How Dollar Hegemony Funds Silicon Valley
The Structural Pipeline From Federal Reserve to Startup Equity
The Hook: Two Engineers, Same Talent, Different Outcomes
Consider two engineers with identical skills who graduated from top CS programs in 2014. One joined a 50-person startup in San Francisco; the other joined a comparable startup in Bangalore.
Both worked 60-hour weeks. Both shipped critical features. Both saw their companies grow to 500+ employees over the next decade.
The SF engineer’s equity stake, after a 2021 IPO, was worth $8 million. The Bangalore engineer’s stake, after an acquisition, was worth ₹3 crore (~$360,000). The SF engineer is now an angel investor funding the next generation; the Bangalore engineer is still working.
This isn’t about talent or effort. It’s about proximity to capital flows. Understanding those flows—where they originate, how they move, and where they concentrate—explains more about tech wealth outcomes than any other variable.
This article traces the structural pipeline that creates this divergence.
What This Article Claims (And What It Doesn’t)
Claims:
- The dollar’s reserve currency status creates structural demand for US financial assets
- This demand funnels global savings through institutional investors into US venture markets
- Geographic concentration of VC creates capital availability in Silicon Valley unmatched elsewhere
- Equity compensation transmits this capital concentration into individual wealth outcomes
- These are contributing factors, not the sole explanation
Does NOT claim:
- That this is a conspiracy or coordinated scheme
- That American engineers are more talented or harder-working
- That non-US tech ecosystems cannot produce successful companies
- That every SF employee gets rich (median outcomes are modest; mean outcomes are distorted by outliers)
- That these structures are permanent or inevitable
The Pipeline: A Map of the Argument
The causal chain runs as follows. Each section below unpacks one link:
┌─────────────────────────────────────────────────────────────────────────────┐
│ THE CAPITAL PIPELINE │
├─────────────────────────────────────────────────────────────────────────────┤
│ │
│ 1. DOLLAR CREATION Fed creates dollars via open market operations │
│ ↓ │
│ 2. GLOBAL DEMAND Reserve currency status forces dollar holding │
│ ↓ │
│ 3. RECYCLING Trade surpluses/oil revenues flow to US assets │
│ ↓ │
│ 4. INSTITUTIONAL POOLS Pensions, SWFs, endowments accumulate capital │
│ ↓ │
│ 5. LP → GP ALLOCATION Institutions invest in VC/PE funds │
│ ↓ │
│ 6. GEOGRAPHIC CLUSTERING Network effects concentrate VC in Bay Area │
│ ↓ │
│ 7. EQUITY TRANSMISSION Startups pay employees in equity │
│ ↓ │
│ 8. WEALTH OUTCOMES IPOs/acquisitions create millionaires │
│ │
└─────────────────────────────────────────────────────────────────────────────┘
Part 1: Dollar Creation and the Fed’s Unique Power
How money enters existence
The Federal Reserve creates US dollars through a process that, while technically mundane, has profound global implications.
When the Fed conducts open market operations, it purchases Treasury securities from primary dealers (24 large financial institutions authorized to trade directly with the Fed). Payment occurs by crediting the dealer’s reserve account at the Fed. This money doesn’t transfer from somewhere else—it’s created as an accounting entry.
During quantitative easing (QE), this process operates at massive scale. The Fed’s balance sheet expanded from $900 billion in 2008 to a peak of approximately $8.9 trillion in April 2022. Even after subsequent tightening, it remains around $6.5-6.6 trillion—roughly 22% of US GDP.
The remittance cycle (important context and caveats)
When Treasury pays interest on bonds held by the Fed, an interesting circular flow can emerge: the Fed receives the interest, deducts operating costs, and remits the excess back to Treasury. Between 2011 and 2021, the Fed returned over $920 billion through this mechanism.
Critical update: This cycle is currently inoperative.
Remittances turned negative in September 2022 and remain so. The Fed now pays more interest on bank reserves (at the federal funds rate, currently ~4.5%) than it earns on its portfolio of longer-duration bonds (purchased when rates were near zero). As of late 2024, the Fed has accumulated a “deferred asset” exceeding $200 billion—an accounting entry representing future remittances owed to itself before it can resume payments to Treasury.
The “costless debt” framing was accurate for 2011-2021 but does not describe the current regime. If interest rates decline substantially, remittances could resume. But treating this as a permanent structural feature of the system is incorrect.
Section summary: The Fed can create dollars from nothing. This capacity expanded dramatically during QE. The Treasury-Fed remittance cycle can reduce effective interest costs, but this depends on the interest rate environment and isn’t guaranteed.
Bridge: Domestic Reserves vs. the International Dollar System
The Fed’s balance sheet operations (described above) directly affect domestic bank reserves and US financial conditions. But the global dollar system—why the world holds and transacts in dollars—operates through different mechanisms:
- Trade invoicing: Commodities (oil, metals, grains) and manufactured goods are priced in dollars by convention, creating transactional demand
- Offshore USD credit: The “eurodollar” market—dollar-denominated lending outside the US—exceeds $13 trillion and operates largely independent of the Fed
- Safe-asset demand: During crises, global capital flows into US Treasuries as the default safe haven, regardless of Fed policy
- Capital account flows: Foreign investors seeking returns in deep, liquid US markets bring dollars back
The Fed influences these systems indirectly—through interest rates that affect capital flows, through liquidity provision during crises, through the credibility of dollar-denominated assets. But the global dollar system isn’t simply “Fed prints money → world holds it.” It’s a network of conventions, infrastructure, and institutional trust that the Fed supports but doesn’t directly control.
This distinction matters: even if the Fed tightened dramatically, dollar dominance would persist because the alternatives (euro, yuan, gold) lack the depth, liquidity, and institutional infrastructure to absorb global transaction and reserve demand.
Part 2: Why the World Holds Dollars
The reserve currency imperative
The dollar’s dominance isn’t primarily about American economic policy—it’s about network effects and institutional path dependence.
Key metrics of dollar dominance:
- ~56% of global foreign exchange reserves are dollar-denominated ($7.4 trillion of $12.9 trillion total)
- ~89% of foreign exchange transactions have the dollar on one side (BIS Triennial Survey, April 2025)
- ~63% of international debt is denominated in dollars (up from 43% in 2007)
- ~84% of trade finance transactions settle in dollars
Note: The reserve share figure (56%) is at a 30-year low, down from 72% in 2001. However, this decline largely reflects diversification into smaller currencies and valuation effects—not displacement by a rival reserve currency. The dollar’s transactional dominance remains overwhelming.
The Triffin dynamic
Belgian-American economist Robert Triffin identified a tension in 1959-60: a reserve currency issuer faces pressure to supply currency globally (which tends to produce deficits) while maintaining confidence (which requires fiscal discipline).
This is not a mathematical identity. The US could theoretically supply dollars through capital account flows while running trade surpluses. But the structural pressures are real: strong dollar demand makes US exports expensive and imports cheap, creating persistent pressure toward trade deficits.
The US has run trade deficits for 50 consecutive years since 1975. The 2024 goods deficit hit $1.21 trillion. This pattern is consistent with Triffin dynamics—but attributing it solely to reserve currency mechanics overstates the case. Fiscal policy, consumption patterns, and relative productivity also matter.
The petrodollar foundation
The dollar’s reserve status was reinforced by the 1974 arrangement with Saudi Arabia: oil priced in dollars, Saudi revenues recycled into US assets, in exchange for security guarantees. Today, an estimated 80% of global oil transactions still occur in dollars (though this figure is an estimate—primary source data is limited).
Section summary: Global trade and finance require holding dollars. This creates structural demand that recycles dollars back into US financial assets. The arrangement is self-reinforcing but not immutable.
Part 3: Where Dollars Accumulate
Trade surpluses and commodity revenues create dollar pools that must be invested somewhere.
Foreign official holdings
Foreign central banks and governments hold approximately $8.5 trillion in US Treasury securities (December 2024). Major holders:
| Country | Treasury Holdings |
|---|---|
| Japan | $1.13 trillion |
| UK | $779 billion |
| China | $765 billion |
| Luxembourg | $409 billion |
| Canada | $379 billion |
These holdings represent approximately 32% of marketable US government debt.
Sovereign wealth funds
Sovereign wealth funds (SWFs) control $13-14 trillion globally. Five now exceed $1 trillion:
| Fund | AUM | Source |
|---|---|---|
| Norway Government Pension Fund | ~$1.86T | Oil revenues |
| China Investment Corporation | ~$1.33T | FX reserves |
| GIC Singapore | ~$1.32T | Trade surpluses |
| Abu Dhabi Investment Authority | ~$1.11T | Oil revenues |
| Kuwait Investment Authority | ~$1.0T | Oil revenues |
Gulf SWFs alone deployed $82 billion in 2023 and $55 billion in the first nine months of 2024, with significant allocations to US tech, AI, and energy transition.
The recycling loop: Countries export goods/commodities → receive dollars → must invest those dollars somewhere safe and liquid → US Treasuries and financial assets are the default destination → dollars return to the US.
Section summary: Global dollar accumulation isn’t hoarding—it’s investment. Trillions flow into US financial assets because there’s no alternative with comparable depth, liquidity, and institutional trust.
Part 4: How Institutional Capital Reaches Venture Markets
The pools described above don’t invest in startups directly. The transmission mechanism runs through institutional asset allocation.
The LP universe
Limited Partners (LPs) provide capital to venture and private equity funds. The major categories:
Pension funds are the largest LP category. US public pension systems hold ~$5.1 trillion in assets, with an average ~14% allocated to private equity—meaning roughly $700+ billion flows to PE/VC funds. The money originates from payroll deductions accumulated over decades. (See Appendix C for individual fund breakdowns.)
Sovereign wealth funds control $13-14 trillion globally, with five funds now exceeding $1 trillion each (Norway, China, Singapore, Abu Dhabi, Kuwait). Gulf SWFs alone deployed $137 billion in 2023-2024, with significant allocations to US tech and AI.
University endowments manage $837 billion across US institutions, led by Harvard ($53B), Texas ($47.5B), and Yale ($41.4B). The “Yale Model” shifted endowment investing toward ~60% alternatives allocation.
Family offices control ~$4.7 trillion globally, with 42-45% allocated to alternatives.
(Detailed fund-by-fund statistics in Appendix C.)
The GP/LP structure
General Partners (GPs) manage funds and make investment decisions. They typically contribute 1-5% of fund capital and receive:
- 2% annual management fee on committed capital
- 20% carried interest on profits above a hurdle rate (typically 8%)
Top-tier funds now command 25-30% carry.
US venture capital manages approximately $1.25 trillion in assets with $308 billion in dry powder (committed but undeployed capital).
Key terms:
- LP (Limited Partner): Provides capital, no operational control
- GP (General Partner): Manages fund, makes investment decisions
- Dry powder: Capital committed to funds but not yet invested
- Carry (carried interest): GP’s share of profits, typically 20%
- Hurdle rate: Minimum return threshold before carry applies
Section summary: Worker pensions, oil revenues, university donations, and family wealth flow through the GP/LP structure into venture funds. This is the transmission mechanism from global savings to startup investment.
Part 5: Why Capital Concentrates in Silicon Valley
Here’s where the pipeline meets geography. Why doesn’t VC capital distribute evenly across the world’s tech hubs?
The numbers
In 2024, Bay Area startups captured approximately $90 billion—57% of all US venture investment. This represents a rebound from ~41% in early 2023, driven almost entirely by AI.
The Bay Area hosts:
- 31% of US unicorns in Silicon Valley proper
- 26% additional in San Francisco
- Combined: 57% of US unicorns, representing ~$1 trillion in value
Q1 2025 saw Bay Area share reach nearly 70% of US venture investment.
For comparison:
- All of Europe: ~$62 billion (roughly 2/3 of Bay Area alone)
- UK (Europe’s leader): ~$19.6 billion
- India: ~$13.7 billion
The causal chain: Why clustering, then why this cluster
Geographic concentration in venture capital follows a specific logic:
Step 1: Power law returns create winner-take-all dynamics
Venture returns are extremely skewed. Data from Horsley Bridge (1985-2014) shows that 6% of deals generate 60% of returns. Approximately 60-70% of investments return little or nothing. VCs need only 1-2 massive winners per fund.
This creates specific behavior: follow-on investment concentrates in emerging winners. GPs “double down” on breakouts. Missing a potential unicorn is existentially threatening; losing money on failures is expected.
Step 2: Information asymmetry rewards proximity
Identifying the 6% that will return capital requires differentiated information: which founders are leaving successful companies, which startups are showing traction, which deals are competitive. This information flows through in-person networks—board meetings, coffee conversations, founder dinners.
A partner at Sequoia learns things on Sand Hill Road that don’t travel over Zoom. This isn’t mystical; it’s the same dynamic that concentrates any information-sensitive activity (trading floors, Hollywood, political capitals).
Step 3: Once a cluster exists, it reinforces itself
- Talent density: 49% of Big Tech engineers and 27% of startup engineers work in the Bay Area (SignalFire). Dense labor markets reduce hiring friction.
- Infrastructure: Specialized law firms, accountants, recruiters, accelerators (Y Combinator), and standardized deal terms reduce transaction costs.
- Recycling: Successful founders become angels. The “PayPal Mafia” model—where exits spawn the next generation of investors and founders—perpetuates geographic concentration.
- Research pipeline: Stanford alone has produced founders of companies worth over $3 trillion.
Addressing the objection: “Isn’t this just culture?”
Culture plays a role—risk tolerance, failure acceptance, entrepreneurial norms. But culture is downstream of capital availability. When capital is abundant, investors can afford to lose. A VC can fund 30 companies knowing 25 will fail if 2-3 become massive. This risk tolerance doesn’t exist where capital is scarce.
The cultural explanations reverse causality: Silicon Valley has risk-tolerant culture because it has abundant capital, not vice versa.
What about London, Tel Aviv, Bangalore?
These ecosystems produce successful companies—but at different scale. Israel’s entire VC market is ~$10-15B annually; the Bay Area alone did ~$90B. The counterexamples prove you can have a startup ecosystem without dollar privilege; they don’t prove you can replicate Silicon Valley’s magnitude of wealth creation.
European median late-stage rounds average $80 million vs $100 million in the Americas. Bay Area startups access 3-5x more capital at equivalent stages than London or Berlin. Same talent, different capital availability.
Section summary: Power law returns create information-sensitive investing. Information flows through networks. Networks cluster geographically. Once clustered, they self-reinforce. Silicon Valley won this dynamic early and compounds the advantage.
Part 6: Equity as the Transmission Mechanism
The final link: how capital concentration becomes individual wealth.
Base compensation sets the floor
San Francisco Bay Area median total compensation for software engineers: $265,000 (Levels.fyi 2024).
Comparison across markets:
| Location | Median SWE Total Comp |
|---|---|
| SF Bay Area | $265,000 |
| Seattle | $242,000 |
| New York | $190,000 |
| Austin | $175,000 |
| London | $126,000 |
| Tel Aviv | $133,000 |
| Singapore | $92,000 |
| Bangalore | $10,000-$54,000 |
At senior levels, the gaps widen. OpenAI averages ~$800,000 total compensation. Staff engineers at FAANG reach $700,000-$900,000. 50-70% of total compensation comes from equity.
But equity is where wealth is created
Base salaries create comfortable lives. Equity creates generational wealth—but only when companies achieve liquidity at scale.
Illustrative case: Nvidia (with data quality caveat)
Media reports estimate Nvidia has created 27,000+ millionaires—approximately 75-80% of its ~36,000 workforce. These figures are journalist extrapolations from stock appreciation and employee headcount, not audited data. They should be treated as illustrative of magnitude, not precise.
What’s verifiable: Nvidia stock appreciated ~800% from 2022-2024. Employees with standard equity grants who held through this period saw substantial wealth creation. One reported case: a mid-level employee retiring with $62 million from accumulated grants.
The pattern—not the precise numbers—is the point: being at the right company during a major appreciation event creates wealth at scale impossible through salary alone.
Earlier examples:
Google’s 2004 IPO created ~900 millionaires in a single day, including non-technical staff (head chef, masseuse). Facebook’s 2012 IPO created ~1,000 millionaires from a ~3,000 workforce.
The power law in equity outcomes
┌──────────────────────────────────────────────────────────────┐
│ STARTUP EQUITY: MEDIAN VS MEAN │
├──────────────────────────────────────────────────────────────┤
│ │
│ MEDIAN OUTCOME: │
│ - Company fails or exits small │
│ - Options expire worthless or worth modest amount │
│ - Net: $0 - $50,000 │
│ │
│ MEAN OUTCOME (dragged up by outliers): │
│ - A few employees hit $1M+ outcomes │
│ - Average across all employees: ~$200,000-500,000 │
│ │
│ TOP DECILE OUTCOME: │
│ - Early employee at company that IPOs at scale │
│ - Outcome: $2M - $50M+ │
│ │
│ Y Combinator data: ~4.5% of YC companies become unicorns │
│ (vs ~2.5% industry seed-stage average) │
│ │
└──────────────────────────────────────────────────────────────┘
Equity is an option, not a guarantee. Most startup employees see modest outcomes. The expected value calculation favors equity only because rare massive outcomes drag up the mean.
Secondary markets provide earlier liquidity
Companies now stay private 10-15 years (vs 4-6 historically). Secondary markets let employees sell shares before IPO:
- Carta: $13 billion in facilitated secondary sales
- Platforms like Forge Global and EquityZen enable transactions
- Typical minimums: $100,000+; commissions: ~5%
This creates another Bay Area advantage: secondary market infrastructure exists there, enabling liquidity that isn’t available in thinner markets.
Section summary: Equity compensation transmits capital concentration into individual wealth. Outcomes follow a power law: most employees see modest returns, but outlier outcomes create millionaires at rates unmatched elsewhere. Being in the ecosystem where these outliers occur changes the distribution of possible outcomes.
Part 7: Implications and Practical Takeaways
For engineers
The decision framework:
If maximizing expected value (and accepting variance):
- Equity-heavy roles at well-funded Bay Area startups offer the highest expected wealth outcomes
- Accept that median outcome is modest; you’re playing for the right tail
- Early-stage = higher variance, higher potential upside
- Later-stage (Series C+) = lower variance, lower but more probable upside
If maximizing median outcome (and minimizing variance):
- Big Tech (FAANG) provides high base + liquid public equity
- Geographic arbitrage: Seattle offers ~90% of SF comp with no state income tax
- Remote roles for US companies from lower-cost locations capture salary arbitrage
If outside the US:
- Target US-market revenue (SaaS, dev tools) to access dollar economics
- Consider US fundraising even if operating elsewhere
- Build network touchpoints in SF (YC, conferences, advisors) to access information flows
For founders
Capital availability is the single largest predictor of startup survival and scaling speed. Implications:
- Fundraising in SF/NY provides access to capital at scale unavailable elsewhere
- If building from India or Europe, consider US entity + US lead investor
- Network effects matter: warm introductions to tier-1 VCs come from the existing network
For non-US readers
The structural pipeline advantages American capital markets. You can partially offset this by:
- Accessing US capital remotely: Many VCs now invest globally, especially post-COVID
- Building for US market: Dollar revenue matters more than founder location
- Network insertion: Y Combinator, On Deck, conferences create weak ties that become strong ties
- Secondary opportunities: As Bay Area founders exit, they angel invest globally
The disadvantage is real but not absolute. Israel, UK, India, and Singapore have produced unicorns. The question is expected value and probability distribution, not binary possibility.
Conclusion: Structural Advantage, Not Destiny
The dollar’s reserve currency status creates a unique capital accumulation advantage for the United States. That capital flows through institutional investors into venture markets concentrated in a specific geography. Individuals with proximity to those flows capture disproportionate wealth-building opportunities.
This isn’t about culture, work ethic, or innovation capacity. Talented engineers exist globally. What differs is the structural flow that makes billion-dollar outcomes routine in one geography and rare in others.
The structure isn’t immutable:
- Dollar reserve share has declined from 72% to 56% over two decades
- Chinese venture market has collapsed amid regulatory pressure
- European policymakers increasingly discuss the “scale-up gap”
- Remote work enables partial geographic arbitrage
But for now, the pipeline remains intact. Understanding it is the first step to navigating it strategically—whether that means relocating, building for US markets from abroad, or accepting the trade-offs of operating outside the capital core.
The game isn’t rigged by conspiracy. It’s rigged by plumbing. And plumbing can be understood.
Appendix A: Glossary
| Term | Definition |
|---|---|
| LP (Limited Partner) | Investor who provides capital to a fund but has no control over investment decisions |
| GP (General Partner) | Fund manager who makes investment decisions and manages portfolio |
| Carry (Carried Interest) | GP’s share of fund profits, typically 20%, above a hurdle rate |
| Hurdle Rate | Minimum return threshold (typically 8%) before GP earns carry |
| Dry Powder | Capital committed to funds but not yet deployed |
| QE (Quantitative Easing) | Central bank policy of purchasing securities to expand money supply |
| Open Market Operations | Fed buying/selling securities to influence money supply and rates |
| Primary Dealers | 24 financial institutions authorized to trade directly with the Fed |
| SWF (Sovereign Wealth Fund) | State-owned investment fund, typically from commodity or trade surpluses |
| Power Law | Distribution where small number of outcomes account for majority of results |
| Secondary Market | Market for trading private company shares before IPO |
| Triffin Dilemma | Tension between supplying global liquidity and maintaining confidence |
| Remittances (Fed) | Excess Fed earnings returned to Treasury |
| Deferred Asset | Accounting entry when Fed operates at loss; future remittances owed to itself |
Appendix B: Sources and Data Quality Notes
High-confidence sources (primary data)
- Federal Reserve: Balance sheet data, remittance reports
- BIS (Bank for International Settlements): FX transaction volumes
- IMF COFER: Reserve currency composition
- Treasury TIC data: Foreign holdings of US securities
- PitchBook/NVCA: US venture capital deployment
Medium-confidence sources (secondary reporting)
- TechCrunch/Crunchbase: Bay Area VC concentration figures
- Levels.fyi: Compensation data (self-reported, large sample)
- SWF Institute: Sovereign wealth fund AUM
Lower-confidence figures (estimates, use with caveat)
- “80% of oil priced in dollars”: Widely cited but lacks primary source
- “84% of trade finance in dollars”: Based on SWIFT sampling, not comprehensive
- Nvidia millionaire counts: Media extrapolations, not audited
When citing figures from this article, use appropriate epistemic markers based on source quality.
Appendix C: Detailed Statistics
Fed Balance Sheet
- Pre-2008: ~$900 billion
- Post-QE1 (2010): ~$2.3 trillion
- Post-QE3 (2014): ~$4.5 trillion
- Peak (April 2022): ~$8.9 trillion
- Current (2025): ~$6.5-6.6 trillion
Fed Remittances to Treasury
- 2011-2021 cumulative: ~$920 billion
- September 2022: Remittances turn negative
- Current deferred asset: ~$200+ billion
Dollar Reserve Share (IMF COFER)
- 2001: 72%
- 2010: 62%
- 2020: 59%
- 2024: 56.3%
US Trade Deficit
- 1975: First deficit year
- 2024: $1.21 trillion (goods)
- Consecutive deficit years: 50
Bay Area VC Concentration
- 2019: 44%
- 2023 (low): ~41%
- 2024: ~57%
- Q1 2025: ~70%
Major Pension Funds (Individual Breakdown)
| Fund | Total AUM | PE Allocation (~14%) |
|---|---|---|
| CalPERS | $556B | ~$78B |
| CalSTRS | $389B | ~$54B |
| NYC Pension Systems | $295B | ~$35B |
| Texas Teachers | $204B | ~$29B |
| Florida SBA | $195B | ~$27B |
Major Sovereign Wealth Funds
| Fund | AUM | Primary Source |
|---|---|---|
| Norway GPFG | ~$1.86T | Oil revenues |
| China Investment Corp | ~$1.33T | FX reserves |
| GIC Singapore | ~$1.32T | Trade surpluses |
| Abu Dhabi ADIA | ~$1.11T | Oil revenues |
| Kuwait Investment Authority | ~$1.0T | Oil revenues |
Major University Endowments
| Institution | Endowment | Alt Allocation |
|---|---|---|
| Harvard | $53B | ~39% PE |
| Texas System | $47.5B | ~35% PE |
| Yale | $41.4B | ~60% alts |
| Stanford | $37.6B | ~45% alts |
| Princeton | $34.1B | ~40% alts |
Foreign Holdings of US Treasuries (Top 10, Dec 2024)
| Country | Holdings |
|---|---|
| Japan | $1.13T |
| UK | $779B |
| China | $765B |
| Luxembourg | $409B |
| Canada | $379B |
| Belgium | $348B |
| Ireland | $339B |
| Switzerland | $303B |
| Taiwan | $287B |
| India | $247B |
Last updated: January 2026. Statistics subject to revision as new data becomes available.