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US state personal-income signals (regional income growth)

Quarterly US state personal-income signals from BEA total personal income (FRED <USPS>OTOT series, 49 states + DC — North Carolina excluded, FRED's NCOTOT is corrupted — 1948-Q1 ->): year-on-year growth, quarter-on-quarter change, 4-quarter volatility, 3-sigma anomaly flags, naive-drift forecasts, 5-year growth z-scores, per-quarter growth ranks, each state's share of US personal income, outperform-vs-US and contraction flags. The income lens on US regions — what households actually receive — complementing state-gdp-signals (output), state-labor-signals (unemployment), and state-cycle-signals (coincident index). The US benchmark is the sum of the 50 included state series each quarter (North Carolina excluded — FRED's NCOTOT is corrupted). All rows normalized to country_code USA. Raw series: U.S. Bureau of Economic Analysis via FRED.

Source: US State Personal-Income Signals (derived)15,634 rowsUpdated: 9/22/2026
personal-incomestatesregionalbeahouseholdsincome-growthmomentumanomaly-detectionforecastingranksignalsfred

Quality

99.7

Attribution

U.S. Bureau of Economic Analysis via FRED; signals by Frontier Data Hub

Schema

ColumnTypeDescription
datestringObservation date (FRED API field date; YYYY-MM-DD, quarterly).
countrystring
country_codestring
series_idstringFRED series code of the form <USPS>OTOT (e.g. CAOTOT): Total Personal Income in the state, Bureau of Economic Analysis, seasonally adjusted annual rate, millions of dollars.
series_labelstringPersonal income is the income received by, or on behalf of, all persons from all sources: wages and salaries, supplements to wages and salaries, proprietors' income, rental income, personal dividend income, personal interest income, and personal current transfer receipts, less contributions for government social insurance (BEA definition).
valuefloatTotal personal income in millions of dollars (seasonally adjusted annual rate). The broadest measure of what households in the state actually receive — wages plus business, capital, and transfer income.
yoy_growth_pctfloat
qoq_change_pctfloat
volatility_4qfloat
anomaly_flaginteger
forecast_1qfloat
growth_z_5yfloat
growth_rankfloat
us_share_pctfloat
outperform_flaginteger
contraction_flaginteger

Sample rows

datecountrycountry_codeseries_idseries_labelvalueyoy_growth_pctqoq_change_pctvolatility_4qanomaly_flagforecast_1qgrowth_z_5ygrowth_rankus_share_pctoutperform_flagcontraction_flag
1950-01-01United StatesUSAAKOTOTTotal Personal Income in Alaska (millions of dollars, SAAR, BEA via FRED)343.400.1556329238413867700
1950-04-01United StatesUSAAKOTOTTotal Personal Income in Alaska (millions of dollars, SAAR, BEA via FRED)373.88.85264997087944400.1678371413985261200
1950-07-01United StatesUSAAKOTOTTotal Personal Income in Alaska (millions of dollars, SAAR, BEA via FRED)408.59.28303905831995400.1769595618160686200
1950-10-01United StatesUSAAKOTOTTotal Personal Income in Alaska (millions of dollars, SAAR, BEA via FRED)439.87.66217870257037700.1837679192524264100
1951-01-01United StatesUSAAKOTOTTotal Personal Income in Alaska (millions of dollars, SAAR, BEA via FRED)470.537.012230634828196.9804456571168631.0607187111064713010.189759825767811410

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/state_income_signals/us_state_personal_income_signals" | jq '{title, rows, columns_count, license}'

Python

import requests

ds = requests.get("https://datazimuts.com/v1/datasets/state_income_signals/us_state_personal_income_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/state_income_signals/us_state_personal_income_signals

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