USDA ERS · DISASTER-HEAVY · MID · AL

Alabama farm subsidy data

Disaster-weighted ERS profile for FY2023; county NASS tables below are a separate 2022 Census population.

Total payments
$98M
Net farm income (2023)
$1.8B

Disaster share inside Alabama's $98M ERS total

Exclusive partition of this state's fiscal-year 2023 USDA ERS total (DISASTER-HEAVY). Conservation and disaster are published line items; the residual is commodity / ARC-PLC / MFP and other program families in the same extract.

Alabama: disaster aid dominates a mid ERS book

Alabama stamps DISASTER-HEAVY · MID on USDA ERS FY2023: disaster aid $54M of $98M total (#35 of 50 by total).

Crop-insurance loss ratio 271% ($108M indemnities on $40M premiums) sits beside the disaster line; read them together, not as substitutes. A ratio above 100% means claims exceeded premiums in this reporting period; it is not, by itself, a measure of a state’s agricultural risk.

County farm-count and sales tables below are the separate 2022 NASS Census population and do not sum to this ERS state total. Figures follow USDA Economic Research Service Farm Income and Wealth Statistics.

Latest release change: +35.2% · $98M FY2023 → $133M FY2024 (MID book; full year table reserved for heavier states).

Cash receipts by commodity in Alabama

Poultry $4.7B (59.0%)
Cattle $682M (8.6%)
Cotton $394M (4.9%)
Corn $249M (3.1%)
Soybeans $188M (2.4%)
Wheat $66M (0.8%)
Total cash receipts: $8.0B

Crop insurance beside Alabama's disaster stamp

Premiums Paid
$40M
Indemnities
$108M
Loss Ratio
271%

Loss ratio = indemnities ÷ premiums. A ratio above 100% means claims exceeded premiums in this reporting period; it is not, by itself, a measure of a state’s agricultural risk.

Alabama vs. every rankable state: what goes into crop insurance isn't what comes out

Each dot is a state that clears the $1M premiums floor, placed by what it pays IN (premiums, left to right) against what its indemnities return relative to that (loss ratio, bottom to top). Paying more into the program is not the same as getting more out of it, a state can sit in the small-payer / outsized-payout quadrant just as easily as the reverse.

Small payer, outsized payoutHeavy payer, heavy claimsLight footprintHeavy payer, net subsidizer$0M$206.8M$413.5M$620.3M$827.0M16.1%140.3%264.5%388.7%512.9%Premiums paid ($M) →← Loss ratio (indemnities ÷ premiums)Texas, Premiums paid ($M) →: $787.7M · ← Loss ratio (indemnities ÷ premiums): 421.3%Oklahoma, Premiums paid ($M) →: $149.3M · ← Loss ratio (indemnities ÷ premiums): 469.4%Kansas, Premiums paid ($M) →: $504.7M · ← Loss ratio (indemnities ÷ premiums): 486.3%Iowa, Premiums paid ($M) →: $701.7M · ← Loss ratio (indemnities ÷ premiums): 147.1%California, Premiums paid ($M) →: $363.6M · ← Loss ratio (indemnities ÷ premiums): 342.3%Nebraska, Premiums paid ($M) →: $447.4M · ← Loss ratio (indemnities ÷ premiums): 318.2%South Dakota, Premiums paid ($M) →: $410.7M · ← Loss ratio (indemnities ÷ premiums): 212.5%Arkansas, Premiums paid ($M) →: $86.3M · ← Loss ratio (indemnities ÷ premiums): 324.6%Minnesota, Premiums paid ($M) →: $445.7M · ← Loss ratio (indemnities ÷ premiums): 193.9%Missouri, Premiums paid ($M) →: $212.2M · ← Loss ratio (indemnities ÷ premiums): 200.2%Wisconsin, Premiums paid ($M) →: $163M · ← Loss ratio (indemnities ÷ premiums): 180.8%Illinois, Premiums paid ($M) →: $467.9M · ← Loss ratio (indemnities ÷ premiums): 54.7%North Dakota, Premiums paid ($M) →: $500M · ← Loss ratio (indemnities ÷ premiums): 156.2%Montana, Premiums paid ($M) →: $140.4M · ← Loss ratio (indemnities ÷ premiums): 221.6%Mississippi, Premiums paid ($M) →: $56.3M · ← Loss ratio (indemnities ÷ premiums): 374.1%Colorado, Premiums paid ($M) →: $149.1M · ← Loss ratio (indemnities ÷ premiums): 283.8%Louisiana, Premiums paid ($M) →: $60.8M · ← Loss ratio (indemnities ÷ premiums): 313.4%Ohio, Premiums paid ($M) →: $169.2M · ← Loss ratio (indemnities ÷ premiums): 51.4%Washington, Premiums paid ($M) →: $184.5M · ← Loss ratio (indemnities ÷ premiums): 341.8%Georgia, Premiums paid ($M) →: $108.8M · ← Loss ratio (indemnities ÷ premiums): 364.7%Oregon, Premiums paid ($M) →: $83.6M · ← Loss ratio (indemnities ÷ premiums): 257.3%Pennsylvania, Premiums paid ($M) →: $29.7M · ← Loss ratio (indemnities ÷ premiums): 218.7%Florida, Premiums paid ($M) →: $133.8M · ← Loss ratio (indemnities ÷ premiums): 432.8%New Mexico, Premiums paid ($M) →: $91.2M · ← Loss ratio (indemnities ÷ premiums): 271.5%New York, Premiums paid ($M) →: $39.9M · ← Loss ratio (indemnities ÷ premiums): 185.8%Kentucky, Premiums paid ($M) →: $84.4M · ← Loss ratio (indemnities ÷ premiums): 172.7%North Carolina, Premiums paid ($M) →: $147.9M · ← Loss ratio (indemnities ÷ premiums): 168%Michigan, Premiums paid ($M) →: $114.9M · ← Loss ratio (indemnities ÷ premiums): 120.5%Indiana, Premiums paid ($M) →: $261.4M · ← Loss ratio (indemnities ÷ premiums): 38.7%Tennessee, Premiums paid ($M) →: $48.3M · ← Loss ratio (indemnities ÷ premiums): 222.4%Idaho, Premiums paid ($M) →: $98.5M · ← Loss ratio (indemnities ÷ premiums): 200.8%Utah, Premiums paid ($M) →: $28.7M · ← Loss ratio (indemnities ÷ premiums): 128.7%Wyoming, Premiums paid ($M) →: $27.9M · ← Loss ratio (indemnities ÷ premiums): 119.1%Virginia, Premiums paid ($M) →: $38.2M · ← Loss ratio (indemnities ÷ premiums): 190.6%South Carolina, Premiums paid ($M) →: $49.4M · ← Loss ratio (indemnities ÷ premiums): 251.7%Arizona, Premiums paid ($M) →: $72.9M · ← Loss ratio (indemnities ÷ premiums): 237.1%Vermont, Premiums paid ($M) →: $2.2M · ← Loss ratio (indemnities ÷ premiums): 369.3%Maryland, Premiums paid ($M) →: $16.5M · ← Loss ratio (indemnities ÷ premiums): 133.2%Nevada, Premiums paid ($M) →: $63M · ← Loss ratio (indemnities ÷ premiums): 98.4%Hawaii, Premiums paid ($M) →: $1M · ← Loss ratio (indemnities ÷ premiums): 402.8%West Virginia, Premiums paid ($M) →: $2.1M · ← Loss ratio (indemnities ÷ premiums): 178.3%Maine, Premiums paid ($M) →: $5M · ← Loss ratio (indemnities ÷ premiums): 169.5%Massachusetts, Premiums paid ($M) →: $2.6M · ← Loss ratio (indemnities ÷ premiums): 486.5%New Jersey, Premiums paid ($M) →: $3.3M · ← Loss ratio (indemnities ÷ premiums): 490.3%Connecticut, Premiums paid ($M) →: $3.7M · ← Loss ratio (indemnities ÷ premiums): 481.9%Delaware, Premiums paid ($M) →: $5.6M · ← Loss ratio (indemnities ÷ premiums): 78%Alabama, Premiums paid ($M) →: $39.9M · ← Loss ratio (indemnities ÷ premiums): 271%
Alabama pays $40M in crop-insurance premiums (#34 of 47 rankable states) against a 271% loss ratio (#19 by claims relative to premiums): a small payer, outsized payout state, not simply "pays a lot" or "pays a little."

47-state rankable cohort, national medians at the crosshair

Source: USDA ERS Farm Income and Wealth Statistics As of 2026-05-15

Counties in Alabama (67)

County Farms
DE Kalb 1,744
Cullman 1,574
Marshall 1,324
Coffee 666
Pike 561
Blount 980
Lawrence 1,139
Dale 421
Geneva 681
Crenshaw 474
Butler 397
Franklin 747
Cherokee 567
Barbour 590
Jackson 1,233
Randolph 611
Covington 809
Marion 612
Etowah 725
Clay 434
Limestone 996
Saint Clair 585
Morgan 1,102
Pickens 397
Baldwin 853

Showing 1-25 of 67 counties, ranked by commodity sales.

Source: USDA Economic Research Service, Farm Income and Wealth Statistics (1995-2024) County data: USDA NASS 2022 Census of Agriculture

Income beside disaster stamp

Gross cash $8.9B · net cash $2.1B · net farm $1.8B · ARC $0M / PLC $0M

USDA ERS Farm Income · FY2023 · County: 2022 NASS Census

Nearest ERS payment peer (DISASTER-HEAVY · MID): Virginia · CONSERVATION-LED · How disaster and program payments stack · DE Kalb County NASS table

What to do with Alabama's numbers

Alabama ranks #35 of 50 states by total ERS farm payments. Three places to take that further:

  • See how Alabama compares against the 4 closest South states by payment volume. Compare states
  • Drill into DE Kalb County, Alabama's top county by commodity sales in the 2022 NASS Census. County detail
  • How disaster and program payments stack for the program-level context behind these totals. Learn more

State payment totals (USDA ERS) and county figures (2022 NASS Census of Agriculture) are separate populations and must not be summed together.

Data sourced from official public datasets. See our methodology for details.