[Show abstract][Hide abstract] ABSTRACT: We use an information-theoretic approach to describe changes in lending relationships between financial institutions around the time of the Lehman Brothers failure. Unlike previous work that conducts maximum likelihood estimation on undirected networks our analysis distinguishes between borrowers and lenders and looks for broader lending relationships (multi-bank lending cycles) that extend beyond the immediate counter-parties. We detect significant changes in lending patterns following implementation of the Interest on Required and Excess Reserves policy by the Federal Reserve in October 2008. Analysis of micro-scale rates of change in the data suggests these changes were triggered by the collapse of Lehman Brothers a few weeks before.
Physica A: Statistical Mechanics and its Applications 04/2015; 424. DOI:10.1016/j.physa.2014.11.034 · 1.73 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Normal anxiety is considered an adaptive response to the possible presence of
danger, but it appears highly susceptible to dysregulation. Anxiety disorders
are prevalent at high frequency in contemporary human societies, yet impose
substantial disability upon their sufferers. This raises a puzzle: why has
evolution left us vulnerable to anxiety disorders? We develop a signal
detection model in which individuals must learn how to calibrate their anxiety
responses: they need to learn which cues indicate danger in the environment. We
study the optimal strategy for doing so, and find that individuals face an
inevitable exploration-exploitation tradeoff between obtaining a better
estimate of the level of risk on one hand, and maximizing current payoffs on
the other. Because of this tradeoff, a subset of the population becomes trapped
in a state of excessive and self-perpetuating anxiety, even when individuals
learn optimally. This phenomenon arises because when individuals become too
cautious, they stop sampling the environment and fail to correct their
misperceptions, whereas when individuals become too careless they continue to
sample the environment and soon discover their mistakes. We suggest that this
process may be involved in the development of excessive anxiety in humans.
[Show abstract][Hide abstract] ABSTRACT: Background: Although the emergence and spread of antibiotic resistance have been well studied for endemic infections, comparably little is understood for epidemic infections such as influenza. The availability of antimicrobial treatments for epidemic diseases raises the urgent question of how to deploy treatments to achieve maximum benefit despite resistance evolution. Recent simulation studies have shown that the number of cases prevented by antimicrobials can be maximized by delaying the use of treatments during an epidemic. Those studies focus on indirect effects of antimicrobial use: preventing disease among untreated individuals. Here, we identify and examine direct effects of antimicrobial use: the number of successfully treated cases.
Methodology: We develop mathematical models to study how the schedule of antiviral use influences the success or failure of subsequent use due to the spread of resistant strains.
Results: Direct effects are maximized by postponing drug use, even with unlimited stockpiles of drugs. This occurs because the early use of antimicrobials disproportionately drives emergence and spread of antibiotic resistance, leading to subsequent treatment failure. However, for antimicrobials with low effect on transmission, the relative benefit of delaying antimicrobial deployment is greatly reduced and can only be reaped if the trajectory of the epidemic can be accurately estimated early.
Conclusions and implications: Health planners face uncertainties during epidemics, including the possibility of early containment. Hence, despite the optimal deployment time near the epidemic peak, it will often be preferable to initiate widespread antimicrobial use as early as possible, particularly if the drug is ineffective in reducing transmission.
[Show abstract][Hide abstract] ABSTRACT: Two categories of evolutionary challenges result from escalating human impacts on the
planet. The first arises from cancers, pathogens, and pests that evolve too quickly and
the second, from the inability of many valued species to adapt quickly enough. Applied
evolutionary biology provides a suite of strategies to address these global challenges
that threaten human health, food security, and biodiversity. This Review highlights both
progress and gaps in genetic, developmental, and environmental manipulations across
the life sciences that either target the rate and direction of evolution or reduce the
mismatch between organisms and human-altered environments. Increased development
and application of these underused tools will be vital in meeting current and future
targets for sustainable development.
[Show abstract][Hide abstract] ABSTRACT: Open access publishing has been proposed as one possible solution to the serials crisis—the rapidly growing subscription prices in scholarly journal publishing. However, open access publishing can present economic pitfalls as well, such as excessive article processing charges. We discuss the decision that an author faces when choosing to submit to an open access journal. We develop an interactive tool to help authors compare among alternative open access venues and thereby get the most for their article processing charges. (JEL I2, C1, A1)
[Show abstract][Hide abstract] ABSTRACT: Abstract In many species, nongenetic phenotypic variation helps mitigate risk associated with an uncertain environment. In some cases, developmental cues can be used to match phenotype to environment-a strategy known as predictive plasticity. When environmental conditions are entirely unpredictable, generating random phenotypic diversity may improve the long-term success of a lineage-a strategy known as diversified bet hedging. When partially reliable information is available, a well-adapted developmental strategy may strike a balance between the two strategies. We use information theory to analyze a model of development in an uncertain environment, where cue reliability is affected by variation both within and between generations. We show that within-generation variation in cues decreases the reliability of cues without affecting their fitness value. This transpires because the optimal balance of predictive plasticity and diversified bet hedging is unchanged. However, within-generation variation in cues does change the developmental mechanisms used to create that balance: developmental sensitivity to such cues not only helps match phenotype to environment but also creates phenotypic diversity that may be useful for hedging bets against environmental change. Understanding the adaptive role of developmental sensitivity thus depends on a proper assessment of both the predictive power and the structure of variation in environmental cues.
The American Naturalist 09/2013; 182(3):313-27. DOI:10.1086/671161 · 3.83 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Costly signalling theory is commonly invoked as an explanation for how honest communication can be stable when interests conflict. However, the signal costs predicted by costly signalling models often turn out to be unrealistically high. These models generally assume that signal cost is determinate. Here, we consider the case where signal cost is instead stochastic. We examine both discrete and continuous signalling games and show that, under reasonable assumptions, stochasticity in signal costs can decrease the average cost at equilibrium for all individuals. This effect of stochasticity for decreasing signal costs is a fundamental mechanism that probably acts in a wide variety of circumstances.
Journal of The Royal Society Interface 07/2013; 10(87):20130469. DOI:10.1098/rsif.2013.0469 · 3.92 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Gender disparities appear to be decreasing in academia according to a number of metrics, such as grant funding, hiring, acceptance at scholarly journals, and productivity, and it might be tempting to think that gender inequity will soon be a problem of the past. However, a large-scale analysis based on over eight million papers across the natural sciences, social sciences, and humanities reveals a number of understated and persistent ways in which gender inequities remain. For instance, even where raw publication counts seem to be equal between genders, close inspection reveals that, in certain fields, men predominate in the prestigious first and last author positions. Moreover, women are significantly underrepresented as authors of single-authored papers. Academics should be aware of the subtle ways that gender disparities can occur in scholarly authorship.
PLoS ONE 07/2013; 8(7):e66212. DOI:10.1371/journal.pone.0066212 · 3.23 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Biogeographic patterns of survival help constrain the causal factors responsible for mass extinction. To test whether biogeography influenced end-Cretaceous (K-Pg) extinction patterns, we used a network approach to delimit biogeographic units (BUs) above the species level in a global Maastrichtian database of 329 bivalve genera. Geographic range is thought to buffer taxa from extinction, but the number of BUs a taxon occurred in superseded geographic range as an extinction predictor. Geographically, we found a latitudinal selectivity gradient for geographic range in the K-Pg, such that higher latitude BUs had lower extinction than expected given the geographic ranges of the genera, implying that (i) high latitude BUs were more resistant to extinction, (ii) the intensity of the K-Pg kill mechanism declined with distance from the tropics, or (iii) both. Our results highlight the importance of macroecological structure in constraining causal mechanisms of extinction and estimating extinction risk of taxa.
[Show abstract][Hide abstract] ABSTRACT: The authors describe a classroom experiment designed to present the idea of two-sided matching, the concept of a stable assignment, and the Gale-Shapley deferred-acceptance mechanism. Participants need no prior training in economics or game theory, but the exercise will also interest trained economists and game theorists.
The Journal of Economic Education 01/2013; 44(1). DOI:10.1080/00220485.2013.740391 · 0.25 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: One strategy for winning a coevolutionary struggle is to evolve rapidly. Most
of the literature on host-pathogen coevolution focuses on this phenomenon, and
looks for consequent evidence of coevolutionary arms races. An alternative
strategy, less often considered in the literature, is to deter rapid
evolutionary change by the opponent. To study how this can be done, we
construct an evolutionary game between a controller that must process
information, and an adversary that can tamper with this information processing.
In this game, a species can foil its antagonist by processing information in a
way that is hard for the antagonist to manipulate. We show that the structure
of the information processing system induces a fitness landscape on which the
adversary population evolves. Complex processing logic can carve long, deep
fitness valleys that slow adaptive evolution in the adversary population. We
suggest that this type of defensive complexity on the part of the vertebrate
adaptive immune system may be an important element of coevolutionary dynamics
between pathogens and their vertebrate hosts. Furthermore, we cite evidence
that the immune control logic is phylogenetically conserved in mammalian
lineages. Thus our model of defensive complexity suggests a new hypothesis for
the lower rates of evolution for immune control logic compared to other immune
[Show abstract][Hide abstract] ABSTRACT: Costly signalling theory has become a common explanation for honest communication when interests conflict. In this paper, we provide an alternative explanation for partially honest communication that does not require significant signal costs. We show that this alternative is at least as plausible as traditional costly signalling, and we suggest a number of experiments that might be used to distinguish the two theories.
Proceedings of the Royal Society B: Biological Sciences 11/2012; 280(1750). DOI:10.1098/rspb.2012.1878 · 5.05 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: In this paper, we show how the Eigenfactor(R) score, originally designed for ranking scholarly journals, can be adapted to rank the scholarly output of authors, institutions, and countries based on authorlevel citation data. Using the methods described herein, we provide Eigenfactor rankings for 84,808 disambiguated authors of 240,804 papers in the Social Science Research Network (SSRN) — a pre and post-print archive devoted to the rapid dissemination of scholarly research in the social sciences and humanities. As an additive metric, the Eigenfactor scores are readily computed for collectives such as departments or institutions as well. We show that a collective’s Eigenfactor score can be computed either by summing the Eigenfactor scores of its members, or by working directly with a collective-level cross-citation matrix. To illustrate, we provide Eigenfactor rankings for institutions and countries in the SSRN repository. With a network-wide comparison of Eigenfactor scores and download tallies, we demonstrate that Eigenfactor scores provide information that is both different from and complementary to that provided by download counts. We see author-level ranking as one filter for navigating the scholarly literature, and note that such rankings generate incentives for more open scholarship, as authors are rewarded for making their work available to the community as early as possible and prior to formal publication. NOTE: Because of the incompleteness of the SSRN CiteReader data at this time, please check back at this URL for updated versions of this paper for updated results over the next 2 years. In addition, when citing this paper please include the following: Data as of March 14, 2011.
Journal of the American Society for Information Science and Technology 08/2012; 64(4). DOI:10.2139/ssrn.1636719 · 1.85 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Structural controllability has been proposed as an analytical framework for making predictions regarding the control of complex networks across myriad disciplines in the physical and life sciences (Liu et al., Nature:473(7346):167-173, 2011). Although the integration of control theory and network analysis is important, we argue that the application of the structural controllability framework to most if not all real-world networks leads to the conclusion that a single control input, applied to the power dominating set, is all that is needed for structural controllability. This result is consistent with the well-known fact that controllability and its dual observability are generic properties of systems. We argue that more important than issues of structural controllability are the questions of whether a system is almost uncontrollable, whether it is almost unobservable, and whether it possesses almost pole-zero cancellations.
PLoS ONE 06/2012; 7(6):e38398. DOI:10.1371/journal.pone.0038398 · 3.23 Impact Factor