USDA ERS · DISASTER-HEAVY · MID · FL

Florida farm subsidy data

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

By ·Data year 2023·USDA ERS → ·USDA NASS Census →

Total payments
$178M
Net farm income (2023)
$3.3B

Disaster share inside Florida's $178M 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.

Florida: disaster aid dominates a mid ERS book

Florida stamps DISASTER-HEAVY · MID on USDA ERS FY2023: disaster aid $137M of $178M total (#23 of 50 by total).

Crop-insurance loss ratio 433% ($579M indemnities on $134M 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: +16.7% · $178M FY2023 → $207M FY2024 (MID book; full year table reserved for heavier states).

Cash receipts by commodity in Florida

Cattle $775M (8.4%)
Poultry $283M (3.1%)
Cotton $78M (0.8%)
Corn $56M (0.6%)
Total cash receipts: $9.2B

Crop insurance beside Florida's disaster stamp

Premiums Paid
$134M
Indemnities
$579M
Loss Ratio
433%

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.

Florida 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) →: $29.7M · ← Loss ratio (indemnities ÷ premiums): 218.7%New Mexico, Premiums paid ($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) →: $38.2M · ← Loss ratio (indemnities ÷ premiums): 190.6%Alabama, Premiums paid ($M) →: $39.9M · ← Loss ratio (indemnities ÷ premiums): 271%South Carolina, Premiums paid ($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) →: $5.6M · ← Loss ratio (indemnities ÷ premiums): 78%Florida, Premiums paid ($M) →: $133.8M · ← Loss ratio (indemnities ÷ premiums): 432.8%
Florida pays $134M in crop-insurance premiums (#19 of 47 rankable states) against a 433% loss ratio (#6 by claims relative to premiums): a heavy 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 Florida (67)

County Farms
Martin 588
Jefferson 597
St. Lucie 404
Jackson 942
Osceola 353
Brevard 584
Sumter 1,117
Putnam 539
Charlotte 263
Santa Rosa 732
Columbia 867
Broward 658
Flagler 89
St. Johns 223
Hamilton 275
Gadsden 489
Sarasota 286
Escambia 515
Walton 695
Hernando 761
Holmes 629
Calhoun 198
Citrus 602
Bradford 418
Taylor 212

Showing 26-50 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 $11.2B · net cash $3.6B · net farm $3.3B · ARC $0M / PLC $0M

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

Nearest ERS payment peer (DISASTER-HEAVY · MID): New Mexico · DISASTER-HEAVY · How disaster and program payments stack · Palm Beach County NASS table

What to do with Florida's numbers

Florida ranks #23 of 50 states by total ERS farm payments. Three places to take that further:

  • See how Florida compares against the 4 closest South states by payment volume. Compare states
  • Drill into Palm Beach County, Florida'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.

Read our methodology - how this data is sourced, computed, and verified.

Data sourced from official public datasets. See our methodology for details.
Compiled from official public sources by the publisher.