The molecular basis of social behavior: models, methods and advances.

Elucidating the molecular and neural basis of complex social behaviors such as communal living, division of labor and warfare requires model organisms that exhibit these multi-faceted behavioral phenotypes. Social insects, such as ants, bees, wasps and termites, are attractive models to address this problem, with rich ecological and ethological foundations. However, their atypical systems of reproduction have hindered application of classical genetic approaches. In this review, we discuss how recent advances in social insect genomics, transcriptomics, and functional manipulations have enhanced our ability to observe and perturb gene expression, physiology and behavior in these species. Such developments begin to provide an integrated view of the molecular and cellular underpinnings of complex social behavior.

Les cures hybrides des lésions anévrismales [Hybrid treatment of aortic aneurysms]

The hybrid treatment of aortic aneurysms is indicated in patients having the ostia of supra aortic or visceral branches taken in to the aneurysm. Indeed, these lesions are not eligible for classic endovascular treatment because the existing endoprostheses cannot provide perfusion of the side branches without inducing major endoleaks. The surgical technique consists of 2 steps: firstly, a by-pass between normal aorta and the major aortic branches involved in the aneurysm is performed to guarantee the perfusion of the organs such as brain, bowel, and after endoprosthesis deployment. Secondly, the endoprosthesis is deployed using the classical technique to isolate the aneurysm. The hybrid approach provides safe and reliable treatment of complex aortic aneurysms with mortality and morbidity rate far below the classical open surgery.

Two-sided learning in New Keynesian models: Dynamics, (lack of) convergence and the value of information

This paper investigates the role of learning by private agents and the central bank(two-sided learning) in a New Keynesian framework in which both sides of the economyhave asymmetric and imperfect knowledge about the true data generating process. Weassume that all agents employ the data that they observe (which may be distinct fordifferent sets of agents) to form beliefs about unknown aspects of the true model ofthe economy, use their beliefs to decide on actions, and revise these beliefs througha statistical learning algorithm as new information becomes available. We study theshort-run dynamics of our model and derive its policy recommendations, particularlywith respect to central bank communications. We demonstrate that two-sided learningcan generate substantial increases in volatility and persistence, and alter the behaviorof the variables in the model in a significant way. Our simulations do not convergeto a symmetric rational expectations equilibrium and we highlight one source thatinvalidates the convergence results of Marcet and Sargent (1989). Finally, we identifya novel aspect of central bank communication in models of learning: communicationcan be harmful if the central bank's model is substantially mis-specified.

Selective hiring and welfare analysis in labor market models

Firms select not only how many, but also which workers to hire. Yet, in standardsearch models of the labor market, all workers have the same probability of being hired.We argue that selective hiring crucially affects welfare analysis. Our model is isomorphicto a search model under random hiring but allows for selective hiring. With selectivehiring, the positive predictions of the model change very little, but the welfare costsof unemployment are much larger because unemployment risk is distributed unequallyacross workers. As a result, optimal unemployment insurance may be higher and welfareis lower if hiring is selective.

Bridging DSGE models and the raw data

A method to estimate DSGE models using the raw data is proposed. The approachlinks the observables to the model counterparts via a flexible specification which doesnot require the model-based component to be solely located at business cycle frequencies,allows the non model-based component to take various time series patterns, andpermits model misspecification. Applying standard data transformations induce biasesin structural estimates and distortions in the policy conclusions. The proposed approachrecovers important model-based features in selected experimental designs. Twowidely discussed issues are used to illustrate its practical use.

Calibration of stochastic volatility models via second order approximation: the Heston model case

Using a suitable Hull and White type formula we develop a methodology to obtain asecond order approximation to the implied volatility for very short maturities. Using thisapproximation we accurately calibrate the full set of parameters of the Heston model. Oneof the reasons that makes our calibration for short maturities so accurate is that we alsotake into account the term-structure for large maturities. We may say that calibration isnot "memoryless", in the sense that the option's behavior far away from maturity doesinfluence calibration when the option gets close to expiration. Our results provide a wayto perform a quick calibration of a closed-form approximation to vanilla options that canthen be used to price exotic derivatives. The methodology is simple, accurate, fast, andit requires a minimal computational cost.

Isotopic variation across the Audubon's-myrtle warbler hybrid zone.

Differences in seasonal migratory behaviours are thought to be an important component of reproductive isolation in many organisms. Stable isotopes have been used with success in estimating the location and qualities of disjunct breeding and wintering areas. However, few studies have used isotopic data to estimate the movements of hybrid offspring in species that form hybrid zones. Here, we use stable hydrogen to estimate the wintering locations and migratory patterns of two common and widespread migratory birds, Audubon's (Setophaga auduboni) and myrtle (S. coronata) warblers, as well as their hybrids. These two species form a narrow hybrid zone with extensive interbreeding in the Rocky Mountains of British Columbia and Alberta, Canada, which has been studied for over four decades. Isotopes in feathers grown on the wintering grounds or early on migration reveal three important patterns: (1) Audubon's and myrtle warblers from allopatric breeding populations winter in isotopically different environments, consistent with band recovery data and suggesting that there is a narrow migratory transition between the two species, (2) most hybrids appear to overwinter in the south-eastern USA, similar to where myrtle warblers are known to winter, and (3) some hybrid individuals, particularly those along the western edge of the hybrid zone, show Audubon's-like isotopic patterns. These data suggest there is a migratory divide between these two species, but that it is not directly coincident with the centre of the hybrid zone in the breeding range. We interpret these findings and discuss them within the context of previous research on hybrid zones, speciation and migratory divides.

Solving non-linear stochastic models by parameterizing expectations: An application to asset pricing with production

A new algorithm called the parameterized expectations approach(PEA) for solving dynamic stochastic models under rational expectationsis developed and its advantages and disadvantages are discussed. Thisalgorithm can, in principle, approximate the true equilibrium arbitrarilywell. Also, this algorithm works from the Euler equations, so that theequilibrium does not have to be cast in the form of a planner's problem.Monte--Carlo integration and the absence of grids on the state variables,cause the computation costs not to go up exponentially when the numberof state variables or the exogenous shocks in the economy increase. \\As an application we analyze an asset pricing model with endogenousproduction. We analyze its implications for time dependence of volatilityof stock returns and the term structure of interest rates. We argue thatthis model can generate hump--shaped term structures.