Seven Things to Watch: Predictions from the Debt-Substitution Model

The debt-substitution model developed in Article 18 identifies three interlocking components—the Distributional Engine, the Debt Patch, and the Dollar Empire—that together explain why GDP growth has felt hollow for most Americans since the 1970s. A good model doesn’t just explain the past; it makes testable claims about the future. The strength of this framework lies in its falsifiable predictions—meaning we can clearly imagine specific evidence that would prove them wrong.

Here are seven key predictions from the model, what to watch for, and what would prove them right or wrong.

Prediction 1: The Cross-Country Validation

Countries with stronger worker protections will show smaller gaps between pay and productivity.

If the U.S. stagnation is driven by a specific policy-institutional shift that weakened labor, then countries that avoided this shift should tell a different story. Nations with robust collective bargaining, sectoral wage agreements, and stronger social contracts should demonstrate a tighter link between productivity growth and worker pay, and consequently, less reliance on household debt to fill the gap.

What to Watch: Compare long-term data (1979-present) for: * Productivity-Pay Gap: The ratio of growth in median/typical worker compensation to growth in output per hour. * Household Debt-to-Income Ratios: The scale of debt households carry relative to their earnings.

Timeframe: Historical analysis (data exists) and ongoing tracking.

Evidence That Would CONFIRM the Prediction: * Germany and Denmark—countries with strong institutional labor representation—show a productivity-pay ratio closer to 0.4:1 or 0.5:1 over the last 40 years. South Korea, a newly industrialized economy with different historical labor dynamics (including authoritarian labor suppression through the 1990s), provides a separate test: do countries with different institutional paths also show different productivity-wage ratios? * These same countries have significantly lower household debt-to-income ratios than the U.S. * The United Kingdom and Canada, which followed a similar “Anglo-Saxon” neoliberal policy path as the U.S., show a productivity-pay gap and debt trajectory much more aligned with the American experience.

Evidence That Would REFUTE the Prediction: * Countries like Germany show a productivity-pay decoupling as severe as America’s (~0.15:1) despite their different institutions. * High household debt is found uniformly across all advanced economies, regardless of labor market structure, suggesting a global, non-policy-driven cause (like technology).

Prediction 2: The Dollar Hegemony Stress Test

Dedollarization will create measurable pressure on the U.S. debt mechanism.

The model identifies the dollar’s privileged global status as the enabling condition for the entire system. It allows the U.S. to export inflation and finance deficits externally. If that status erodes—through active dedollarization by other nations—the model predicts the underlying instability of the debt patch will become visible.

What to Watch: Monitor these indicators in tandem: * Dollar Share of Global Reserves: Tracked by the IMF. * U.S. Current Account Balance (the current account tracks exports and imports of goods, services, and investment income; a deficit means the U.S. receives more value from the world than it sends in return): The trade and investment imbalance the dollar system finances. * Domestic Inflation & Debt Serviceability: Can the U.S. maintain debt growth and low inflation if external demand for dollars weakens?

Timeframe: Next 5-15 years.

Evidence That Would CONFIRM the Prediction: * A sustained decline in the dollar’s reserve share is followed, with a lag, by either (a) a forced reduction in the U.S. current account deficit, (b) a rise in domestic inflation as dollar creation stays internal, or (c) pressure on household debt service ratios as financing becomes more expensive. * Attempts by the Federal Reserve to conduct large-scale stimulus (like QE) during a period of declining dollar hegemony meet with significant currency depreciation and inflation.

Evidence That Would REFUTE the Prediction: * The dollar’s reserve share declines steadily, but the U.S. continues to run large deficits without currency pressure, inflation, or rising debt stress. This would suggest other, more fundamental factors are sustaining the system.

Prediction 3: The Crisis Periodicity

Each successive financial crisis will be larger, require more intervention, and yield a weaker wage recovery.

The model sees crises not as random accidents but as symptoms of the debt patch reaching its temporary limits. Each patch—household debt, then government debt—has a capacity. When one exhausts, a larger crisis erupts, requiring a more massive government/Fed response to restart the engine, often by activating a new debt category. The recovery that follows increasingly benefits asset owners (profits) over workers (wages).

What to Watch: Compare the sequence of modern crises: 1987 (Black Monday), 1989-91 (S&L Crisis), 1998 (LTCM) & 2001 (Dot-com), 2008 (GFC), 2020 (COVID). * Scale of Intervention: Size of Fed balance sheet expansion, fiscal stimulus as % of GDP. * Nature of Recovery: Growth in corporate profits vs. growth in real median wages in the 3-5 years post-crisis.

Timeframe: Historical analysis (partially supported — requires additional data verification for full confirmation) and observation of the next major crisis.

Evidence That Would CONFIRM the Prediction: * The pattern holds: 2008 required more intervention than 2001, which required more than 1987. The 2020 response was larger than 2008’s. * The post-2008 recovery was starkly profit-led; the post-2020 recovery saw massive asset inflation alongside stagnant real wages. The next crisis recovery continues this trend.

Evidence That Would REFUTE the Prediction: * A future major financial crisis is resolved with relatively modest intervention, and is followed by a broad-based, wage-led recovery where median income growth outpaces profit growth for a sustained period.

Prediction 4: The Finance-Debt Correlation

States and countries with larger financial sectors will have higher household debt.

This is a direct test of the “rent extraction” mechanism. If the financial sector grows by creating and profiting from debt, then economies where finance is a larger slice of the pie should show higher levels of indebtedness among their populations. This should be visible both within the U.S. and across countries.

What to Watch: * Within US: Per-capita household debt levels vs. the size of the finance/insurance sector as a share of state GDP. * International: Household debt-to-GDP ratios vs. the financial sector’s share of national GDP across OECD countries.

Timeframe: Historical and contemporary cross-sectional analysis.

Evidence That Would CONFIRM the Prediction: * A strong, positive correlation (e.g., r > 0.6) is found. (An r-value of 0.6 or higher means roughly 36% of the variation in household debt is explained by financial sector size—a meaningful threshold in social science data, where many factors compete simultaneously for explanatory power.) States like New York, Connecticut, and Delaware show higher debt per capita. Countries with oversized finance sectors (UK, Switzerland) show higher household debt ratios than countries where finance is smaller (Germany, Italy).

Evidence That Would REFUTE the Prediction: * No correlation exists, or the correlation is negative. High household debt is found in regions with small financial sectors, suggesting debt is driven by other factors (housing costs, culture) and the financial sector simply responds to demand.

Prediction 5: QE and Wealth Distribution

Periods of quantitative easing will correlate with rising wealth inequality, not wage-led growth.

The model views post-2008 central bank policy (QE) as a life-support mechanism for the debt patch, now using government and central bank balance sheets. Because QE works by boosting asset prices (bonds, stocks, real estate), its benefits flow overwhelmingly to those who own assets—the wealthy. It is not designed to, and should not be expected to, spur broad wage growth.

What to Watch: Compare periods of active Fed QE (2008-2014, 2020-2022) to periods of balance sheet stability or reduction. * Wealth Inequality: The Gini coefficient for wealth and the share of total wealth held by the top 1%. * Asset vs. Wage Growth: S&P 500 total returns vs. growth in real average hourly earnings.

Timeframe: Analysis of the last 15 years and observation of future QE cycles.

Evidence That Would CONFIRM the Prediction: * Charts show sharp step-ups in wealth concentration during and immediately following QE periods. * During QE, asset price inflation dramatically outpaces wage growth. Wage growth remains stagnant in real terms.

Evidence That Would REFUTE the Prediction: * A major QE program is followed by a period where real wage growth accelerates and outpaces asset price growth, leading to a measurable reduction in wealth inequality. This would suggest QE can successfully stimulate the broad, real economy.

Prediction 6: Debt Ceiling Dynamics

When one category of debt maxes out, growth requires a new category to expand.

The model posits that “growth” in the modern U.S. economy is functionally dependent on expanding debt somewhere in the system. When households hit a debt service wall (~13% of disposable income in 2007), growth stalled, triggering the GFC. The baton was then passed to massive expansion of federal debt. The prediction is that this is a structural relay race.

What to Watch: Track the growth rates of major debt categories: Household, Corporate, Federal Government, Student Loans. * Key Indicator: Look for deceleration in the growth rate of the dominant debt category (e.g., household debt pre-2008, federal debt post-2023) and see if it coincides with economic slowdown unless another category begins accelerating.

Timeframe: Ongoing, multi-year observation.

Evidence That Would CONFIRM the Prediction: * As federal debt growth slows (due to political or market constraints), economic growth falters unless another category—perhaps a resumption of household debt growth or a new explosion in corporate debt—takes up the slack. * The end of the student loan moratorium in 2023 acts as a drag on consumption, requiring another debt or stimulus lever to be pulled to maintain growth rates.

Evidence That Would REFUTE the Prediction: * The U.S. economy achieves a period of strong, sustained GDP growth alongside flat or declining aggregate debt-to-GDP ratios across all major categories. This would demonstrate a true, debt-free productivity and wage-led expansion.

Prediction 7: The Irreversibility Test

Standard pro-business policies (tax cuts, deregulation) will produce profit-led, not wage-led, outcomes.

Once the distributional engine is entrenched—with a large financial sector and weakened labor—the model predicts the system’s response to standard stimulus is locked in. Capital, not labor, is positioned to capture the benefits. The 2017 corporate tax cut (TCJA), which led to record stock buybacks rather than wage surges, is cited as preliminary evidence.

What to Watch: The next major legislative policy marketed as a growth booster for the middle class—a large corporate tax cut, significant deregulation, etc. * Track the Flow: Compare the subsequent growth in corporate profits, dividends, and stock buybacks to the growth in real wages and median household income over the following 2-4 years.

Timeframe: Observation of the next major policy shift.

Evidence That Would CONFIRM the Prediction: * The policy leads to a significant, disproportionate rise in capital income and corporate valuations compared to a muted, lagging rise in worker compensation. The profit share of national income increases.

Evidence That Would REFUTE the Prediction: * A major corporate tax cut or deregulation spurring a business investment boom that tightens the labor market, leading to sustained real wage growth that matches or exceeds profit growth for several years—a classic wage-led recovery.

Tracking These Predictions With Systematic Monitoring

Structured predictions like these are well-suited to AI-assisted monitoring. Working through the source-anchored methodology described in Article 17, it is possible to track indicators like the dollar’s reserve share, cross-country productivity-pay ratios, and debt service burdens as new data becomes available—without relying on a single analyst’s attention or memory. Each data point that confirms or challenges a prediction adds to the model’s empirical record. Over time, this kind of systematic tracking transforms a theoretical framework into a living scorecard: a running test of whether the debt-substitution model continues to describe the world.

What Does Watching These Indicators Mean?

Economics is not a laboratory science. We cannot run controlled experiments on entire nations. Therefore, the credibility of a model hinges on its predictive power—its ability to make specific, risky forecasts about how the world will behave. The seven predictions above are the debt-substitution model’s exam. They are “falsifiable,” meaning we can clearly imagine evidence that would prove them wrong.

Monitoring these indicators does more than test a theory. It provides a structured lens through which to interpret economic news. Is a new trade agreement part of shoring up dollar hegemony? Is a “strong” jobs report masking stagnant real wages? Does a new Fed policy inflate your 401(k) while doing nothing for your paycheck?

If these predictions continue to bear out, it suggests the U.S. economy is operating on a structural logic that is difficult to escape through conventional policy. The debt patch provides stability in the short term but may build greater instability for the long term. The ultimate test, hinted at in Prediction 2, is what happens when the enabling conditions—like the dollar’s exorbitant privilege—begin to change.

The value of a model is not whether it offers a comforting story, but whether it helps us see more clearly. By watching these seven things, we can better understand not just where the economy has been, but where it might be going next.

For detailed data sources and methodology, see Article 17: Sources and Observations.