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

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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.

Source: US county income migration (IRS Statistics of Income, keyless)
Rows: 13,631
Columns: 28
Source cadence: Yearly
Last refreshed: Oct 1, 2026
Theme: demographics

Column	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)

First 10 sample rows — a preview, not the complete dataset.

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

Profiled Oct 1, 2026 from snapshot 20261001T015444Z-66ec7dc139c4

Measured

Completeness: 100%
Rows: 13,631
Columns: 28
Columns with gaps: 0

Column	Missing	Distinct	Range	Distribution
year_pairvarchar	0%	5	—	2022-20232,747 2020-20212,741 2021-20222,740
filing_yearbigint	0%	5	2,019 → 2,023median 2,021
county_fipsvarchar	0%	2,715	—	010015 010035 010055
county_namevarchar	0%	1,496	—	Washington County140 Jefferson County125 Franklin County113
state_abbrvarchar	0%	55	—	TX815 GA714 VA649
state_fipsvarchar	0%	49	—	48815 13714 51649
countryvarchar	0%	1	—	United States13,631
country_codevarchar	0%	1	—	USA13,631
in_returnsbigint	0%	5,338	43 → 124,328median 816	273 outside 1st–99th percentile
in_exemptionsbigint	0%	5,875	56 → 182,748median 1,534	271 outside 1st–99th percentile
in_agi_kbigint	0%	13,966	1,386 → 14,786,315median 44,127	274 outside 1st–99th percentile
out_returnsbigint	0%	4,501	43 → 188,686median 775	273 outside 1st–99th percentile
out_exemptionsbigint	0%	5,807	66 → 320,983median 1,415	268 outside 1st–99th percentile
out_agi_kbigint	0%	11,474	1,466 → 24,550,778median 38,302	274 outside 1st–99th percentile
net_returnsbigint	0%	2,463	-70,554 → 21,934median 18	274 outside 1st–99th percentile
net_exemptionsbigint	0%	3,654	-145,543 → 40,250median 65	274 outside 1st–99th percentile
net_agi_kbigint	0%	12,746	-16,473,227 → 7,035,958median 1,675	274 outside 1st–99th percentile
avg_agi_per_return_in_usddouble	0%	13,684	13,956 → 771,669median 52,599	274 outside 1st–99th percentile
avg_agi_per_return_out_usddouble	0%	12,861	14,837 → 341,681median 50,156	274 outside 1st–99th percentile
agi_arrival_premium_usddouble	0%	11,308	-239,501 → 560,820median 2,057	274 outside 1st–99th percentile
nonmigrant_returnsbigint	0%	8,412	346 → 3,944,880median 11,507	274 outside 1st–99th percentile
migration_turnoverdouble	0%	14,253	0.0486 → 0.5353median 0.1229	274 outside 1st–99th percentile
net_agi_per_resident_return_usddouble	0%	16,872	-25,985 → 67,100median 218.9	274 outside 1st–99th percentile
income_migration_heat_scoredouble	0%	12,318	0 → 100median 50	137 outside 1st–99th percentile
migration_income_tiervarchar	0%	5	—	strong_gain3,541 loss3,216 neutral2,711
methodology_breakbigint	0%	2	0 → 1median 0
source_urlvarchar	0%	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	0%	12,950	—	00013cd87baac6e71 00064d9023564ca81 000eb724013c51301

Point any LLM at the metadata endpoint — the documentation above is machine-readable too (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)

API endpoint: https://datazimuts.com/v1/datasets/irs_soi_county_income_migration_intel/us_county_income_migration_annual

Tip: fetch /llms.txt for the full machine-readable catalog.

Cite this snapshot

Pinned to snapshot 20261001T015444Z-66ec7dc139c4 and its content hash, so readers get exactly the data you used.

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/en/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/en/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=en&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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