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Datasets / Money Flows
federalreserve.gov/

Fed Distributional Financial Accounts

Freeauth: noneCustom#money-flows#historical-data#time-series#macro-economic#risk✓ verified Nov 1, 2026

Fed Distributional Financial Accounts

Quarterly estimates of U.S. household wealth levels and shares by wealth, income, age, generation, education and race, with assets, liabilities and net-worth components allocated from the Financial Accounts using Survey of Consumer Finances distributions. The keyless ZIP contains CSV tables, definitions and detail dictionaries; no key is needed.

Required Attribution:

Please cite the Board of Governors of the Federal Reserve System as the source.

Coverage

United States quarterly observations run from 1989 Q3 through the latest quarter; the checked bundle reaches 2026 Q2. The provider updates the dataset with new DFA releases, while quarters beyond the latest triennial Survey of Consumer Finances use forecast distributional balance sheets.

Verdict

A distributional money-flow signal for a trading or AI agent studying which household groups hold assets, debts and net worth across the U.S. cycle. It is quarterly and aggregate rather than account-level data. The construction reconciles two datasets with different concepts and frequencies, interpolates between triennial surveys and forecasts beyond the latest survey, so recent subgroup estimates are model-based and can be revised. Use the official release when a visualization and release disagree.

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Use in your agent

Load Fed household wealth groups into pandas and Parquet. Checked against the provider's documentation on Nov 1, 2026.

Raw skill file (/skills/fed-distributional-financial-accounts.md)Also in our MCP server: call get_ingestion_skill with {"slug": "fed-distributional-financial-accounts"}.

Access

  • No account or key is required for the complete DFA ZIP.
  • The ZIP includes CSV tables plus text definitions and detail dictionaries.

Request

bash
curl -O 'https://www.federalreserve.gov/releases/z1/dataviz/download/zips/dfa.zip'

Format

ZIP of CSV tables for levels and shares by net-worth, income, age, generation, education and race groups, plus text definitions and dictionaries.

Load into pandas and Parquet

Needs Python 3 with requests, pandas and pyarrow.

python
"""Fed DFA net-worth level table from ZIP -> pandas -> Parquet."""
import io
import zipfile
import requests
import pandas as pd

URL = "https://www.federalreserve.gov/releases/z1/dataviz/download/zips/dfa.zip"
r = requests.get(URL, timeout=60)
r.raise_for_status()
with zipfile.ZipFile(io.BytesIO(r.content)) as z:
    with z.open("dfa-networth-levels.csv") as f:
        df = pd.read_csv(f)
df["Date"] = pd.PeriodIndex(df["Date"].str.replace(":", ""), freq="Q").to_timestamp("Q")
df.to_parquet("fed_dfa_networth_levels.parquet", index=False)
print(len(df), "rows", df["Date"].min().date(), "to",
      df["Date"].max().date(), "columns", len(df.columns))

Run by us on 2026-11-01 (python 3.13.5 | pandas 3.1.0 | pyarrow 26.0.0 | requests 2.34.2). Result: 740 rows 1989-09-30 to 2026-06-30 columns 15

Limits

  • Rate limit: Not stated.
  • Observations are quarterly and begin in 1989 Q3.
  • The complete checked ZIP contained 27 files and was 895,897 bytes.

Quirks

  • Date values use strings such as 1989:Q3; convert them through a quarterly PeriodIndex.
  • Level and share tables are separate, as are summary and detailed component tables.
  • Recent distributions beyond the latest Survey of Consumer Finances are forecast before being scaled to Financial Accounts aggregates.

Terms and attribution

  • Board website information is public domain unless otherwise indicated.
  • Cite the Board as the source and check for separately identified non-Board material.

Sources

Information and education only. Not financial, investment, legal or tax advice. Listings can be inaccurate, incomplete or out of date and are provided "as is". Free tiers, limits and licenses belong to each provider and can change, so check the provider's own terms before you rely on them. Terms & Disclaimer