Growth, convergence and public investment : a bayesian model averaging approach

The aim of this paper is twofold. First, we study the determinants of economic growth among a wide set of potential variables for the Spanish provinces (NUTS3). Among others, we include various types of private, public and human capital in the group of growth factors. Also,we analyse whether Spanish provinces have converged in economic terms in recent decades. Thesecond objective is to obtain cross-section and panel data parameter estimates that are robustto model speci¯cation. For this purpose, we use a Bayesian Model Averaging (BMA) approach.Bayesian methodology constructs parameter estimates as a weighted average of linear regression estimates for every possible combination of included variables. The weight of each regression estimate is given by the posterior probability of each model.

Estudi de l'estat de Salut autopercebut: Modelització de l'índex d'utilitat EQ-5D mitjançant un model tobit

Objective: Health status measures usually have an asymmetric distribution and present a highpercentage of respondents with the best possible score (ceiling effect), specially when they areassessed in the overall population. Different methods to model this type of variables have beenproposed that take into account the ceiling effect: the tobit models, the Censored Least AbsoluteDeviations (CLAD) models or the two-part models, among others. The objective of this workwas to describe the tobit model, and compare it with the Ordinary Least Squares (OLS) model,that ignores the ceiling effect.Methods: Two different data sets have been used in order to compare both models: a) real datacomming from the European Study of Mental Disorders (ESEMeD), in order to model theEQ5D index, one of the measures of utilities most commonly used for the evaluation of healthstatus; and b) data obtained from simulation. Cross-validation was used to compare thepredicted values of the tobit model and the OLS models. The following estimators werecompared: the percentage of absolute error (R1), the percentage of squared error (R2), the MeanSquared Error (MSE) and the Mean Absolute Prediction Error (MAPE). Different datasets werecreated for different values of the error variance and different percentages of individuals withceiling effect. The estimations of the coefficients, the percentage of explained variance and theplots of residuals versus predicted values obtained under each model were compared.Results: With regard to the results of the ESEMeD study, the predicted values obtained with theOLS model and those obtained with the tobit models were very similar. The regressioncoefficients of the linear model were consistently smaller than those from the tobit model. In thesimulation study, we observed that when the error variance was small (s=1), the tobit modelpresented unbiased estimations of the coefficients and accurate predicted values, specially whenthe percentage of individuals wiht the highest possible score was small. However, when theerrror variance was greater (s=10 or s=20), the percentage of explained variance for the tobitmodel and the predicted values were more similar to those obtained with an OLS model.Conclusions: The proportion of variability accounted for the models and the percentage ofindividuals with the highest possible score have an important effect in the performance of thetobit model in comparison with the linear model.

Avalanches in a fluctuationless first-order phase transition in a random-bond Ising model

We study the behavior of the random-bond Ising model at zero temperature by numerical simulations for a variable amount of disorder. The model is an example of systems exhibiting a fluctuationless first-order phase transition similar to some field-induced phase transitions in ferromagnetic systems and the martensitic phase transition appearing in a number of metallic alloys. We focus on the study of the hysteresis cycles appearing when the external field is swept from positive to negative values. By using a finite-size scaling hypothesis, we analyze the disorder-induced phase transition between the phase exhibiting a discontinuity in the hysteresis cycle and the phase with the continuous hysteresis cycle. Critical exponents characterizing the transition are obtained. We also analyze the size and duration distributions of the magnetization jumps (avalanches).

Comment on "Kinetics of spinodal decomposition in the ising model with vacancy diffusion"

In a recent paper [Phys. Rev. B 50, 3477 (1994)], P. Fratzl and O. Penrose present the results of the Monte Carlo simulation of the spinodal decomposition problem (phase separation) using the vacancy dynamics mechanism. They observe that the t1/3 growth regime is reached faster than when using the standard Kawasaki dynamics. In this Comment we provide a simple explanation for the phenomenon based on the role of interface diffusion, which they claim is irrelevant for the observed behavior.

Spanning avalanches in the three-dimensional Gaussian random-field Ising model with metastable dynamics: Field dependence and geometrical properties

Spanning avalanches in the 3D Gaussian Random Field Ising Model (3D-GRFIM) with metastable dynamics at T=0 have been studied. Statistical analysis of the field values for which avalanches occur has enabled a Finite-Size Scaling (FSS) study of the avalanche density to be performed. Furthermore, a direct measurement of the geometrical properties of the avalanches has confirmed an earlier hypothesis that several types of spanning avalanches with two different fractal dimensions coexist at the critical point. We finally compare the phase diagram of the 3D-GRFIM with metastable dynamics with the same model in equilibrium at T=0.

Influence of the driving mechanism on the response of systems with athermal dynamics: The example of the random-field Ising model

We investigate the influence of the driving mechanism on the hysteretic response of systems with athermal dynamics. In the framework of local mean-field theory at finite temperature (but neglecting thermally activated processes), we compare the rate-independent hysteresis loops obtained in the random field Ising model when controlling either the external magnetic field H or the extensive magnetization M. Two distinct behaviors are observed, depending on disorder strength. At large disorder, the H-driven and M-driven protocols yield identical hysteresis loops in the thermodynamic limit. At low disorder, when the H-driven magnetization curve is discontinuous (due to the presence of a macroscopic avalanche), the M-driven loop is reentrant while the induced field exhibits strong intermittent fluctuations and is only weakly self-averaging. The relevance of these results to the experimental observations in ferromagnetic materials, shape memory alloys, and other disordered systems is discussed.

Random-field Potts model with dipolarlike interactions: Hysteresis avalanches and microstructure

A model for the study of hysteresis and avalanches in a first-order phase transition from a single variant phase to a multivariant phase is presented. The model is based on a modification of the random-field Potts model with metastable dynamics by adding a dipolar interaction term truncated at nearest neighbors. We focus our study on hysteresis loop properties, on the three-dimensional microstructure formation, and on avalanche statistics.

Statistical hadronization of supercooled quark-gluon plasma

The fast simultaneous hadronization and chemical freeze-out of supercooled quark-gluon plasma, created in relativistic heavy ion collisions, can lead to the reheating of the expanding matter and to the change in a collective flow profile. We use the assumption of statistical nature of the hadronization process, and study quantitatively the freeze-out in the framework of hydrodynamical Bjorken model with different simple quark-gluon plasma equations of state.

Numerical signs fos a transition in the 2d Random Field Ising Model at T=0

Intensive numerical studies of exact ground states of the two-dimensional ferromagnetic random field Ising model at T=0, with a Gaussian distribution of fields, are presented. Standard finite size scaling analysis of the data suggests the existence of a transition at ¿c=0.64±0.08. Results are compared with existing theories and with the study of metastable avalanches in the same model.

Dynamics of the two-dimensional gonihedric spin model

In this paper, we study dynamical aspects of the two-dimensional (2D) gonihedric spin model using both numerical and analytical methods. This spin model has vanishing microscopic surface tension and it actually describes an ensemble of loops living on a 2D surface. The self-avoidance of loops is parametrized by a parameter ¿. The ¿=0 model can be mapped to one of the six-vertex models discussed by Baxter, and it does not have critical behavior. We have found that allowing for ¿¿0 does not lead to critical behavior either. Finite-size effects are rather severe, and in order to understand these effects, a finite-volume calculation for non-self-avoiding loops is presented. This model, like his 3D counterpart, exhibits very slow dynamics, but a careful analysis of dynamical observables reveals nonglassy evolution (unlike its 3D counterpart). We find, also in this ¿=0 case, the law that governs the long-time, low-temperature evolution of the system, through a dual description in terms of defects. A power, rather than logarithmic, law for the approach to equilibrium has been found.

Mean field model for spatially extended systems in the presence of multiplicative noise

We present a mean field model that describes the effect of multiplicative noise in spatially extended systems. The model can be solved analytically. For the case of the phi4 potential it predicts that the phase transition is shifted. This conclusion is supported by numerical simulations of this model in two dimensions.

Studying Avalanches in the ground-state of the two-dimensional random field Ising model driven by an external field

We study the exact ground state of the two-dimensional random-field Ising model as a function of both the external applied field B and the standard deviation ¿ of the Gaussian random-field distribution. The equilibrium evolution of the magnetization consists in a sequence of discrete jumps. These are very similar to the avalanche behavior found in the out-of-equilibrium version of the same model with local relaxation dynamics. We compare the statistical distributions of magnetization jumps and find that both exhibit power-law behavior for the same value of ¿. The corresponding exponents are compared.

Phase-field model for Hele-Shaw flows with arabitrary contrast II: numerical approach

We present a phase-field model for the dynamics of the interface between two inmiscible fluids with arbitrary viscosity contrast in a rectangular Hele-Shaw cell. With asymptotic matching techniques we check the model to yield the right Hele-Shaw equations in the sharp-interface limit, and compute the corrections to these equations to first order in the interface thickness. We also compute the effect of such corrections on the linear dispersion relation of the planar interface. We discuss in detail the conditions on the interface thickness to control the accuracy and convergence of the phase-field model to the limiting Hele-Shaw dynamics. In particular, the convergence appears to be slower for high viscosity contrasts.

Reentrant transition induced by multiplictative noise in the Time Dependent Ginzburg-Landau model

An effect of multiplicative noise in the time-dependent Ginzburg-Landau model is reported, namely, that noise at a relatively low intensity induces a phase transition towards an ordered state, whereas strong noise plays a destructive role, driving the system back to its disordered state through a reentrant phase transition. The phase diagram is calculated analytically using a mean-field theory and a more sophisticated approach and is compared with the results from extensive numerical simulations.