Justified Communication Equilibrium

Justified communication equilibrium (JCE) is an equilibrium refinement for signaling games with cheap-talk communication. A strategy profile must be a JCE to be a stable outcome of nonequilibrium learning when receivers are initially trusting and senders play many more times than receivers. In the learning model, the counterfactual “speeches” that have been informally used to motivate past refinements are messages that are actually sent. Stable profiles need not be perfect Bayesian equilibria, so JCE sometimes preserves equilibria that existing refinements eliminate. Despite this, it resembles the earlier refinements D1 and NWBR, and it coincides with them in co-monotonic signaling games. (JEL C70, D82, D83, J23, M51)

Evolutionary coexistence in a fluctuating environment by specialization on resource level

Microbial communities in fluctuating environments can contain many species and diversity within species, both in natural environments such as the human gut, and in laboratory settings when communities are propagated for a long time. Whether this diversity is at the species level, within the species level, or a combination of both, the question remains: what processes lead to the origination and maintenance of this diversity? When nutrient levels fluctuate over time, one possibly relevant process is that different types specialize on low and high nutrient levels. The relevance of this process is supported by observations of types co-existing through this mechanism when put together in the laboratory, and simple models, which show that negative frequency dependence of two types, specialized on low and high resource level, can stabilize coexistence. However, when microbial populations are in an environment for a long time, they will evolve. In this article we determine what happens when species can evolve; whether branching can occur to create diversity and whether evolution will destabilize coexistence. We find that for the trade-off data between growth at low and high substrate concentrations, available for the bacterium Escherichia coli and the yeast Saccharomyces cerevisiae on glucose, there is only a small portion of the trait-space that allows for coexistence. Moreover, this coexistence is destabilized by evolution, and the only evolutionary stable outcome is a single strategy. When we combine two species that are well-adapted on their own, we do find that they can form an evolutionary singular coalition. We conclude that although specialization on resource level can support diversity within a species, it is likely not a cause by itself. In contrast, for species consortia this specialization can lead to evolutionary stable coexistence.

Self-Organized Criticality in Economic Fluctuations: The Age of Maturity

Self-Organized Criticality (SOC) has been proposed as a paradigm that may rationalize the emergence of macrofinancial fluctuations. The wave of innovative thinking sparked by this proposal continues to produce interesting contributions in many areas of economics, ranging from macroeconomics to finance. In this review, we propose a guided tour to these achievements, highlighting that analysis of SOC equilibria is a promising avenue to establish a nexus between i) a statistical equilibrium characterized by the spontaneous emergence of dynamic critical fluctuations and ii) a strategic equilibrium concept modeling a large number of interacting players. The critical state is the stable outcome arising from a trade-off between cooperation and competition.

Deferred Acceptance with Compensation Chains

In a foundational paper, Gale and Shapley (1962) introduced the deferred acceptance algorithm that achieves a stable outcome in a two-sided matching market by letting one side of the market make proposals to the other side. What happens when both sides of the market can propose? In “Deferred Acceptance with Compensation Chains,” Dworczak answers this question by constructing an equitable version of the Gale–Shapley algorithm in which the sequence of proposers can be arbitrary. The main result of the paper shows that the extended algorithm, equipped with so-called compensation chains, is not only guaranteed to converge in polynomial time to a stable outcome, but—in contrast to the original Gale–Shapley algorithm—achieves all stable matchings (as the sequence of proposers vary). The proof of convergence uses a novel potential function. The algorithm may find applications in settings where both stability and fairness are desirable features of the matching process.

Managing differentiated disintegration: Insights from comparative federalism on post-Brexit EU–UK relations

This article applies insights from comparative federalism to analyse different models for managing future EU–UK relations. The argument is that the stability of the EU–UK relationship before as well as after Brexit is best understood by examining the presence of federal safeguards. Drawing on Kelemen, four types of safeguards are identified as the means for balancing centrifugal and centripetal forces. During the United Kingdom’s European Union membership, the strong glue provided by structural and judicial safeguards was undone by the weakness of partisan and socio-cultural ones. However, each post-Brexit scenario is characterised by weaker structural and judicial safeguards. The most stable outcome is an indeterminate Brexit that limits the incentive to politicise sovereignty and identity concerns by ending free movement of people and reducing the saliency of European Union rules. Such stability is nevertheless relative in that, from a comparative perspective, federal-type safeguards were stronger when the United Kingdom was still in the European Union.

Phylogenomic proof of Recurrent Demipolyploidization and Evolutionary Stalling of the “Triploid Bridge” in Arundo (Poaceae)

Polyploidization is a frequent phenomenon in plants, which entails the increase from one generation to the next by multiples of the haploid number of chromosomes. While tetraploidization is arguably the most common and stable outcome of polyploidization, over evolutionary time triploids often constitute only a transient phase, or a “triploid bridge”, between diploid and tetraploid levels. In this study, we reconstructed in a robust phylogenomic and statistical framework the evolutionary history of polyploidization in Arundo, a small genus from the Poaceae family with promising biomass, bioenergy and phytoremediation species. Through the obtainment of 10 novel leaf transcriptomes for Arundo and outgroup species, our results prove that recurrent demiduplication has likely been a major driver of evolution in this species-poor genus. Molecular dating further demonstrates that the species originating by demiduplication stalled in the “triploid bridge” for evolutionary times in the order of millions of years without undergoing tetratploidization. Nevertheless, we found signatures of molecular evolution highlighting some of the processes that accompanied the genus radiation. Our results clarify the complex nature of Arundo evolution and are valuable for future gene functional validation as well as reverse and comparative genomics efforts in the Arundo genus and other Arundinoideae.

Shifts in evolutionary balance of microbial phenotypes under environmental changes

Environmental conditions shape entire communities by driving microbial interactions. These interactions then find their reflection in the evolutionary outcome of microbial competition. In static, homogeneous environments a robust, or evolutionary stable, outcome in microbial communities is reachable, if it exists. However, introducing heterogeneity and time-dependence in microbial ecology leads to stochastic evolutionary outcomes determined by specific environmental changes. We utilise evolutionary game theory to provide insight into phenotypic competition in dynamic environments. We capture these effects in a perturbed evolutionary game describing microbial interactions at a phenotypic level. We show that under regular periodic environmental fluctuations a stable state that preserves dominant phenotypes is reached. However, rapid environmental shifts, especially in a cyclic interactions, can lead to critical shifts in the evolutionary balance among phenotypes. Our analysis suggests that an understanding of the robustness of the systems current state is necessary to understand when system will shift to the new equilibrium. This can be done by understanding the systems overall margin of safety, that is, what level of perturbations it can take before its equilibrium changes. In particular, the extent to which an environmental shift affects the system’s behaviour.

Robustness against Agent Failure in Hedonic Games

We study how stability can be maintained even after any set of at most k players leave their groups, in the context of hedonic games. While stability properties ensure an outcome to be robust against players' deviations, it has not been considered how an unexpected change caused by a sudden deletion of players affects stable outcomes. In this paper we propose a novel criterion that reshapes stability form robustness aspect. We observe that some stability properties can be no longer preserved even when a single agent is removed. However, we obtain positive results by focusing on symmetric friend-oriented hedonic games. We prove that we can efficiently decide the existence of robust outcomes with respect to Nash stability underdeletion of any number of players or contractual individual stability under deletion of a single player. We also prove that symmetric additively separable games always admit an individual stable outcome that is robust with respect to individual rationality.

Causal Inference About Good and Bad Outcomes

People learn differently from good and bad outcomes. We argue that valence-dependent learning asymmetries are partly driven by beliefs about the causal structure of the environment. If hidden causes can intervene to generate bad (or good) outcomes, then a rational observer will assign blame (or credit) to these hidden causes, rather than to the stable outcome distribution. Thus, a rational observer should learn less from bad outcomes when they are likely to have been generated by a hidden cause, and this pattern should reverse when hidden causes are likely to generate good outcomes. To test this hypothesis, we conducted two experiments ( N = 80, N = 255) in which we explicitly manipulated the behavior of hidden agents. This gave rise to both kinds of learning asymmetries in the same paradigm, as predicted by a novel Bayesian model. These results provide a mechanistic framework for understanding how causal attributions contribute to biased learning.