Regime assignments use canonical definitions established 2026-03-08 (K-Means k=5, Fiat Transition Era). View WCSS analysis.
Macro Economic Regime Clustering (1971–1987)FIAT TRANSITION ERA
Published 2026-03-08
This analysis identifies distinct macroeconomic regimes by applying unsupervised K-Means clustering to 17 weekly-aggregated macro indicators spanning 1971 to 1987 (887 weeks of data). The algorithm discovered 5 distinct regimes, each characterized by a unique combination of growth, inflation, credit, and risk conditions.
Identified Regimes
Each row summarizes one regime: its auto-generated label, the number of weeks assigned to it, the span of dates it covers, and the three indicator values (with z-scores) that most distinguish it from the others.
| ID | Label | Weeks | Date Span | Top Distinguishing Features (centroid) |
|---|---|---|---|---|
| 0 | Expanding / Low BAA Spread / Low Short-10Y Spread | 169 | 1973-02-02 – 1979-09-28 | Capacity Utilization: 86.47 (z=+1.36); BAA Spread: 1.35 (z=-1.14); Short-10Y Spread: -0.50 (z=-1.14) |
| 1 | Tightening / Low 3m10y Spread / Low Short-10Y Spread | 95 | 1979-10-05 – 1982-02-26 | 3M Treasury Yield: 13.64 (z=+2.08); Fed Funds Rate: 15.81 (z=+2.03); 2Y Treasury Yield: 13.72 (z=+1.78) |
| 2 | Low Industrial Production / Low Fed Funds Rate / Low CPI | 266 | 1971-01-01 – 1978-03-31 | Industrial Production: 42.92 (z=-1.05); Fed Funds Rate: 5.14 (z=-0.99); CPI: 51.12 (z=-0.97) |
| 3 | Deteriorating / Recessionary / Credit Stress | 109 | 1974-11-01 – 1983-03-25 | Initial Jobless Claims: 556807.34 (z=+1.88); Recession Probability: 63.69 (z=+1.74); BAA Spread: 3.04 (z=+1.58) |
| 4 | Expanding / Inflationary / Optimistic | 248 | 1983-04-01 – 1987-12-25 | M2 Money Supply: 2437.92 (z=+1.36); GDP: 8521.99 (z=+1.31); CPI: 107.32 (z=+1.24) |
Visualization
Top panel — PCA Feature Space: Each dot represents one week projected into two principal components (capturing 65.7% of total variance). Color indicates the assigned regime. Dots that form tight, well-separated clusters indicate regimes with distinctive macro fingerprints.
Bottom panel — Regime Timeline: The same regime assignments plotted chronologically, so you can see when each macro regime was in force. The legend below the timeline panel identifies each color.
Regime Fingerprints — Feature Z-Scores
The table below shows the standardized z-score of each feature's cluster centroid. A value of +2.0 means that regime has a feature value roughly 2 standard deviations above the historical average; −2.0 means 2 standard deviations below. Dark red = strongly above average Dark blue = strongly below average
| Feature | Regime 0 Expanding / Low BAA Spread / Low Short-10Y Spread | Regime 1 Tightening / Low 3m10y Spread / Low Short-10Y Spread | Regime 2 Low Industrial Production / Low Fed Funds Rate / Low CPI | Regime 3 Deteriorating / Recessionary / Credit Stress | Regime 4 Expanding / Inflationary / Optimistic |
|---|---|---|---|---|---|
| GDP | -0.49 | +0.22 | -0.95 | -0.09 | +1.31 |
| Unemployment Rate | -1.12 | +0.09 | -0.13 | +1.42 | +0.25 |
| CPI | -0.75 | +0.39 | -0.97 | +0.37 | +1.24 |
| Fed Funds Rate | +0.28 | +2.03 | -0.99 | +0.51 | -0.13 |
| Initial Jobless Claims | -0.78 | +0.58 | -0.40 | +1.88 | -0.09 |
| Consumer Sentiment | -0.68 | -1.00 | +0.29 | -1.27 | +1.09 |
| Recession Probability | +0.10 | +0.34 | -0.45 | +1.74 | -0.47 |
| Industrial Production | -0.10 | +0.47 | -1.05 | -0.28 | +1.13 |
| 3M Treasury Yield | +0.12 | +2.08 | -0.94 | +0.47 | -0.07 |
| 2Y Treasury Yield | -0.16 | +1.78 | -0.55 | +0.65 | -0.27 |
| 10Y Treasury Yield | -0.50 | +1.48 | -0.86 | +0.81 | +0.34 |
| M2 Money Supply | -0.69 | +0.08 | -0.90 | +0.10 | +1.36 |
| Capacity Utilization | +1.36 | +0.06 | +0.06 | -1.38 | -0.40 |
| NFCI | +0.61 | +1.31 | -0.59 | +0.85 | -0.67 |
| BAA Spread | -1.14 | -0.19 | -0.05 | +1.58 | +0.21 |
| 3m10y Spread | -1.08 | -1.61 | +0.42 | +0.43 | +0.71 |
| Short-10Y Spread | -1.14 | -1.58 | +0.77 | +0.06 | +0.53 |
Methodology
Data Sources
Indicators are sourced entirely from the FRED (St. Louis Fed) API and cover 1971 to 1987. The following series are used:
- FRED Macro Series — Real GDP, Unemployment Rate, CPI (All Urban), Federal Funds Rate, Initial Jobless Claims, Consumer Sentiment (UMich), Smoothed US Recession Probability, Industrial Production Index, 3-Month Treasury Bill, 10-Year Treasury, 2-Year Treasury (bridged with 1-Year Treasury prior to June 1976), M2 Money Supply, Total Capacity Utilization, Chicago Fed NFCI, Moody's Baa Corporate Bond Yield
- S&P 500 (FMP API) — Daily prices used solely to compute realized volatility (21-week rolling annualized std of weekly log-returns)
- Derived Features — BAA Spread (Baa − 10Y Treasury), 3m10y Spread (10Y − 3M Treasury), Short-10Y Spread (10Y − spliced 1Y/2Y Treasury)
VIX, HY OAS, IG OAS, 5-Year Breakeven Inflation, Fed Balance Sheet, retail sales, and sector performance data are not available for the full historical period and are excluded.
Weekly Aggregation
All daily series are averaged to week-ending-Friday frequency. Monthly and quarterly series (GDP, CPI, unemployment, etc.) are forward-filled up to 92 days before resampling so that every week carries the most recently released value. Weeks with fewer than 50 % of features populated are dropped. Any remaining individual NaNs are filled with the column median before clustering.
Feature Preprocessing
All 17 features are standardized to zero mean and unit variance
(sklearn.preprocessing.StandardScaler) so that indicators with
vastly different magnitudes (VIX in 10–80, GDP in $ trillions) contribute
equally to the K-Means distance metric.
Clustering Algorithm
K-Means clustering (sklearn.cluster.KMeans,
n_init=20, random_state=42) with
k = 5 clusters. The canonical
k=5 is fixed and stored as canonical regime definitions in S3.
Regime assignments use nearest-centroid (Euclidean distance) in standardized
feature space.
Cluster Labeling
Each cluster is automatically labeled using the three features whose standardized centroid values deviate most from the global mean (largest absolute z-score). A positive deviation uses the feature's descriptive direction tag (e.g. a VIX centroid well above average → "Stressed"); a negative deviation uses "Low <feature name>".
Visualization
Principal Component Analysis (PCA) projects all 17 features into two dimensions for the scatter plot. PC1 and PC2 together capture 65.7% of total variance (35.6% + 30.0%).
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