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  • A New Way to See Agricultural Bankruptcy Trends

    A New Way to See Agricultural Bankruptcy Trends

    Agricultural financial distress can be easy to see but difficult to quantify. Chapter 12 bankruptcy, specifically designed for family farmers and fishermen, has traditionally been used as the sole measurement of that stress in the legal system.

    However, agricultural businesses who do not qualify for Chapter 12 may instead file under Chapter 11.  For example, many farm families rely on income from outside the farm to keep their operation afloat, potentially disqualifying them from Chapter 12 eligibility. Other families, given the high cost of agricultural inputs and equipment, exceed the amount of debt that is allowable in that chapter. In circumstances like these, filing for Chapter 11 allows the farm to continue operating while developing a plan to restructure and repay its debts.

    Until now, the number of farms filing under Chapter 11 has been unknown, and those additional indicators of financial stress unrecognized.  The National Agricultural Law Center, together with the National Association of State Departments of Agriculture, worked together to identify many of those operations.  The result is the Data on Economic and Bankruptcy Trends, or “DEBT” project.

    The DEBT project features an interactive map that allows users to explore ag related Chapter 11 & Chapter 12 bankruptcy filings between January 2021 and June 2026. Information can be filtered and viewed by bankruptcy chapter, year, and quarter, allowing users to examine where and when agricultural bankruptcy filings have occurred and identify trends over time. Users can select locations on the map to view individual cases and access additional information, including links to corresponding federal court records.  The page also includes access to the underlying dataset.

    It was completed in conjunction with SAS, an advanced analytics company that turns data into usable information. Using Public Access to Court Electronic Records (PACER), an online system providing access to federal court files and case dockets, SAS developed an automated process to cross-reference bankruptcy records with publicly available data from the USDA Farm Service Agency. When an entity appeared in both a bankruptcy filing and FSA program recipient list, it was an indicator that the entity was an agricultural operation. 

    It is not a perfect indicator.  Not all farmers facing significant financial stress file for bankruptcy, not all farm bankruptcies filed were tracked in this new set of data, and alternatives such as Chapter 7 and Chapter 13 are also available, but as of yet uncounted in the current DEBT dataset.  But the project and interactive map is a good first step to better recognizing the farm financial stress issue. 

     Through this project 1,401 agricultural bankruptcies were identified. The majority of those- 1,200- were filed under Chapter 12. However, 201 additional bankruptcies with an agricultural connection were filed under the requirements of Chapter 11.  In other words, agricultural bankruptcies over the past 5 years are at least 16% higher than anyone had previously realized.

    The information gathered in the DEBT project has also given us more data to forecast 2026 possibilities.  In the first half of 2026, there have been at least 208 agricultural bankruptcies: 177 filed under Chapter 12 and 31 under Chapter 11.  To compare with last year’s data; at the halfway point of 2026, agricultural bankruptcies reached 61% of the total number recorded in all of 2025.  If filings continue at this pace, 2026 would see approximately 416 agricultural bankruptcies- about 22% higher than 2025.

    While this project does not solve the problems of farm financial stress, it provides a more comprehensive view of trends across the agricultural sector. The data can help identify changes over time, geographic patterns, and emerging financial challenges affecting agricultural operations. When considered more broadly, these filings offer valuable information for farmers, attorneys, policymakers, researchers, lenders, and others seeking to understand the economic conditions affecting agriculture.

    Recommended citation format: Rumley, Elizabeth. “A New Way to See Agricultural Bankruptcy Trends.” Southern Ag Today 6(39.5). September 25, 2026. Permalink

  • Sugar is sweet, just sweeter in some places…

    Sugar is sweet, just sweeter in some places…

    Authors: Shawn Wade and Darren Hudson, International Center for Agricultural Competitiveness, Texas Tech University

    Sugar is sweet… especially for foreign sugar producers who find themselves at the receiving end of generous subsidies and other policies meant to protect their domestic production.

    Sugar remains one of the most highly protected commodities in the world, with import tariffs (or tariff rate quotas, TRQs) being the most common policy tool. Applied tariffs range from 0 to 100% globally, with the United States on the low end according to the World Trade Organization (WTO). Many of the largest producers, including China, India, and Turkey, have applied tariffs of far more than 20% (Figure 1), whereas the U.S. is at 12.1%.

    Added to the import controls, many of the largest producers utilize production/input subsidies, tax credits, and state monopoly trading mechanisms which give their producers significant advantages over U.S. producers. In fact, monetary transfers to Chinese and Indian producers have been around $2-3 billion per year since 2005, nearly 3x the OECD (Organization for Economic Co-operation and Development) average. A 2024 U.S. government report submitted to the WTO documented $17.6 billion in subsidies to Indian sugar producers in 2022 alone, even after a WTO dispute panel ruled that India had violated its WTO commitments on sugar.[1]

    And, the proliferation of ethanol mandates has provided significant indirect support to sugar prices, especially where sugar is the primary feedstock. By contrast, the U.S. sugar program is designed to operate at “no net cost” to the U.S. taxpayer, and U.S. biofuel policies are not related to sugarbeet or sugarcane production.

    With U.S. production being below self-sufficiency (<= 90% of domestic production), the door is open to sugar imports from more highly subsidized markets. Our analysis (linked below) outlines the policies in place around the world that impact sugar markets.

    This is an especially timely analysis as the U.S. sugar industry is asking the U.S. Trade Representative to use Section 301 authorities in response to what the industry is calling “unreasonable and discriminatory trade practices.” [2]

    Sugar is a popular target in the subsidy debate, but it is helpful to understand just how much support is being provided around the world to inform that debate.

    Figure 1.  Average Applied Most-Favored Nation (MFN) Import Tariffs for HS17 (Sugars and Sugar Confectionary), Last Reported Year for Each Country.

    To view the entire report go to the Texas Tech International Center for Agricultural Competitiveness website: https://www.depts.ttu.edu/aaec/icac/

    [1] Study available at:  https://docs.wto.org/dol2fe/Pages/SS/directdoc.aspx?filename=q:/G/AG/W245.pdf&Open=True

    [2] See https://sugaralliance.org/sugar-expert-testifies-on-unfair-trade-practices-harming-american-farmers-workers/41277

    Recommended citation format: Wade, Shawn. “Sugar is sweet, just sweeter in some places…” Southern Ag Today 6(39.4). September 24, 2026. Permalink

  • An Update of the United States Sugarcane and Sugarbeet Crops

    An Update of the United States Sugarcane and Sugarbeet Crops

    Authors: Michael Deliberto, Associate Professor and Louisiana Farm Bureau Endowed Professor in Agricultural Policy, Department of Agricultural Economics and Agribusiness, Louisiana State University Ag Center. Karen L. DeLong, Professor, Department of Agricultural and Resource Economics, University of Tennessee, Knoxville

    Introduction

    Industry experts are projecting supply uncertainty for the beet and cane sugar crops for fiscal year (FY) 2026/27. The primary contributing factors to this uncertainty include drought-related reductions in sugarbeet planted acreage, relatively low sugar prices, high input costs, and uncertainty about sugar demand, potentially stemming from the growing popularity of GLP-1 weight-loss drugs. While the lower beet sugar production was anticipated because of reduced planted acreage, increased cane sugar production from expanded sugarcane acreage may only partially offset the decline because of a new infestation of pasture mealybug that is affecting the southern U.S. sugarcane crop (Figure 1).

    Figure 1. Planted Acres Reported to the USDA Farm Service Agency for U.S. Sugarbeets and Sugarcane, 2009-2026. Source: USDA Farm Service Agency (2026a).

    Sugarbeet and Sugarcane Production

    According to the USDA National Agricultural Statistics Service (NASS) August 2026 Crop Production report, the 2026 harvested sugarbeet area is projected at 1.008 million acres, the third lowest in 45 years. The projected sugarbeet harvested area was reduced for five of the 10 sugarbeet-producing states, with the largest declines being in Idaho and North Dakota (USDA NASS, 2026). According to the USDA Farm Service Agency (2026a), prevented-planted sugarbeet acreage totals 30,560 acres and failed acreage is projected at 2,861 acres for a combined total of 33,421 acres (3.33% of total sugarbeet planted area), which is the largest amount on record (Figure 2).[1] The majority of the prevented-planted acreage was located in Nebraska (13,042 acres), Idaho (6,890 acres), Colorado (5,503 acres), and Wyoming (4,444 acres). In many of those regions, reduced snowfall depleted irrigation supplies that would normally be used to irrigate sugarbeets (Nebraska Public Media, 2026). In addition to the poor spring planting conditions, the August U.S. Agriculture in Drought report states that 59% of sugarbeet production is in areas experiencing drought, compared with 55% the previous week and 32% during the same period last year (USDA, 2026).

    Figure 2. Prevented and Failed U.S. Sugarbeet Acreage Reported to the USDA Farm Service Agency, 2009-2026. Source: USDA Farm Service Agency (2026a).

    USDA’s September World Agricultural Supply and Demand Estimates (WASDE) (2026) projects U.S. FY 2026/27 beet sugar production at 4.769 million short tons raw value (STRV), reflecting two consecutive years of decline (down 307,000 STRV year-over-year) and the lowest beet sugar output since FY 2019/20. U.S. cane sugar output is projected at 4.071 million STRV, 3% lower than the record FY 2025/26 sugarcane crop.

    Sugarcane processors in Florida have indicated negative impacts on the sugarcane crop from pasture mealybug infestation. In addition, all of Florida’s sugarcane production is in areas experiencing drought, according to the August U.S. Agriculture in Drought report (USDA, 2026). Much of the crop was also affected by a historic freeze in February, which may have affected the rootstock (Hudson, 2026). While none of Louisiana’s sugarcane-producing areas are currently experiencing drought, mealybug infestation is present, and potential impacts are still being assessed. Louisiana FY 2026/27 cane sugar production is now projected at a new record high of 2.266 million STRV, marking the fifth year that Louisiana has surpassed Florida’s production and its seventh consecutive year of growth.

    Given the challenges associated both with drought and pasture mealybug, USDA revised its projections for the FY 2026/27 U.S. cane sugar production downward by 0.6% in the August 2026 WASDE, to 4.159 million STRV.

    Sugar Imports

    For FY 2026/27, U.S. sugar imports are projected at 3.582 million STRV, about 740,000 STRV or 26% higher than the revised FY 2025/26 estimate (Figure 3) (USDA WASDE, 2026). The increase largely reflects a sharp adjustment to imports of Mexican sugar, which are projected at 1.346 million short tons, unchanged from July but more than 500% higher than the 220,000 short tons forecast for the current year. However, the levels of over-quota (Tier-2) sugar imports are still expected to increase the total U.S. sugar supply.

    The U.S. produced a record volume of sugar in FY 2024/25, and projections call for record cane sugar production for FY 2025/26 and near-record cane sugar output in FY 2026/27. At the same time, historically large volumes of Tier-2 (over-quota) sugar have entered the U.S. market as low global sugar prices make it profitable for traders (even with applicable duties) to import and sell sugar competitively in the U.S. market. Annual Tier-2 sugar imports generally remained below 100,000 STRV for nearly two decades before exceeding 200,000 STRV in FY 2019/20 and surging to approximately 1.2 million STRV in FY 2023/24, as reported in our previous Southern Ag Today article (https://southernagtoday.org/2026/04/23/how-to-ensure-a-domestic-sugar-industry-increase-the-tier-2-sugar-tariff/).

    Figure 3. U.S. Sugar Imports, by Source, FY 2022/23-FY 2026/27.

    Note: FY 2025/26 is estimated and FY 2026/27 is projected. Source: USDA WASDE (2026).

    Although Tier-2 sugar imports may decline this year, they remain historically elevated. With continued low world sugar prices, Tier-2 sugar imports are likely to continue to enter the U.S. at high levels, boosting overall U.S. sugar supplies. Those additional imports of low-priced world sugar will likely continue to limit domestic sugar price increases that would otherwise help domestic sugar farmers offset inflation-driven increases in input costs.

    [1] The USDA Risk Management Agency (2026) defines prevented planting as “the failure to plant an insured crop with the proper equipment by the final planting date or late planting period, if applicable. To qualify, you must be prevented from planting by an insured cause of loss that is general to the surrounding area and that prevents other producers from planting acreage with similar characteristics.”  The USDA Farm Service Agency (2026b) definition of failed acreage is “acreage that was timely planted with the intent to harvest, but because of disaster related conditions, the crop failed before it could be brought to harvest.”

    References

    Hudson, L. 2026. “Florida’s February Freeze: The $3 Billion Cold Shock to the State’s Crops.” Retrieved from: https://www.wusf.org/weather/2026-03-06/floridas-february-freeze-the-3-billion-cold-shock-to-the-states-crops

    Nebraska Public Media. 2026. Drought Could Reduce Nebraska Sugar Beet Crop by One-Third. Retrieved from: https://nebraskapublicmedia.org/en/news/news-articles/drought-could-reduce-nebraska-sugar-beet-crop-by-one-third/?utm_source=chatgpt.com

    USDA. 2026. U.S. Drought Monitor. Retrieved from: www.usda.gov/sites/default/files/documents/AgInDrought.pdf

    USDA Farm Service Agency. 2026a. Crop Acreage Data. Retrieved from: https://www.fsa.usda.gov/tools/informational/freedom-information-act-foia/electronic-reading-room/frequently-requested/crop-acreage-data

    USDA Farm Service Agency. 2026b. Acreage and Compliance Determinations. Retrieved from: https://www.fsa.usda.gov/Internet/FSA_File/2-cp.pdf

    USDA NASS. 2026. August 12, 2026, Crop Production Report. Retrieved from: https://esmis.nal.usda.gov/publication/crop-production

    USDA Risk Management Agency. 2026. Prevented Planting Insurance Provisions-Drought. Retrieved from: https://www.rma.usda.gov/sites/default/files/2024-02/Prevented-Planting-Insurance-Provisions-Drought-Fact-Sheet.pdf

    USDA WASDE. 2026. WASDE Report. Retrieved from: https://www.usda.gov/about-usda/general-information/staff-offices/office-chief-economist/commodity-markets/wasde-report

    Recommended citation format: Deliberto, Michael, and Karen L. DeLong. “An Update of the United States Sugarcane and Sugarbeet Crops.” Southern Ag Today 6(39.3). September 23, 2026. Permalink

  • How Higher LRP Subsidies Changed the Cost Comparison with CME Put Options

    How Higher LRP Subsidies Changed the Cost Comparison with CME Put Options

    Authors: Eunchun Park, James L. Mitchell, Xiaoyi Fang, and Lawson Connor[a]

    Livestock Risk Protection (LRP) and Chicago Mercantile Exchange (CME) put options both protect cattle producers against lower prices while preserving the opportunity to benefit if prices rise. These risk management tools are not identical, but they function similarly, and their premiums can be compared to assess the cost of establishing a price floor. Understanding how these products compare in terms of cost is especially important in the current market environment, as record-high cattle prices and heightened market volatility have made price protection increasingly expensive. Additionally, USDA’s 2019 and 2020 subsidy expansions substantially changed that comparison.

    In a recently published article, Park et al. (2026) compared LRP premiums with similar (matched) CME put premiums before and after the subsidy expansions. The study matched LRP endorsements with CME put options from 2005 through 2024. The main sample included 6,115 fed cattle endorsements and 34,645 feeder cattle endorsements. Each endorsement was paired with a put for the same cattle market and contract month and with a coverage level within one percentage point of the LRP contract.

    The comparison uses a “net wedge” equal to the matched CME put premium minus the producer-paid LRP premium minus an assumed $0.20 per cwt implementation cost. A positive wedge means the put premium exceeds the producer-paid LRP premium after the assumed cost; a negative wedge means LRP was relatively more expensive than the put. Before July 2019, average net wedges were -$0.948 per cwt for fed cattle and -$0.604 for feeder cattle. After the tiered subsidy schedule began in July 2020, those averages became $0.105 and $0.119, respectively.

    The sign change did not occur because gross LRP premiums fell below option prices. In the post-2020 sample, gross LRP premiums exceeded matched put premiums by $1.880 per cwt for fed cattle and $2.696 for feeder cattle. The statutory subsidy components averaged $2.186 and $3.016 per cwt, more than enough to offset those gross gaps on average.


    Figure 1 applies the pre-expansion subsidy rate to the post-2020 contracts while holding gross LRP and matched put premiums fixed. The average net wedge changed from $0.105 to -$1.276 per cwt for fed cattle and from $0.119 to -$1.788 for feeder cattle.

    These are averages, not guaranteed savings on every endorsement. Even after July 2020, only 49.9 percent of matched fed cattle endorsements and 46.9 percent of matched feeder cattle endorsements had a positive net wedge. LRP and CME puts also differ in contract size, settlement, eligibility, liquidity, brokerage costs, margin requirements, and basis exposure. A positive wedge does not imply risk-free arbitrage, and LRP will not be cheaper for every producer.

    This is important for many Southern cattle producers since their sale lots are often smaller than standardized futures contract sizes. LRP can be tailored by head count and target weight, while CME cattle options correspond to standardized 40,000-pound live cattle or 50,000-pound feeder cattle futures contracts (USDA RMA, 2026; CME Group, n.d.). When comparing the two, producers should first match the LRP endorsement end month to the CME contract month and use similar coverage levels. The comparison should then be made on an all-in $/cwt basis, with attention to the expected local cash sale price. After the subsidy expansion, LRP became less expensive than matched CME puts on average, although that was not true for every endorsement.


    Figure 1. Post-2020 net wedges under actual and pre-expansion subsidy rates

    Note. The counterfactual holds matched CME put premiums and gross LRP premiums fixed while replacing actual post-2020 subsidy rates with the pre-expansion rate. A net wedge is equal to the matched CME put premium minus the producer-paid LRP premium minus an assumed $0.20 per cwt implementation cost. Source: Park et al. (2026), Table 4.

    References

    Park, E., X. Fang, L. Connor, and J. L. Mitchell. 2026. “Subsidy Expansions, Pricing Wedges, and Derivative Markets: Evidence from Livestock Risk Protection.” Journal of Risk and Insurance, 1-29. doi:10.1111/jori.70068.

    U.S. Department of Agriculture, Risk Management Agency. 2026. Livestock Risk Protection Insurance Standards Handbook (FCIC-20010), 2027 crop year. USDA RMA handbook PDF.

    CME Group. n.d. Cattle Futures and Options Fact Card. Accessed August 25, 2026. CME cattle futures and options fact card PDF.

    [a] Eunchun Park, Lawson Connor, and James L. Mitchell are assistant professors in the Department of Agricultural Economics and Agribusiness at the University of Arkansas. Xiaoyi Fang is a postdoctoral fellow in the department. Mitchell is also the livestock marketing extension specialist for the University of Arkansas System Division of Agriculture.

    Recommended citation format: Park, Eunchun, James L. Mitchell, Xiaoyi Fang, and Lawson Connor. “How Higher LRP Subsidies Changed the Cost Comparison with CME Put Options.” Southern Ag Today 6(39.2). September 22, 2026. Permalink

  • Analyzing the Relationship Between the Yield Ratio and Optimal Crop Insurance Coverage Levels

    Analyzing the Relationship Between the Yield Ratio and Optimal Crop Insurance Coverage Levels

    Authors: Dr. Hunter D. Biram, Assistant Professor and Extension Agricultural Economist, University of Arkansas, Mr. Enil Serrano Puerto, Ph.D. Student, University of Kentucky, Dr. Grant Gardner, Assistant Extension Professor, University of Kentucky

    The Federal Crop Insurance Program (FCIP) has been a standard in farm risk management with nearly 500 million acres insured across row crops, forages, and specialty crops, resulting in up to $192 billion in insured liability in 2024, or 78% of the total value of U.S. crops (USDA-RMA and USDA-ERS, 2026). Despite its popularity as a risk management tool, the question of the best coverage level remains each year. Because premium rates are capped at annual increases of 20%, base premiums tend to change very little from year to year. However, the expected insurance price used to calculate coverage is influenced by futures market prices. As a result, insurance costs can fluctuate based on changes in commodity prices and the mix of crop acres planted by producers. This often leaves farmers with the question of how much insurance to buy or whether to renew with the same coverage from the year before. In response, a large suite of tools has been developed by university extension services. A total of 13 decision aids have been developed by universities from across the U.S., with 9 focusing on farm programs (i.e., Agriculture Risk Coverage and Price Loss Coverage) administered by the Farm Service Agency (FSA), and 4 focusing on federal crop insurance programs administered by the Risk Management Agency (RMA) (Serrano, Gardner, and Biram, Forthcoming). We add a decision aid to this suite of tools that provides analysis for both FSA farm programs and federal crop insurance programs, the Crop Insurance Decision-Maker (CIDM). The CIDM is a free, web-based decision aid that provides expected revenue net of production expenses and insurance premiums paid under scenarios with and without crop insurance. After analyzing multiple scenarios, the CIDM highlights the risk management option with the highest expected net return as a potential optimal coverage choice. The tool further provides analysis of farmer risk preferences by including data for farmers who are risk-averse and are concerned about extreme weather and pest pressure lowering expected net returns.

    In an article published in the latest edition of the Journal of the American Society of Farm Managers and Rural Appraisers (JASMFRA), Serrano, Gardner, and Biram (2026) provide an explanation for CIDM, how to interpret the results in the decision aid, how the results were generated, and where it fits in the greater suite of farmer decision aids. In most instances, results follow those of Biram et al. (2022), who show that even in the presence of ARC and PLC, the optimal decision in most cases is to choose 80-85% coverage. Biram et al. (2022) show that the base premium rate drives the coverage level, with higher base premiums resulting in increasing cost of insurance, and therefore lower optimal coverage levels. 

    We suggest here that another driver of optimal coverage is the ratio of the farm-level yield expectation, measured by the Actual Production History, to the county-level yield expectation measured by the county Reference Yield determined by RMA. Using Arkansas and Kentucky as examples, Figures 1 and 2 plot optimal coverage levels for risk-averse farmers across various yield ratio levels based on Serrano, Gardner, and Biram (2026). We first note that in all instances, except for cotton grown in one county in Arkansas, purchasing some level of crop insurance is always preferred to not purchasing any crop insurance at all (see Figures 1-2). We also find that the optimal coverage level is at least 70% or greater when the farm-level yield expectation is at least half that of the county yield expectation for Arkansas (Figure 1) or the farm yield expectation is at least 60% of the county yield expectation in Kentucky.

    Since these general results are across multiple combinations of states, counties, and coverages, we direct farmers and other users involved in the crop insurance purchase process to consult the CIDM for optimal coverage in a specific county.

    Figure 1. The Relationship Between the Yield Ratio and Optimal Coverage Level in Arkansas

    Figure 2. The Relationship Between the Yield Ratio and Optimal Coverage Level in Kentucky

    References

    Biram, H. D., Coble, K. H., Harri, A., Park, E., & Tack, J. (2022). Mitigating price and yield risk using revenue protection and agriculture risk coverage. Journal of Agricultural and Applied Economics, 54(2), 319-333.

    Serrano, E., Gardner, G., & Biram, H.D. (2026). Enhancing Crop Insurance Decisions with Data-Driven Tools. Journal of the American Society of Farm Managers and Rural Appraisers.

    United States Department of Agriculture, Economic Research Service. (Accessed 2026). Farm income and wealth statistics.

    United States Department of Agriculture, Risk Management Agency. (Accessed 2026). Revised premium ratings for corn and soybeans: Frequently asked questions.