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US sticky vs flexible inflation signals (underlying inflation gauge, persistence regime)

Monthly signals derived from the Atlanta Fed's sticky-price and flexible-price CPI series (redistributed by FRED, 1968 ->; both series are published as 12-month percent changes): 30-month annualized point-change volatility, 3-month point-change momentum, the 12-month percent change itself, 3-sigma anomaly flags vs a trailing 12-month baseline, naive-drift 1-month forecasts, a per-month cross-series volatility rank, the sticky-minus-flexible spread (pp — the underlying-inflation gauge) and a 10-year sticky-inflation z-score (the persistence-regime gauge). All rows are normalized to country_code USA so they join cleanly with US macro data. Raw series: Federal Reserve Bank of St. Louis (FRED); underlying data: Federal Reserve Bank of Atlanta.

Source: Sticky vs Flexible Inflation Signals (derived)1,408 rowsUpdated: 9/22/2026
inflationsticky-pricescore-inflationcpimonetary-policyvolatilitymomentumanomaly-detectionforecastingsignalsfred

Quality

99.4

Attribution

Federal Reserve Bank of St. Louis (FRED; underlying data: Federal Reserve Bank of Atlanta; derived signals by Frontier Data Hub)

Schema

ColumnTypeDescription
datestringObservation date (FRED API field date; YYYY-MM-DD).
countrystring
country_codestring
series_idstringFRED series ID (CORESTICKM159SFRBATL for sticky-price CPI less food and energy, FLEXCPIM159SFRBATL for flexible-price CPI); IDs resolve to the series page at https://fred.stlouisfed.org/series/<id>.
series_labelstringOfficial FRED series title as published for the series (Federal Reserve Bank of Atlanta sticky/flexible price CPI data).
valuefloat12-month percent change (percent), monthly, seasonally adjusted — the Atlanta Fed publishes these series as percent change from year ago, not index levels; see the series notes for the sticky/flexible classification methodology.
volatility_30dfloat
momentum_3mfloat
yoy_change_pctfloat
anomaly_flaginteger
forecast_1mfloat
rankinteger
sticky_flexible_spreadfloat
sticky_z_10yfloat

Sample rows

datecountrycountry_codeseries_idseries_labelvaluevolatility_30dmomentum_3myoy_change_pctanomaly_flagforecast_1mranksticky_flexible_spreadsticky_z_10y
1968-01-01United StatesUSACORESTICKM159SFRBATLSticky Price Consumer Price Index less Food and Energy3.651861063.6518610600.5697291179999997
1968-01-01United StatesUSAFLEXCPIM159SFRBATLFlexible Price Consumer Price Index3.0821319423.08213194200.5697291179999997
1968-02-01United StatesUSACORESTICKM159SFRBATLSticky Price Consumer Price Index less Food and Energy3.6738194113.67381941100.41336798500000027
1968-02-01United StatesUSAFLEXCPIM159SFRBATLFlexible Price Consumer Price Index3.2604514263.26045142600.41336798500000027
1968-03-01United StatesUSACORESTICKM159SFRBATLSticky Price Consumer Price Index less Food and Energy4.1421639754.14216397500.5723831349999999

Download sample data

Download the full sample snapshot for this dataset (sample rows, not the complete dataset).

Use with an LLM

Point any LLM at the metadata endpoint — the documentation above is machine-readable too (JSON-LD + Croissant).

cURL

curl "https://datazimuts.com/v1/datasets/sticky_inflation_signals/us_sticky_vs_flexible_inflation_signals" | jq '{title, rows, columns_count, license}'

Python

import requests

ds = requests.get("https://datazimuts.com/v1/datasets/sticky_inflation_signals/us_sticky_vs_flexible_inflation_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)

API endpoint: https://datazimuts.com/v1/datasets/sticky_inflation_signals/us_sticky_vs_flexible_inflation_signals

Tip: fetch /llms.txt for the full machine-readable catalog.