US county business-bankruptcy filings, quarterly
Quarterly US county business-bankruptcy intelligence panel built from the Administrative Office of the U.S. Courts Table F-5A (business and nonbusiness cases commenced, by county and chapter; keyless .xlsx, verified live 2026-10-01). Each vintage covers the trailing 12 months ending on the quarter date (AOUSC convention); the panel carries business filings (all chapters plus Chapter 7/11/13/other splits) per county FIPS, summed across the table's circuit sections to correct venue-transfer undercounting (the same county can appear under several circuits). Carries calendar year-over-year changes in business filings and the Chapter-11 reorganization share. Method caveats: '-' cells are true zeros per AOUSC convention; counties are debtor counties as recorded in filings (venue rules let cases be filed away from the debtor's county, which the cross-circuit summing addresses but cannot fully undo); the 'OUTSIDE U.S.' aggregate is excluded; a county genuinely absent from a vintage is an absent row, never a zero-filled one. Who joins this: B2B sales teams join business_yoy on quarter_end + county_fips/state_code as a regional distress feature; credit-exposed shops and subscription businesses condition expansion forecasts on county business-bankruptcy momentum.
- Rows
- 18,714
- Columns
- 17
- Source cadence
- Quarterly
- Last refreshed
- Oct 1, 2026
- Theme
- economy
| Column | Type | Description |
|---|---|---|
| quarter_end | date | Quarter-end date of the vintage. Each vintage covers the trailing 12 months ending on this date (AOUSC F-5A convention) — the panel join key with county_fips. (unit: date) |
| year_quarter | string | Calendar quarter as YYYY-QN (panel join key). (unit: string) |
| county_fips | string | 5-digit county FIPS code ('US' for the national aggregate row). (unit: string) |
| county_name | string | County name as published by AOUSC (most common spelling across circuit sections; 'United States' for the national row). (unit: string) |
| state_code | string | USPS 2-letter state code from the county FIPS prefix (empty for the national row). (unit: string) |
| state_name | string | State name (empty for the national row). (unit: string) |
| country | string | Country name (shared normalization layer). (unit: string) |
| country_code | string | ISO 3166-1 alpha-3 country code (USA). (unit: string) |
| business_all | integer | Business bankruptcy cases commenced with predominant business debt, all chapters, trailing 12 months, summed across circuit sections (venue-normalized). '-' cells in the source are true zeros per AOUSC convention. (unit: cases, trailing 12 months) |
| business_ch7 | integer | Business cases under Chapter 7 (liquidation), trailing 12 months. (unit: cases, trailing 12 months) |
| business_ch11 | integer | Business cases under Chapter 11 (reorganization), trailing 12 months. (unit: cases, trailing 12 months) |
| business_ch13 | integer | Business cases under Chapter 13 (individual reorganization with business debt), trailing 12 months. (unit: cases, trailing 12 months) |
| business_other | integer | Business cases under other chapters (9, 12, 15), trailing 12 months. (unit: cases, trailing 12 months) |
| business_yoy | integer | Change in business_all vs the trailing-12-month vintage ending one calendar year earlier (non-overlapping windows; null when that vintage is unavailable). (unit: cases) |
| business_yoy_pct | string | Percent change in business_all vs the vintage one calendar year earlier (null when unavailable, or when the base vintage had zero business filings). (unit: percent) |
| ch11_share | string | Chapter-11 reorganization share of business filings (business_ch11 / business_all; null when business_all is 0). (unit: ratio) |
| row_hash | string | Deterministic 16-hex sha256 of quarter_end + county_fips + business_all (idempotency key). (unit: string) |
First 10 sample rows — a preview, not the complete dataset.
| quarter_end | year_quarter | county_fips | county_name | state_code | state_name | country | country_code | business_all | business_ch7 | business_ch11 | business_ch13 | business_other | business_yoy | business_yoy_pct | ch11_share | row_hash |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2025-03-31 | 2025-Q1 | 01001 | AUTAUGA | AL | Alabama | United States | USA | 3 | 1 | 1 | 1 | 0 | — | — | 0.333 | ffd9161ed129f176 |
| 2025-06-30 | 2025-Q2 | 01001 | AUTAUGA | AL | Alabama | United States | USA | 3 | 1 | 1 | 1 | 0 | — | — | 0.333 | 7e8da43794c2910f |
| 2025-09-30 | 2025-Q3 | 01001 | AUTAUGA | AL | Alabama | United States | USA | 3 | 1 | 1 | 1 | 0 | — | — | 0.333 | 6b1fe086e14f76b3 |
| 2025-12-31 | 2025-Q4 | 01001 | AUTAUGA | AL | Alabama | United States | USA | 2 | 1 | 0 | 1 | 0 | — | — | 0 | 91dd30434ebce206 |
| 2026-03-31 | 2026-Q1 | 01001 | AUTAUGA | AL | Alabama | United States | USA | 2 | 2 | 0 | 0 | 0 | -1 | -33.333 | 0 | e22c6185adef6e15 |
| 2026-06-30 | 2026-Q2 | 01001 | AUTAUGA | AL | Alabama | United States | USA | 1 | 1 | 0 | 0 | 0 | -2 | -66.667 | 0 | ad2e917330fe4ab4 |
| 2025-03-31 | 2025-Q1 | 01003 | BALDWIN | AL | Alabama | United States | USA | 16 | 10 | 5 | 1 | 0 | — | — | 0.313 | 7b0e6b1ac3cedb32 |
| 2025-06-30 | 2025-Q2 | 01003 | BALDWIN | AL | Alabama | United States | USA | 15 | 8 | 6 | 1 | 0 | — | — | 0.4 | d891c348392c25e2 |
| 2025-09-30 | 2025-Q3 | 01003 | BALDWIN | AL | Alabama | United States | USA | 14 | 5 | 8 | 1 | 0 | — | — | 0.571 | fa638d03ff7da05b |
| 2025-12-31 | 2025-Q4 | 01003 | BALDWIN | AL | Alabama | United States | USA | 13 | 3 | 9 | 1 | 0 | — | — | 0.692 | 6595bd666c6d2dd5 |
Profiled Oct 1, 2026 from snapshot 20261001T232343Z-cc7a7fee63d4
Measured- Completeness
- 89%
- Rows
- 18,714
- Columns
- 17
- Columns with gaps
- 3
| Column | Missing | Distinct | Range | Distribution |
|---|---|---|---|---|
| quarter_enddate | 0% | 6 | Mar 31, 2025 → Jun 30, 2026 | — |
| year_quartervarchar | 0% | 6 | — |
|
| county_fipsvarchar | 0% | 2,816 | — |
|
| county_namevarchar | 0% | 2,089 | — |
|
| state_codevarchar | 0% | 64 | — |
|
| state_namevarchar | 0% | 65 | — |
|
| countryvarchar | 0% | 1 | — |
|
| country_codevarchar | 0% | 1 | — |
|
| business_allbigint | 0% | 267 | 0 → 26,941median 1 | 185 outside 1st–99th percentile |
| business_ch7bigint | 0% | 164 | 0 → 15,298median 0 | 183 outside 1st–99th percentile |
| business_ch11bigint | 0% | 155 | 0 → 9,766median 0 | 187 outside 1st–99th percentile |
| business_ch13bigint | 0% | 36 | 0 → 1,443median 0 | 171 outside 1st–99th percentile |
| business_otherbigint | 0% | 20 | 0 → 540median 0 | 141 outside 1st–99th percentile |
| business_yoybigint | 67.1% | 102 | -108 → 3,898median 0 | 120 outside 1st–99th percentile |
| business_yoy_pctdouble | 80.2% | 546 | -100 → 1,588median 0 | 33 outside 1st–99th percentile |
| ch11_sharedouble | 38.9% | 732 | 0 → 1median 0.1071 | |
| row_hashvarchar | 0% | 17,969 | — |
|
- Current
20261001T232343Z-cc7a7fee63d4 · sha256 cc7a7fee63d4…
18,714 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/uscourts_bankruptcy_intel/us_county_business_bankruptcy_quarterly" | jq '{title, rows, columns_count, license}'import requests
ds = requests.get("https://datazimuts.com/v1/datasets/uscourts_bankruptcy_intel/us_county_business_bankruptcy_quarterly").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/uscourts_bankruptcy_intel/us_county_business_bankruptcy_quarterly
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 20261001T232343Z-cc7a7fee63d4 and its content hash, so readers get exactly the data you used.
US County Business-Bankruptcy Intelligence (uscourts.gov, keyless). (2026). US county business-bankruptcy filings, quarterly [Data set, snapshot 20261001T232343Z-cc7a7fee63d4, sha256 cc7a7fee63d4]. Datazimuts. Retrieved 2026-10-02, from https://datazimuts.com/en/datasets/uscourts_bankruptcy_intel/us_county_business_bankruptcy_quarterly?snapshot=20261001T232343Z-cc7a7fee63d4
@misc{dz_uscourts_bankruptcy_intel_us_county_busi_cc7a7fee,
title = {{US county business-bankruptcy filings, quarterly}},
author = {{US County Business-Bankruptcy Intelligence (uscourts.gov, keyless)}},
year = {2026},
publisher = {Datazimuts},
howpublished = {\url{https://datazimuts.com/en/datasets/uscourts_bankruptcy_intel/us_county_business_bankruptcy_quarterly?snapshot=20261001T232343Z-cc7a7fee63d4}},
note = {Snapshot 20261001T232343Z-cc7a7fee63d4, sha256 cc7a7fee63d4419d4051f9911349d945a13cec3f9c8437452a1db9ca8a46045b; accessed 2026-10-02}
}Embed a table or a chart
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