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Farmers use pesticides to reduce yield losses. The efficacies of pesticidetreatments are often evaluated by analyzing the average treatment effects andrisks. The stochastic efficiency with respect to a function is often employedin such evaluations through ranking the certainty equivalents of eachtreatment. The main challenge of using this method is gathering an adequatenumber of observations to produce results with statistical power. However, inmany cases, only a limited number of trials are replicated in fieldexperiments, leaving an inadequate number of observations. In addition, thismethod focuses only on the farmer's profit without incorporating the impact ofdisease pressure on yield and profit. The objective of our study is to proposea methodology to address the issue of an insufficient number of observationsusing simulations and take into account the effect of disease pressure on yieldthrough a quantile regression model. We apply this method to the case ofstrawberry disease management in Florida.

Evaluating Pest Management Strategies: A Robust Method and its Application to Strawberry Disease Management