US county income-migration intelligence (IRS SOI, annual)

Usage commercial OKÀ jour

Le jeu complet n’est pas encore publié — revenez après la prochaine actualisation.Télécharger l'exemple CSV Télécharger l'exemple JSONLignes d’exemple seulement (jusqu’à 20) — pas le jeu de données complet.

Annual US county income-migration panel, 2018-2019 onward: IRS Statistics of Income county-to-county migration files (keyless), reduced to verified per-county totals with fail-loud accounting identities. Net AGI flow (inflow minus outflow, $1,000s), mean arriving vs departing household income and the arrival premium, migration turnover, net income per resident return, a documented 0-100 income-migration heat score with tiers, and a methodology-break flag on the 2022-2023 enhanced-matching vintage. One row per county x tax-year pair (~14k rows, 5 vintages); suppressed micro-counties are dropped and counted, never imputed. Sibling dataset `us_county_migration_annual` covers the 2022-2023 vintage only; this panel spans five vintages (2018-2019 through 2022-2023) with additional intelligence: the heat score, tiers, turnover, and the methodology-break flag. Who joins this: online shops join county_fips + year to test whether net income migration leads local demand; subscription businesses use the tier and arrival premium as geo features for churn/expansion models; sales teams weight territories by the heat score.

Les titres et les descriptions proviennent des sources de données, en anglais.

Source: US county income migration (IRS Statistics of Income, keyless)
Lignes: 13 631
Colonnes: 28
Cadence de la source: Annuelle
Dernière actualisation: 1 oct. 2026
Thème: demographics

Colonne	Type	Description
year_pair	string	Tax-year pair of the migration flow, 'YYYY-YYYY' (filing year 2 minus filing year 1); vintage join key. (unit: year range)
filing_year	integer	Second tax year of the pair (the year the returns were filed); the vintage's reference year. (unit: year)
county_fips	string	5-digit county FIPS code (2-digit state + 3-digit county); geographic join key. Primary key with year_pair. (unit: FIPS)
county_name	string	County name as published by SOI (clean pair-row name where available). (unit: string)
state_abbr	string	USPS state abbreviation of the county. (unit: string)
state_fips	string	2-digit state FIPS code. (unit: FIPS)
country	string	Country name (shared normalization layer). (unit: string)
country_code	string	ISO 3166-1 alpha-3 country code (USA). (unit: string)
in_returns	integer	Tax returns filed by households that moved INTO the county that year (SOI 'Total Migration-US and Foreign' inflow, verified by accounting identities). (unit: returns)
in_exemptions	integer	Personal exemptions claimed on in-migrant returns (~individuals who moved in). (unit: exemptions)
in_agi_k	integer	Total adjusted gross income of in-migrant households, in thousands of USD. (unit: USD 1,000s)
out_returns	integer	Tax returns filed by households that moved OUT of the county that year (verified outflow total). (unit: returns)
out_exemptions	integer	Personal exemptions claimed on out-migrant returns (~individuals who moved out). (unit: exemptions)
out_agi_k	integer	Total adjusted gross income of out-migrant households, in thousands of USD. (unit: USD 1,000s)
net_returns	integer	in_returns minus out_returns; positive = net household inflow. (unit: returns)
net_exemptions	integer	in_exemptions minus out_exemptions; positive = net individual inflow. (unit: exemptions)
net_agi_k	integer	Net AGI flow attributable to migration (in_agi_k minus out_agi_k), in thousands of USD; positive = the county gained purchasing power through migration. (unit: USD 1,000s)
avg_agi_per_return_in_usd	float	Mean AGI of arriving households = 1000 * in_agi_k / in_returns. Null when in_returns is 0. (unit: USD)
avg_agi_per_return_out_usd	float	Mean AGI of departing households = 1000 * out_agi_k / out_returns. Null when out_returns is 0. (unit: USD)
agi_arrival_premium_usd	float	avg_agi_per_return_in_usd minus avg_agi_per_return_out_usd; positive = arrivals are richer than leavers ('brain gain'). Null when either side is null. (unit: USD)
nonmigrant_returns	integer	Tax returns filed by non-migrating households in the county (the resident tax base; turnover denominator). (unit: returns)
migration_turnover	float	(in_returns + out_returns) / (nonmigrant_returns + in_returns + out_returns): share of the county's tax-return population that moved in or out that year. (unit: fraction 0-1)
net_agi_per_resident_return_usd	float	1000 * net_agi_k / nonmigrant_returns: the migration income flow scaled by the resident tax base. (unit: USD)
income_migration_heat_score	float	0-100 = 100 * Phi(z), Phi = standard normal CDF, z the robust within-vintage z-score of net_agi_per_resident_return_usd (median/MAD). 50 = neutral, ~84 = one robust deviation of income inflow. (unit: score 0-100)
migration_income_tier	string	Heat-score bands: strong_gain [80,100], gain [60,80), neutral [40,60), loss [20,40), strong_loss [0,20). (unit: string)
methodology_break	integer	1 for the 2022-2023 vintage (SOI's enhanced return-matching process — a new series, not directly comparable to earlier vintages), else 0. (unit: 0/1)
source_url	string	The two SOI CSV URLs behind the vintage's rows. (unit: URL)
row_hash	string	Deterministic 16-hex sha256 of year_pair + county_fips + in/out returns + net_agi_k (idempotency key). (unit: string)

10 premières lignes d’exemple — un aperçu, pas le jeu de données complet.

year_pair	filing_year	county_fips	county_name	state_abbr	state_fips	country	country_code	in_returns	in_exemptions	in_agi_k	out_returns	out_exemptions	out_agi_k	net_returns	net_exemptions	net_agi_k	avg_agi_per_return_in_usd	avg_agi_per_return_out_usd	agi_arrival_premium_usd	nonmigrant_returns	migration_turnover	net_agi_per_resident_return_usd	income_migration_heat_score	migration_income_tier	source_url	row_hash
2018-2019	2 019	01001	Autauga County	AL	01	United States	USA	1 917	4 307	104 525	1 758	3 960	95 832	159	347	8 693	54 525,3	54 511,945	13,355	18 240	0,168	476,59	72,916	gain	https://www.irs.gov/pub/irs-soi/countyinflow1819.csv + https://www.irs.gov/pub/irs-soi/countyoutflow1819.csv	10b4ef4325031b0c
2018-2019	2 019	01101	Montgomery County	AL	01	United States	USA	4 619	9 395	225 793	5 361	10 931	314 298	-742	-1 536	-88 505	48 883,525	58 626,749	-9 743,224	74 199	0,119	-1 192,806	7,037	strong_loss	https://www.irs.gov/pub/irs-soi/countyinflow1819.csv + https://www.irs.gov/pub/irs-soi/countyoutflow1819.csv	dfe539dcfe2907f6
2018-2019	2 019	01103	Morgan County	AL	01	United States	USA	2 377	4 856	117 540	2 305	4 579	107 664	72	277	9 876	49 448,885	46 708,894	2 739,991	40 630	0,103	243,072	62,508	gain	https://www.irs.gov/pub/irs-soi/countyinflow1819.csv + https://www.irs.gov/pub/irs-soi/countyoutflow1819.csv	7f402ed7e98e8470
2018-2019	2 019	01107	Pickens County	AL	01	United States	USA	243	486	8 984	299	626	11 540	-56	-140	-2 556	36 971,193	38 595,318	-1 624,124	5 806	0,085	-440,234	29,672	loss	https://www.irs.gov/pub/irs-soi/countyinflow1819.csv + https://www.irs.gov/pub/irs-soi/countyoutflow1819.csv	9eff2a7cce60a420
2018-2019	2 019	01109	Pike County	AL	01	United States	USA	577	1 091	21 720	713	1 384	28 167	-136	-293	-6 447	37 642,981	39 504,909	-1 861,928	9 563	0,119	-674,161	20,446	loss	https://www.irs.gov/pub/irs-soi/countyinflow1819.csv + https://www.irs.gov/pub/irs-soi/countyoutflow1819.csv	db87993fefe3a3fa
2018-2019	2 019	01011	Bullock County	AL	01	United States	USA	134	293	4 292	173	355	4 923	-39	-62	-631	32 029,851	28 456,647	3 573,203	2 964	0,094	-212,888	40,123	neutral	https://www.irs.gov/pub/irs-soi/countyinflow1819.csv + https://www.irs.gov/pub/irs-soi/countyoutflow1819.csv	a385b3bd9ed15feb
2018-2019	2 019	01111	Randolph County	AL	01	United States	USA	401	834	19 311	395	779	19 959	6	55	-648	48 157,107	50 529,114	-2 372,007	7 068	0,101	-91,681	46,061	neutral	https://www.irs.gov/pub/irs-soi/countyinflow1819.csv + https://www.irs.gov/pub/irs-soi/countyoutflow1819.csv	1271722eb5588b28
2018-2019	2 019	01113	Russell County	AL	01	United States	USA	2 423	5 398	93 416	2 336	5 249	104 668	87	149	-11 252	38 553,859	44 806,507	-6 252,648	16 778	0,221	-670,64	20,571	loss	https://www.irs.gov/pub/irs-soi/countyinflow1819.csv + https://www.irs.gov/pub/irs-soi/countyoutflow1819.csv	048109f2997690e9
2018-2019	2 019	01115	St. Clair County	AL	01	United States	USA	2 364	4 752	148 717	1 983	3 955	113 744	381	797	34 973	62 909,052	57 359,556	5 549,496	28 672	0,132	1 219,761	93,794	strong_gain	https://www.irs.gov/pub/irs-soi/countyinflow1819.csv + https://www.irs.gov/pub/irs-soi/countyoutflow1819.csv	525974bf077da4b1
2018-2019	2 019	01117	Shelby County	AL	01	United States	USA	6 532	12 688	451 012	5 811	10 896	390 813	721	1 792	60 199	69 046,54	67 254,001	1 792,539	72 391	0,146	831,581	85,389	strong_gain	https://www.irs.gov/pub/irs-soi/countyinflow1819.csv + https://www.irs.gov/pub/irs-soi/countyoutflow1819.csv	85fb8fade8210811

Profilé le 1 oct. 2026 à partir de l’instantané 20261001T015444Z-66ec7dc139c4

Mesuré

Complétude: 100 %
Lignes: 13 631
Colonnes: 28
Colonnes incomplètes: 0

Colonne	Distinctes	Plage	Distribution
year_pairvarchar	5	—	2022-20232 747 2020-20212 741 2021-20222 740
filing_yearbigint	5	2 019 → 2 023médiane 2 021
county_fipsvarchar	2 715	—	010015 010035 010055
county_namevarchar	1 496	—	Washington County140 Jefferson County125 Franklin County113
state_abbrvarchar	55	—	TX815 GA714 VA649
state_fipsvarchar	49	—	48815 13714 51649
countryvarchar	1	—	United States13 631
country_codevarchar	1	—	USA13 631
in_returnsbigint	5 338	43 → 124 328médiane 816	273 hors du 1er–99e centile
in_exemptionsbigint	5 875	56 → 182 748médiane 1 534	271 hors du 1er–99e centile
in_agi_kbigint	13 966	1 386 → 14 786 315médiane 44 127	274 hors du 1er–99e centile
out_returnsbigint	4 501	43 → 188 686médiane 775	273 hors du 1er–99e centile
out_exemptionsbigint	5 807	66 → 320 983médiane 1 415	268 hors du 1er–99e centile
out_agi_kbigint	11 474	1 466 → 24 550 778médiane 38 302	274 hors du 1er–99e centile
net_returnsbigint	2 463	-70 554 → 21 934médiane 18	274 hors du 1er–99e centile
net_exemptionsbigint	3 654	-145 543 → 40 250médiane 65	274 hors du 1er–99e centile
net_agi_kbigint	12 746	-16 473 227 → 7 035 958médiane 1 675	274 hors du 1er–99e centile
avg_agi_per_return_in_usddouble	13 684	13 956 → 771 669médiane 52 599	274 hors du 1er–99e centile
avg_agi_per_return_out_usddouble	12 861	14 837 → 341 681médiane 50 156	274 hors du 1er–99e centile
agi_arrival_premium_usddouble	11 308	-239 501 → 560 820médiane 2 057	274 hors du 1er–99e centile
nonmigrant_returnsbigint	8 412	346 → 3 944 880médiane 11 507	274 hors du 1er–99e centile
migration_turnoverdouble	14 253	0,0486 → 0,5353médiane 0,1229	274 hors du 1er–99e centile
net_agi_per_resident_return_usddouble	16 872	-25 985 → 67 100médiane 218,9	274 hors du 1er–99e centile
income_migration_heat_scoredouble	12 318	0 → 100médiane 50	137 hors du 1er–99e centile
migration_income_tiervarchar	5	—	strong_gain3 541 loss3 216 neutral2 711
methodology_breakbigint	2	0 → 1médiane 0
source_urlvarchar	5	—	https://www.irs.gov/pub/irs-soi/countyinflow2223.csv + https://www.irs.gov/pub/irs-soi/countyoutflow2223.csv2 747 https://www.irs.gov/pub/irs-soi/countyinflow2021.csv + https://www.irs.gov/pub/irs-soi/countyoutflow2021.csv2 741 https://www.irs.gov/pub/irs-soi/countyinflow2122.csv + https://www.irs.gov/pub/irs-soi/countyoutflow2122.csv2 740
row_hashvarchar	12 950	—	00013cd87baac6e71 00064d9023564ca81 000eb724013c51301

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/irs_soi_county_income_migration_intel/us_county_income_migration_annual" | jq '{title, rows, columns_count, license}'

Python

import requests

ds = requests.get("https://datazimuts.com/v1/datasets/irs_soi_county_income_migration_intel/us_county_income_migration_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/irs_soi_county_income_migration_intel/us_county_income_migration_annual

Astuce : récupérez /llms.txt pour le catalogue complet lisible par machine.

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Épinglé à l’instantané 20261001T015444Z-66ec7dc139c4 et à son empreinte, pour que vos lecteurs obtiennent exactement les données utilisées.

APA

US county income migration (IRS Statistics of Income, keyless). (2026). US county income-migration intelligence (IRS SOI, annual) [Data set, snapshot 20261001T015444Z-66ec7dc139c4, sha256 66ec7dc139c4]. Datazimuts. Retrieved 2026-10-01, from https://datazimuts.com/fr/datasets/irs_soi_county_income_migration_intel/us_county_income_migration_annual?snapshot=20261001T015444Z-66ec7dc139c4

BibTeX

@misc{dz_irs_soi_county_income_migration_intel_us_66ec7dc1,
  title        = {{US county income-migration intelligence (IRS SOI, annual)}},
  author       = {{US county income migration (IRS Statistics of Income, keyless)}},
  year         = {2026},
  publisher    = {Datazimuts},
  howpublished = {\url{https://datazimuts.com/fr/datasets/irs_soi_county_income_migration_intel/us_county_income_migration_annual?snapshot=20261001T015444Z-66ec7dc139c4}},
  note         = {Snapshot 20261001T015444Z-66ec7dc139c4, sha256 66ec7dc139c48837d6c457c2bec1f677e22c0045d7acbfd0dbe92ba220cb134e; accessed 2026-10-01}
}

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<iframe src="https://datazimuts.com/embed/chart?dataset=irs_soi_county_income_migration_intel%2Fus_county_income_migration_annual&lang=fr&theme=auto&snapshot=20261001T015444Z-66ec7dc139c4&x=year_pair&y=filing_year&agg=avg" title="US county income-migration intelligence (IRS SOI, annual)" width="100%" height="380" style="border:0" loading="lazy"></iframe>

US county income-migration intelligence (IRS SOI, annual)

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