A synthesis of behavioural and mainstream economics
Mainstream economic theory is based on the rationality assumption: thatpeople act as best they can to promote their interests. In contrast,behavioural economics holds that people act by behavioural rules of thumb,often with poor results. We propose a synthesis according to which peopleindeed act by rules, which usually work well, but may work poorly inexceptional or contrived scenarios. The reason is that like physicalfeatures, behavioural rules are the product of evolutionary processes; andevolution works on the usual, the common -- not the exception, not thecontrived scenario.
Analysis and interventions in large network games: graphon games and graphon contagion
Many of today’s most promising technological systems involve very large numbers of autonomous agents that influence each other and make strategic decisions within a network structure. Examples include opinion dynamics, targeted marketing in social networks, economic exchange and international trade in financial networks, product adoption decisions and social contagion. While traditional tools for network game analysis assumed that a social planner has full knowledge of the network of interactions, when we turn to very large networks two issues emerge. First, collecting data about the exact network of interactions becomes very expensive or not at all possible because of privacy and proprietary concerns. Second, methods for designing optimal interventions that rely on the exact network structure typically do not scale well with the population size. To obviate these issues, in this talk I will present a framework in which the central planner designs interventions based on probabilistic information about agent’s interactions, which can easily be inferred from aggregated data, instead of exact network data. I will introduce the tool of “graphon games” as a way to formally describe strategic interactions in this framework and I will illustrate how this tool can be exploited to design interventions that are robust to stochastic network variations. I will cover two main applications: design of targeted interventions for linear quadratic network games and design of optimal seeding policies for threshold contagion processes. In both cases, I will illustrate how the graphon approach leads to interventions that are asymptotically optimal in terms of the population size and can be easily computed without requiring exact network data.
Keeping Your Friends Close: Land Allocation with Friends
We examine the problem of assigning plots of land to
prospective buyers who prefer living next to their friends. They care not only
about the plot they receive, but also about their neighbors. This externality
results in a highly non-trivial problem structure, as both friendship and land
value play a role in determining agent behavior. We examine mechanisms that
guarantee truthful reporting of both land values and friendships. We propose
variants of random serial dictatorship (RSD) that can offer both truthfulness
and welfare guarantees. Interestingly, our social welfare guarantees are
parameterized by the value of friendship: if these values are low, enforcing
truthful behavior results in poor welfare guarantees and imposes significant
constraints on agents' choices; if they are high, we achieve good approximation
to the optimal social welfare. Based on joint work with Neel Patel, Alan Tsang and Yair
On the characterization of generalized additive games
Generalized Additive Games (GAGs) are coalitional games where the value of a coalition is calculated as a sum of individual values (provided by players not necessarily in the coalition). In this paper we characterize classes of GAGs that satisfy properties like monotonicity, superadditivity, (total) balancedness, Population Monotonicity Allocation Scheme- (PMAS-)admissibility and supermodularity, for all nonnegative individual values. We also illustrate the application of such conditions over particular GAGs studied in the literature of coalitional games.
Innovation and Strategic Network Formation
We study a model of innovation with a large number of firms that create new technologiesby combining several discrete ideas. These ideas can be acquired by private investment orvia social learning. Firms face a choice between secrecy, which protects existing intellectualproperty, and openness, which facilitates learning from others. Their decisions determine
interaction rates between firms, and these interaction rates enter our model as link proba-bilities in a learning network. Higher interaction rates impose both positive and negative
externalities on other firms, as there is more learning but also more competition. We showthat the equilibrium learning network is at a critical threshold between sparse and dense
networks. At equilibrium, the positive externality from interaction dominates: the innova-tion rate and even average firm profits would be dramatically higher if the network were
denser. So there are large returns to increasing interaction rates above the critical threshold.Nevertheless, several natural types of interventions fail to move the equilibrium away fromcriticality. One policy solution is to introduce informational intermediaries, such as publicinnovators who do not have incentives to be secretive. These intermediaries can facilitate ahigh-innovation equilibrium by transmitting ideas from one private firm to another.
Fattori di qualità nei dati biomedici e clinici - S.T.I.T.C.H. - Sapienza information-based Technology Innovation Center for Health (S.T.I.T.C.H.) Sapienza
L’interoperabilità come chiave del corretto uso del dato medico nella pratica clinica e nella ricerca medico/scientifica (Mauro Giacomini, Università di Genova)
Un esempio di cartella clinica per un reparto di cardiologia integrata nel sistema informativo ospedaliero e territoriale (Elena Lazarova, Università di Genova)
Un registro standardizzato per la raccolta e il riuso di dati medici per i reparti di malattie infettive liguri (Sara Mora, Università di Genova)
Risk-aversion and diversity in network routing
n network routing users often tradeoff different objectives in selecting their best route. An example is transportation networks, where due to uncertainty of travel times, drivers may tradeoff the average travel time versus the variance of a route. Or they might tradeoff time and cost, such as the cost paid in tolls.
We wish to understand the effect of two conflicting criteria in route selection, by studying the resulting traffic assignment (equilibrium) in the network. We investigate two perspectives of this topic: (1) How does the equilibrium cost of a risk-averse population compare to that of a risk-neutral population? (i.e., how much longer do we spend in traffic due to being risk-averse) (2) How does the equilibrium cost of a heterogeneous (diverse) population compare to that of a comparable homogeneous user population?
We provide characterizations to both questions above.
Based on joint work with Richard Cole, Thanasis Lianeas and Nicolas Stier-Moses.
Sequential Competition and the Strategic Origins of Preferential Attachment
There exists a wide gap between the predictions of strategic models of network formation and empirical observations of the characteristics of socio-economic networks. Empirical observations underline a complex structure characterized by fat-tailed degree distribution, short average distance, large clustering coefficient and positive assortativity. Game theoretic models offer a detailed representation of individuals’ incentives but they predict the emergence of much simpler structures than these observed empirically. Random network formation processes, such as preferential attachment, provide a much better fit to empirical observations but generally lack micro-foundations. In order to bridge this gap, we propose to model network formation as extensive games and investigate under which conditions equilibria of these games are observationally equivalent with random network formation process. In particular, we introduce a class of games in which players compete with their predecessors and their successors for the costs and benefits induced by link formation. We show that the focal equilibrium that emerges in this setting is one where players use probability distributions with full support and target the whole network with probabilities inversely proportional to the costs and benefits associated to each node. Notably, when the cost is inversely proportional to the degree of a node, equilibrium play induces a preferential attachment process.
Cost Sharing over Combinatorial Domains - Georgios Birmpas (Oxford University)
We study mechanism design for combinatorial cost sharing. Imagine that multiple items or services are available to be shared among a set of interested agents. The outcome of a mechanism in this setting consists of an assignment, determining for each item the set of players who are granted service, together with respective payments. Although there are several works studying specialized versions of such problems, there has been almost no progress for general combinatorial cost sharing domains until recently [DobzinskiO17]. The main goal of our work is to further understand this interplay in terms of budget balance and social cost approximation. Towards this, we provide a refinement of cross-monotonicity (trace-monotonicity) that is applicable to iterative mechanisms. The trace here refers to the order in which players become finalized. On top of this, we also provide two parameterizations of cost functions which capture the behavior of their average cost-shares. Based on our trace-monotonicity property, we design a scheme of ascending cost sharing mechanisms which is applicable to the combinatorial cost sharing setting with symmetric submodular valuations. Using our first cost function we identify conditions under which our mechanism is weakly group-strategyproof, O(1)-budget-balanced and O(logn)-approximate with respect to the social cost. Finally, we consider general valuation functions and exploit our second parameterization to derive a more fine-grained analysis of the Sequential Mechanism introduced by Moulin. This mechanism is budget balanced by construction, but in general only guarantees a poor social cost approximation of n. We identify conditions under which the mechanism achieves improved social cost approximation guarantees.