Design of the rainfall index annual forage program

Abstract

<jats:sec><jats:title content-type="abstract-subheading">Purpose</jats:title><jats:p>The 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.</jats:p></jats:sec><jats:sec><jats:title content-type="abstract-subheading">Design/methodology/approach</jats:title><jats:p>The 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.</jats:p></jats:sec><jats:sec><jats:title content-type="abstract-subheading">Findings</jats:title><jats:p>The 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.</jats:p></jats:sec><jats:sec><jats:title content-type="abstract-subheading">Practical implications</jats:title><jats:p>Producers 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.</jats:p></jats:sec><jats:sec><jats:title content-type="abstract-subheading">Originality/value</jats:title><jats:p>Considerably 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.</jats:p></jats:sec>

Soil Moisture Information Improves Drought Risk Protection Provided by the USDA Livestock Forage Disaster Program

“…Some of this literature measured risk as the probability of not receiving a payment when there was a loss (i.e., occurrence of false negatives) (Keller and Saitone, 2022;Yu et al, 2019), while other research used mean-variance or mean-semi-variance (Cho and Brorsen, 2021;ShalekBriski et al, 2021;Westerhold et al, 2018). We evaluated both types of measures, although rather than semi-variance we used target deviations based on Fishburn (1977).…”