Tools

Enterprise budgets can range from straightforward to highly detailed, but all serve as valuable tools for estimating the expected costs and returns of crop production. The budgets provided for both annual and perennial crops are designed to reflect typical long-term averages across varying conditions, offering a practical benchmark rather than a precise prediction. Because actual results depend on factors such as soil characteristics, market access, and management practices, outcomes will differ from farm to farm. This Ag Decision Maker Toolset is intended to support producers in analyzing these variables, improving planning accuracy, and making informed financial and operational decisions that enhance overall farm performance.

This set of interactive farm management tools helps producers estimate the costs associated with owning and operating key grain-handling equipment. The toolset includes calculators for machinery ownership costs, grain truck transportation costs, and grain wagon transportation costs. Users can enter information such as purchase price, equipment age, fuel and labor costs, repair expenses, hauling capacity, and annual use to estimate per-unit and annual operating costs. The tools are based on the economic methods used in Iowa State University Extension and Outreach’s Ag Decision Maker resources and allow producers to evaluate equipment investments, compare transportation methods, and better understand the true cost of moving grain from field to market.

This tool contains estimates of production costs for common livestock enterprises in Iowa. Estimates are intended to reflect average or above average levels of management using common types of technology. Input prices reflect expected average price levels during the year. Data was drawn from farm record summaries, feed consumption research and price projections, and are intended to be used for planning purposes only. For individual farms, expected costs and input requirements based on past results should be substituted whenever possible.

The Agricultural Foreign Investment Disclosure Act (AFIDA) is a federal law enacted in 1978 that requires foreign individuals, companies, and governments to report their interests in U.S. agricultural land. The law was created in response to growing concerns in the 1970s about transparency in land ownership and its implications for food security and national interest.

The Share Weighted Size Index (SWSI) measures how farm production is concentrated among small or large farms in each U.S. state for crops like corn, soybeans, and wheat, among others. Using public data from the Census of Agriculture, it assigns a value between 0 and 1 where higher values mean more production is controlled by large farms, indicating greater consolidation. Developed by Lacy, Orazem, and Schneekloth (2022), the index tracks changes in farm structure over time.

The estimated costs of corn, corn silage, soybean, alfalfa, and pasture maintenance in this report are based on data from several sources. They include the annual Iowa Farm Business Association record summaries, production and costs data from the Departments of Economics, Agricultural and Biosystems Engineering, and Agronomy at Iowa State University, and a survey of selected agricultural cooperatives and other input suppliers around the state. These cost estimates intend to represent average costs for farms in Iowa. Very large or small farms may have lower or higher fixed costs per acre. Starting in 2023, projected land costs are based on the previous year's results in the Cash Rental Rates for Iowa Survey, and a poll of the Iowa State University Extension and Outreach Farm Management team and Farm Financial Associates.

This decision tool provides a historical representation of land values across all 99 counties in Iowa annually since 1950. In particular, we offer comparative visualizations for nominal land values and inflation-adjusted land values to 2015 levels, annual percentage change in county land values, as well as aggregate dollar-amount changes in land values for a selected time period.

This decision tool provides an interactive and intuitive way to compare land values across all 99 counties in Iowa annually since 1950. In particular, we offer visualizations for nominal land values and inflation-adjusted land values to 2015 levels, annual percentage change in county land values, as well as aggregate dollar-amount changes in land values for a selected time period.

This tool calculates the potential internal rate of return from installing a complete mix anaerobic digester on a swine farm based on default investment and state-specific energy prices.

The decision tool, Economics of Cover Crops, provides worksheets to analyze three different cover crop scenarios:
• Projected economic costs and benefits of crop crops without grazing or harvesting
• Projected economic costs and benefits of crop crops with grazing or harvesting
• Actual economic costs and benefits resulting from cover crops, including grazing or harvesting.

This tool provides a wide array of information for about 140 lakes in Iowa, including visitation patterns, water quality, lake usage, and the value of a lake to its local economy. Additionally, this site contains economic analysis of the benefits to Iowans and communities from improvements in water quality. The information and analysis are part of an ongoing research initiative by Iowa State University.

To help understand how and why COVID-19 disrupted the agricultural supply chain the ways it did, and to help prevent similar things from happening in the future, Jacobs will lead a newly-funded USDA study. The project, Agricultural Supply Chain Disruptions: Costs and Mitigation Strategies to Enhance Resiliency of Ag Supply Chains aims to enhance the resiliency of the beef, pork, dairy, and egg supply chains in the Midwest in the face of future disruptions and was recently awarded a two-year, $458,000 National Institute of Food and Agriculture COVID-19 Rapid Response Program grant. The grant is part of more than $14 million in USDA funding announced to help study the most critical issues facing consumers during the pandemic.

The return over operating costs is one signal of the level of profitability to producing ethanol. This return is calculated as the difference between the revenues from ethanol plant outputs (ethanol and dried distillers grains with solubles [DDGS]) and the costs of variable production inputs (corn, natural gas, and other costs such as enzymes, labor, electricity and water).

CARD is tracking biodiesel returns over operating costs based on a typical continuous flow plant that uses soybean oil as feedstock for biodiesel production. Given soybean oil and biodiesel prices for Iowa reported weekly by the Agricultural Marketing Service, and methanol prices reported monthly by Methanex, we have computed the biodiesel operating returns from April 13, 2007, to the present.

This decision tool provides a simple and intuitive way to compare annual ARC-CO and PLC payments for corn and soybean base acres across counties in Iowa. A detailed description of the ARC/PLC programs and other ISU Extension and Outreach Farm Bill decision tools are available on the Iowa State University Extension and Outreach website.

The cash rental rate information is from a survey of farmers, landowners, agricultural lenders, and professional farm managers. They supplied information based on their best judgments about typical cash rental rates for high, medium, and low quality cropland in their counties, as well as for land devoted to production of hay, oats, and pasture. You can find the original survey on the Iowa State University Extension and Outreach website.

Lean hog future prices are from Chicago Mercantile Exchange (CME) Group, compiled by Barchart; Cash prices are from the USDA-AMS National Daily Direct Hog Prior Day Report – Slaughtered Swine report (LM_HG201), complied by the Livestock Marketing Information Center.

Actual weekly hog slaughter numbers come from Actual Slaughter Under Federal Inspection (SJ_LS711), queried via USDA/NASS Quick Stats. Predicted weekly slaughter numbers in 2022 and 2023 are derived from historical slaughter numbers together with inventory information from Quarterly Hogs and Pigs report.

Corn yield prediction provides valuable information about production and prices prior to harvest. Publicly available high-quality corn yield prediction can help address emergent information asymmetry problems and, in doing so, improve price efficiency in futures markets.

Jiang et al. (2018) developed a Long Short-Term Memory (LSTM) model to predict corn yields in ten corn belt states that achieved promising results with the sample data. Overall, the model prediction is only 0.83 bushel per acre (bpa) lower than actual corn yields, a smaller difference than the corresponding prediction from USDA. About 80% of the LSTM county-level corn yield predictions fall within ±20 bpa of actual yields. The model uses ten variables that affect corn yields, which were constructed from data sets provided by the USDA, USDA-NRCS, USDA-NASS, NOAA, and IBM weather underground.

This decision tool is intended to help farmers who do not currently use cover crops evaluate the expected annual net returns to cover crop adoption under alternative scenarios, and to serve as a benchmark for farmers who are already using cover crops and want to improve the return on their investment.

This tool provides a visual representation of the net price distribution of national daily market hog sales. Multiple dates can be viewed simultaneously for comparisons across time. Swine sales are categorized into five types, as published by USDA’s Agricultural Marketing Service. Data used in this tool is publicly available and is derived from the National Daily Direct Hog Prior Day Report - Average Net Price Distribution(LM_HG215).

This figure shows the revealed comparative (dis)advantages of six leading export countries (based on 2019 export values) for five agricultural commodities. The radius of each country’s circle is proportional to its commodity export value in billions of US dollars. Circle positions correspond to relative revealed comparative advantages. The area above the diagonal line indicates a comparative advantage for that commodity/nation and the area below the diagonal line indicates a comparative disadvantage. See the following APR article for more information: The United States’ Competitive Positions in Beef, Corn, Pork, Soy, and Wheat Exports: 1980–2019.