Rationalizing (Non-)Equilibrium Bidding in Maximum-Value Auctions Without Beliefs About Others’ Behavior

We propose a novel approach to the modelling of second-price Maximum-Value auctions that assumes no belief about others’ behavior and no expected profit maximization. This individual decision-making model, naive Impulse Balance Equilibrium or nIBE, deals with bidders’ anticipated regrets from winning and from losing the auction. It exploits the stochastic properties of the auction format and rationalizes: (i) Nash equilibrium bidding, (ii) (non-)monotone overbidding and (iii) fully cursed equilibrium bidding. We fit this model to the available data and find that it explains median bids better than the Nash equilibrium prediction and, overall, as well as cursed-equilibrium. Furthermore, nIBE and the noise-free variant of cursed equilibrium typically outperform HQRE models with level-k or cursed equilibrium beliefs in terms of in- and out-of-sample quartile predictions.