Bidding challenges learning theories, since with the same bid, experiences vary stochastically: the same choice can result in either a gain or a loss. In such an environment the question arises how the nearly universally documented phenomenon of loss aversion affects the adaptive dynamics. We...

We develop a dynamic matching and bargaining game with aggregate uncertainty about the relative scarcity of a commodity. We use our model to study price discovery in a decentralized exchange economy: Traders gradually learn about the state of the market through a sequence of multilateral...

In this study, we designed a delayed payment mechanism in laboratory second price auctions (SPAs) under which subjects received a cash endowment two weeks after the experiment day and had to use their own money to pay the experimental loss (if any) on the experiment day. We compared the effect...

Overbidding in second-price auctions (SPAs) has been shown to be persistent and associated with cognitive ability. We study experimentally to what extent cross-game learning can reduce overbidding in SPAs, taking into account cognitive skills. Employing an order-balanced design, we use...

Overbidding in second-price auctions (SPAs) has been shown to be persistent and associated with cognitive ability. We study experimentally to what extent cross-game learning can reduce overbidding in SPAs, taking into account cognitive skills. Employing an order-balanced design, we use...

In this paper we consider equilibrium behavior in a Dutch (descending price) auction where the bidders are uninformed of their valuations with probability 1-q and can acquire information about their valuation at a positive cost during the auction. We assume that the information acquisition...

The role of automated agents in the electronic marketplace has been growing steadily and has been attracting a lot of research from the artificial intelligence community as well as from economists. We consider the problem of homogeneous sellers of a single raw material or component vying for...

Agent-based simulations are performed to study adaptive learning in the context of asymmetric first-price auctions. Non-linearity of the Nash equilibrium strategies is used to investigate the effect of task complexity on adaptive learning by varying the degree of approximation the agents can...

The role of automated agents in the electronic marketplace has been growing steadily and has been attracting a lot of research from the artificial intelligence community as well as from economists. We consider the problem of homogeneous sellers of a single raw material or component vying for...

Learning is a subject of intense research in experimental economics. We contribute to this debate by presenting persuasive evidence that learning took place among uninformed heterogeneous agents on a quasi-stock market during a large-scale natural experiment that by size, incentives, and...