931 resultados para Cournot equilibrium, non-cooperative oligopoly, quasi-competitiveness, stability


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Theories on social capital and on social entrepreneurship have mainly highlighted the attitude of social capital to generate enterprises and to foster good relations between third sector organizations and the public sector. This paper considers the social capital in a specific third sector enterprise; here, multi-stakeholder social cooperatives are seen, at the same time, as social capital results, creators and incubators. In the particular enterprises that identify themselves as community social enterprises, social capital, both as organizational and relational capital, is fundamental: SCEs arise from but also produce and disseminate social capital. This paper aims to improve the building of relational social capital and the refining of helpful relations drawn from other arenas, where they were created and from where they are sometimes transferred to other realities, where their role is carried on further (often working in non-profit, horizontally and vertically arranged groups, where they share resources and relations). To represent this perspective, we use a qualitative system dynamic approach in which social capital is measured using proxies. Cooperation of volunteers, customers, community leaders and third sector local organizations is fundamental to establish trust relations between public local authorities and cooperatives. These relations help the latter to maintain long-term contracts with local authorities as providers of social services and enable them to add innovation to their services, by developing experiences and management models and maintaining an interchange with civil servants regarding these matters. The long-term relations and the organizational relations linking SCEs and public organizations help to create and to renovate social capital. Thus, multi-stakeholder cooperatives originated via social capital developed in third sector organizations produce new social capital within the cooperatives themselves and between different cooperatives (entrepreneurial components of the third sector) and the public sector. In their entrepreneurial life, cooperatives have to contrast the "working drift," as a result of which only workers remain as members of the cooperative, while other stakeholders leave the organization. Those who are not workers in the cooperative are (stake)holders with "weak ties," who are nevertheless fundamental in making a worker's cooperative an authentic social multi-stakeholders cooperative. To maintain multi-stakeholder governance and the relations with third sector and civil society, social cooperatives have to reinforce participation and dialogue with civil society through ongoing efforts to include people that provide social proposals. We try to represent these processes in a system dynamic model applied to local cooperatives, measuring the social capital created by the social cooperative through proxies, such as number of volunteers and strong cooperation with public institutions. Using a reverse-engineering approach, we can individuate the determinants of the creation of social capital and thereby give support to governance that creates social capital.

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A quasi-defined medium that supports the growth of Streptococcus agalactiae as pigmented colonies has been developed. The medium contains starch, a peptic digest of albumin, amino acids, nucleosides, vitamins, and salts. The presence of free cysteine, which could be replaced with other sulphur-containing compounds and to a lesser degree by reducing agents, was required for pigment formation.

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This paper is a sequel to ``Normal forms, stability and splitting of invariant manifolds I. Gevrey Hamiltonians", in which we gave a new construction of resonant normal forms with an exponentially small remainder for near-integrable Gevrey Hamiltonians at a quasi-periodic frequency, using a method of periodic approximations. In this second part we focus on finitely differentiable Hamiltonians, and we derive normal forms with a polynomially small remainder. As applications, we obtain a polynomially large upper bound on the stability time for the evolution of the action variables and a polynomially small upper bound on the splitting of invariant manifolds for hyperbolic tori.

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BACKGROUND: Invasive fungal diseases are important causes of morbidity and mortality. Clarity and uniformity in defining these infections are important factors in improving the quality of clinical studies. A standard set of definitions strengthens the consistency and reproducibility of such studies. METHODS: After the introduction of the original European Organization for Research and Treatment of Cancer/Invasive Fungal Infections Cooperative Group and the National Institute of Allergy and Infectious Diseases Mycoses Study Group (EORTC/MSG) Consensus Group definitions, advances in diagnostic technology and the recognition of areas in need of improvement led to a revision of this document. The revision process started with a meeting of participants in 2003, to decide on the process and to draft the proposal. This was followed by several rounds of consultation until a final draft was approved in 2005. This was made available for 6 months to allow public comment, and then the manuscript was prepared and approved. RESULTS: The revised definitions retain the original classifications of "proven," "probable," and "possible" invasive fungal disease, but the definition of "probable" has been expanded, whereas the scope of the category "possible" has been diminished. The category of proven invasive fungal disease can apply to any patient, regardless of whether the patient is immunocompromised, whereas the probable and possible categories are proposed for immunocompromised patients only. CONCLUSIONS: These revised definitions of invasive fungal disease are intended to advance clinical and epidemiological research and may serve as a useful model for defining other infections in high-risk patients.

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Evaluating the possible benefits of the introduction of genetically modified (GM) crops must address the issue of consumer resistance as well as the complex regulation that has ensued. In the European Union (EU) this regulation envisions the “co-existence” of GM food with conventional and quality-enhanced products, mandates the labelling and traceability of GM products, and allows only a stringent adventitious presence of GM content in other products. All these elements are brought together within a partial equilibrium model of the EU agricultural food sector. The model comprises conventional, GM and organic food. Demand is modelled in a novel fashion, whereby organic and conventional products are treated as horizontally differentiated but GM products are vertically differentiated (weakly inferior) relative to conventional ones. Supply accounts explicitly for the land constraint at the sector level and for the need for additional resources to produce organic food. Model calibration and simulation allow insights into the qualitative and quantitative effects of the large-scale introduction of GM products in the EU market. We find that the introduction of GM food reduces overall EU welfare, mostly because of the associated need for costly segregation of non-GM products, but the producers of quality-enhanced products actually benefit.

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Explaining the evolution of sociality is challenging because social individuals face disadvantages that must be balanced by intrinsic benefits of living in a group. One potential route towards the evolution of sociality may emerge from the avoidance of dispersal, which can be risky in some environments. Although early studies found that local competition may cancel the benefits of cooperation in viscous populations, subsequent studies have identified conditions, such as the presence of kin recognition or specific demographic conditions, under which altruism will still spread. Most of these studies assume that the costs of cooperating outweigh the direct benefits (strong altruism). In nature, however, many organisms gain synergistic benefits from group living, which may counterbalance even costly altruistic behaviours. Here, we use an individual based model to investigate how dispersal and social behaviour co-evolve when social behaviours result in synergistic benefits that counterbalance the relative cost of altruism to a greater extent than assumed in previous models. When the cost of cooperation is high, selection for sociality responds strongly to the cost of dispersal. In particular, cooperation can begin to spread in a population when higher cooperation levels become correlated with lower dispersal tendencies within individuals. In contrast, less costly social behaviours are less sensitive to the cost of dispersal. In line with previous studies, we find that mechanisms of global population control also affect this relationship: when whole patches (groups) go extinct each generation, selection favours a relatively high dispersal propensity, and social behaviours evolve only when they are not very costly. If random individuals within groups experience mortality each generation to maintain a global carrying capacity, on the other hand, social behaviours spread and dispersal is reduced, even when the latter is not costly.

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Abstract The object of game theory lies in the analysis of situations where different social actors have conflicting requirements and where their individual decisions will all influence the global outcome. In this framework, several games have been invented to capture the essence of various dilemmas encountered in many common important socio-economic situations. Even though these games often succeed in helping us understand human or animal behavior in interactive settings, some experiments have shown that people tend to cooperate with each other in situations for which classical game theory strongly recommends them to do the exact opposite. Several mechanisms have been invoked to try to explain the emergence of this unexpected cooperative attitude. Among them, repeated interaction, reputation, and belonging to a recognizable group have often been mentioned. However, the work of Nowak and May (1992) showed that the simple fact of arranging the players according to a spatial structure and only allowing them to interact with their immediate neighbors is sufficient to sustain a certain amount of cooperation even when the game is played anonymously and without repetition. Nowak and May's study and much of the following work was based on regular structures such as two-dimensional grids. Axelrod et al. (2002) showed that by randomizing the choice of neighbors, i.e. by actually giving up a strictly local geographical structure, cooperation can still emerge, provided that the interaction patterns remain stable in time. This is a first step towards a social network structure. However, following pioneering work by sociologists in the sixties such as that of Milgram (1967), in the last few years it has become apparent that many social and biological interaction networks, and even some technological networks, have particular, and partly unexpected, properties that set them apart from regular or random graphs. Among other things, they usually display broad degree distributions, and show small-world topological structure. Roughly speaking, a small-world graph is a network where any individual is relatively close, in terms of social ties, to any other individual, a property also found in random graphs but not in regular lattices. However, in contrast with random graphs, small-world networks also have a certain amount of local structure, as measured, for instance, by a quantity called the clustering coefficient. In the same vein, many real conflicting situations in economy and sociology are not well described neither by a fixed geographical position of the individuals in a regular lattice, nor by a random graph. Furthermore, it is a known fact that network structure can highly influence dynamical phenomena such as the way diseases spread across a population and ideas or information get transmitted. Therefore, in the last decade, research attention has naturally shifted from random and regular graphs towards better models of social interaction structures. The primary goal of this work is to discover whether or not the underlying graph structure of real social networks could give explanations as to why one finds higher levels of cooperation in populations of human beings or animals than what is prescribed by classical game theory. To meet this objective, I start by thoroughly studying a real scientific coauthorship network and showing how it differs from biological or technological networks using divers statistical measurements. Furthermore, I extract and describe its community structure taking into account the intensity of a collaboration. Finally, I investigate the temporal evolution of the network, from its inception to its state at the time of the study in 2006, suggesting also an effective view of it as opposed to a historical one. Thereafter, I combine evolutionary game theory with several network models along with the studied coauthorship network in order to highlight which specific network properties foster cooperation and shed some light on the various mechanisms responsible for the maintenance of this same cooperation. I point out the fact that, to resist defection, cooperators take advantage, whenever possible, of the degree-heterogeneity of social networks and their underlying community structure. Finally, I show that cooperation level and stability depend not only on the game played, but also on the evolutionary dynamic rules used and the individual payoff calculations. Synopsis Le but de la théorie des jeux réside dans l'analyse de situations dans lesquelles différents acteurs sociaux, avec des objectifs souvent conflictuels, doivent individuellement prendre des décisions qui influenceront toutes le résultat global. Dans ce cadre, plusieurs jeux ont été inventés afin de saisir l'essence de divers dilemmes rencontrés dans d'importantes situations socio-économiques. Bien que ces jeux nous permettent souvent de comprendre le comportement d'êtres humains ou d'animaux en interactions, des expériences ont montré que les individus ont parfois tendance à coopérer dans des situations pour lesquelles la théorie classique des jeux prescrit de faire le contraire. Plusieurs mécanismes ont été invoqués pour tenter d'expliquer l'émergence de ce comportement coopératif inattendu. Parmi ceux-ci, la répétition des interactions, la réputation ou encore l'appartenance à des groupes reconnaissables ont souvent été mentionnés. Toutefois, les travaux de Nowak et May (1992) ont montré que le simple fait de disposer les joueurs selon une structure spatiale en leur permettant d'interagir uniquement avec leurs voisins directs est suffisant pour maintenir un certain niveau de coopération même si le jeu est joué de manière anonyme et sans répétitions. L'étude de Nowak et May, ainsi qu'un nombre substantiel de travaux qui ont suivi, étaient basés sur des structures régulières telles que des grilles à deux dimensions. Axelrod et al. (2002) ont montré qu'en randomisant le choix des voisins, i.e. en abandonnant une localisation géographique stricte, la coopération peut malgré tout émerger, pour autant que les schémas d'interactions restent stables au cours du temps. Ceci est un premier pas en direction d'une structure de réseau social. Toutefois, suite aux travaux précurseurs de sociologues des années soixante, tels que ceux de Milgram (1967), il est devenu clair ces dernières années qu'une grande partie des réseaux d'interactions sociaux et biologiques, et même quelques réseaux technologiques, possèdent des propriétés particulières, et partiellement inattendues, qui les distinguent de graphes réguliers ou aléatoires. Entre autres, ils affichent en général une distribution du degré relativement large ainsi qu'une structure de "petit-monde". Grossièrement parlant, un graphe "petit-monde" est un réseau où tout individu se trouve relativement près de tout autre individu en termes de distance sociale, une propriété également présente dans les graphes aléatoires mais absente des grilles régulières. Par contre, les réseaux "petit-monde" ont, contrairement aux graphes aléatoires, une certaine structure de localité, mesurée par exemple par une quantité appelée le "coefficient de clustering". Dans le même esprit, plusieurs situations réelles de conflit en économie et sociologie ne sont pas bien décrites ni par des positions géographiquement fixes des individus en grilles régulières, ni par des graphes aléatoires. De plus, il est bien connu que la structure même d'un réseau peut passablement influencer des phénomènes dynamiques tels que la manière qu'a une maladie de se répandre à travers une population, ou encore la façon dont des idées ou une information s'y propagent. Ainsi, durant cette dernière décennie, l'attention de la recherche s'est tout naturellement déplacée des graphes aléatoires et réguliers vers de meilleurs modèles de structure d'interactions sociales. L'objectif principal de ce travail est de découvrir si la structure sous-jacente de graphe de vrais réseaux sociaux peut fournir des explications quant aux raisons pour lesquelles on trouve, chez certains groupes d'êtres humains ou d'animaux, des niveaux de coopération supérieurs à ce qui est prescrit par la théorie classique des jeux. Dans l'optique d'atteindre ce but, je commence par étudier un véritable réseau de collaborations scientifiques et, en utilisant diverses mesures statistiques, je mets en évidence la manière dont il diffère de réseaux biologiques ou technologiques. De plus, j'extrais et je décris sa structure de communautés en tenant compte de l'intensité d'une collaboration. Finalement, j'examine l'évolution temporelle du réseau depuis son origine jusqu'à son état en 2006, date à laquelle l'étude a été effectuée, en suggérant également une vue effective du réseau par opposition à une vue historique. Par la suite, je combine la théorie évolutionnaire des jeux avec des réseaux comprenant plusieurs modèles et le réseau de collaboration susmentionné, afin de déterminer les propriétés structurelles utiles à la promotion de la coopération et les mécanismes responsables du maintien de celle-ci. Je mets en évidence le fait que, pour ne pas succomber à la défection, les coopérateurs exploitent dans la mesure du possible l'hétérogénéité des réseaux sociaux en termes de degré ainsi que la structure de communautés sous-jacente de ces mêmes réseaux. Finalement, je montre que le niveau de coopération et sa stabilité dépendent non seulement du jeu joué, mais aussi des règles de la dynamique évolutionnaire utilisées et du calcul du bénéfice d'un individu.

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We estimate a forward-looking monetary policy reaction function for thepostwar United States economy, before and after Volcker's appointmentas Fed Chairman in 1979. Our results point to substantial differencesin the estimated rule across periods. In particular, interest ratepolicy in the Volcker-Greenspan period appears to have been much moresensitive to changes in expected inflation than in the pre-Volckerperiod. We then compare some of the implications of the estimated rulesfor the equilibrium properties of inflation and output, using a simplemacroeconomic model, and show that the Volcker-Greenspan rule is stabilizing.

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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.

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This paper explores the relationships between noncooperative bargaining games and the consistent value for non-transferable utility (NTU) cooperative games. A dynamic approach to the consistent value for NTU games is introduced: the consistent vector field. The main contribution of the paper is to show that the consistent field is intimately related to the concept of subgame perfection for finite horizon noncooperative bargaining games, as the horizon goes to infinity and the cost of delay goes to zero. The solutions of the dynamic system associated to the consistent field characterize the subgame perfect equilibrium payoffs of the noncooperative bargaining games. We show that for transferable utility, hyperplane and pure bargaining games, the dynamics of the consistent fields converge globally to the unique consistent value. However, in the general NTU case, the dynamics of the consistent field can be complex. An example is constructed where the consistent field has cyclic solutions; moreover, the finite horizon subgame perfect equilibria do not approach the consistent value.

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This paper illustrates the philosophy which forms the basis of calibrationexercises in general equilibrium macroeconomic models and the details of theprocedure, the advantages and the disadvantages of the approach, with particularreference to the issue of testing ``false'' economic models. We provide anoverview of the most recent simulation--based approaches to the testing problemand compare them to standard econometric methods used to test the fit of non--lineardynamic general equilibrium models. We illustrate how simulation--based techniques can be used to formally evaluate the fit of a calibrated modelto the data and obtain ideas on how to improve the model design using a standardproblem in the international real business cycle literature, i.e. whether amodel with complete financial markets and no restrictions to capital mobility is able to reproduce the second order properties of aggregate savingand aggregate investment in an open economy.

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In an experimental standard Cournot Oligopoly we test the importance ofmodels of behavior characterized by imitation of succesful behavior. Wefind that the players appear to the rather reluctant to imitate.

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This paper studies equilibria for economies characterized by moral hazard(hidden action), in which the set of contracts marketed in equilibrium isdetermined by the interaction of financial intermediaries.The crucial aspect of the environment that we study is thatintermediaries are restricted to trade non-exclusive contracts: theagents' contractual relationships with competing intermediaries cannot bemonitored (or are not contractible upon). We fully characterize equilibrium allocations and contracts. In thisset-up equilibrium allocations are clearly incentive constrainedinefficient. A robust property of equilibria with non-exclusivity isthat the contracts issued in equilibrium do not implement the optimalaction. Moreover we prove that, whenever equilibrium contracts doimplement the optimal action, intermediaries make positive profits andequilibrium allocations are third best inefficient (where the definitionof third best efficiency accounts for constraints which capture thenon-exclusivity of contracts).

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In this article we show that in the presence of trading constraints, such as short sale constraints, the standard definition of a Rational Expectations Equilibrium allows for equilibrium prices that reveal information unknown to any active trader in the market. We propose a new definition of the Rational Expectations Equilibrium that incorporates a stronger measurability condition than measurability with respect to the join of the information sets of the agents and give an example of non-existence of equilibrium. The example is robust to perturbations on the data of the economy and the introduction of new assets.

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The only currently available method to measure brain glycogen in vivo is 13C NMR spectroscopy. Incorporation of 13C-labeled glucose (Glc) is necessary to allow glycogen measurement, but might be affected by turnover changes. Our aim was to measure glycogen absolute concentration in the rat brain by eliminating label turnover as variable. The approach is based on establishing an increased, constant 13C isotopic enrichment (IE). 13C-Glc infusion is then performed at the IE of brain glycogen. As glycogen IE cannot be assessed in vivo, we validated that it can be inferred from that of N-acetyl-aspartate IE in vivo: After [1-13C]-Glc ingestion, glycogen IE was 2.2 +/- 0.1 fold that of N-acetyl-aspartate (n = 11, R(2) = 0.77). After subsequent Glc infusion, glycogen IE equaled brain Glc IE (n = 6, paired t-test, p = 0.37), implying isotopic steady-state achievement and complete turnover of the glycogen molecule. Glycogen concentration measured in vivo by 13C NMR (mean +/- SD: 5.8 +/- 0.7 micromol/g) was in excellent agreement with that in vitro (6.4 +/- 0.6 micromol/g, n = 5). When insulin was administered, the stability of glycogen concentration was analogous to previous biochemical measurements implying that glycogen turnover is activated by insulin. We conclude that the entire glycogen molecule is turned over and that insulin activates glycogen turnover.