Long-Term Forecasting with Prediction Markets - A Field Experiment on Applicability and Expert Confidence

While prediction markets have become increasingly popular to forecast the near-term future, the literature provides little evidence on how they perform for long-term problems. For assessing the long-term, decision-makers traditionally rely on experts, although empirical research disputes the value of expert advice. Reporting on findings from a field experiment in which we implemented two prediction markets in parallel to a Delphi study, this paper addresses two questions. First, we analyze the applicability of prediction markets for long-term problems whose outcome cannot be judged for a long time. Second, by comparing trading behavior of an expert and a student market, we analyze whether there is evidence that supports the assumption that experts possess superior knowledge. Our results show that prediction markets provide similar results as the well-established Delphi method. We conclude that prediction markets appear to be applicable for long-term forecasting. Furthermore, we observe differences in the confidence of experts and non-experts. Our findings indicate that, in contrast to students, experts reveal their information well-considered based on what they think they know. Finally, we discuss how such analyses of market participants' confidence provide valuable information to decision-makers and may be used to improve on traditional forecasting methods.