About StratMac

Macroeconomic Intelligence

StratMac maps the structural landscape of the global economy — tracking where capital flows, where wealth concentrates, and where divergences signal instability. We strip away nominal noise and examine the economy through a real vs. nominal, flow vs. stock, and cross-border dependency framework. Our goal is not to forecast, but to reveal the underlying architecture of economic forces that conventional metrics hide.

In a world where central banks print fiat currency at unprecedented scale, nominal prices are no longer a reliable signal. A rising S&P 500 or growing GDP looks reassuring in dollar terms until you denominator it against the economy's real output or strip out the price level. StratMac systematically applies these corrections, letting the data tell a different story — one of hidden inflation, disguised wealth transfers, and mounting systemic fragility.

Philosophy

The core insight driving StratMac is that nominal dollar values are a veil obscuring real performance. A nominal reading of any series fuses two independent forces into a single number: the real economic activity underneath, plus the monetary veil thrown over it by inflation and currency debasement. As central banks expand the money supply, a dollar-denominated series can rise even while the real output or wealth underneath is flat or falling — and rising nominal values can look healthy precisely when real value is being quietly eroded. To part the veil and expose the real signal, we re-express dollar series in dimensionless terms: dividing by U.S. GDP (or another unitless denominator) to de-dollarize, and using purchasing-power parity for cross-border comparisons.

Real vs. Nominal: CPI deflation strips out consumer price inflation, revealing whether an indicator is genuinely growing, stagnant, or declining in purchasing-power terms. This is the standard real-economics lens — essential but incomplete on its own.

Flow vs. Stock: Flow variables (GDP, payrolls, Fed funds) measure the rate of economic activity. Stock variables (national debt, household wealth) measure accumulated positions. Disconnects between flows and stocks — rising debt-to-GDP, for instance — are a classic signature of systemic risk that compounding growth rates alone cannot capture.

Cross-Border Dependencies: Capital does not respect borders. We track how foreign holdings of U.S. debt, trade imbalances, and reserve currency flows create feedback loops that amplify or suppress domestic signals. A domestic recovery that depends on foreign capital inflows is qualitatively different from one that is self-financed.

Where capital flows, wealth concentrates. Where divergences between real and nominal, flow and stock, domestic and foreign widen, instability accumulates. StratMac surfaces these fault lines.

Indicators Tracked

StratMac organizes its signals into fifteen sections. Every domestic U.S. card is either the raw published value or, where we want the de-dollarized real signal, the series expressed as a share of U.S. GDP (or of another unitless denominator). Cross-country cards use purchasing-power-parity (PPP) comparisons. Representative coverage:

Methodology

StratMac's core principle is that dollar-denominated series are normalized to dimensionless ratios before they can be compared. Raw dollar figures (M2, household net worth, national debt) are scaled against other dollar figures (U.S. GDP); cross-country levels are scaled through purchasing-power parity. Percentage and index series (CPI, PPI, rates, breakevens) are already dimension-free and are left as the raw published value — they are the price-level / money-erosion measure, not something to be deflated away. No raw dollar magnitude escapes to influence relative readings. This is the de-dollarization that removes money illusion and answers: what is this number's real claim on the economy's output?

Signal pipeline. Each de-dollarized (or inherently ratio) series is fit with an ARIMA(1,1,0) model; the one-step-ahead forecast residual is standardized by its own residual standard deviation (a sigma deviate), ranked against the series' history to a percentile, and checked for a 3-period same-sign streak. The result is a color badge — how far a move is from what recent trend could predict, in units of that series' own noise. This makes a move in GDP directly comparable to a move in CPI without reintroducing units.

De-dollarizer by convention. Domestic U.S. ratios divide by U.S. nominal GDP (GDPC1); international comparisons use World Bank purchasing-power-parity (PPP) GDP. Fiscal and wealth ratios are already unitless. CPI/PPI and breakeven-inflation series are intentionally left raw — they are the price-level / money-erosion measure, not something to be deflated away.

Full attribution. Every card lists its exact FRED series ID (or World Bank / WID source) on our public Sources & Method page. Domestic series are accessed through the Federal Reserve Economic Database (FRED), which re-hosts them from the agencies that actually produce them — chiefly the Bureau of Economic Analysis (BEA), Bureau of Labor Statistics (BLS), U.S. Census Bureau, and the Federal Reserve Board, plus EIA, Freddie Mac, S&P/Case-Shiller, and the University of Michigan among others. Cross-country series come from the World Bank WDI and WID. Series are refreshed on the scheduled pipeline cycle.

Technology

Leaflet Python FRED (public CSV) ARIMA σ-signal World Bank WDI WID GH Actions

Contact

[email protected]