is the score increment from supporting $\mathcal{P}$.

Step 3: Payoff functions. By A3, the IAB mechanism credibly commits to score-dependent payoffs. The politician can therefore compute the payoff differentials:

For the electoral component, by Equation 49.13: \[ \Delta P_i = P_i(\theta_i^0 + \Delta\theta) - P_i(\theta_i^0) = \delta \cdot \Delta\theta + \epsilon_i \cdot [I_i(\theta_i^0 + \Delta\theta) - I_i(\theta_i^0)] \]

For the post-office component, by Equation 49.15: \[ \Delta Y_i = Y(\tau(\theta_i^0 + \Delta\theta)) - Y(\tau(\theta_i^0)) \]

For the legacy component: \[ \Delta S_i = S_i(\theta_i^0 + \Delta\theta) - S_i(\theta_i^0) \]

Step 4: Utility comparison. By A1, politician $i$ maximizes expected utility $U_i$ as defined in Equation 49.3. The change in utility from choosing $a_i = 1$ versus $a_i = 0$ is:

\[ \Delta U_i = U_i(a_i = 1) - U_i(a_i = 0) = \alpha_i \cdot \Delta P_i + \beta_i \cdot \Delta Y_i + \gamma_i \cdot \Delta S_i - c_i \]

where $c_i > 0$ represents the concentrated costs from opposition interests.

Step 5: Optimality. When $\alpha_i \cdot \Delta P_i + \beta_i \cdot \Delta Y_i + \gamma_i \cdot \Delta S_i > c_i$, we have $\Delta U_i > 0$. Since $a_i \in \{0, 1\}$ and choosing $a_i = 1$ yields strictly higher utility, $a_i = 1$ is the unique best response.

Step 6: Uniqueness. The best response is unique because the action space is finite (binary) and $\Delta U_i > 0$ implies strict preference. No indifference exists. $\square$

49.8.4 Proof of Corollary 1 (Funding Threshold)

Statement. Under A4, there exists a funding level $\bar{F}$ such that for all $F > \bar{F}$, Equation 49.16 holds for all politicians with $c_i < \bar{c}$ for some threshold $\bar{c}(F)$ increasing in $F$.

Proof.

Step 1: Funding dependence. By construction of the IAB mechanism, both $\Delta P_i$ and $\Delta Y_i$ are increasing functions of the total IAB funding $F$:

Electoral layer: Higher $F$ implies larger independent expenditure capacity $M$ in Equation 49.14, increasing $\Delta P_i$
Post-office layer: Higher $F$ implies more fellowship positions and higher salaries, increasing $\Delta Y_i$

Let $\Delta P_i(F)$ and $\Delta Y_i(F)$ denote these functions, with $\frac{\partial \Delta P_i}{\partial F} > 0$ and $\frac{\partial \Delta Y_i}{\partial F} > 0$.

Step 2: Define the benefit function. Let: \[ B_i(F) = \alpha_i \cdot \Delta P_i(F) + \beta_i \cdot \Delta Y_i(F) + \gamma_i \cdot \Delta S_i \]

Since $\alpha_i, \beta_i > 0$ and both $\Delta P_i(F)$ and $\Delta Y_i(F)$ are increasing in $F$, we have $\frac{\partial B_i}{\partial F} > 0$.

Step 3: Threshold construction. For any $\bar{c} > 0$, define: \[ \bar{F}(\bar{c}) = \inf \{F : B_i(F) \geq \bar{c} \text{ for all } i\} \]

This is well-defined because $B_i(F) \to \infty$ as $F \to \infty$ (under A4, the mechanism can scale payoffs arbitrarily with funding).

Step 4: Monotonicity. For $F > \bar{F}(\bar{c})$, we have $B_i(F) > \bar{c}$ for all $i$. Hence, for any politician with $c_i < \bar{c}$: \[ B_i(F) > \bar{c} > c_i \] which is precisely the incentive compatibility condition Equation 49.16.

Step 5: Increasing threshold. The function $\bar{c}(F) = \min_i B_i(F)$ is increasing in $F$ because each $B_i(F)$ is increasing. $\square$

49.8.5 Proof of Proposition 2 (Multiple Equilibria Without IABs)

Statement. Under A1–A2 and A5, without the IAB mechanism, the game among $N$ politicians has at least two pure strategy Nash equilibria: (i) the all-defect equilibrium $(0, \ldots, 0)$, and (ii) potentially the all-cooperate equilibrium $(1, \ldots, 1)$ if coordination is feasible. The all-defect equilibrium is more stable when $c_i > \epsilon$ for all $i$.

Proof.

Step 1: Payoff structure without IABs. By Equation 49.11, the payoff gain from choosing $a_i = 1$ versus $a_i = 0$ is: \[ \Delta U_i^{\text{pre-IAB}} = \epsilon - c_i \] where $\epsilon$ represents diffuse voter approval and $c_i$ represents concentrated opposition costs.

Step 2: All-defect equilibrium. Consider the strategy profile $(a_1, \ldots, a_N) = (0, \ldots, 0)$. For any politician $i$, unilateral deviation to $a_i = 1$ yields: \[ \Delta U_i = \epsilon - c_i < 0 \quad \text{(by assumption } c_i > \epsilon \text{)} \] Since no politician can improve utility by unilateral deviation, $(0, \ldots, 0)$ is a Nash equilibrium.

Step 3: Potential cooperation equilibrium. If politicians can coordinate (through party discipline, repeated game dynamics, or reputation mechanisms), the all-cooperate profile $(1, \ldots, 1)$ may be sustainable. In this case:

Collective benefits may exceed individual costs if policy success generates concentrated rewards (e.g., historical legacy, party brand value)
Defection can be punished in subsequent interactions

However, this equilibrium requires coordination mechanisms external to the single-shot game.

Step 4: Risk dominance. An equilibrium is risk-dominant if it is the best response to the belief that opponents choose each strategy with equal probability. Under uniform mixing, the expected payoff from $a_i = 0$ exceeds that from $a_i = 1$ when $c_i > \epsilon$, making $(0, \ldots, 0)$ risk-dominant. $\square$

49.8.6 Proof of Proposition 3 (Equilibrium Selection With IABs)

Statement. Under A1–A5, if the IAB mechanism is funded such that Equation 49.16 holds for all $i$, then $(1, \ldots, 1)$ is the unique Nash equilibrium.

Proof.

Step 1: Dominant strategy. By Proposition 1, when Equation 49.16 holds for politician $i$, choosing $a_i = 1$ is the unique best response regardless of other politicians’ choices. This is because the payoff comparison depends only on $i$’s own score change and the pre-committed IAB payoff rules, not on the actions of other politicians.

Formally, $\Delta U_i > 0$ holds for all strategy profiles $(a_{-i}) \in \{0,1\}^{N-1}$ of other politicians.

Step 2: Strict dominance. Since $a_i = 1$ yields strictly higher utility than $a_i = 0$ for all $a_{-i}$, the strategy $a_i = 1$ strictly dominates $a_i = 0$.

Step 3: Unique equilibrium. When every player has a strictly dominant strategy, the profile of dominant strategies is the unique Nash equilibrium. Since $a_i = 1$ is strictly dominant for all $i \in \{1, \ldots, N\}$, the profile $(1, \ldots, 1)$ is the unique Nash equilibrium.

Step 4: Uniqueness verification. No other strategy profile can be a Nash equilibrium because at any profile containing $a_i = 0$ for some $i$, politician $i$ has a profitable deviation to $a_i = 1$. $\square$

49.8.7 Proof of Proposition 4 (Investor Participation as Dominant Strategy)

Statement. Under A6, if $pR > 1$ and $\delta_j > 0$, then pledging $x_j > 0$ strictly dominates $x_j = 0$ for all investors $j$.

Proof.

Step 1: Action space. Investor $j$ chooses $x_j \in \{0\} \cup \mathbb{R}_{>0}$. We compare the payoff of any $x_j > 0$ against $x_j = 0$.

Step 2: State space. The payoff-relevant states are determined by the aggregate pledges of other investors, $X_{-j} = \sum_{k \neq j} x_k$. Two cases obtain:

Case A: $X_{-j} + x_j \geq \bar{X}$ (threshold met with $j$’s participation)
Case B: $X_{-j} + x_j < \bar{X}$ (threshold not met even with $j$’s participation)

Note: there is a third logical case where $X_{-j} \geq \bar{X}$ (threshold met without $j$), but this is subsumed by Case A.

Step 3: Payoff comparison in Case A. When the threshold is met:

\[ V_j(x_j > 0) = x_j(pR - 1) > 0 = V_j(0) \]

The inequality holds because $pR > 1$ by assumption and $x_j > 0$.

Step 4: Payoff comparison in Case B. When the threshold is not met:

\[ V_j(x_j > 0) = \delta_j > 0 = V_j(0) \]

The inequality holds because $\delta_j > 0$ by assumption.

Step 5: Dominance. In both Case A and Case B, $V_j(x_j > 0) > V_j(0)$. Since the state space is exhaustive (every realization of $X_{-j}$ falls into Case A or Case B), pledging $x_j > 0$ yields strictly higher utility than $x_j = 0$ in every state. Therefore $x_j > 0$ strictly dominates $x_j = 0$. $\square$

49.8.8 Proof of Corollary 2 (Full Participation Equilibrium)

Statement. The unique Nash equilibrium of the dominant assurance contract game is full participation: $(x_1, \ldots, x_M) \gg 0$.

Proof.

Step 1: Dominant strategy. By Proposition 4, for each investor $j$, pledging $x_j > 0$ strictly dominates $x_j = 0$, regardless of other investors’ actions.

Step 2: Unique equilibrium. When every player has a strictly dominant strategy, the profile of dominant strategies constitutes the unique Nash equilibrium. Any profile containing $x_j = 0$ for some $j$ is not a Nash equilibrium because investor $j$ has a profitable deviation to $x_j > 0$.

Step 3: Existence. The profile $(x_1, \ldots, x_M) \gg 0$ is a Nash equilibrium because no investor can improve utility by deviating to $x_j = 0$ (which yields strictly lower payoff by Proposition 4). $\square$

Appendix B: Detailed Application Specifications

This appendix provides detailed IAB specifications for the candidate domains discussed in Section 6.

49.8.9 Climate Change

Policy objective. Reduce global greenhouse gas emissions in line with Paris Agreement targets (limiting warming to 1.5–2°C).

Scoring metric. The Climate Leadership Score $\theta_i^C$ is computed as a weighted average:

\[ \theta_i^C = w_1 \cdot V_i^{\text{legislation}} + w_2 \cdot V_i^{\text{treaty}} + w_3 \cdot V_i^{\text{budget}} + w_4 \cdot V_i^{\text{oversight}} \]

where:

$V_i^{\text{legislation}}$: Voting record on climate legislation (carbon pricing, renewable standards, efficiency mandates)
$V_i^{\text{treaty}}$: Support for international climate agreements
$V_i^{\text{budget}}$: Votes on clean energy appropriations and fossil fuel subsidy reform
$V_i^{\text{oversight}}$: Participation in climate-related oversight activities

Weights $w_j$ sum to 1 and are calibrated to policy impact.

Electoral layer specification.

Score Tier	Independent Expenditure Rule
$\theta_i^C \geq 80$	Full support: +$M per competitive race
$60 \leq \theta_i^C < 80$	Neutral: no expenditure
$\theta_i^C < 60$	Opposition: −$M per competitive race

Post-office layer specification.

Tier 1 ($\theta_i^C \geq 75$): Eligibility for clean energy foundation boards, climate advisory positions, green bank directorships
Tier 2 ($60 \leq \theta_i^C < 75$): Standard think tank positions
Tier 3 ($\theta_i^C < 60$): Fossil fuel industry positions remain available but climate-aligned positions closed

Calibration notes. Fossil fuel industry opposition spending averages $100–500M annually on federal elections. IAB funding at $1B+ annually would satisfy Equation 49.16 for most legislators in competitive districts.

49.8.10 Nuclear Disarmament

Policy objective. Verified reduction of global nuclear arsenals and strengthened non-proliferation.

Scoring metric. The Nuclear Safety Score $\theta_i^N$:

\[ \theta_i^N = w_1 \cdot V_i^{\text{treaty}} + w_2 \cdot V_i^{\text{NDAA}} + w_3 \cdot V_i^{\text{nonprolif}} + w_4 \cdot V_i^{\text{oversight}} \]

where:

$V_i^{\text{treaty}}$: Votes on arms control treaty ratification (New START, CTBT, etc.)
$V_i^{\text{NDAA}}$: Votes on National Defense Authorization Act amendments affecting nuclear posture
$V_i^{\text{nonprolif}}$: Support for non-proliferation funding and diplomacy
$V_i^{\text{oversight}}$: Engagement with nuclear policy oversight

Electoral layer specification. Peace-focused PACs commit to independent expenditure rules analogous to the climate case, with thresholds calibrated to the nuclear policy domain.

Post-office layer specification.

Tier 1: Arms control advisory positions, security fellowships at peace-oriented institutions, disarmament diplomacy roles
Tier 2: General foreign policy positions
Tier 3: Defense contractor positions remain available but arms control positions closed

Calibration notes. Defense contractor opposition is substantial (over $100M annually in lobbying). However, the concentrated-diffuse asymmetry is extreme: nuclear war risks affect all humanity. IAB funding levels comparable to current defense lobbying would create countervailing incentives.

49.8.11 Pandemic Preparedness

Policy objective. Strengthen global health security infrastructure to prevent and respond to pandemic threats.

Scoring metric. The Pandemic Readiness Score $\theta_i^P$:

\[ \theta_i^P = w_1 \cdot V_i^{\text{funding}} + w_2 \cdot V_i^{\text{IHR}} + w_3 \cdot V_i^{\text{surge}} + w_4 \cdot V_i^{\text{oversight}} \]

where:

$V_i^{\text{funding}}$: Votes on CDC, BARDA, and global health security appropriations
$V_i^{\text{IHR}}$: Support for International Health Regulations compliance and funding
$V_i^{\text{surge}}$: Votes on pandemic surge capacity and stockpile funding
$V_i^{\text{oversight}}$: Engagement with health security oversight

Electoral layer specification. Global health PACs commit to score-dependent independent expenditures supporting high-scorers in competitive races.

Post-office layer specification.

Tier 1: WHO advisory positions, global health security fellowships, pandemic preparedness foundation leadership
Tier 2: General health policy positions
Tier 3: Pharmaceutical industry positions remain available but global health leadership positions closed

Calibration notes. Pharmaceutical industry lobbying exceeds $300M annually. However, pandemic preparedness funding faces less concentrated opposition than military or fossil fuels, suggesting lower IAB funding thresholds may achieve incentive compatibility.

49.8.12 Comparative Analysis

Table 49.11 summarizes key parameters across domains.

Table 49.11: Comparative IAB Parameters Across Domains

Domain	Opposition Cost $c_i$	Existing Lobbying	IAB Threshold $\bar{F}$
Climate	$2–10M	$150M+ (2024)	~$1B
Nuclear	$2–8M	$130M+ (2024)	~$500M
Pandemic	$1–5M	$50–150M	~$300M
Pragmatic Clinical Trials	$1–4M	$20–100M	~$200M

These estimates are illustrative and require empirical calibration. The general pattern suggests that domains with lower concentrated opposition (pandemic preparedness, health research) require lower IAB funding to achieve incentive compatibility, while domains with entrenched industrial opposition (climate, defense) require larger investments.

Conservative estimate: weapons manufacturers ~$2T, fossil fuel companies ~$2.5T, pharmaceutical companies ~$4T (though pharma may align with IABs). Total concentrated opposition: $2T-$5T depending on domain.↩︎