Consistency and the Walrasian allocations correspondence

We characterize the Walrasian allocations correspondence, in classesof exchange economies with smooth and convex preferences, by means of consistency requirements and other axioms. We present three characterizationresults; all of which require consistency, converse consistency and standard axioms. Two characterizations hold also on domains with a finite number ofpotential agents, one of them requires envy freeness (with respect to trades) and the other--core selection; a third characterization, that requires coreselection, applies only to a variable number of agents domain, but is validalso when the domain includes only a small variety of preferences.

Variable Kernel estimates: On the impossibility of tuning the parameters

For the standard kernel density estimate, it is known that one can tune the bandwidth such that the expected L1 error is within a constant factor of the optimal L1 error (obtained when one is allowed to choose the bandwidth with knowledge of the density). In this paper, we pose the same problem for variable bandwidth kernel estimates where the bandwidths are allowed to depend upon the location. We show in particular that for positive kernels on the real line, for any data-based bandwidth, there exists a densityfor which the ratio of expected L1 error over optimal L1 error tends to infinity. Thus, the problem of tuning the variable bandwidth in an optimal manner is ``too hard''. Moreover, from the class of counterexamples exhibited in the paper, it appears thatplacing conditions on the densities (monotonicity, convexity, smoothness) does not help.

Influence of male nutritional conditions on the performance and alimentary selection of wild females of Anastrepha obliqua (Macquart)(Diptera, Tephritidae)

Influence of male nutritional conditions on the performance and alimentary selection of wild females of Anastrepha obliqua (Macquart) (Diptera, Tephritidae). The behavior of A. obliqua females is regulated by endogenous and exogenous factors and among these the presence of males. Experiments were carried out to investigate whether the presence of males and their nutritional condition may affect the behavior of self-selection feeding and the performance of A. obliqua females. Females were sorted in groups containing yeast-deprived females and males, and non-yeast-deprived females and males. The females were maintained apart from the males by a transparent plastic screen. Several yeast and sucrose combinations were offered to the females in a single diet block or in separate blocks. Ingestion, egg production, longevity and diet efficiency were determined. The non-yeast-deprived males positively influenced the females performance when the latter were fed with yeast and sucrose in distinct diet blocks. Performance was better in the groups without males and with yeast-deprived males where the females could not select the nutrient proportions (yeast and sucrose in a single diet block).

Adverse selection, credit and efficiency: The case of the missing market

We analyze a standard environment of adverse selection in credit markets. In our environment,entrepreneurs who are privately informed about the quality of their projects need toborrow from banks. Conventional wisdom says that, in this class of economies, the competitiveequilibrium is typically inefficient.We show that this conventional wisdom rests on one implicit assumption: entrepreneurscan only borrow from banks. If an additional market is added to provide entrepreneurs withadditional funds, efficiency can be attained in equilibrium. An important characteristic of thisadditional market is that it must be non-exclusive, in the sense that entrepreneurs must be ableto simultaneously borrow from many different lenders operating in it. This makes it possible toattain efficiency by pooling all entrepreneurs in the new market while separating them in themarket for bank loans.

Comparative genomics of chemosensory protein genes reveals rapid evolution and positive selection in ant-specific duplicates.

Gene duplications can have a major role in adaptation, and gene families underlying chemosensation are particularly interesting due to their essential role in chemical recognition of mates, predators and food resources. Social insects add yet another dimension to the study of chemosensory genomics, as the key components of their social life rely on chemical communication. Still, chemosensory gene families are little studied in social insects. Here we annotated chemosensory protein (CSP) genes from seven ant genomes and studied their evolution. The number of functional CSP genes ranges from 11 to 21 depending on species, and the estimated rates of gene birth and death indicate high turnover of genes. Ant CSP genes include seven conservative orthologous groups present in all the ants, and a group of genes that has expanded independently in different ant lineages. Interestingly, the expanded group of genes has a differing mode of evolution from the orthologous groups. The expanded group shows rapid evolution as indicated by a high dN/dS (nonsynonymous to synonymous changes) ratio, several sites under positive selection and many pseudogenes, whereas the genes in the seven orthologous groups evolve slowly under purifying selection and include only one pseudogene. These results show that adaptive changes have played a role in ant CSP evolution. The expanded group of ant-specific genes is phylogenetically close to a conservative orthologous group CSP7, which includes genes known to be involved in ant nestmate recognition, raising an interesting possibility that the expanded CSPs function in ant chemical communication.

PyRate: a new program to estimate speciation and extinction rates from incomplete fossil data

Despite the advancement of phylogenetic methods to estimate speciation and extinction rates, their power can be limited under variable rates, in particular for clades with high extinction rates and small number of extant species. Fossil data can provide a powerful alternative source of information to investigate diversification processes. Here, we present PyRate, a computer program to estimate speciation and extinction rates and their temporal dynamics from fossil occurrence data. The rates are inferred in a Bayesian framework and are comparable to those estimated from phylogenetic trees. We describe how PyRate can be used to explore different models of diversification. In addition to the diversification rates, it provides estimates of the parameters of the preservation process (fossilization and sampling) and the times of speciation and extinction of each species in the data set. Moreover, we develop a new birth-death model to correlate the variation of speciation/extinction rates with changes of a continuous trait. Finally, we demonstrate the use of Bayes factors for model selection and show how the posterior estimates of a PyRate analysis can be used to generate calibration densities for Bayesian molecular clock analysis. PyRate is an open-source command-line Python program available at http://sourceforge.net/projects/pyrate/.

Testing financing constraints on firm investment using variable capital

We consider a dynamic multifactor model of investment with financing imperfections,adjustment costs and fixed and variable capital. We use the model to derive a test offinancing constraints based on a reduced form variable capital equation. Simulation resultsshow that this test correctly identifies financially constrained firms even when the estimationof firms investment opportunities is very noisy. In addition, the test is well specified inthe presence of both concave and convex adjustment costs of fixed capital. We confirmempirically the validity of this test on a sample of small Italian manufacturing companies.

Improving generalized regression analysis for the spatial prediction of forest communities

Aim This study used data from temperate forest communities to assess: (1) five different stepwise selection methods with generalized additive models, (2) the effect of weighting absences to ensure a prevalence of 0.5, (3) the effect of limiting absences beyond the environmental envelope defined by presences, (4) four different methods for incorporating spatial autocorrelation, and (5) the effect of integrating an interaction factor defined by a regression tree on the residuals of an initial environmental model. Location State of Vaud, western Switzerland. Methods Generalized additive models (GAMs) were fitted using the grasp package (generalized regression analysis and spatial predictions, http://www.cscf.ch/grasp). Results Model selection based on cross-validation appeared to be the best compromise between model stability and performance (parsimony) among the five methods tested. Weighting absences returned models that perform better than models fitted with the original sample prevalence. This appeared to be mainly due to the impact of very low prevalence values on evaluation statistics. Removing zeroes beyond the range of presences on main environmental gradients changed the set of selected predictors, and potentially their response curve shape. Moreover, removing zeroes slightly improved model performance and stability when compared with the baseline model on the same data set. Incorporating a spatial trend predictor improved model performance and stability significantly. Even better models were obtained when including local spatial autocorrelation. A novel approach to include interactions proved to be an efficient way to account for interactions between all predictors at once. Main conclusions Models and spatial predictions of 18 forest communities were significantly improved by using either: (1) cross-validation as a model selection method, (2) weighted absences, (3) limited absences, (4) predictors accounting for spatial autocorrelation, or (5) a factor variable accounting for interactions between all predictors. The final choice of model strategy should depend on the nature of the available data and the specific study aims. Statistical evaluation is useful in searching for the best modelling practice. However, one should not neglect to consider the shapes and interpretability of response curves, as well as the resulting spatial predictions in the final assessment.

Adverse selection, credit and efficiency: The case of the missing market

We analyze a standard environment of adverse selection in credit markets. In our environment,entrepreneurs who are privately informed about the quality of their projects needto borrow in order to invest. Conventional wisdom says that, in this class of economies, thecompetitive equilibrium is typically inefficient.We show that this conventional wisdom rests on one implicit assumption: entrepreneurscan only access monitored lending. If a new set of markets is added to provide entrepreneurswith additional funds, efficiency can be attained in equilibrium. An important characteristic ofthese additional markets is that lending in them must be unmonitored, in the sense that it doesnot condition total borrowing or investment by entrepreneurs. This makes it possible to attainefficiency by pooling all entrepreneurs in the new markets while separating them in the marketsfor monitored loans.

Hiring and firing costs, adverse selection and long-term unemployment

In this paper, we present a matching model with adverse selection that explains why flows into and out of unemployment are much lower in Europe compared to North America, while employment-to-employment flows are similar in the two continents. In the model,firms use discretion in terms of whom to fire and, thus, low quality workers are more likely to be dismissed than high quality workers. Moreover, as hiring and firing costs increase, firms find it more costly to hire a bad worker and, thus, they prefer to hire out of the pool of employed job seekers rather than out of the pool of the unemployed, who are more likely to turn out to be 'lemons'. We use microdata for Spain and the U.S. and find that the ratio of the job finding probability of the unemployed to the job finding probability of employed job seekers was smaller in Spain than in the U.S. Furthermore, using U.S. data, we find that the discrimination of the unemployed increased over the 1980's in those states that raised firing costs by introducing exceptions to the employment-at-will doctrine.

Improved estimation of the covariance matrix of stock returns with an application to portofolio selection

This paper proposes to estimate the covariance matrix of stock returnsby an optimally weighted average of two existing estimators: the samplecovariance matrix and single-index covariance matrix. This method isgenerally known as shrinkage, and it is standard in decision theory andin empirical Bayesian statistics. Our shrinkage estimator can be seenas a way to account for extra-market covariance without having to specifyan arbitrary multi-factor structure. For NYSE and AMEX stock returns from1972 to 1995, it can be used to select portfolios with significantly lowerout-of-sample variance than a set of existing estimators, includingmulti-factor models.