3,105 research outputs found
Cruise Report 72-KB-23: Inshore fisheries habitat evaluation and monitoring program
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The status of the California spiny lobster resource
California spiny lobsters, Panulirus interruptus, are the object of intense fisheries prosecuted by both commercial and sport fishermen in California. Recent evidence indicates that the resource may be declining, and an investigation of the population dynamics is needed. It is recommended that the investigation assess the magnitude of the fishery, identify population units and investigate the adequacy of existing gear regulations. (14pp.
Equilibrium Selection in Static and Dynamic Entry Games
We experimentally examine equilibrium refinements in static and dynamic binary choice games of complete information with strategic complementarities known as “entry†games. Our aim is to assess the predictive power of two different equilibrium selection principles. In static entry games, we test the theory of global games as an equilibrium selection device. This theory posits that players play games of complete information as if they were playing a related global game of incomplete information. In dynamic entry games, individuals decide not only whether to enter but also when to enter. Once entry occurs it is irreversible. The number of people who have already entered is part of the state description, and individuals can condition their decisions on that information. If the state variable does not indicate that entry is dominated, the efficient subgame perfect equilibrium prediction calls for all players to enter. Further, if there is a cost of delay, entry should occur immediately, thereby eliminating the coordination problem. This subgame perfect entry threshold in the dynamic game will generally differ from the global game threshold in static versions of the same entry game. Nevertheless, our experimental findings suggest that observed entry thresholds in both static and dynamic versions of the same entry game are surprisingly similar. The mean entry threshold in the static game lies below the global game equilibrium threshold while the mean entry threshold in the dynamic game lies above the efficient subgame perfect equilibrium threshold. An important implication of this finding is that if one were to observe only the value of the state variable and the number of people who enter by the end of the game one could not determine whether the static or the dynamic game had been played.
Agent-Based Models and Human Subject Experiments
This paper considers the relationship between agent-based modeling and economic decision-making experiments with human subjects. Both approaches exploit controlled ``laboratory'' conditions as a means of isolating the sources of aggregate phenomena. Research findings from laboratory studies of human subject behavior have inspired studies using artificial agents in ``computational laboratories'' and vice versa. In certain cases, both methods have been used to examine the same phenomenon. The focus of this paper is on the empirical validity of agent-based modeling approaches in terms of explaining data from human subject experiments. We also point out synergies between the two methodologies that have been exploited as well as promising new possibilities.agent-based models, human subject experiments, zero- intelligence agents, learning, evolutionary algorithms
Correlated equilibria, good and bad : an experimental study
We report results from an experiment that explores the empirical validity of correlated equilibrium, an important generalization of the Nash equilibrium concept. Specifically, we seek to
understand the conditions under which subjects playing the game of Chicken will condition their behavior on private, third–party recommendations drawn from known distributions. In a “good–recommendations” treatment, the distribution we use is a correlated equilibrium with payoffs better
than any symmetric payoff in the convex hull of Nash equilibrium payoff vectors. In a “bad–recommendations” treatment, the distribution is a correlated equilibrium with payoffs worse than any Nash equilibrium payoff vector. In a “Nash–recommendations” treatment, the distribution is a convex combination of Nash equilibrium outcomes (which is also a correlated equilibrium), and in a fourth “very–good–recommendations” treatment, the distribution yields high payoffs, but is not a correlated equilibrium. We compare behavior in all of these treatments to the case where subjects do not receive recommendations. We find that when recommendations are not given to
subjects, behavior is very close to mixed–strategy Nash equilibrium play. When recommendations are given, behavior does differ from mixed–strategy Nash equilibrium, with the nature of the differ-
ences varying according to the treatment. Our main finding is that subjects will follow third–party recommendations only if those recommendations derive from a correlated equilibrium, and further,if that correlated equilibrium is payoff–enhancing relative to the available Nash equilibria
Poverty, Poaching and Trafficking: What are the links?
A rapid review of academic and grey literature revealed that the links between poverty, poaching and trafficking are under-researched and poorly understood. Yet, the assumption that poaching occurs because of poverty is omnipresent, with little ‘hard evidence’ to support the claim. Despite this, the authors are confident that the links are there, based on the evidence gathered. However, their understandings are hampered by a series of factors: trafficking and poaching are overwhelmingly framed as an issue of conservation/biodiversity loss rather than of poverty and development; it is difficult to collect clear and detailed data on poaching precisely because of its illicit nature; and many of the cases examined are also linked in with conflict zones, making research even more challenging
A model of learning and emulation with artificial adaptive agents
We study adaptive learning behavior in a sequence of n-period endowment overlapping generations economies with fiat currency, where n refers to the number of periods in agents' lifetimes. Agents initially have heterogeneous beliefs and seek to form multi-step-ahead forecasts of future prices using a forecast rule chosen from a vast set of possible forecast rules. Agents take optimal actions given their forecasts of future prices. They learn in every period by creating new forecast rules and by emulating the forecast rules of other agents. Computational experiments with artificial adaptive agents are conducted. These experiments yield three qualitatively different types of outcomes. In one, the initially heterogeneous population of artificial agents learns to coordinate on a low inflation, stationary perfect foresight equilibrium. In another, we observe persistent currency collapse. The third outcome is a lack of coordination within the allotted time frame. One possible outcome, a stationary perfect foresight equilibrium with a relatively high inflation rate, is never observed.Consumption (Economics)
Learning and excess volatility
We introduce adaptive learning behavior into a general equilibrium lifecycle economy with capital accumulation. Agents form forecasts of the rate of return to capital assets using least squares autoregressions on past data. We show that, in contrast to the perfect foresight dynamics, the dynamical system under learning possesses equilibria characterized by persistent excess volatility in returns to capital. We explore a quantitative case for these learning equilibria. We use an evolutionary search algorithm to calibrate a version of the system under learning and show that this system can generate data that matches some features of the time series data for U.S. stock returns and per capita consumption. We argue that this finding provides support for the hypothesis that the observed excess volatility of asset returns can by explained by changes in investor expectations against a background of relatively small changes in fundamental factors.Capital ; Stock - Prices
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