Design of the rainfall index annual forage program

• Published in: Agricultural finance review Vol. 81; no. 1; pp. 114 - 131
• Main Authors: ShalekBriski, Abby, Brorsen, Wade, Rogers, James K, Biermacher, Jon T, Marburger, David, Edwards, Jeff
• Format: Journal Article
• Language: English
• Published: Bingley Emerald Publishing Limited 21-01-2021; Emerald Group Publishing Limited
• Subjects: Adverse selection; Agricultural production; Agriculture; Annual rainfall; Cattle; Crop growth; Crop yield; Developing countries; Farms; Freezing; Income; Indemnity; Industrialized nations; Insurance coverage; Intervals; LDCs; Livestock; Moral hazard; Nonlinear systems; Nonlinearity; Policyholders; Precipitation; Rain; Rainfall index; Risk management; Risk reduction; Rye; Temperature; Triticale; Weather; Winter; United States > US; Oklahoma; Precipitation; Index insurance; Annual forage; G22; Rainfall index; Q18; Wheat pasture
• ISSN: 0002-1466; 2041-6326
• DOI: 10.1108/AFR-11-2019-0120

PurposeThe authors determine the effectiveness of the Rainfall Index Annual Forage Program (RIAFP) in offsetting yield risk of winter annual forage growers. The authors also evaluate the effectiveness in reducing risk of potential alternative weather indices.Design/methodology/approachThe RIAFP is designed to compensate forage producers when yield losses occur. Prior research found weak correlation between the rainfall index and actual winter annual forage yields. The authors use long-term small-plot variety trials of rye, ryegrass, wheat, triticale and oats with rainfall recorded on site and measure the correlation of the index with actual rainfall and actual yields. The alternative indices include frequency of precipitation events and of days with temperature below freezing.FindingsThe correlation between actual rainfall and the current RMA index was strongly positive as in previous research. Correlations between forage yields and monthly intervals of the current RMA index were mostly statistically insignificant, and many had an unexpected sign. All indices had some correlations that were inconsistent across time intervals and forage variety. The inconsistent signs suggest a nonlinear relationship with weather and forage yield, indicating that rainfall can be too much or too little. The number of days below freezing has the most potential of the three measures examined.Practical implicationsProducers should view the winter forage RIAFP as a risk-increasing income-transfer farm program. A product to reduce the risk for forage producers may need to use a crop growth simulation model or another approach that can capture the nonlinearity.Originality/valueConsiderably more data were considered than in past research. Past research did not consider alternative weather indices. The program should be continued if its goal is to serve as disguised income transfer, but it should be discontinued if its goal is to reduce risk.