Stochastic dominance and absolute risk aversion

In this paper we propose the infimum of the Arrow-Pratt index of absolute risk aversion as a measure of global risk aversion of a utility function. We then show that, for any given arbitrary pair of distributions, there exists a threshold level of global risk aversion such that all increasing concave utility functions with at least as much global risk aversion would rank the two distributions in the same way. Furthermore, this threshold level is sharp in the sense that, for any lower level of global risk aversion, we can find two utility functions in this class yielding opposite preference relations for the two distributions.

Pareto-improving optimal capital and labor taxes

We show a standard model where the optimal tax reform is to cut labor taxes and leave capital taxes very high in the short and medium run. Only in the very long run would capital taxes be zero. Our model is a version of Chamley??s, with heterogeneous agents, without lump sum transfers, an upper bound on capital taxes, and a focus on Pareto improving plans. For our calibration labor taxes should be low for the first ten to twenty years, while capital taxes should be at their maximum. This policy ensures that all agents benefit from the tax reform and that capital grows quickly after when the reform begins. Therefore, the long run optimal tax mix is the opposite from the short and medium run tax mix. The initial labor tax cut is financed by deficits that lead to a positive long run level of government debt, reversing the standard prediction that government accumulates savings in models with optimal capital taxes. If labor supply is somewhat elastic benefits from tax reform are high and they can be shifted entirely to capitalists or workers by varying the length of the transition. With inelastic labor supply there is an increasing part of the equilibrium frontier, this means that the scope for benefitting the workers is limited and the total benefits from reforming taxes are much lower.

Testing for poverty dominance: an application to Canada

The paper proposes and applies statistical tests for poverty dominance that check for whether poverty comparisons can be made robustly over ranges of poverty lines and classes of poverty indices. This helps provide both normative and statistical confidence in establishing poverty rankings across distributions. The tests, which can take into account the complex sampling procedures that are typically used by statistical agencies to generate household-level surveys, are implemented using the Canadian Survey of Labour and Income Dynamics (SLID) for 1996, 1999 and 2002. Although the yearly cumulative distribution functions cross at the lower tails of the distributions, the more recent years tend to dominate earlier years for a relatively wide range of poverty lines. Failing to take into account SLID's sampling variability (as is sometimes done) can inflate significantly one's confidence in ranking poverty. Taking into account SLID's complex sampling design (as has not been done before) can also decrease substantially the range of poverty lines over which a poverty ranking can be inferred.

Stochastic dominance and absolute risk aversion

In this paper we proose the infimum of the Arrow-Pratt index of absoluterisk aversion as a measure of global risk aversion of a utility function.We then show that, for any given arbitrary pair of distributions, thereexists a threshold level of global risk aversion such that all increasingconcave utility functions with at least as much global risk aversion wouldrank the two distributions in the same way. Furthermore, this thresholdlevel is sharp in the sense that, for any lower level of global riskaversion, we can find two utility functions in this class yielding oppositepreference relations for the two distributions.

Cumulative dominance and heuristic performance in binary multi-attribute choice

Several studies have reported high performance of simple decision heuristics multi-attribute decision making. In this paper, we focus on situations where attributes are binary and analyze the performance of Deterministic-Elimination-By-Aspects (DEBA) and similar decision heuristics. We consider non-increasing weights and two probabilistic models for the attribute values: one where attribute values are independent Bernoulli randomvariables; the other one where they are binary random variables with inter-attribute positive correlations. Using these models, we show that good performance of DEBA is explained by the presence of cumulative as opposed to simple dominance. We therefore introduce the concepts of cumulative dominance compliance and fully cumulative dominance compliance and show that DEBA satisfies those properties. We derive a lower bound with which cumulative dominance compliant heuristics will choose a best alternative and show that, even with many attributes, this is not small. We also derive an upper bound for the expected loss of fully cumulative compliance heuristics and show that this is moderateeven when the number of attributes is large. Both bounds are independent of the values ofthe weights.

Risk dominance selects the leader. An experimental analysis

Coordination games arise very often in studies of industrial organization and international trade. This type of games has multiple strict equilibria, and therefore the identification of testable predictions isvery difficult. We study a vertical product differentiation model with two asymmetric players choosing first qualities and then prices. This game has two equilibria for some parameter values. However, we apply the risk dominance criterion suggested by Harsanyi and Selten and show that it always selects the equilibrium where the leader is the firm having some initial advantage. We then perform an experimental analysis totest whether the risk dominance prediction is supported by the behaviour oflaboratory agents. We show that the probability that the risk dominance prediction is right depends crucially on the degree of asymmetry of the game. The stronger the asymmetries the higher the predictive power of the risk dominance criterion.

A note on the dual scaling of dominance data and its relationship to correspondence analysis

Dual scaling of a subjects-by-objects table of dominance data (preferences,paired comparisons and successive categories data) has been contrasted with correspondence analysis, as if the two techniques were somehow different. In this note we show that dual scaling of dominance data is equivalent to the correspondence analysis of a table which is doubled with respect to subjects. We also show that the results of both methods can be recovered from a principal components analysis of the undoubled dominance table which is centred with respect to subject means.

Time consistent Pareto solutions in common access resource gameswith asymmetric players

In the analysis of equilibrium policies in a di erential game, if agents have different time preference rates, the cooperative (Pareto optimum) solution obtained by applying the Pontryagin's Maximum Principle becomes time inconsistent. In this work we derive a set of dynamic programming equations (in discrete and continuous time) whose solutions are time consistent equilibrium rules for N-player cooperative di erential games in which agents di er in their instantaneous utility functions and also in their discount rates of time preference. The results are applied to the study of a cake-eating problem describing the management of a common property exhaustible natural resource. The extension of the results to a simple common property renewable natural resource model in in nite horizon is also discussed.

Time consistent Pareto solutions in common access resource gameswith asymmetric players

In the analysis of equilibrium policies in a di erential game, if agents have different time preference rates, the cooperative (Pareto optimum) solution obtained by applying the Pontryagin's Maximum Principle becomes time inconsistent. In this work we derive a set of dynamic programming equations (in discrete and continuous time) whose solutions are time consistent equilibrium rules for N-player cooperative di erential games in which agents di er in their instantaneous utility functions and also in their discount rates of time preference. The results are applied to the study of a cake-eating problem describing the management of a common property exhaustible natural resource. The extension of the results to a simple common property renewable natural resource model in in nite horizon is also discussed.

Carbohydrate and nitrogen stores in Festuca paniculata under mowing explain dominance in subalpine grasslands

Cessation of traditional management threatens semi-natural grassland diversity through the colonisation or increase of competitive species adapted to nutrient-poor conditions. Regular mowing is one practice that controls their abundance. This study evaluated the ecophysiological mechanisms limiting short- and long-term recovery after mowing for Festuca paniculata, a competitive grass that takes over subalpine grasslands in the Alps following cessation of mowing. We quantified temporal variations in carbon (C) and nitrogen (N) content, starch, fructan and total soluble sugars in leaves, stem bases and roots of F. paniculata during one growth cycle in mown and unmown fields and related them to the dynamics of soil mineral N concentration and soil moisture. Short-term results suggest that the regrowth of F. paniculata following mowing might be N-limited, first because of N dilution by C increments in the plant tissue, and second, due to low soil mineral N and soil moisture at this time of year. However, despite short-term effects of mowing on plant growth, C and N content and concentration at the beginning of the following growing season were not affected. Nevertheless, total biomass accumulation at peak standing biomass was largely reduced compared to unmown fields. Moreover, lower C storage capacity at the end of the growing season impacted C allocation to vegetative reproduction during winter, thereby dramatically limiting the horizontal growth of F. paniculata tussocks in the long term. We conclude that mowing reduces the growth of F. paniculata tussocks through both C and N limitation. Such results will help understanding how plant responses to defoliation regulate competitive interactions within plant communities.

Wave-height hazard analysis in Eastern Coast of Spain : Bayesian approach using generalized Pareto distribution

Standard practice of wave-height hazard analysis often pays little attention to the uncertainty of assessed return periods and occurrence probabilities. This fact favors the opinion that, when large events happen, the hazard assessment should change accordingly. However, uncertainty of the hazard estimates is normally able to hide the effect of those large events. This is illustrated using data from the Mediterranean coast of Spain, where the last years have been extremely disastrous. Thus, it is possible to compare the hazard assessment based on data previous to those years with the analysis including them. With our approach, no significant change is detected when the statistical uncertainty is taken into account. The hazard analysis is carried out with a standard model. Time-occurrence of events is assumed Poisson distributed. The wave-height of each event is modelled as a random variable which upper tail follows a Generalized Pareto Distribution (GPD). Moreover, wave-heights are assumed independent from event to event and also independent of their occurrence in time. A threshold for excesses is assessed empirically. The other three parameters (Poisson rate, shape and scale parameters of GPD) are jointly estimated using Bayes' theorem. Prior distribution accounts for physical features of ocean waves in the Mediterranean sea and experience with these phenomena. Posterior distribution of the parameters allows to obtain posterior distributions of other derived parameters like occurrence probabilities and return periods. Predictives are also available. Computations are carried out using the program BGPE v2.0

Carbohydrate and nitrogen stores in Festuca paniculata under mowing explain dominance in subalpine grasslands

Cessation of traditional management threatens semi-natural grassland diversity through the colonisation or increase of competitive species adapted to nutrient-poor conditions. Regular mowing is one practice that controls their abundance. This study evaluated the ecophysiological mechanisms limiting short- and long-term recovery after mowing for Festuca paniculata, a competitive grass that takes over subalpine grasslands in the Alps following cessation of mowing. We quantified temporal variations in carbon (C) and nitrogen (N) content, starch, fructan and total soluble sugars in leaves, stem bases and roots of F. paniculata during one growth cycle in mown and unmown fields and related them to the dynamics of soil mineral N concentration and soil moisture. Short-term results suggest that the regrowth of F. paniculata following mowing might be N-limited, first because of N dilution by C increments in the plant tissue, and second, due to low soil mineral N and soil moisture at this time of year. However, despite short-term effects of mowing on plant growth, C and N content and concentration at the beginning of the following growing season were not affected. Nevertheless, total biomass accumulation at peak standing biomass was largely reduced compared to unmown fields. Moreover, lower C storage capacity at the end of the growing season impacted C allocation to vegetative reproduction during winter, thereby dramatically limiting the horizontal growth of F. paniculata tussocks in the long term. We conclude that mowing reduces the growth of F. paniculata tussocks through both C and N limitation. Such results will help understanding how plant responses to defoliation regulate competitive interactions within plant communities.

Identifying the preferred subset of enzymatic profiles in nonlinear kinetic metabolic models via multiobjective global optimization and pareto filters

Optimization models in metabolic engineering and systems biology focus typically on optimizing a unique criterion, usually the synthesis rate of a metabolite of interest or the rate of growth. Connectivity and non-linear regulatory effects, however, make it necessary to consider multiple objectives in order to identify useful strategies that balance out different metabolic issues. This is a fundamental aspect, as optimization of maximum yield in a given condition may involve unrealistic values in other key processes. Due to the difficulties associated with detailed non-linear models, analysis using stoichiometric descriptions and linear optimization methods have become rather popular in systems biology. However, despite being useful, these approaches fail in capturing the intrinsic nonlinear nature of the underlying metabolic systems and the regulatory signals involved. Targeting more complex biological systems requires the application of global optimization methods to non-linear representations. In this work we address the multi-objective global optimization of metabolic networks that are described by a special class of models based on the power-law formalism: the generalized mass action (GMA) representation. Our goal is to develop global optimization methods capable of efficiently dealing with several biological criteria simultaneously. In order to overcome the numerical difficulties of dealing with multiple criteria in the optimization, we propose a heuristic approach based on the epsilon constraint method that reduces the computational burden of generating a set of Pareto optimal alternatives, each achieving a unique combination of objectives values. To facilitate the post-optimal analysis of these solutions and narrow down their number prior to being tested in the laboratory, we explore the use of Pareto filters that identify the preferred subset of enzymatic profiles. We demonstrate the usefulness of our approach by means of a case study that optimizes the ethanol production in the fermentation of Saccharomyces cerevisiae.