Supplier-induced demand as strategic framing

This paper develops a model of supplier-induced demand as strategic framing where the patient has reference-dependent references, and the physician can persuade the patient to buy a treatment by affecting the patient.s reference point. In the main result, the patient is assumed to have a constant rate of risk aversion (lovingness) in the gain (loss) region. Two scenarios are treated. In the cure scenario, the physician wants to frame the patient.s decision problem such that he prefers to buy a risky curative treatment rather than no treatment. It is shown that the physician is most persuasive if she sets a high reference point, such that the patient sees all payoffs as losses down from that reference point. In the prevention scenario, the physician wants to frame the patient.s decision problem such that he prefers a safe preventive treatment rather than no treatment. In this case, the physician.s optimal framing either involves framing all payoffs as gains, thus making the patient riskaverse. Alternatively, loss aversion is exploited by framing only the fact of getting ill (rather than having prevented illness) as a loss.supplier-induced demand, prospect theory, strategic framing

Giffen Behaviour and Asymmetric Substitutability

Let a consumer consume two goods, and let good 1 be a Giffen good. Then a well-known necessary condition for such behaviour is that good 1 is an inferior good. This paper shows that an additional necessary for such behaviour is that good 1 is a gross substitute for good 2, and that good 2 is a gross complement to good 1 (strong asymmetric gross substitutability). It is argued that identifying asymmetric gross substitutability as an additional necessary condition gives better insight into Giffen behaviour, both on an analytical level and an intuitive level. In particular, the paper uses the concept of asymmetric gross substitutability to give a taxonomy of preferences, which includes preferences that are locally characterised by Giffen behaviour, and also uses this concept to introduce new decompositions of the effect of a change in own price on the demand for a good, different from those known in the literature.Giffen behaviour, asymmetric substitutability

A note on Seiberg-Witten central charge

The central charge for the Seiberg-Witten low-energy effective Action is computed using Noether supercharges. A reliable method to construct supersymmetric Noether currents is presented.Comment: 6 pages, Latex. Changed reference

Two-way Flow Networks with Small Decay

The set of equilibrium networks in the two-way flow model of network formation (Bala and Goyal, 2000) is very sensitive to the introduction of decay. Even if decay is small enough so that equilibrium networks are minimal, the set of equilibrium architectures becomes much richer, especially when the benefit functions are nonlinear. However, not much is known about these architectures. In this paper we remedy this gap in the literature. We characterize the equilibrium architectures. Moreover, we show results on the relative stability of different types of architectures. Three of the results are that (i) at most one players receives multiple links, (ii) the absolute diameter of equilibrium networks can be arbitrarily large, and (iii) large (small) diameter networks are relatively stable under concave (convex) benefit functions.Network formation, two-way flow model, decay, non-linear benefits

Three is a crowd - inefficient communication in the multi-player electronic mail game

In a two-player stag hunt with asymmetric information, players may lock each other into requiring a large number of confirmations and confirmations of confirmations from one another before eventually acting. This intuition has been formalized in the electronic mail game (EMG). The literature provides extensions on the EMG that eliminate inefficient equilibria, suggesting that no formal rules are needed to prevent players from playing inefficiently. The present paper investigates whether these results extend to the multi-player EMG. We show that standard equilibrium refinements cannot eliminate inefficient equilibria. While two players are predicted to play efficiently, many players need formal rules telling them when who talks to whom.Multi-Player Electronic Mail Game, Collective Action, Communication Networks

Strategic Vagueness and Appropriate Contexts

This paper brings together several approaches to vagueness, and ends by suggesting a new approach. The common thread in these approaches is the crucial role played by context. Using a single example where there is a conflict of interest between speaker and listener, we start by treating game-theoretic rationales for vagueness, and for the related concepts of generality and ambiguity. We argue that the most plausible application of these models to vagueness in natural language is one where the listener only imperfectly observes the context in which the speaker makes her utterances. We next look at a rationale for vagueness when there is no conflict between speaker and listener, and which is an application of Horn's rule. Further, we tackle the Sorites paradox. This paradox apparently violates standard axioms of rational behaviour. Yet, once it is taken into account that vague language is used in an appropriate context, these axioms are no longer violated. We end with a behavioural approach to vagueness, where context directly enters agents. preferences. In an application of prospect theory, agents think in terms of gains and losses with respect to a reference point. Vague predicates now allow agents to express their subjective valuations, without necessarily specifying the context.Vagueness, signalling games, decision theory, prospect theory

Strategic Network Disruption and Defense

Networks are one of the essential building blocks of society. Not only do firms cooperate in R&D networks, but firms themselves may be seen as networks of information-exchanging workers. Social movements increasingly make use of networks to exchange information, just as on the negative side criminal and terrorist networks use them. However, the literature on networks has mainly focused on the cooperative side of networks and has so far neglected the competition side of networks. Networks themselves may face competition from actors with opposing interests to theirs. Several R&D networks may compete with one another. The firm as a network of employees obviously faces competition. In particular, given the importance of connectivity for networks, competing networks may try to disrupt each other, by trying to convince key players in competing networks to defect, or to stop sponsoring key links (strategic network disruption). In response, networks that face competition will adapt their structure, and will avoid vulnerable network structures. Such network competition is what our paper is concerned with.Strategic Network Disruption, Strategic Network Design, Noncooperative Network Games

Game-theoretic pragmatics under conflicting and common interests

This paper combines a literature overview of existing literature in game-theoretic pragmatics, with new models that fill some voids in the literature. We start with an overview of signaling games with a conflict of interest between sender and receiver, and show that the literature on such games can be classified into models with direct, costly, noisy and imprecise signals. We then argue that this same subdivision can be used to classify signaling games with common interests, where we fill some voids in the literature. For each of the signaling games treated, we show how equilibrium- refinement arguments and evolutionary arguments can be interpreted in the light of pragmatic inference.Signaling games, pragmatics, equilibrium refinements, evolutionary game theory

Combining mechanistic and data-driven techniques for predictive modelling of wastewater treatment plants

Mechanistic models are widely used for modelling of wastewater treatment plants. However, as they are based on simplified and incomplete domain knowledge, they often lack accurate predictive capabilities. In contrast, data-driven models are able to make accurate predictions, but only in the operational regions that are sufficiently described by the dataset used. We investigate an alternative hybrid model, combining mechanistic and data-driven techniques. We show that the hybrid approach combines the strengths of both modelling paradigms. It allows for accurate predictions out of the training dataset without the need for complete domain knowledge. Moreover, this approach is not limited to wastewater treatment plants and can potentially be applied wherever mechanistic models are used