A simple model of search engine pricing

We present a simple model of how a monopolistic search engine optimally determines the average quality of firms in its search pool. In our model, there is a continuum of consumers, who use the search engine’s pool, and there is a continuum of firms, whose entry to the pool is restricted by a price set by the search engine. We show that a monopolistic search engine may have an incentive to set a relatively low price that encouarges low-relevance advertisers to enter the search pool. This conclusion is independent of whether the search engine charges a price per click or a fixed access fee

Can anticipatory feelings explain anomalous choices of information sources?

The well-being of agents is often directly affected by their beliefs, in the form of anticipatory feelings such as anxiety and hopefulness. Economists have tried to model this effect by introducing beliefs as arguments in decision makers' vNM utility function. One might expect that such a model would be capable of explaining anomalous attitudes to information that we observe in reality. We show that the model has several shortcomings in this regard, as long as Bayesian updating is retained. (c) 2005 Elsevier Inc. All rights reserved

On the strategic use of attention grabbers

When a �firm decides which products to offer or put on display, it takes into account the products' ability to attract attention to the brand name as a whole. Thus, the value of a product to the �firm emanates from the consumer demand it directly meets, as well as the indirect demand it generates for the firms other products. We explore this idea in the context of a stylzed model of competition between media content providers (broadcast TV channels, internet portals, newspapers) over consumers with limited attention. We characterize the equilibrium use of products as attention grabbers and its implications for consumer conversion, industry profi�ts and (mostly vertical) product differentiation

Consumer optimism and price discrimination

In many principal-agent environments, the two parties hold different prior beliefs regarding the agent's future preferences. These differences may be due to inherent biases such as over-optimism or over-pessimism. We analyze the principal's optimal contract design under the assumption that the agent's prior is private information. In order to screen the agent's prior, the principal devises a menu of contingent contracts, some of which are 'speculative' as they involve betting on the agent's future action. We characterize the optimal menu and show that the characterization enables us to interpret real-life contract design in a variety of economic contexts

Contradiction as a form of contractual incompleteness

A simple model is presented, in which contradictory instructions are viewed as a type of contract incompleteness. The model provides a complexity-based rationale for contradictory instructions. If there are complexity bounds on the contract, there may be an incentive to introduce contradictions, leaving for another agent the task of interpreting them. The optimal amount of contradictions depends on the complexity bound, the conflict of interests with the interpreter, and the institutional constraints on his interpretations. In particular, a higher complexity bound may result in a larger amount of contradictions

Search Design and Broad Matching

We study decentralized mechanisms for allocating firms into search pools. The pools are created in response to noisy preference signals provided by consumers, who then browse the pools via costly random sequential search. Surplus-maximizing search pools are implementable in symmetric Nash equilibrium. Full extraction of the maximal surplus is implementable if and only if the distribution of consumer types satisfies a set of simple inequalities, which involve the relative fractions of consumers who like different products and the Bhattacharyya coefficient of similarity between their conditional signal distributions. The optimal mechanism can be simulated by a keyword auction with broad matching. (JEL C78, D44, D82

A Model of Competing Narratives

We formalize the argument that political disagreements can be traced to a "clash of narratives". Drawing on the "Bayesian Networks" literature, we model a narrative as a causal model that maps actions into consequences, weaving a selection of other random variables into the story. An equilibrium is defined as a probability distribution over narrative-policy pairs that maximizes a representative agent's anticipatory utility, capturing the idea that public opinion favors hopeful narratives. Our equilibrium analysis sheds light on the structure of prevailing narratives, the variables they involve, the policies they sustain and their contribution to political polarization

Managing intrinsic motivation in a long-run relationship

We study a repeated principal–agent interaction, in which the principal offers a ”spot” wage contract at every period, and the agent’s outside option follows a Markov process with shocks. If the agent rejects an offer, the two parties are permanently separated. At any period during the relationship, the agent is productive as long as his wage does not fall below a ”reference point”, which is defined as his lagged-expected wage in that period. We characterize the game’s unique Markov perfect equilibrium. The equilibrium path exhibits an aspect of wage rigidity. The agent’s total discounted rent is equal to the maximal shock value

Cheating with models

Beliefs and decisions are often based on confronting models with data. What is the largest "fake" correlation that a misspecified model can generate, even when it passes an elementary misspecification test? We study an "analyst" who fits a model, represented by a directed acyclic graph, to an objective (multivariate) Gaussian distribution. We characterize the maximal estimated pairwise correlation for generic Gaussian objective distributions, subject to the constraint that the estimated model preserves the marginal distribution of any individual variable. As the number of model variables grows, the estimated correlation can become arbitrarily close to one, regardless of the objective correlation

Consumer optimism and price

We study monopolistic design of a menu of non-linear tariffs when consumers have biased prior beliefs regarding their future preferences. In our model, consumers are "optimistic'' if their prior belief assigns too much weight to states of nature characterized by large gains from trade. A consumer's degree of optimism is his private information, and the monopolist employs the menu of non-linear tariffs to screen it. We characterize the optimal menu and show that the existence of non-common priors has significant qualitative implications for price discrimination and ex-post inefficiency. Finally, the characterization enables us to interpret aspects of real-life menus of non-linear tariffs