US county economic momentum intelligence (annual)
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Interroger dans l’atelierLe jeu complet n’est pas encore publié — revenez après la prochaine actualisation.Télécharger l'exemple CSVTélécharger l'exemple JSONLignes d’exemple seulement (jusqu’à 20) — pas le jeu de données complet.
County x year panel of economic momentum from BEA GDP by County (keyless bulk-download zips, full annual history 2001 -> latest, 3,127 counties). Real levels in thousands of chained 2017 dollars with YoY growth, 5y/10y CAGRs, and growth spreads vs the county's state and the nation in percentage points. Percentile-of-own-history growth and level scores (trailing 20 years) feed a documented 0-100 county-momentum index with per-year ranks and g1-g4 tiers. Dominant industry, current-dollar share, and industry HHI concentration per county-year (disclosed industries only — BEA suppresses values to avoid disclosure; suppressed rows are flagged). Surge, cooling, contraction, back-to-back-contraction, record-high, and preliminary flags mark regime years; the state and US national backdrop rides on every row.
Les titres et les descriptions proviennent des sources de données, en anglais.
- Lignes
- 74 702
- Colonnes
- 37
- Cadence de la source
- Annuelle
- Dernière actualisation
- 30 sept. 2026
- Thème
- economy
| Colonne | Type | Description |
|---|---|---|
| row_hash | string | Deterministic 16-hex sha256 over as_of, county_fips, year, real_gdp_k, county_momentum_index; identical input produces an identical hash. |
| as_of | date | Snapshot anchor: the latest year present in both BEA vintages (YYYY-01-01). |
| county_fips | string | 5-digit county FIPS join key (state FIPS + county code). |
| county_name | string | County name as published by BEA (GeoName), with the '*' footnote marker on newly delineated Alaska county equivalents stripped. |
| state_fips | string | 2-digit state FIPS. |
| state_code | string | USPS state code; gated against the county GeoName suffix. |
| state_name | string | State name. |
| country_code | string | ISO alpha-3 join key; constant 'USA'. |
| year | integer | Panel year. |
| year_start | date | Year start date (YYYY-01-01) — the ISO date join key. |
| real_gdp_k | float | Real GDP, not seasonally adjusted (annual), from the CAGDP9 vintage. (unit: thousands of chained 2017 dollars/year) |
| nominal_gdp_k | float | GDP in current dollars, not seasonally adjusted (annual), from the CAGDP2 vintage. (unit: thousands of current dollars/year) |
| gdp_yoy | float | Year-on-year change of real GDP. (unit: ratio) |
| cagr_5y | float | 5-year compound annual growth rate of real GDP: (level / level.shift(5))**(1/5) - 1. (unit: ratio) |
| cagr_10y | float | 10-year compound annual growth rate of real GDP. (unit: ratio) |
| growth_vs_state_pp | float | County YoY growth minus the county's state YoY growth, in percentage points. (unit: pp) |
| growth_vs_us_pp | float | County YoY growth minus US national YoY growth, in percentage points. (unit: pp) |
| growth_score | float | Percentile of the current YoY within the county's own trailing 20 years of YoY values (100*(r-1)/(n-1), average ranks; null with <8 window observations or zero variance). (unit: 0-100) |
| level_score | float | Percentile of the current real-GDP level within the county's own trailing 20 years of levels (same documented formula). (unit: 0-100) |
| county_momentum_index | float | Documented 0-100 county-momentum index: 0.6 * growth_score + 0.4 * level_score; null when either leg is null. (unit: 0-100) |
| momentum_rank | integer | Per-year rank by county_momentum_index (1 = strongest; competition ranking, ties broken by county_fips asc). |
| momentum_tier | string | g4_strong (>=75) / g3_healthy (>=50) / g2_soft (>=25) / g1_weak (<25). |
| surge_flag | boolean | True when county_momentum_index >= 75. |
| cooling_flag | boolean | True when county_momentum_index <= 25. |
| contraction_flag | boolean | True when real GDP contracted year-on-year (gdp_yoy < 0). |
| recession_flag | boolean | True on back-to-back annual contractions (contraction this year and last). |
| record_high_flag | boolean | True when the real level exceeds every prior year (>=4 prior observations). |
| preliminary_flag | boolean | True for the as_of year — BEA's first estimate, revised in later releases. |
| top_industry | string | Largest of the 15 top-level industries by current-dollar GDP in the county-year. |
| top_industry_share_pct | float | Current-dollar share of top_industry in the county-year total. (unit: percent) |
| industry_hhi | float | Industry concentration: sum of squared current-dollar industry shares x 10000 (0 = perfectly diversified, 10000 = single industry). Shares are over disclosed industries only, so on suppressed rows this is a lower bound on true concentration. (unit: 0-10000) |
| industry_suppressed_flag | boolean | True when BEA suppressed (D) at least one top-level industry value for the county-year: top_industry / shares / HHI then cover disclosed industries only, with shares expressed against the published county total. |
| state_real_gdp_k | float | Year's state real GDP (context column, replicated per row). (unit: thousands of chained 2017 dollars/year) |
| state_gdp_yoy | float | Year's state real-GDP YoY. (unit: ratio) |
| us_real_gdp_k | float | Year's US national real GDP (context column, replicated per row). (unit: thousands of chained 2017 dollars/year) |
| us_gdp_yoy | float | Year's US national real-GDP YoY. (unit: ratio) |
| provenance_url | string | Exact BEA bulk-download zip behind the row. |
10 premières lignes d’exemple — un aperçu, pas le jeu de données complet.
| row_hash | as_of | county_fips | county_name | state_fips | state_code | state_name | country_code | year | year_start | real_gdp_k | nominal_gdp_k | gdp_yoy | cagr_5y | cagr_10y | growth_vs_state_pp | growth_vs_us_pp | growth_score | level_score | county_momentum_index | momentum_rank | momentum_tier | surge_flag | cooling_flag | contraction_flag | recession_flag | record_high_flag | preliminary_flag | top_industry | top_industry_share_pct | industry_hhi | industry_suppressed_flag | state_real_gdp_k | state_gdp_yoy | us_real_gdp_k | us_gdp_yoy | provenance_url |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| d06bccfee10495a7 | 2024-01-01T00:00:00 | 01001 | Autauga | 01 | AL | Alabama | USA | 2 001 | 2001-01-01T00:00:00 | 1 041 239 | 760 973 | — | — | — | — | — | — | — | — | — | — | — | — | false | false | false | false | Manufacturing | 24,78 | 1 395,7 | false | 168 448 296 | — | 14 230 726 000 | — | https://apps.bea.gov/regional/zip/CAGDP9.zip |
| ae43cabb32e902c1 | 2024-01-01T00:00:00 | 01001 | Autauga | 01 | AL | Alabama | USA | 2 002 | 2002-01-01T00:00:00 | 1 080 135 | 800 045 | 0,037 | — | — | 1,372 | 2,035 | — | — | — | — | — | — | — | false | false | false | false | Manufacturing | 23,34 | 1 363,4 | false | 172 430 379 | 0,024 | 14 472 712 000 | 0,017 | https://apps.bea.gov/regional/zip/CAGDP9.zip |
| c33a4895920316b5 | 2024-01-01T00:00:00 | 01001 | Autauga | 01 | AL | Alabama | USA | 2 003 | 2003-01-01T00:00:00 | 1 111 465 | 834 208 | 0,029 | — | — | -0,353 | 0,105 | — | — | — | — | — | — | — | false | false | false | false | Finance, insurance, real estate, rental, and leasing | 20,54 | 1 239,1 | false | 178 039 962 | 0,033 | 14 877 312 000 | 0,028 | https://apps.bea.gov/regional/zip/CAGDP9.zip |
| 370126bcc3652730 | 2024-01-01T00:00:00 | 01001 | Autauga | 01 | AL | Alabama | USA | 2 004 | 2004-01-01T00:00:00 | 1 283 522 | 984 461 | 0,155 | — | — | 8,811 | 11,632 | — | — | — | — | — | — | — | false | false | false | false | Finance, insurance, real estate, rental, and leasing | 20,03 | 1 251,2 | false | 189 913 745 | 0,067 | 15 449 757 000 | 0,038 | https://apps.bea.gov/regional/zip/CAGDP9.zip |
| 24f49e26107d3b33 | 2024-01-01T00:00:00 | 01001 | Autauga | 01 | AL | Alabama | USA | 2 005 | 2005-01-01T00:00:00 | 1 297 102 | 1 015 320 | 0,011 | — | — | -2,803 | -2,426 | — | — | — | — | — | — | — | false | false | true | false | Finance, insurance, real estate, rental, and leasing | 20,66 | 1 287,5 | false | 197 246 483 | 0,039 | 15 987 957 000 | 0,035 | https://apps.bea.gov/regional/zip/CAGDP9.zip |
| 202540f1fe376095 | 2024-01-01T00:00:00 | 01001 | Autauga | 01 | AL | Alabama | USA | 2 006 | 2006-01-01T00:00:00 | 1 384 119 | 1 124 089 | 0,067 | 0,059 | — | 5,351 | 3,924 | — | — | — | — | — | — | — | false | false | true | false | Manufacturing | 20,42 | 1 245,4 | false | 199 923 857 | 0,014 | 16 433 148 000 | 0,028 | https://apps.bea.gov/regional/zip/CAGDP9.zip |
| 9d7813e16aff8b3d | 2024-01-01T00:00:00 | 01001 | Autauga | 01 | AL | Alabama | USA | 2 007 | 2007-01-01T00:00:00 | 1 407 555 | 1 182 234 | 0,017 | 0,054 | — | 0,642 | -0,311 | — | — | — | — | — | — | — | false | false | true | false | Finance, insurance, real estate, rental, and leasing | 19,79 | 1 202,9 | false | 202 025 481 | 0,011 | 16 762 445 000 | 0,02 | https://apps.bea.gov/regional/zip/CAGDP9.zip |
| a89cb0d57e8d8bca | 2024-01-01T00:00:00 | 01001 | Autauga | 01 | AL | Alabama | USA | 2 008 | 2008-01-01T00:00:00 | 1 283 751 | 1 097 703 | -0,088 | 0,029 | — | -8,272 | -8,909 | — | 57,143 | — | — | — | — | — | true | false | false | false | Finance, insurance, real estate, rental, and leasing | 21,46 | 1 239,4 | false | 200 967 427 | -0,005 | 16 781 485 000 | 0,001 | https://apps.bea.gov/regional/zip/CAGDP9.zip |
| d40944bcf9e736dd | 2024-01-01T00:00:00 | 01001 | Autauga | 01 | AL | Alabama | USA | 2 009 | 2009-01-01T00:00:00 | 1 316 046 | 1 175 769 | 0,025 | 0,005 | — | 5,887 | 5,092 | 42,857 | 75 | 55,71 | 992 | g3_healthy | false | false | false | false | false | false | Finance, insurance, real estate, rental, and leasing | 19,31 | 1 255,8 | false | 194 192 061 | -0,034 | 16 349 110 000 | -0,026 | https://apps.bea.gov/regional/zip/CAGDP9.zip |
| c069f17e206783d4 | 2024-01-01T00:00:00 | 01001 | Autauga | 01 | AL | Alabama | USA | 2 010 | 2010-01-01T00:00:00 | 1 409 007 | 1 262 883 | 0,071 | 0,017 | — | 4,354 | 4,368 | 87,5 | 100 | 92,5 | 372 | g4_strong | true | false | false | false | true | false | Finance, insurance, real estate, rental, and leasing | 19,24 | 1 297,8 | false | 199 454 968 | 0,027 | 16 789 750 000 | 0,027 | https://apps.bea.gov/regional/zip/CAGDP9.zip |
Profilé le 1 oct. 2026 à partir de l’instantané 20260930T215314Z-5e054b2261ec
Mesuré- Complétude
- 91,6 %
- Lignes
- 74 702
- Colonnes
- 37
- Colonnes incomplètes
- 14
20012024
| Colonne | Manquant | Distinctes | Plage | Distribution |
|---|---|---|---|---|
| row_hashvarchar | 0 % | 92 804 | — |
|
| as_oftimestamp | 0 % | 1 | 1 janv. 2024 → 1 janv. 2024 | — |
| county_fipsvarchar | 0 % | 2 745 | — |
|
| county_namevarchar | 0 % | 2 216 | — |
|
| state_fipsvarchar | 0 % | 52 | — |
|
| state_codevarchar | 0 % | 55 | — |
|
| state_namevarchar | 0 % | 59 | — |
|
| country_codevarchar | 0 % | 1 | — |
|
| yearbigint | 0 % | 26 | 2 001 → 2 024médiane 2 013 | |
| year_starttimestamp | 0 % | 21 | 1 janv. 2001 → 1 janv. 2024 | — |
| real_gdp_kdouble | 0 % | 73 566 | 5 420 → 813 692 135médiane 932 938 | 1 496 hors du 1er–99e centile |
| nominal_gdp_kdouble | 0 % | 92 737 | 4 402 → 1 006 673 239médiane 885 828 | 1 496 hors du 1er–99e centile |
| gdp_yoydouble | 4,2 % | 70 657 | -0,8931 → 2,97médiane 0,0161 | 1 432 hors du 1er–99e centile |
| cagr_5ydouble | 20,9 % | 68 368 | -0,3111 → 0,8677médiane 0,012 | 1 184 hors du 1er–99e centile |
| cagr_10ydouble | 41,7 % | 45 809 | -0,184 → 0,4227médiane 0,0113 | 872 hors du 1er–99e centile |
| growth_vs_state_ppdouble | 4,2 % | 64 438 | -84,48 → 291,9médiane -0,4536 | 1 432 hors du 1er–99e centile |
| growth_vs_us_ppdouble | 4,2 % | 58 651 | -90,87 → 294,89médiane -0,6772 | 1 432 hors du 1er–99e centile |
| growth_scoredouble | 33,4 % | 116 | 0 → 100médiane 50 | |
| level_scoredouble | 29,2 % | 121 | 0 → 100médiane 84,21 | |
| county_momentum_indexdouble | 33,4 % | 1 979 | 0 → 100médiane 58,95 | |
| momentum_rankbigint | 33,4 % | 3 178 | 1 → 3 113médiane 1 555 | 988 hors du 1er–99e centile |
| momentum_tiervarchar | 33,4 % | 4 | — |
|
| surge_flagboolean | 33,4 % | 2 | — |
|
| cooling_flagboolean | 33,4 % | 2 | — |
|
| contraction_flagboolean | 0 % | 2 | — |
|
| recession_flagboolean | 0 % | 2 | — |
|
| record_high_flagboolean | 0 % | 2 | — |
|
| preliminary_flagboolean | 0 % | 2 | — |
|
| top_industryvarchar | 0 % | 16 | — |
|
| top_industry_share_pctdouble | 0 % | 5 402 | 0,03 → 99,89médiane 25,62 | 1 496 hors du 1er–99e centile |
| industry_hhidouble | 0 % | 21 870 | 0 → 9 977médiane 1 394 | 1 496 hors du 1er–99e centile |
| industry_suppressed_flagboolean | 0 % | 2 | — |
|
| state_real_gdp_kdouble | 0 % | 1 197 | 25 329 792 → 3 306 928 555médiane 302 025 663 | 1 433 hors du 1er–99e centile |
| state_gdp_yoydouble | 0,07 % | 1 173 | -0,6003 → 0,2316médiane 0,0205 | 1 646 hors du 1er–99e centile |
| us_real_gdp_kdouble | 0 % | 25 | 14 230 726 000 → 23 358 435 000médiane 17 812 167 000 | |
| us_gdp_yoydouble | 4,2 % | 24 | -0,0258 → 0,0615médiane 0,0252 | 6 227 hors du 1er–99e centile |
| provenance_urlvarchar | 0 % | 1 | — |
|
- Actuelle
20260930T215314Z-5e054b2261ec · sha256 5e054b2261ec…
74 702 lignes · premier instantané
Dirigez n’importe quel LLM vers le point d’accès des métadonnées — la documentation ci-dessus est aussi lisible par machine (JSON-LD + Croissant).
cURL
curl "https://datazimuts.com/v1/datasets/bea_county_gdp_intel/us_county_economic_momentum_annual" | jq '{title, rows, columns_count, license}'Python
import requests
ds = requests.get("https://datazimuts.com/v1/datasets/bea_county_gdp_intel/us_county_economic_momentum_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)Point d’accès API : https://datazimuts.com/v1/datasets/bea_county_gdp_intel/us_county_economic_momentum_annual
Astuce : récupérez /llms.txt pour le catalogue complet lisible par machine.
D’où viennent ces données et ce qui en a été fait. Le travail des autres apparaît sous forme de décomptes ; seuls les projets partagés sont nommés.
Citer cet instantané
Épinglé à l’instantané 20260930T215314Z-5e054b2261ec et à son empreinte, pour que vos lecteurs obtiennent exactement les données utilisées.
APA
US County Economic Momentum Intelligence. (2026). US county economic momentum intelligence (annual) [Data set, snapshot 20260930T215314Z-5e054b2261ec, sha256 5e054b2261ec]. Datazimuts. Retrieved 2026-10-01, from https://datazimuts.com/fr/datasets/bea_county_gdp_intel/us_county_economic_momentum_annual?snapshot=20260930T215314Z-5e054b2261ec
BibTeX
@misc{dz_bea_county_gdp_intel_us_county_economic__5e054b22,
title = {{US county economic momentum intelligence (annual)}},
author = {{US County Economic Momentum Intelligence}},
year = {2026},
publisher = {Datazimuts},
howpublished = {\url{https://datazimuts.com/fr/datasets/bea_county_gdp_intel/us_county_economic_momentum_annual?snapshot=20260930T215314Z-5e054b2261ec}},
note = {Snapshot 20260930T215314Z-5e054b2261ec, sha256 5e054b2261ec768f8fa68c4547138f9f627046731c2541646cda1dde18197b33; accessed 2026-10-01}
}Intégrer un tableau ou un graphique
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HTML
<iframe src="https://datazimuts.com/embed/chart?dataset=bea_county_gdp_intel%2Fus_county_economic_momentum_annual&lang=fr&theme=auto&snapshot=20260930T215314Z-5e054b2261ec&x=year&y=year&agg=avg" title="US county economic momentum intelligence (annual)" width="100%" height="380" style="border:0" loading="lazy"></iframe>
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