864 resultados para Information search – models


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Two-stage game models of information acquisition in stochastic oligopoliesrequire the unrealistic assumption that firms observe the precision ofinformation chosen by their competitors before determining quantities. Thispaper analyzes secret information acquisition as a one-stage game. Relativeto the two-stage game firms are shown to acquire less information. Policyimplications based on the two-stage game yield, therefore, too high taxes ortoo low subsidies for research activities. For the case of heterogeneousduopoly it is shown that comparative statics results partly depend on theobservability assumption.

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We show that unconditionally efficient returns do not achieve the maximum unconditionalSharpe ratio, neither display zero unconditional Jensen s alphas, when returns arepredictable. Next, we define a new type of efficient returns that is characterized by thoseunconditional properties. We also study a different type of efficient returns that is rationalizedby standard mean-variance preferences and motivates new Sharpe ratios and Jensen salphas. We revisit the testable implications of asset pricing models from the perspective ofthe three sets of efficient returns. We also revisit the empirical evidence on the conditionalvariants of the CAPM and the Fama-French model from a portfolio perspective.

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Until recently farm management made little use of accounting and agriculture has been largely excluded from the scope of accounting standards. This article examines the current use of accounting in agriculture and points theneed to establish accounting standards for agriculture. Empirical evidence shows that accounting can make a significant contribution to agricultural management and farm viability and could also be important for other agents involved in agricultural decision making. Existing literature on failureprediction models and farm viability prediction studies provide the starting point for our research, in which two dichotomous logit models were applied to subsamples of viable and unviable farms in Catalonia, Spain. The firstmodel considered only non-financial variables, while the other also considered financial ones. When accounting variables were added to the model, a significant reduction in deviance was observed.

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We perform an experiment on a pure coordination game with uncertaintyabout the payoffs. Our game is closely related to models that have beenused in many macroeconomic and financial applications to solve problemsof equilibrium indeterminacy. In our experiment each subject receives anoisy signal about the true payoffs. This game has a unique strategyprofile that survives the iterative deletion of strictly dominatedstrategies (thus a unique Nash equilibrium). The equilibrium outcomecoincides, on average, with the risk-dominant equilibrium outcome ofthe underlying coordination game. The behavior of the subjects convergesto the theoretical prediction after enough experience has been gained. The data (and the comments) suggest that subjects do not apply through"a priori" reasoning the iterated deletion of dominated strategies.Instead, they adapt to the responses of other players. Thus, the lengthof the learning phase clearly varies for the different signals. We alsotest behavior in a game without uncertainty as a benchmark case. The gamewith uncertainty is inspired by the "global" games of Carlsson and VanDamme (1993).

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We use subjects actions in modified dictator games to perform a within-subject classification ofindividuals into four different types of interdependent preferences: Selfish, Social Welfaremaximizers, Inequity Averse and Competitive. We elicit beliefs about other subjects actions inthe same modified dictator games to test how much of the existent heterogeneity in others actions is known by subjects. We find that subjects with different interdependent preferences infact have different beliefs about others actions. In particular, Selfish individuals cannotconceive others being non-Selfish while Social Welfare maximizers are closest to the actualdistribution of others actions. We finally provide subjects with information on other subjects actions and re-classify individuals according to their (new) actions in the same modified dictatorgames. We find that social information does not affect Selfish individuals, but that individualswith interdependent preferences are more likely to change their behavior and tend to behavemore selfishly.

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This paper theoretically and empirically documents a puzzle that arises when an RBC economy with a job matching function is used to model unemployment. The standard model can generate sufficiently large cyclical fluctuations in unemployment, or a sufficiently small response of unemployment to labor market policies, but it cannot do both. Variable search and separation, finite UI benefit duration, efficiency wages, and capital all fail to resolve this puzzle. However, either sticky wages or match-specific productivity shocks can improve the model's performance by making the firm's flow of surplus more procyclical, which makes hiring more procyclical too.

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A new direction of research in Competitive Location theory incorporatestheories of Consumer Choice Behavior in its models. Following thisdirection, this paper studies the importance of consumer behavior withrespect to distance or transportation costs in the optimality oflocations obtained by traditional Competitive Location models. To dothis, it considers different ways of defining a key parameter in thebasic Maximum Capture model (MAXCAP). This parameter will reflectvarious ways of taking into account distance based on several ConsumerChoice Behavior theories. The optimal locations and the deviation indemand captured when the optimal locations of the other models are usedinstead of the true ones, are computed for each model. A metaheuristicbased on GRASP and Tabu search procedure is presented to solve all themodels. Computational experience and an application to 55-node networkare also presented.

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BACKGROUND: Internet is commonly used by the general population, notably for health information-seeking. There has been little research into its use by patients treated for a psychiatric disorder. AIM: To evaluate the use of internet by patients with psychiatric disorders in searching for general and medical information. METHODS: In 2007, 319 patients followed in a university hospital psychiatric out-patient clinic, completed a 28-items self-administered questionnaire. RESULTS: Two hundred patients surveyed were internet users. Most of them (68.5%) used internet in order to find health-related information. Only a small part of the patients knew and used criteria reflecting the quality of contents of the websites consulted. Knowledge of English and private Internet access were the factors significantly associated with the search of information on health on Internet. CONCLUSIONS: Internet is currently used by patients treated for psychiatric disorders, especially for medical seeking information.

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Models are presented for the optimal location of hubs in airline networks, that take into consideration the congestion effects. Hubs, which are the most congested airports, are modeled as M/D/c queuing systems, that is, Poisson arrivals, deterministic service time, and {\em c} servers. A formula is derived for the probability of a number of customers in the system, which is later used to propose a probabilistic constraint. This constraint limits the probability of {\em b} airplanes in queue, to be lesser than a value $\alpha$. Due to the computational complexity of the formulation. The model is solved using a meta-heuristic based on tabu search. Computational experience is presented.

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Many models in the economics literature deal with strategic situations withprivately informed agents. In those models the information structure isassumed to be exogenous and common knowledge. We consider whether suchmodels, and the results they produce, are robust with respect theendogenization of the information structure. The results depend on whetherinformation acquisition is secret or private, and on whether the strategicsituation involves simultaneous or sequential moves. In particular we findthat only when information is secretly acquired and moves are simultaneous,the results are fully robust. When information is acquired secretly butmoves are sequential additional equilibria may appear. Instead, privateinformation acquisition may make the equilibrium set smaller.

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In this paper I show how borrowing constraints and job search interact.I fit a dynamic model to data from the National Longitudinal Survey(1979-cohort) and show that borrowing constraints are significant. Agentswith more initial assets and more access to credit attain higher wagesfor several periods after high school graduation. The unemployed maintaintheir consumption by running down their assets, while the employed saveto buffer against future unemployment spells. I also show that, unlikein models with exogenous income streams, unemployment transfers, byallowing agents to attain higher wages do not 'crowd out' but increasesaving.

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When can a single variable be more accurate in binary choice than multiple sources of information? We derive analytically the probability that a single variable (SV) will correctly predict one of two choices when both criterion and predictor are continuous variables. We further provide analogous derivations for multiple regression (MR) and equal weighting (EW) and specify the conditions under which the models differ in expected predictive ability. Key factors include variability in cue validities, intercorrelation between predictors, and the ratio of predictors to observations in MR. Theory and simulations are used to illustrate the differential effects of these factors. Results directly address why and when one-reason decision making can be more effective than analyses that use more information. We thus provide analytical backing to intriguing empirical results that, to date, have lacked theoretical justification. There are predictable conditions for which one should expect less to be more.

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The main goal of this research is to investigate how people with different cultural background differ in their interaction style and visual behavior on search engine results pages (SERP), more specifically between groups from the Middle Eastern region vs. Western Europe. We conducted a controlled eye-tracking experiment to explore and evaluate the visual behavior of Arabs and Spaniardusers when scanning through the first page of the search results in Google. Big differences can be observed in the 4 aspects studied: U.A.E. participants stayed on the SERPs for longer, they read more results and they read each snippet in a more complete way than Spaniards. In Spain, people tended to scan the SERP, reading less text on each snippet, and choose a result among the first top rankedones without hardly seeing those in bottom positions.

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Abstract : The existence of a causal relationship between the spatial distribution of living organisms and their environment, in particular climate, has been long recognized and is the central principle of biogeography. In turn, this recognition has led scientists to the idea of using the climatic, topographic, edaphic and biotic characteristics of the environment to predict its potential suitability for a given species or biological community. In this thesis, my objective is to contribute to the development of methodological improvements in the field of species distribution modeling. More precisely, the objectives are to propose solutions to overcome limitations of species distribution models when applied to conservation biology issues, or when .used as an assessment tool of the potential impacts of global change. The first objective of my thesis is to contribute to evidence the potential of species distribution models for conservation-related applications. I present a methodology to generate pseudo-absences in order to overcome the frequent lack of reliable absence data. I also demonstrate, both theoretically (simulation-based) and practically (field-based), how species distribution models can be successfully used to model and sample rare species. Overall, the results of this first part of the thesis demonstrate the strong potential of species distribution models as a tool for practical applications in conservation biology. The second objective this thesis is to contribute to improve .projections of potential climate change impacts on species distributions, and in particular for mountain flora. I develop and a dynamic model, MIGCLIM, that allows the implementation of dispersal limitations into classic species distribution models and present an application of this model to two virtual species. Given that accounting for dispersal limitations requires information on seed dispersal, distances, a general methodology to classify species into broad dispersal types is also developed. Finally, the M~GCLIM model is applied to a large number of species in a study area of the western Swiss Alps. Overall, the results indicate that while dispersal limitations can have an important impact on the outcome of future projections of species distributions under climate change scenarios, estimating species threat levels (e.g. species extinction rates) for a mountainous areas of limited size (i.e. regional scale) can also be successfully achieved when considering dispersal as unlimited (i.e. ignoring dispersal limitations, which is easier from a practical point of view). Finally, I present the largest fine scale assessment of potential climate change impacts on mountain vegetation that has been carried-out to date. This assessment involves vegetation from 12 study areas distributed across all major western and central European mountain ranges. The results highlight that some mountain ranges (the Pyrenees and the Austrian Alps) are expected to be more affected by climate change than others (Norway and the Scottish Highlands). The results I obtain in this study also indicate that the threat levels projected by fine scale models are less severe than those derived from coarse scale models. This result suggests that some species could persist in small refugias that are not detected by coarse scale models. Résumé : L'existence d'une relation causale entre la répartition des espèces animales et végétales et leur environnement, en particulier le climat, a été mis en évidence depuis longtemps et est un des principes centraux en biogéographie. Ce lien a naturellement conduit à l'idée d'utiliser les caractéristiques climatiques, topographiques, édaphiques et biotiques de l'environnement afin d'en prédire la qualité pour une espèce ou une communauté. Dans ce travail de thèse, mon objectif est de contribuer au développement d'améliorations méthodologiques dans le domaine de la modélisation de la distribution d'espèces dans le paysage. Plus précisément, les objectifs sont de proposer des solutions afin de surmonter certaines limitations des modèles de distribution d'espèces dans des applications pratiques de biologie de la conservation ou dans leur utilisation pour évaluer l'impact potentiel des changements climatiques sur l'environnement. Le premier objectif majeur de mon travail est de contribuer à démontrer le potentiel des modèles de distribution d'espèces pour des applications pratiques en biologie de la conservation. Je propose une méthode pour générer des pseudo-absences qui permet de surmonter le problème récurent du manque de données d'absences fiables. Je démontre aussi, de manière théorique (par simulation) et pratique (par échantillonnage de terrain), comment les modèles de distribution d'espèces peuvent être utilisés pour modéliser et améliorer l'échantillonnage des espèces rares. Ces résultats démontrent le potentiel des modèles de distribution d'espèces comme outils pour des applications de biologie de la conservation. Le deuxième objectif majeur de ce travail est de contribuer à améliorer les projections d'impacts potentiels des changements climatiques sur la flore, en particulier dans les zones de montagnes. Je développe un modèle dynamique de distribution appelé MigClim qui permet de tenir compte des limitations de dispersion dans les projections futures de distribution potentielle d'espèces, et teste son application sur deux espèces virtuelles. Vu que le fait de prendre en compte les limitations dues à la dispersion demande des données supplémentaires importantes (p.ex. la distance de dispersion des graines), ce travail propose aussi une méthode de classification simplifiée des espèces végétales dans de grands "types de disperseurs", ce qui permet ainsi de d'obtenir de bonnes approximations de distances de dispersions pour un grand nombre d'espèces. Finalement, j'applique aussi le modèle MIGCLIM à un grand nombre d'espèces de plantes dans une zone d'études des pré-Alpes vaudoises. Les résultats montrent que les limitations de dispersion peuvent avoir un impact considérable sur la distribution potentielle d'espèces prédites sous des scénarios de changements climatiques. Cependant, quand les modèles sont utilisés pour évaluer les taux d'extinction d'espèces dans des zones de montages de taille limitée (évaluation régionale), il est aussi possible d'obtenir de bonnes approximations en considérant la dispersion des espèces comme illimitée, ce qui est nettement plus simple d'un point dé vue pratique. Pour terminer je présente la plus grande évaluation à fine échelle d'impact potentiel des changements climatiques sur la flore des montagnes conduite à ce jour. Cette évaluation englobe 12 zones d'études réparties sur toutes les chaines de montages principales d'Europe occidentale et centrale. Les résultats montrent que certaines chaines de montagnes (les Pyrénées et les Alpes Autrichiennes) sont projetées comme plus sensibles aux changements climatiques que d'autres (les Alpes Scandinaves et les Highlands d'Ecosse). Les résultats obtenus montrent aussi que les modèles à échelle fine projettent des impacts de changement climatiques (p. ex. taux d'extinction d'espèces) moins sévères que les modèles à échelle large. Cela laisse supposer que les modèles a échelle fine sont capables de modéliser des micro-niches climatiques non-détectées par les modèles à échelle large.

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In the Arabidopsis root meristem, polar auxin transport creates a transcriptional auxin response gradient that peaks at the stem cell niche and gradually decreases as stem cell daughters divide and differentiate [1-3]. The amplitude and extent of this gradient are essential for both stem cell maintenance and root meristem growth [4, 5]. To investigate why expression of some auxin-responsive genes, such as the essential root meristem growth regulator BREVIS RADIX (BRX) [6], deviates from this gradient, we combined experimental and computational approaches. We created cellular-level root meristem models that accurately reproduce distribution of nuclear auxin activity and allow dynamic modeling of regulatory processes to guide experimentation. Expression profiles deviating from the auxin gradient could only be modeled after intersection of auxin activity with the observed differential endocytosis pattern and positive autoregulatory feedback through plasma-membrane-to-nucleus transfer of BRX. Because BRX is required for expression of certain auxin response factor targets, our data suggest a cell-type-specific endocytosis-dependent input into transcriptional auxin perception. This input sustains expression of a subset of auxin-responsive genes across the root meristem's division and transition zones and is essential for meristem growth. Thus, the endocytosis pattern provides specific positional information to modulate auxin response.