Loss Of Agent Research Articles

Asymmetric taxation, limited liability, and agency conflicts

Current income tax systems are characterized by an asymmetric treatment of gains and losses. This implies that the (effective) tax rate on profits exceeds that on losses. We study the contractural relationship between two parties (the principal and the agent). For example, such a relationship occurs if a franchisee (agent) contracts with a franchiser (principal) or when a new partner (agent) enters a partnership (principal). We focus on the effect of the agent's asymmetric taxation on the principal's optimal contract and show that the principal's expected profit is a non-monotonous function of the agent's loss tax rate. In particular, we show that the principal can be strictly better off if the agent is taxed more heavily. This result stands in contrast to the existing literature, which has only shown that lower taxation at the agent's level increases the principal's expected profit.

Risk Prevention Activities and Uncertainty Attitude

As it is well-known, the three main tools used by a decision maker in order to deal with disliked risks are saving, insurance and prevention. In general, when an activity allows to reduce the expected cost of an agent's loss we speak of prevention activity. Focusing the attention on loss reduction and on loss prevention decisions, up to now most of the literature has concentrated on static models in a single-period framework, or on special dynamic models with a two-period setting. In our paper we focus our attention on the role played by time with the aim of characterizing the optimal prevention activities. In particular, our study is devoted to the analysis of loss prevention actions, with different assumptions about the timing decisions.

Mean Field Equilibria of Dynamic Auctions with Learning

We study learning in a dynamic setting where identical copies of a good are sold over time through a sequence of second price auctions. Each agent in the market has an 'unknown' independent private valuation which determines the distribution of the reward she obtains from the good; for example, in sponsored search settings, advertisers may initially be unsure of the value of a click. Though the induced dynamic game is complex, we simplify analysis of the market using an approximation methodology known as 'mean field equilibrium' (MFE). The methodology assumes that agents optimize only with respect to long run average estimates of the distribution of other players' bids. We show a remarkable fact: in a mean field equilibrium, the agent has an optimal strategy where she bids truthfully according to a 'conjoint valuation'. The conjoint valuation is the sum of her current expected valuation, together with an overbid amount that is exactly the expected marginal benefit to one additional observation about her true private valuation. Under mild conditions on the model, we show that an MFE exists, and that it is a good approximation to a 'rational' agent's behavior as the number of agents increases. Formally, if every agent except one follows the MFE strategy, then the remaining agent's loss on playing the MFE strategy converges to zero as the number of agents in the market increases. We conclude by discussing the implications of the auction format and design on the auctioneer's revenue. In particular, we establish a dynamic version of the revenue equivalence theorem, and discuss optimal selection of reserve prices in dynamic auctions.