We propose a novel approach to the modelling of behavior in first-price and allpay auctions that builds on the presumption that bidders do not engage in game-theoretic reasoning. Our models, AsP (for Aspired-Payoff) and nIBE (for naïve Impulse Balance Equilibrium), exploit the information available to bidders and assume risk neutrality, no best-responding behavior and no profit-maximization. Their parameter-free variants entail either overbidding or Nash equilibrium bidding. We assess their

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... anatory power with the data of first-price and all-pay auction experiments and find that overall, our models outperform Nash in explaining the data on either format. Assuming probability misperception further improves their goodness-of-fit. Assuming impulse weighting in nIBE may lead to overbidding and organizes the effect of end-of-round information feedback on behavior in repeated auctions.