US county solo-economy intelligence (annual)
Annual US county solo-economy intelligence from the keyless U.S. Census Nonemployer Statistics bulk county files (2020-2024): one row per year per county (~3,143 counties) for the all-industries total — the annual census of businesses with no paid employees (sole proprietorships, partnerships, corporations without payroll). Each row carries nonemployer establishment counts, total receipts (normalized to whole dollars from the published $1,000s), average receipts per establishment, and the Census noise-infusion flag. Derived: exact year-over-year changes in establishments/receipts (null when the prior year is absent, never interpolated), 2020->2024 four-year CAGRs, and a documented 0-100 solo-economy score (50% winsorized establishment momentum + 50% winsorized receipts momentum, min-maxed over scored county-years) with per-state ranks and quartile tiers. Method: parse the all-industries county panel from each NES county file, resolve FIPS to canonical county names via the Census gazetteer (Connecticut's 2022 county-to-planning-region switch handled), null suppressed cells (never zero-fill), keep receipts in dollars. Caveats: cells carry Census noise infusion (flagged); scores are relative history gauges, not forecasts; reference year lags ~1.5 years. U.S. federal public domain (commercial reuse allowed with attribution to the U.S. Census Bureau).
- Source
- U.S. Census Bureau
- Rows
- 15,711
- Columns
- 21
- Source cadence
- Yearly
- Last refreshed
- Oct 2, 2026
- Theme
- economy
| Column | Type | Description |
|---|---|---|
| country_code | string | ISO alpha-3 country code (USA for every row). (unit: ISO 3166-1 alpha-3) |
| year | integer | NES reference year: the 12 months ending December of the reference year. |
| fips | string | 5-digit county FIPS code (2-digit state + 3-digit county), zero-padded. |
| county_name | string | Canonical county name from the Census county gazetteer (union of the 2018/2021/2024 vintages; later wins). |
| state_fips | string | 2-digit state FIPS code, zero-padded. |
| state_abbr | string | USPS 2-letter state abbreviation. |
| state_name | string | State name. |
| nonemployer_establishments | float | Number of nonemployer business establishments in the county (businesses with no paid employees subject to federal income tax, receipts of $1,000+; $1+ for Construction). Null where the publisher suppressed the cell (never zero-filled). (unit: count) |
| nonemployer_receipts_usd | float | Total receipts of nonemployer businesses in the county, in whole dollars (NES publishes receipts in $1,000s; converted verbatim). Null where suppressed. (unit: USD) |
| receipts_per_establishment_usd | float | Average receipts per nonemployer establishment (nonemployer_receipts_usd / nonemployer_establishments). (unit: USD) |
| noise_flag | string | Census disclosure-avoidance noise-infusion flag on the receipts cell: G = low noise, H = medium noise, J = high noise, S = withheld (did not meet publication standards). Per the NES glossary. |
| est_yoy_pct | float | Year-over-year percent change in nonemployer establishments, computed only against the exact prior reference year for the same FIPS. Null when the prior year is absent (never interpolated). (unit: percent) |
| rcpt_yoy_pct | float | Year-over-year percent change in nonemployer receipts, same exact-prior-year rule as est_yoy_pct. (unit: percent) |
| est_cagr_4y_pct | float | Four-year compound annual growth rate of nonemployer establishments, 2020 -> 2024. Carried on the 2024 row only; null where the 2020 base is missing or zero. (unit: percent) |
| rcpt_cagr_4y_pct | float | Four-year compound annual growth rate of nonemployer receipts, 2020 -> 2024. Same 2024-row-only rule. (unit: percent) |
| solo_economy_score | float | Documented 0-100 composite: 100 * (0.50 * min-max of winsorized est_yoy_pct (+-25pp) + 0.50 * min-max of winsorized rcpt_yoy_pct (+-25pp)), min-max taken over the snapshot's scored county-years (2021-2024). Higher = the county's solo-business base is growing in both count and receipts. A relative history gauge, not a forecast. (unit: 0-100) |
| solo_economy_rank_state | string | Within each (state, year), rank of solo_economy_score (1 = strongest). |
| solo_economy_tier | string | Quartile tier of solo_economy_score over scored county-years: p1 (top) .. p4. |
| as_of | string | Fetch date (ISO) of the snapshot build. (unit: ISO date) |
| source_url | string | The exact NES bulk zip URL the row's reference year was parsed from. (unit: URL) |
| row_hash | string | Deterministic 16-hex SHA-256 of 'NES-SOLO|year|fips' — stable row identity across snapshots. |
First 10 sample rows — a preview, not the complete dataset.
| country_code | year | fips | county_name | state_fips | state_abbr | state_name | nonemployer_establishments | nonemployer_receipts_usd | receipts_per_establishment_usd | noise_flag | est_yoy_pct | rcpt_yoy_pct | est_cagr_4y_pct | rcpt_cagr_4y_pct | solo_economy_score | solo_economy_rank_state | solo_economy_tier | as_of | source_url | row_hash |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| USA | 2,024 | 01001 | Autauga County | 01 | AL | Alabama | 4,047 | 195,293,000 | 48,256.239 | G | 2.612 | 4.131 | 3.134 | 4.492 | 56.74 | 30 | p3 | 2026-10-02 | https://www2.census.gov/programs-surveys/nonemployer-statistics/datasets/2024/historical-datasets/nonemp24co.zip | ac780d03ecfb4e74 |
| USA | 2,024 | 01003 | Baldwin County | 01 | AL | Alabama | 25,088 | 1,525,125,000 | 60,791.016 | G | 3.473 | 1.514 | 4.126 | 7.104 | 54.99 | 36 | p3 | 2026-10-02 | https://www2.census.gov/programs-surveys/nonemployer-statistics/datasets/2024/historical-datasets/nonemp24co.zip | 6ef05ecff13e9d45 |
| USA | 2,024 | 01005 | Barbour County | 01 | AL | Alabama | 1,543 | 66,360,000 | 43,007.129 | G | -8.264 | -7.116 | 0.393 | 4.447 | 34.62 | 67 | p4 | 2026-10-02 | https://www2.census.gov/programs-surveys/nonemployer-statistics/datasets/2024/historical-datasets/nonemp24co.zip | d3ed89885ebcab32 |
| USA | 2,024 | 01007 | Bibb County | 01 | AL | Alabama | 1,191 | 59,807,000 | 50,215.785 | G | -2.297 | 5.417 | 1.548 | 6.008 | 53.12 | 47 | p3 | 2026-10-02 | https://www2.census.gov/programs-surveys/nonemployer-statistics/datasets/2024/historical-datasets/nonemp24co.zip | 4997b1fdbf95d76b |
| USA | 2,024 | 01009 | Blount County | 01 | AL | Alabama | 4,276 | 231,418,000 | 54,120.206 | G | 3.56 | 1.411 | 2.44 | 6.179 | 54.97 | 37 | p3 | 2026-10-02 | https://www2.census.gov/programs-surveys/nonemployer-statistics/datasets/2024/historical-datasets/nonemp24co.zip | 70e23dfea7ddee42 |
| USA | 2,024 | 01011 | Bullock County | 01 | AL | Alabama | 623 | 26,998,000 | 43,335.474 | G | 6.496 | 21.52 | 3.448 | 3.629 | 78.02 | 1 | p1 | 2026-10-02 | https://www2.census.gov/programs-surveys/nonemployer-statistics/datasets/2024/historical-datasets/nonemp24co.zip | e6bca56e8e3f4d3c |
| USA | 2,024 | 01013 | Butler County | 01 | AL | Alabama | 1,137 | 47,414,000 | 41,700.967 | G | 1.973 | -0.173 | 2.727 | 5.183 | 51.8 | 50 | p4 | 2026-10-02 | https://www2.census.gov/programs-surveys/nonemployer-statistics/datasets/2024/historical-datasets/nonemp24co.zip | 0f59e6060ef7425c |
| USA | 2,024 | 01015 | Calhoun County | 01 | AL | Alabama | 7,520 | 346,448,000 | 46,070.213 | G | 3.24 | 0.798 | 2.401 | 7.123 | 54.04 | 43 | p3 | 2026-10-02 | https://www2.census.gov/programs-surveys/nonemployer-statistics/datasets/2024/historical-datasets/nonemp24co.zip | eac5fe65888ab5d1 |
| USA | 2,024 | 01017 | Chambers County | 01 | AL | Alabama | 2,477 | 81,684,000 | 32,976.988 | G | 6.721 | 2.543 | 5.037 | 4.498 | 59.26 | 19 | p3 | 2026-10-02 | https://www2.census.gov/programs-surveys/nonemployer-statistics/datasets/2024/historical-datasets/nonemp24co.zip | 03eec400b18b07ce |
| USA | 2,024 | 01019 | Cherokee County | 01 | AL | Alabama | 1,991 | 108,148,000 | 54,318.433 | G | 7.563 | 0.021 | 3.65 | 2.889 | 57.58 | 25 | p3 | 2026-10-02 | https://www2.census.gov/programs-surveys/nonemployer-statistics/datasets/2024/historical-datasets/nonemp24co.zip | 260b223fd381c376 |
- Current
20261002T102016Z-07efe9db29ea · sha256 07efe9db29ea…
15,711 rows · first snapshot
Point any LLM at the metadata endpoint — the documentation above is machine-readable too (JSON-LD + Croissant).
curl "https://datazimuts.com/v1/datasets/census_nonemployer_intel/us_county_nonemployer_intel_annual" | jq '{title, rows, columns_count, license}'import requests
ds = requests.get("https://datazimuts.com/v1/datasets/census_nonemployer_intel/us_county_nonemployer_intel_annual").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/census_nonemployer_intel/us_county_nonemployer_intel_annual
Tip: fetch /llms.txt for the full machine-readable catalog.
Where this data comes from and what was made from it. Other people's work shows as counts; only shared projects are named.
Cite this snapshot
Pinned to snapshot 20261002T102016Z-07efe9db29ea and its content hash, so readers get exactly the data you used.
U.S. Census Bureau. (2026). US county solo-economy intelligence (annual) [Data set, snapshot 20261002T102016Z-07efe9db29ea, sha256 07efe9db29ea]. Datazimuts. Retrieved 2026-10-02, from https://datazimuts.com/en/datasets/census_nonemployer_intel/us_county_nonemployer_intel_annual?snapshot=20261002T102016Z-07efe9db29ea
@misc{dz_census_nonemployer_intel_us_county_nonem_07efe9db,
title = {{US county solo-economy intelligence (annual)}},
author = {{U.S. Census Bureau}},
year = {2026},
publisher = {Datazimuts},
howpublished = {\url{https://datazimuts.com/en/datasets/census_nonemployer_intel/us_county_nonemployer_intel_annual?snapshot=20261002T102016Z-07efe9db29ea}},
note = {Snapshot 20261002T102016Z-07efe9db29ea, sha256 07efe9db29eac369893f236bd97edf9356109eefcbafd19641bc9156218b9730; accessed 2026-10-02}
}Embed a table or a chart
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