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We study dynamic unstructured bargaining with deadlines and one-sided private information about the amount available to share (the \"pie size\"). Using mechanism design theory, we show that given the players' incentives, the equilibrium incidence of bargaining failures (\"strikes\") should increase with the pie size, and we derive a condition under which strikes are efficient. In our setting, no equilibrium satisfies both equality and efficiency in all pie sizes. We derive two equilibria that resolve the trade-off between equality and efficiency by favoring either equality or efficiency. Using a novel experimental paradigm, we confirm that strike incidence is decreasing in the pie size. Subjects reach equal splits in small pie games (in which strikes are efficient), while most payoffs are close to either the efficient or the equal equilibrium prediction, when the pie is large. We employ a machine learning approach to show that bargaining process features recorded early in the game improve out-of-sample prediction of disagreements at the deadline. The process feature predictions are as accurate as predictions from pie sizes only, and adding process and pie data together improves predictions even more.

We study a bargaining model in which a buyer makes frequent offers to a privately informed seller, while gradually learning about the seller’s type from “news.” We show that the buyer’s ability to leverage this information to extract more surplus from the seller is remarkably limited. In fact, the buyer gains nothing from the ability to negotiate a better price despite the fact that a negotiation must take place in equilibrium. During the negotiation, the buyer engages in a form of costly “experimentation” by making offers that are sure to earn her negative payoffs if accepted, but speed up learning and improve her continuation payoff if rejected. We investigate the effects of market power by comparing our results to a setting with competitive buyers. Both efficiency and the seller’s payoff can decrease by introducing competition among buyers.

Suppose that agents can exert costly effort that creates nonrival, heterogeneous benefits for each other. At each possible outcome, a weighted, directed network describing marginal externalities is defined. We show that Pareto efficient outcomes are those at which the largest eigenvalue of the network is 1. An important set of efficient solutions—Lindahl outcomes—are characterized by contributions being proportional to agents’ eigenvector centralities in the network. The outcomes we focus on are motivated by negotiations. We apply the results to identify who is essential for Pareto improvements, how to efficiently subdivide negotiations, and whom to optimally add to a team.

We propose a price-theoretic approach to Bayesian persuasion by establishing an analogy between the sender’s problem and finding Walrasian equilibria of a persuasion economy. The sender, who acts as a consumer, purchases posterior beliefs at their prices using the prior distribution as her endowment. A single firm has the technology to garble the state. Welfare theorems provide a verification tool for optimality of a persuasion scheme and characterize the structure of prices that support the optimal solution. This approach yields a tractable solution method for persuasion problems in which the sender’s utility depends only on the expected state.

We provide a framework for empirical analysis of negotiated-price markets. Using mortgage market data and a search and negotiation model, we characterize the welfare impact of search frictions and quantify the role of search costs and brand loyalty for market power. Search frictions reduce consumer surplus by $12/month/consumer, 28 percent of which can be associated with discrimination, 22 percent with inefficient matching, and 50 percent with search costs. Banks with large consumer bases have margins 70 percent higher than those with small consumer bases. The main source of this incumbency advantage is brand loyalty; however, price discrimination based on search frictions accounts for almost a third.

We consider a situation in which two parties have concluded an efficient contract corresponding to one major bargaining solution. After the parties have agreed on one particular contract, an unanticipated shock may change the contract outcomes in a way that benefits one party but harms the other party. If this happens, they have the option to either stay with the original exchange contract or adjust some contract parameters such as the price. We propose a model to perform such adjustments automatically, to obtain the same bargaining solution as in the initial contract under the restriction that the new contract dominates the outcomes of the original contract. We study several bargaining solutions within this general framework. These bargaining solutions offer various sharing rules to distribute the benefit between the parties. To reflect practical considerations, we only consider adjustments made via one contract parameter (the price), while all other parameters result from the original contract and the random shock. To evaluate the efficiency of the proposed approach, we also compare it to a full re-negotiation scenario, in which all parameters can be modified within the boundaries resulting after the random shock. However, waiting and re-negotiation might be costly compared to the situation when the smart contract executes the adjustment automatically. Therefore, the automatic adjustment might be more efficient compared to the other types of contracts. We present several numerical examples and run large random simulations, which we also check statistically.

We conduct a series of laboratory experiments to understand what role commitment and reputation play in bargaining. The experiments implement the Abreu and Gul (2000) bargaining model that demonstrates how introducing behavioral types, which are obstinate in their demands, creates incentives for all players to build reputations for being hard bargainers. The data are qualitatively consistent with the theory, as subjects mimic induced types. Furthermore, we find evidence for the presence of complementary types, whose initial demands acquiesce to induced behavioural demands. However, there are quantitative deviations from the theory: subjects make aggressive demands too often and participate in longer conflicts before reaching agreements. Overall, the results suggest that the Abreu and Gul (2000) model can be used to gain insights to bargaining behavior, particularly in environments where the process underlying obstinate play is well established.

We propose three mechanisms to reach compromise between two opposing parties. They are based on the use of Rules of k Names, whereby one of the parties proposes a shortlist and the other chooses from it. Methods of this class are used in practice to appoint Supreme Court justices and have been recently proposed for arbitration selection processes. Those we suggest are flexible and allow the parties to participate in the endogenous determination of the role of proposer and the shortlist size. They involve few stages, implement the Unanimity Compromise Set, and are robust to the strategic inclusion of candidates.

Research summary: This article exploits a natural experiment to estimate the causal effect of political uncertainty on bargaining outcomes in cross-border acquisitions. We argue that political uncertainty alters the relative bargaining power between acquiring versus target firms. The host country's political uncertainty makes the returns on cross-border acquisitions more unpredictable. Accordingly, foreign acquirers demand compensation for such uncertainty in negotiations, otherwise they will not consider their acquisitions profitable. Thus, when political uncertainty is high in the host country, ceteris paribus, foreign acquirers have greater bargaining power, which leads to more favorable outcomes for acquirers. Using national elections to measure political uncertainty, we find evidence strongly supporting our prediction. Target firms capture a smaller portion of the acquisition gains than do acquiring firms, when political uncertainty is high. Managerial summary: The uncertainty about the host government policies is a major concern for firms considering cross-border acquisitions. However, we know little about how such uncertainty influences cross-border deal negotiations and outcomes. This research investigates the effect of political uncertainty on the bargaining outcomes in cross-border acquisitions. We argue that high political uncertainty in the host country strengthens the foreign acquirer's bargaining position relative to the acquired firm. The outcome of investment is harder to predict under political uncertainty, and therefore the foreign acquirer will require compensation for political uncertainty such as paying a lower takeover premium and using a contingent payment option. Without such compensation, the foreign acquirer may not find it attractive to make a deal. Our empirical results support our argument.