A BARGAINING APPROACH TO COORDINATION IN NETWORKS

This paper presents a model in which players interact via the formation of costly links and the benefits of bilateral interactions are determined by a coordination game. A novel contribution of this paper is that the fraction of the cost borne by each player involved in a bilateral link is not fixed exogenously, but results from bargaining. We analyze the model both in a static and a dynamic setting. Whereas the static game has multiplicity of equilibria, we show that only one is stochastically stable.Coordination; Nash bargaining solution; Risk-dominance; Stochastic stability

NETWORK FORMATION AND COORDINATION: BARGAINING THE DIVISION OF LINK COSTS

This paper presents a model of network formation with costly links. We endogenize the amount of cost born by each player involved in a bilateral link by considering that these shares result from bargaining. We analyze this feature in a context of coordination games. We show that, if the cost of the link is not too high, the complete network arises and players coordinate on the same action. If this cost is higher than the risk-dominance premium the efficient action is selected; instead, if it is lower, the risk-dominant action prevails.Coordination, Nash bargaining solution, Markov process

CNO abundances in the Galactic bulge

The carbon, nitrogen, and oxygen abundances and trends in the bulge are discussed in the context of our recent analysis of these elements in an on-going project based on near-IR spectra (Ryde et al. 2009). We obtained these using the CRIRES spectrometer on the VLT. The formation and evolution of the Milky Way bulge can be constrained by studying elemental abundances of bulge stars. Due to the large and variable visual extinction in the line-of-sight towards the bulge, an analysis in the near-IR is preferred.Comment: Contributed talk at Chemical Abundances in the Universe, Connecting First Stars to Planets, Proceedings of the International Astronomical Union, IAU Symposium, Volume 265, K. Cunha, M. Spite and B. Barbuy, eds, Cambridge University Press, in pres

Voting in small networks with cross-pressure

We present a model of participation in elections in small networks, in which citizens su¤er from cross-pressures if voting against the alternative preferred by some of their social contacts. We analyze how the existence of cross-pressures may shape voting decisions, and so, political outcomes; and how candidates may exploit this e¤ect to their interest.Network; Voting; Cross-Cutting.

Bounded Confidence under Preferential Flip: A Coupled Dynamics of Structural Balance and Opinions

In this work we study the coupled dynamics of social balance and opinion formation. We propose a model where agents form opinions under bounded confidence, but only considering the opinions of their friends. The signs of social ties -friendships and enmities- evolve seeking for social balance, taking into account how similar agents' opinions are. We consider both the case where opinions have one and two dimensions. We find that our dynamics produces the segregation of agents into two cliques, with the opinions of agents in one clique differing from those in the other. Depending on the level of bounded confidence, the dynamics can produce either consensus of opinions within each clique or the coexistence of several opinion clusters in a clique. For the uni-dimensional case, the opinions in one clique are all below the opinions in the other clique, hence defining a "left clique" and a "right clique". In the two-dimensional case, our numerical results suggest that the two cliques are separated by a hyperplane in the opinion space. We also show that the phenomenon of unidimensional opinions identified by DeMarzo, Vayanos and Zwiebel (Q J Econ 2003) extends partially to our dynamics. Finally, in the context of politics, we comment about the possible relation of our results to the fragmentation of an ideology and the emergence of new political parties.Comment: 8 figures, PLoS ONE 11(10): e0164323, 201

A physical model suggests that hip-localized balance sense in birds improves state estimation in perching: implications for bipedal robots

In addition to a vestibular system, birds uniquely have a balance-sensing organ within the pelvis, called the lumbosacral organ (LSO). The LSO is well developed in terrestrial birds, possibly to facilitate balance control in perching and terrestrial locomotion. No previous studies have quantified the functional benefits of the LSO for balance. We suggest two main benefits of hip-localized balance sense: reduced sensorimotor delay and improved estimation of foot-ground acceleration. We used system identification to test the hypothesis that hip-localized balance sense improves estimates of foot acceleration compared to a head-localized sense, due to closer proximity to the feet. We built a physical model of a standing guinea fowl perched on a platform, and used 3D accelerometers at the hip and head to replicate balance sense by the LSO and vestibular systems. The horizontal platform was attached to the end effector of a 6 DOF robotic arm, allowing us to apply perturbations to the platform analogous to motions of a compliant branch. We also compared state estimation between models with low and high neck stiffness. Cross-correlations revealed that foot-to-hip sensing delays were shorter than foot-to-head, as expected. We used multi-variable output error state-space (MOESP) system identification to estimate foot-ground acceleration as a function of hip- and head-localized sensing, individually and combined. Hip-localized sensors alone provided the best state estimates, which were not improved when fused with head-localized sensors. However, estimates from head-localized sensors improved with higher neck stiffness. Our findings support the hypothesis that hip-localized balance sense improves the speed and accuracy of foot state estimation compared to head-localized sense. The findings also suggest a role of neck muscles for active sensing for balance control: increased neck stiffness through muscle co-contraction can improve the utility of vestibular signals. Our engineering approach provides, to our knowledge, the first quantitative evidence for functional benefits of the LSO balance sense in birds. The findings support notions of control modularity in birds, with preferential vestibular sense for head stability and gaze, and LSO for body balance control,respectively. The findings also suggest advantages for distributed and active sensing for agile locomotion in compliant bipedal robots

Branching Deregulation and Merger Optimality

The U.S. banking industry has been characterized by intense merger activity in the absence of economies of scale and scope. We claim that the loosening of geographic constraints on U.S. banks is responsible for this consolidation process, irrespective of value-maximizing motives. We demonstrate this by putting forward a theoretical model of banking competition and studying banks’ strategic responses to geographic deregulation. We show that even in the absence of economies of scale and scope, bank mergers represent an optimal response. Also, we show that the consolidation process is characterized by merger waves and that some equilibrium mergers are not profitable per se -they yield losses- but become profitable as the waves of mergers unfold.Banking Competition, Deregulation, Mergers

Maximizing the Expected Revenue: The Use of Machine Learning Models for the Case of a Soccer Ball Company

Every company begins with a fundamental questions and re-asks this questions several times throughout the company´s life, what is the product that will create enough value for it´s customers so that enough money can be charged to make a profit and keep on creating more value? So basically, a company´s strategy begins with a great product design and a price tag that customers are willing to pay that will maximize revenue. In past years, pricing has been so unattended because usually the responsibility tends to fall under different areas of the company and due to it´s complexity, task associated with setting prices are often not on top of the incumbency list. Ergo, prices are not varied enough for different product items, market segments and purchased occasion, impacting the demand, sales and perceived value of the product and brand. Therefore, this study aimed to determine how can machine learning models help create value and maximize revenue by determining the best product and price for a soccer ball company in Mexico. As a result, this research was able to determine that there are 3 different customer segments and that each of them values different characteristics of the soccer ball. Also, that a random forest model was the best model to calculate the purchase probabilities compared to a naive bayes model, a general linear model with logit link and a support vector machine model. Given those probabilities, the expected revenue was calculated for all the different product profiles, or combinations of the ball, and concluded that a price discriminated model with 3 balls; 1 targeted for each customer segment, can increase the expected revenue from an approximate of $166 to$1,572 dollars, proving that machine learning models and information-based decision making processes should be a must for every compan

Sedimentología de la Formación Calizas con oncolitos de Higueruelas (Malm) en la región de Muel-Belchite (Provincia de Zaragoza)

El estudio sedimentológico de la Formación Higueruelas (Malm) en la región de Muel-Belchite, permite definir un ciclo regresivo con gran variedad de facies y ambientes, con desarrollo en la plataforma interna de montículos algales y coralinos, y sedimentación oolítica litoral