Are expert judgements a reliable tool for predicting food chain actor decisions?

Summary

Historically, food and agriculture policy have remained largely independent of one another. However, initiatives such the EU’s Farm to Fork program are seeking to shift the dynamic to further integrate agriculture and food policy. This begs the question of whether industry experts are prepared for this integration or if they are more knowledgeable or potentially biased to one side. This thesis utilizes a novel hands-on prediction experiment stemming from three Discrete Choice Experiments (DCE’s) showcasing consumer preference for dairy products, and dairy farmer preference for cattle feeding regimes. We explore how well food and agriculture industry experts understand farmers and consumers, and if these experts are better able to anticipate the actions of one side versus the other. The implementation of such a prediction analysis within the agriculture industry, especially covering both sides of the food system, remains novel. We further explore other questions such as: Does education level impact forecast accuracy? Does expertise play a role in predictions? Do experts outperform non-experts? To explore these questions DCE results were compared to over 2,300 prediction observations gathered from food, agriculture, and economics experts from around the globe and from students enrolled in agriculture-based programs at a Swedish University. Early results suggest industry experts provide more accurate forecasts when compared to students. Preliminary results also suggest individuals with lower education levels displayed higher prediction accuracy, when compared to those who have a PhD, and there was little statistical significance showing and forecast bias between consumer and farmer predictions for industry experts.