US state coincident-activity signals (Philadelphia Fed index momentum, state-vs-nation divergence, anomalies)
Monthly signals derived from the Philadelphia Fed's Coincident Economic Activity Indexes (redistributed by FRED): 30-month annualized change volatility, 3-month momentum, year-over-year change, 3-sigma anomaly flags vs a trailing 12-month baseline, naive-drift 1-month forecasts, a per-month cross-state volatility rank, the state-minus-nation cycle-divergence gauge and a 24-month growth z-score (the state business-cycle heat gauge). Covers the national index plus all 50 state indexes from 1979. All rows are normalized to country_code USA so they join cleanly with US macro data; the state identity rides in series_id. Raw series: Federal Reserve Bank of St. Louis (FRED); underlying data: Federal Reserve Bank of Philadelphia.
Qualité
Attribution
Federal Reserve Bank of St. Louis (FRED; underlying data: Federal Reserve Bank of Philadelphia; derived signals by Frontier Data Hub)
Schéma
| Colonne | Type | Description |
|---|---|---|
| date | string | Observation date (FRED API field date; YYYY-MM-DD). |
| country | string | |
| country_code | string | |
| series_id | string | FRED series ID: USPHCI for the national index, <USPS>PHCI for each state's index (e.g. TXPHCI for Texas); FRED IDs resolve to the series page at https://fred.stlouisfed.org/series/<id>. |
| series_label | string | Official FRED series title as published for the series (Federal Reserve Bank of Philadelphia data). |
| value | float | Coincident Economic Activity Index value (Index 2007=100): combines nonfarm payroll employment, the unemployment rate, average hours worked in manufacturing, and wages and salaries; the trend for each state's index is set to the trend of its gross state product. See the series notes for methodology. |
| volatility_30d | float | |
| momentum_3m | float | |
| yoy_change_pct | float | |
| anomaly_flag | integer | |
| forecast_1m | float | |
| rank | integer | |
| us_gap | float | |
| growth_z_24m | float |
Exemple de lignes
| date | country | country_code | series_id | series_label | value | volatility_30d | momentum_3m | yoy_change_pct | anomaly_flag | forecast_1m | rank | us_gap | growth_z_24m |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1979-01-01 | United States | USA | AKPHCI | Coincident Economic Activity Index for Alaska | 61.24 | — | — | — | 0 | — | — | — | — |
| 1979-01-01 | United States | USA | ALPHCI | Coincident Economic Activity Index for Alabama | 50.77 | — | — | — | 0 | — | — | — | — |
| 1979-01-01 | United States | USA | ARPHCI | Coincident Economic Activity Index for Arkansas | 49.06 | — | — | — | 0 | — | — | — | — |
| 1979-01-01 | United States | USA | AZPHCI | Coincident Economic Activity Index for Arizona | 29.92 | — | — | — | 0 | — | — | — | — |
| 1979-01-01 | United States | USA | CAPHCI | Coincident Economic Activity Index for California | 40.34 | — | — | — | 0 | — | — | — | — |
Télécharger un échantillon
Téléchargez l'échantillon complet de ce jeu de données (lignes d'exemple, pas le jeu complet).
Utiliser avec un LLM
Dirigez n’importe quel LLM vers le point d’accès des métadonnées — la documentation ci-dessus est aussi lisible par machine (JSON-LD + Croissant).
cURL
curl "https://datazimuts.com/v1/datasets/state_cycle_signals/us_state_coincident_activity_signals" | jq '{title, rows, columns_count, license}'Python
import requests
ds = requests.get("https://datazimuts.com/v1/datasets/state_cycle_signals/us_state_coincident_activity_signals").json()
print(ds["title"], ds["rows"], "rows")
# Sample rows for an LLM context window
for row in ds.get("sample_rows", [])[:5]:
print(row)Point d’accès API: https://datazimuts.com/v1/datasets/state_cycle_signals/us_state_coincident_activity_signals
Astuce : récupérez /llms.txt pour le catalogue complet lisible par machine.