Decision-Theoretic Prediction and Policy Design of GDP Slot Auctions

Abstract

We examine the potential for a simple auction to allocate arrival slots during Ground Delay Programs (GDP’s) more efficiently than the currently used sys- tem. The analysis of these auctions uses Predictive Game Theory (PGT) Wolpert and Bono (2010a,b), a new approach that produces a probability distribution over strategies instead of an equilibrium set. We compare the simple auction with other allocation methods, including combinatorial auctions and theoretical benchmarks using data from a one-hour GDP at Chicago Midway. We find that the simple slot auction overcomes several practical shortcomings of other approaches, while offering economically significant efficiency gains with respect to current practices and the potential to lower airline costs. We also find that the second price version of the simple auction dominates the first price version in nearly every decision-relevant category. This is despite the fact that none of the conventional arguments for second price auctions, such as dominant strategy implementability, even apply to GDP slot auctions. Finally, the results indicate that combinatorial auctions, if made operationally practical, might be more efficient than our auction, even though the combinatorial auction does not implement the social optimum in dominant strategies.