USDA ERS · DISASTER-HEAVY · MID · NM

New Mexico 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
$165M
Net farm income (2023)
$1.5B

Disaster share inside New Mexico's $165M 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.

New Mexico: disaster aid dominates a mid ERS book

New Mexico stamps DISASTER-HEAVY · MID on USDA ERS FY2023: disaster aid $101M of $165M total (#24 of 50 by total).

Crop-insurance loss ratio 272% ($247M indemnities on $91M 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: +11.9% · $165M FY2023 → $185M FY2024 (MID book; full year table reserved for heavier states).

Cash receipts by commodity in New Mexico

Cattle $1.7B (43.0%)
Cotton $48M (1.2%)
Corn $37M (0.9%)
Wheat $7M (0.2%)
Total cash receipts: $4.0B

Crop insurance beside New Mexico's disaster stamp

Premiums Paid
$91M
Indemnities
$247M
Loss Ratio
272%

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.

New Mexico 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) →: $133.8M · ← Loss ratio (indemnities ÷ premiums): 432.8%New York, Premiums paid ($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) →: $5.6M · ← Loss ratio (indemnities ÷ premiums): 78%New Mexico, Premiums paid ($M) →: $91.2M · ← Loss ratio (indemnities ÷ premiums): 271.5%
New Mexico pays $91M in crop-insurance premiums (#23 of 47 rankable states) against a 272% loss ratio (#18 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 New Mexico (33)

County Farms
Curry 665
Chaves 485
Roosevelt 638
Dona Ana 1,990
Lea 411
Luna 213
San Juan 2,877
Eddy 346
Union 343
Colfax 269
Socorro 453
Quay 592
Torrance 577
Valencia 978
Hidalgo 152
Otero 467
Rio Arriba 1,285
Sierra 269
San Miguel 776
DE Baca 175
Santa FE 591
Catron 305
Lincoln 359
Bernalillo 964
Grant 334

Showing 1-25 of 33 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 $4.6B · net cash $1.5B · net farm $1.5B · ARC $1M / PLC $0M

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

Nearest ERS payment peer (DISASTER-HEAVY · MID): New York · COMMODITY-LED · How disaster and program payments stack · Curry County NASS table

What to do with New Mexico's numbers

New Mexico ranks #24 of 50 states by total ERS farm payments. Three places to take that further:

  • See how New Mexico compares against the 4 closest West states by payment volume. Compare states
  • Drill into Curry County, New Mexico'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.